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Transcript of Arthur Pantelides Dissertation Without Appendix
ASSESSMENT OF THE RELATIVE VALUE OF KNOWLEDGE TRANSFER PROCESSES TO THE SUCCESS OF
INTERNATIONAL PROJECTS
by
Arthur Simon Pantelides
B.S. in Aerospace Engineering, May 1989, Boston University
M.S. in Mechanical Engineering, May 1991, Boston University
M.E.M. Engineering Management, August 2002, The George Washington University
A Dissertation submitted to
the Faculty of The School of Engineering and Applied Science
of The George Washington University in partial satisfaction of the requirements
for the degree of Doctor of Philosophy
May 17, 2009
Dissertation directed by
Shahram Sarkani Professor of Engineering Management and Systems Engineering
Thomas Andrew Mazzuchi
Professor of Operations Research and Engineering Management
The School of Engineering and Applied Science of the George Washington University
certifies that Arthur Simon Pantelides has passed the Final Examination for the degree
of Doctor of Science as of March 6th 2009. This is the final approved form of the
dissertation.
ASSESSMENT OF THE RELATIVE VALUE OF KNOWLEDGE TRANSFER PROCESSES TO THE SUCCESS OF INTERNATIONAL PROJECTS
Arthur Simon Pantelides
Dissertation Research Committee :
Shahram Sarkani, Professor of Engineering Management and Systems Engineering, Dissertation Co-Director Thomas Andrew Mazzuchi, Professor of Operations Research and Engineering Management, Dissertation Co-Director E. Lile Murphree, Professor of Engineering Management and Systems Engineering, Committee Chair Frank Allario, Professor of Engineering Management and Systems Engineering, Committee Member Gerhard Antony, President, Neugart USA LP, Committee Member
ii
© Copyright by Arthur Simon Pantelides, 2009 All Rights Reserved
iii
Dedicated to My Parents
Thank You for Everything That You Have Done for Me.
And
Dedicated to the Next Generation : Max, Alex, and Mila
May You Do Great Things !
iv
Acknowledgements
Above all, I would like to thank my family who always encouraged me to pursue my
studies to completion.
I would especially like to thank Miss Effi Vakalou who helped me significantly with this
final report, with her diligent reading, re-reading, and great editing skills, as well as for
her translations with German text; and her overall support.
Thank you to my colleagues at Sumitomo Drive Technologies and Sumitomo Heavy
Industries who provided much feedback, suggestions, reviews, and clarifications.
With a special thanks to Mr. and Mrs. Jun Asai for assisting with the Japanese language
and translations.
I am grateful to Dr. Shahram Sarkani, Dr. Thomas Mazzuchi, and Dr. Frank Allario for
their continued support and guidance; and for maintaining a top-notch academic
program which I am proud to have completed.
Finally, I would like to thank my mentor Dr. Gerhard Antony, a great engineer,
businessman, and wonderful person, who has provided hours and hours of great
conversation not only on the subject matter but in life in general for close to 15 years
I have had the privilege to know him.
v
Abstract
ASSESSMENT OF THE RELATIVE VALUE OF KNOWLEDGE TRANSFER
PROCESSES TO THE SUCCESS OF INTERNATIONAL PROJECTS
As the activities of companies become global in nature there is an emerging need to
understand the processes that lead to the success of large projects in which the core
competency is centered in a parent company, an engineering development center that is
located in a subsidiary company in another country, and special application customers
that are distributed across the globe. This situation requires an ever-increasing role for
professional project managers in subsidiary companies to cross international boundaries
in order to connect the parent company with the ultimate user who has a specific
application.
The modern Project Manager must consider many facets of their responsibilities
including : (1) managing corporate knowledge as a strategic asset; (2) transferring
corporate knowledge to the project team and transferring engineering capabilities back
to corporate; and, (3) developing customer requirements that ensure project success. In
order to meet these responsibilities, the project manager needs to understand the
diversity of technical communication from parent to subsidiary, the cultural vagaries of
these communications, in addition to maintaining an eye on the knowledge transfer
process. The challenges for an organization is to manage its knowledge assets and
handle knowledge transfer between headquarters and its subsidiaries in an optimum
manner so that international projects succeed in meeting their objectives.
vi
The project manager is a key player in the process. Statistics show however that most
international projects either fail or do not achieve their ultimate business goals and it’s
not clear at this point what are the primary causes.
This study will investigate, identify, and analyze the factors and attributes associated
with successes of international projects examining cultural and knowledge transfer
processes of foreign-owned heavy machinery companies with U.S. subsidiaries.
The study will consider a very important tool in managing such projects – technical
communications. It plans to improve understanding of how communication structures
and mechanisms of companies are integrating factors between culture and the
knowledge transfer chain, and how, in turn, they impact project success. Based on the
findings, the study will propose a conceptual framework from which key cultural
attributes and knowledge transfer processes within certain communication mechanisms,
can be modeled for potentially identifying project success.
vii
Table of Contents
DEDICATION…………………………………………………………………………….. iv
ACKNOWLEDGEMENTS………………………………………………………………. v
ABSTRACT………………………………………………………………………………. vi
TABLE OF CONTENTS………………………………………………………………… viii
LIST OF FIGURES……………………………………………………………………… xi
LIST OF TABLES………………………………………………………………………. xiii
CHAPTER 1 : INTRODUCTION……………………………………………………….. 1
1.1 Problem Statement…………………………………………………………. 4
1.2 Research Background……………………………………………………… 5
1.3 Research Objectives and Value to the Discipline………………………. 6
1.4 Thesis Organization………………………………………………………… 12
CHAPTER 2 : LITERATURE REVIEW……………………………………………….. 14
2.1 Knowledge Management and Transfer…………………………………… 14
2.2 Culture……………………………………………………………………….. 28
2.2.1 National Culture…………………………………………………. 29
2.2.2 Corporate / Organizational Culture……………………………. 39
2.3 Communication : Methodologies, Mechanisms, and Tools……………. 46
2.3.1 Theoretical Basis………………………………………………… 47
2.3.2 Groups and Teams……………………………………………… 58
2.3.3 International / Intercultural Communications…………………. 64
2.3.4 Communications by Engineers………………………………… 66
2.4 Project Management……………………………………………………….. 69
2.4.1 Communicating Effective Project Management……………… 70
viii
2.4.2 The Successful Project………………………………………… 72
2.5 Literature Review Summary & Research Potential……………………… 76
CHAPTER 3 : RESEARCH DESIGN and METHODOLOGY………………………. 82
3.1 Research Objectives - Hypotheses Mapping……………………………. 82
3.2 Method……………………………………………………………………….. 92
3.3 Population…………………………………………………………………… 93
3.4 Instrument / Cross-Cultural Survey Research Design………………….. 98
3.4.1 Basic Principles and Best Practices…………………………… 99
3.4.2 Pilot Study Program…………………………………………….. 102
3.4.3 Cross-Cultural Survey Limitations & Difficulties……………… 105
3.4.4 Final Question Development and Mapping……………………110
3.5 Validation & Reliability……………………………………………………… 117
3.6 Analysis Approach………………………………………………………….. 119
CHAPTER 4 : RESULTS and DATA ANALYSIS…………………………………… 121
4.1 Survey Results……………………………………………………………… 121
4.1.1 Basic Information / Demographics……………………………. 124
4.1.2 Headquarters & Subsidiary Communication…………………. 127
4.1.3 Headquarters & Subsidiary KT and Corporate Culture…….. 132
4.1.4 What is Project Success……………………………………….. 138
4.1.5 Project Success at Your Company…………………………… 142
4.2 Data Analysis / Hypotheses Testing …………………………………….. 145
4.2.1 Targeted Correlational Analysis………………………………. 148
4.2.2 Statistical Significance & Measures of Association…………. 169
4.2.2.1 Chi-square test (χ2) and Cramer’s V…………….. 169
ix
4.2.2.2 ANOVA Confirmation by Survey Question……… 182
4.2.3 Analysis Summary……………………………………………. 182
CHAPTER 5 : CONCLUSION…………………………………………………. ……… 186
5.1 Discussion and Implications………………………………………. ……… 186
5.2 Theoretical Construct and Future Research……………………………. 198
REFERENCES…………………………………………………………………………… 201
APPENDICES……………………………………………………………………………. 209
APPENDIX A : Hofstede Summary & Relational Mapping……………………. 210
APPENDIX B : Survey Instrument………………………………………………. 212
APPENDIX C : Survey Raw & Supplemental Data……………………………. 229
APPENDIX D : Illustrative Example Case……………………………………… 250
APPENDIX E : Sample Multilingual Documentation from the Industry……… 251
APPENDIX F : Photographs from the Industry………..............……………… 252
APPENDIX G : Comprehensive List of Gross Population…………………… 253
x
List of Figures
Figure 1-1 – Basic Concept of Research…………………………………………….. 3
Figure 1-2 – Conceptual Framework…………………………………………………. 9
Figure 2-1 – Three Models of Communication………………………………………. 50
Figure 2-2 – Integrating Research Components…………………………………….. 77
Figure 2-3 – Identifying the Research Focus Within the Framework……………… 79
Figure 2-4 – Higher-Tier Knowledge Transfer Models for Parent-Subsidiary…….. 80
Figure 3-1 – Higher-Level Research Objective………………………………………. 84
Figure 3-2 – Sub-Hypotheses Cluster-Mapping and Inter-Relationship…………… 90
Figure 3-3 – Hypotheses Development and Mapping to Objectives……………….. 91
Figure 3-4 – AGMA Website ScreenPrint…………………………………………….. 96
Figure 3-5 – Likert Scale Used in Survey Instrument…………………………………100
Figure 3-6 – Pilot Program Protocol Considerations…………………………………. 104
Figure 3-7 – Survey Instrument Front-Cover Instructions Page……………………. 109
Figure 3-8 – Overall Survey Question Mapping……………………………………… 116
Figure 4-1 – Surveys Return Results…………………………………………………. 121
Figure 4-2 – Survey Language Results………………………………………………. 122
Figure 4-3 – Geographic Location of Respondent Company Results…………….. 122
Figure 4-4 – Response Rates by Region……………………………………………… 123
Figure 4-5 – Number of Returned Surveys by Week………………………………… 123
Figure 4-6 – Job Classification by Target Country…………………………………… 124
Figure 4-7 – Company Size, Age, Expat Situation Profile Results…………………. 126
Figure 4-8a,b – Survey Question 45 : Project Results Charts………………………. 143
xi
Figure 4-9a,b – Survey Question 46 : Project Results Charts……………………… 143
Figure 4-10a,b – Survey Question 47 : Project Results Charts……………………. 143
Figure 4-11a,b – Survey Question 48 : Project Results Charts…………………….. 143
Figure 4-12a,b – Survey Question 49 : Project Results Charts…………………….. 144
Figure 4-13a,b – Survey Question 50 : Project Results Charts…………………….. 144
xii
List of Tables
Table 2-1 – Four Modes of Knowledge Conversion…………………………………. 17
Table 2-2 – Comparison of Management Models Regarding Knowledge Creation……………………………………………………… 19 Table 2-3 – Frictions and Potential Solutions to Knowledge Transfer…………….. 24
Table 2-4a – Mapping Communication Traditions and Theories…………………… 54
Table 2-4b – Mapping Communication Traditions and Theories : Ref. 1…………. 55 Table 2-4c – Mapping Communication Traditions and Theories : Ref. 2………… 56 Table 2-4d – Mapping Communication Traditions and Theories : Final Refinement………………………………………………………… 57 Table 2-5a – Mapping of Positive and Negative Group Role Behavior Characteristics of Teams……………………………………………….. 61
Table 2-5b – Mapping of Positive and Negative Group Role Behavior Characteristics of Teams : Relationship to 3 Constructs……………. 62
Table 2-5c – Mapping of Positive and Negative Group Role Behavior Characteristics of Teams : Characteristic Grouping…………………. 63
Table 3-1 – Overall Population Potential Target Pool……………………………….. 95
Table 3-2 – Final Distribution Population Companies / Organizations…………….. 97
Table 3-3 – Questionnaire Rationalization Summary………………………………… 113
Table 3-4 – Data Collection Timeline………………………………………………….. 118
Table 4-1 – One-on-One Communication Structure Survey Data…………………. 127
Table 4-2 – One-to-Many Communication Structure Survey Data…………………. 128
Table 4-3 – Man-to-One Communication Structure Survey Data………………….. 129
Table 4-4 – Many-to-Many Communication Structure Survey Data……………….. 130
Table 4-5 – Written / Documented Communications Survey Data………………… 130
Table 4-6 – Verbal, Face-to-Face Communications Survey Data…………………. 131
xiii
Table 4-7 – Trust Survey Data…………………………………………………………. 132
Table 4-8 – Hold-Back of Information Either by Headquarters or Subsidiary Data 1…………………………………………………………. 133 Table 4-9 – Hold-Back of Information Either by Headquarters or Subsidiary Data 2………………………………………………………… 134 Table 4-10 – Technical Project Specs & Customer Knowledge Survey Data……. 135
Table 4-11 – Technology Tools Survey Data………………………………………… 135
Table 4-12 – Cooperation & Collaboration / Culture Survey Data…………………. 136
Table 4-13 – Structure of Decision-Making and Processes Survey Data…………. 136
Table 4-14 – Employee Input Into Decision-Making Survey Data…………………. 137
Table 4-15 – Shared-Meaning Between Headquarters and Subsidiary Survey Data……………………………………………………………… 138 Table 4-16 – Project Success : Time, Budget, Performance Survey Data……….. 138
Table 4-17 – Post-Project Reviews Survey Data……………………………………. 139
Table 4-18 – Employee Morale, Satisfaction, and Project Success Survey Data… 139
Table 4-19 – Customer Satisfaction and Repeat Business, and Project Success.. 140
Table 4-20 – Financial, Commercial Gains, Market Share, and Project Success… 140
Table 4-21 – Risk Management and Project Success Survey Data………………. 141
Table 4-22 – Projects and Opportunity for Knowledge Creation…………………… 141
Table 4-23 – Project Success and Successful Knowledge Transfer………………. 142
Table 4-24 – Descriptive Statistics Analysis Summary of Survey Questions……… 147
Table 4-25 – Chi-square and Cramer’s V Significance and Association Values….. 181 and Interpretations
Table 4-26 – Analysis Results Summary and Hypotheses Disposition…………… 183
Table 5-1 – Variable Utilization Matrix…………………………………………………. 187
xiv
CHAPTER 1 – INTRODUCTION
One can argue that there is no such thing as a true “local” project anymore. This is
especially true with larger-scale power-transmission machinery projects for a growing list
of industrial applications.
A waste-water treatment facility in Argentina for example, may utilize three-dozen
thousand- horsepower machines purchased from a Japanese heavy industry
conglomerate. The project is managed by the company’s overseas technical center in
the United States. This operation may include engineers from Asia, Europe, as well as
the United States. Machinery parts are sourced from Japan, China, Brazil, and Italy; with
engineering expertise from these same countries as well as Germany and Sweden. In
this example, it is critical to manage clear specifications and technical knowledge
transfer between the Argentinean customer, the global parts suppliers, and the
Japanese original equipment manufacturer of the main units. Clearly the managing
project team at the subsidiary operation in the U.S. of the Japanese company has its
work cut out for it. Unfortunately the project failed. In this case a key technical
specification was not communicated and all the units had to be retrofitted after
installation resulting in a 40% cost overrun.
A German company is building the new international airport in Athens, Greece. The
Project Manager is from England with most of his experience actually in the Netherlands.
His core team is made up of local Greek engineers. The miles of conveyor systems for
the airport’s baggage handling system require over a thousand power transmission units
sourced from Italy. The team manages to successfully complete the design and
implementation of the system early, under budget, and with improved performance of the
1
system. On the other hand, the sky-ramps which lead from the terminal to the planes,
are powered by German units, with Japanese variable frequency controller drives. The
project is marginally successful according to the Czech company who managed it since
no one foresaw a key factor in the local operating conditions due to the areas very hot
weather in the summer months.
These three different but similar examples demonstrate that projects are increasingly
becoming more international in nature; thus more complex from a management
perspective. One can argue that globalization and industry began with Columbus in 1492
eventually evolving from Europe to the Americas, then continuing its evolution across the
Pacific into Asia, from Japan and Korea, to Taiwan, into China and SouthEast Asia and
into India. Who knows what will be the next evolutionary jump in this global circum-
transformation, Russia, the Middle East, Africa ? What we know, as Thomas Friedman
writes, “…the world is flat” [42] and its created opportunities for international project
management that did not previously exist. But along with these opportunities there are
also challenges.
This research study proposes to investigate and assess the value of knowledge transfer
processes to the success of international projects. It will seek out and identify key
attributes linking knowledge transfer with project success once “success” is defined
within the current research context. The research will utilize power-transmission
industrial machinery manufacturers within its case study and scope due to 3 key
reasons :
1. Internationally there are only 4 or 5 truly global manufacturers of this type of
large-scale industrial equipment with subsidiaries in the United States;
enabling us to obtain representative data that is strongly representative of the
industry
2
2. These manufacturers have a fairly diverse cultural base; essentially these
companies are either Japanese, Italian, German, or Swiss. This provides for
a good cultural sampling for our research; meaning that the cultural aspects
of communication, technology transfer and project management can be fairly
well-represented.
3. This type of machinery is fundamental in virtually all industries utilizing power
and motion transmission thus it can be considered an important core
technology.
Figure 1-1 : Basic Concept of the Research ( Photos used with permission from Sumitomo Drive Technologies; the authors place of business )
Overseas Parent’s
Headquarters
U.S. Subsidiary Gearbox & Motor
Manufacturer
U.S. or Foreign Customer and
System Integrator
Final Job Sitein U.S. or
other Country
Technical Knowledge Transfer & Mana
Project S
Final Site Performance Regement pecifications quirements
Impact on Cust. Job Site Project Startup Success
Managing U.S. Operation- Customer R l ti hi
Managing the Parent-Subsidiary R l ti hi
3
1.1 Problem Statement
The majority of foreign (and in most cases American) heavy machinery companies
manufacturing in the United States are not optimizing their knowledge transfer functions
and it is hypothesized that this directly effects the success of their large industrial
projects.
To improve probability of project success in large projects requiring technical information
flow between a company’s foreign headquarters outside the U.S. and its local U.S.-
based operations, the company’s knowledge transfer processes need to be optimized
within a set of attributes. Suboptimal processes result in :
poor delivery performance – resulting in late project startup by the customer;
thus schedule / time - a typical metric of project success, is not being met
project cost overruns – resulting in decreased margins for the manufacturer;
another project success metric (cost) not being met
suboptimum performance requirement fulfillment resulting in increased after-
market involvement by both sides (manufacturer and customer, and in some
cases the customers’ customer or end-user); another project success metric
widely used (performance), not being met
customer dissatisfaction resulting in non-recurring business for the machinery
manufacturer
poor morale in the non-technical employees of the gear manufacturer ( in
departments and areas such as : purchasing, production control, logistics,
customer service, management / executive)
4
high turnover in technical employees of the gear manufacturer ( in departments
and areas such as : engineering, design, production ); including Project Managers
dissatisfaction of the gear manufacturers’ headquarters personnel outside the U.S.
resulting in further technical decisions that may not be the right ones; a sort of
spiral effect
It is hypothesized that for foreign industrial machinery manufacturers producing in the
U.S. a key factor influencing this overall suboptimum performance is how technical
knowledge transfer is structured (channels and attributes) and subsequently managed
between U.S. operations and their overseas foreign-based headquarters; and how this
affects project team success. Thus the problem is a structural management problem with
influences and variables of knowledge management, culture, (both corporate and
national), communication, and other factors to be identified, quantified, evaluated,
reported, and a theory introduced for remedying the situation so that large international
project and teams can have a better probability of success.
The concept of KTS, or Knowledge Transfer Supply-Chain between a U.S. subsidiary
and its overseas headquarters and its impact on project performance will be used as a
key measure. The study seeks out to identify specific attributes within this KTS structure
of these multinational companies that define successful projects. We propose that KTS
is of significant value to international project / team success.
1.2 Research Background
According to Joshi, Sarker, and Sarker, “research in the area of knowledge transfer has
been conducted from three different epistemological stances : cognitivistic,
5
connectionistic, and autopoietic”[66]. The cognitivistic approach views knowledge as
data. According to Joshi et al. the connectionistic approach views knowledge as
contextual in which local differences exist and impact the knowledge entity [66]. Those
that follow this theory contend that knowledge transfer within this context is difficult due
to the “…contextualized nature of the knowledge” [66] and factors of shared
understanding. The autopoietic perspective is rooted in the notion that knowledge and
thus knowledge transfer is based on an autonomous and evolutionary foundation which
develops on its own and with knowledge not really being shared but more being created
[87]. We believe that within the context and scope of our research pertaining to
international companies, the connectionistic perspective will be most suitable.
1.3 Research Objectives and Value to the Discipline
The primary assumption going forward is that there is in fact a correlation among the
way foreign company expats and local representatives working in a subsidiary in the U.S.
and within an engineering and manufacturing function in our study population are
managed and the way communication flows between them and headquarters
(knowledge transfer). There does exist a relationship that can be identified and used to
model and describe a knowledge transfer function or process; and this can be related to
project success.
Essentially the study will be initiated with the assumption that these knowledge transfer
processes can be identified, quantified, modeled, and utilized to improve chance of
success of projects. There will be certain assumptions that will have to be made as to
what constitutes “success.” These will be identified and addressed.; one possibility is
the speed at which technical information flows and eventually results in on-time project
6
completion or on-time delivery of product. This can be a good approach because it does
not take into account the product itself but an auxiliary operational metric instead. Thus,
certain assumptions regarding the operation and the metrics to be used will have to be
made.
Research Objectives
1. Establish what is the most meaningful concept of project success to the target
study companies. How do they measure success and what are the similarities in
measuring project success among them. Establish these common factors for
success that can then be used to further the investigation.
2. Identify specific knowledge transfer attributes and descriptive variables of
multinational industrial manufacturing companies with foreign headquarters and U.S.
subsidiaries involved in international projects (our target companies). Make a
preliminary judgment on how these attributes and descriptive variables are related,
if at all, to the company’s project management successes; what is important, what is
not important, etc.
3. Identify key correlations in knowledge transfer processes between the 3 culturally
diverse groups of companies that make up the majority of our target industrial
manufacturers (German, Italian, Japanese); identify communication attributes that
related to the companies’ corporate and national culture and how these establish a
tool link with the knowledge transfer function.
4. Establish a final correlated relationship between knowledge transfer factors and
project success; conclude a final relationship among the attributes and variables of
knowledge transfer and project success, and establish a conceptual model for this.
7
5. Increase the knowledge and understanding in the fields of International Project
Management, Intra-Corporate Technical Communication Management, Knowledge
Management / Transfer Methodology. These are areas which would be a great
interest to students of engineering management, international business, operations
management even sociology and organizational behavior.
The innovation that will result from this study will be a conceptual model utilizing a
defined set of attributes and relationships for setting up optimized knowledge transfer
channels between a technical / manufacturing company’s foreign headquarters and its
subsidiary operations within the United States. These channels will enable the operation
to be better equipped in managing larger scale international projects which require
information flow (marketing requirements) upstream to the manufacturers’ headquarters
and downstream (final technical specifications and product) to the final customer which
may be located in the U.S. or in another country. The research will identify key attributes
integral to knowledge transfer for successful international projects.
Thru a literature review we will identify past research which has addressed various
aspects of the discipline of Project Management including substantial work done on
project management’s relationship to project team culture, and project management
communication aspects. However, we will show and seek to address a fundamental
lack of research in the area of integrating knowledge transfer and its utilization of
various communication methodologies as it relates to various aspects and levels
of culture (national, team, corporate) leading to success in international projects.
Specific attributes will be identified within this overall integration concept which when
properly considered and balanced by future project managers, will enable an improved
8
probability of success. This integrative theoretical concept model of knowledge transfer,
communication processes, culture, within international projects leading to a success
probability will be finally derived. This integration or relation hypothesis and its
resulting, and supporting success attributes is the innovation of the research.
A conceptual framework established by the author is shown in Figure 1-2.
Figure 1-2 : Conceptual Framework
There has been extensive research into project management, to a lesser extent but still
noteworthy research has been done on the cultural aspects of project teams and their
dynamics. However, based on Shenhar and Dvir’s Project paper Management Research
9
- The Challenge and Opportunity, [107] a paper appearing in the June 2007 Project
Management Journal, there are several areas that require considerable research
opportunities. In this recent journal article, they contend that statistics of project success
suggest that most projects fall short of meeting their goals. The authors offer areas of
potential future research in regards to three aspects of project management and
success : from a strategic business aspect, from a operations process aspect, and from
a team leadership aspect. Our study will focus on 2 of these areas : operational /
process and team leadership. Knowledge transfer as it relates to project success is
integral to the process of project management; while the cultural side which in turn also
relates how processes are accomplished within multinational companies is related more
towards the team and leadership dynamics aspect.
Our study is unique in that it will attempt to integrate and present factors which in
themselves are the binding variables for the various past aspects of project management.
What is meant is that there has been significant past research in the field, however there
has been little research in the area and affect of combining knowledge transfer
with communication mechanisms as tools for the transfer, and cultural aspects
and relating these to project success. It is this combination which our study seeks to
research and contribute to the body of knowledge.
Our research can be available to be used by international industrial companies who are
considering to establishing operations in the U.S. The research can present the factors
which would lead to a higher probability of project success once those companies are in
the U.S. These factors relating to knowledge transfer and the mechanisms for it
(communication channels, etc.) can be combined with a company’s cultural makeup
(both corporate culture and national culture) to provide an optimum scenario for that
10
company to set up its project management processes. Thus, the stakeholders and
interested parties could possibly be :
The heavy industrial machinery industry, and companies especially from, but
not limited to, Japan, Italy, and Germany who have a stake in overseas
operations and project management while the core of their knowledge resides
at their headquarters back home. Other countries which are gaining ground
here are : Korea, Finland, and Sweden.
Chinese companies who are considering structuring potentially new operations
in the U.S. and getting into the industry in the next 5 to 10 years that will be
involved in project management and knowledge transfer with their headquarters.
It is felt that the research that will result from the study of Japanese companies
will be of great interest to the Chinese.
Academics and students of Engineering and Project Management; Social
Scientists in team communication and culture disciplines and studies ;
knowledge management students and professionals, especially those in the
area of studying knowledge transfer; and business management students and
researchers, especially those interested in structuring operations and business
processes within a multinational setting.
This study will add to the body of knowledge in managing engineers and technical
personnel and contribute further to the overall understanding and discipline of
Engineering and Project Management from an international point of view. We feel that
this is becoming more and more important since companies are operating from an
increasingly more global perspective. For example, family-owned manufacturers in
11
Northern Italy, a region well-known for its entrepreneurial manufacturing character, are
now expanding into the U.S. and even China. Whereas before these companies and
region of Italy was thought of as the “China of Europe” now they are operating
internationally. Without a doubt the culture and processes that are set-up contribute to
such a company’s project management success.
There are many such national examples from Italy, to Japan, to Germany and others. In
some cases choices are made to have local headquarters personnel relocate to the USA,
subsequent knowledge transfer is handled a certain way under certain conditions in
regards to projects. In some cases these companies are too small and no personnel is
interested to relocate, so local personnel must be found; knowledge transfer under this
condition is handled differently. The study will provide insight to the discipline in
identifying optimum processes.
1.4 Thesis Organization
This dissertation consists of five chapters : Introduction, Literature Review, Research
Design and Methodology, Results and Data Analysis, and Conclusions.
Chapter 1 – Introduction provides a general introduction and outlines the problem and
background related to the study. This chapter also outlines the research objectives and
key questions which the investigation is structured around.
Chapter 2 – Literature Review provides a comprehensive literature review of the
major areas addressed in the investigation : Knowledge Management and Transfer,
12
Culture, Communication Methodologies Mechanisms and Tools, and Project
Management. Because the scope of research includes areas that are fairly extensive in
themselves, such as the topic of Culture, or Communication, this Chapter is focused on
those specific areas of the literature in each segment which relate to our particular
investigation. The chapter is completed with a visual literature map demonstrating the
particular area in which our research will be focusing.
Chapter 3 – Research Design and Methodology outlines the research methodology
utilized in our research. It begins with our Research-Objectives-Hypotheses mapping
and process which outlines and demonstrates the full integration across the research.
We also outline the methodology for our cross-cultural research and provide a detailed
description of the survey tool used to gather our data.
Chapter 4 – Results and Data Analysis presents the overall survey results and the
data analysis these results were subjected to in the investigation. This is outlined in four
main areas : Headquarters and Subsidiary Communications, Knowledge Transfer,
Corporate Culture, and Project Success. Results are initially presented utilizing cross-
tabulated contingency tables which is a very common and accepted method for
representing survey data. Additionally, this data is analyzed using targeted correlational
analysis based on our hypotheses and utilizing chi-square (χ2) and Cramer’s V
methodologies for statistical significance and measures of association.
Chapter 5 – Conclusions provides a discussion of our findings and implications for the
industry. It provides for final conclusions and recommendations for continued process
improvements within the particular industry and finally presents the limitations of the
study while proposing recommendations for future research.
13
CHAPTER 2 – LITERATURE REVIEW
2.1 Knowledge Management and Transfer
Widely recognized by scholars as the foundation reference in the area knowledge
management, Ikujiro Nonaka’s and Hirotaka Takeuchi’s “The Knowledge-Creating
Company” [87] was first published in 1995, in English interestingly enough, before
being translated to Japanese the following year. In the text Nonaka and Takeuchi
provide a strong foundation for the discipline of knowledge management. It is here that
the concept of tacit vs. explicit knowledge is outlined in great detail and in fact linked to
the cultural delineation of East vs. West conceptual approaches to business and social
interaction in general. Nonaka and Takeuchi describe explicit knowledge as “…that
which can be articulated in formal language including grammatical statements,
mathematical expressions, specifications, manuals, and so forth” [87]. Tacit knowledge
is “…hard to articulate with formal language” [87]. The authors define it as “…personal
knowledge embedded in individual experience,” [87], and that which “…involves
intangible factors such as personal belief, perspective, and the value system” [87]. This
is important because it provides a link to one of our sub-hypotheses relating knowledge
transfer and cultural aspects of a company. Nonaka and Takeuchi discuss the cognitive
dimension of tacit knowledge and how this reflects our image of reality (now) and one’s
vision of the future [87]. This further integrates the concept of culture and in fact some of
the basic research done by Geert Hofstede in his work Culture and Organizations :
Software of the Mind [58].
14
In “The Knowledge-Creating Company” Takeuchi and Nonaka contend that this tacit
knowledge has become “…an important source of Japanese companies’
competitiveness” [87]. We intend to investigate this within the particular scope of our
research and in particular within the framework of project success. What is not covered
in the text is any kind of research that extends the hypotheses to Japanese company
subsidiaries. This will also be part of our focus.
An interesting aspect of Nonaka’s and Takeuchi’s work is their assessment of what in
fact actually is knowledge and the relationship between Eastern and Western thought.
They argue that the Western tradition of “…epistemology, rationalism, and empiricism
differs sharply with regard to what constitutes the actual source of knowledge” [87].
Within the West this further evolves into pragmatism which can be seen as somewhat of
a uniquely American philosophical tradition. While in the East, Japan (one of our focus
countries in our study) has a different evolution of its intellectual tradition in regards to
knowledge, namely : “… (1) oneness of humanity and nature; (2) oneness of body and
mind; and (3) oneness of self and other” [87]. According to Nonaka and Takeuchi,
“…these traits have formed the foundation of the Japanese view towards knowledge as
well as the Japanese approach towards management…” [87]. Once again our
approach will be to consider these also within the context of the subsidiary relationship
(Japanese Parent Company, U.S. Subsidiary Operation) where there is a duality and in
fact a dynamic at work. Do these still hold true ?
A central focus in Nonaka’s and Takeuchi’s text are the processes which collectively
make up knowledge conversion and subsequent transfer, these are : tacit to explicit
(externalization); explicit to explicit (combination); explicit to tacit (internalization);
15
and tacit to tacit (socialization) [87]. These processes are outlined in some detail
below.
Socialization : Tacit Tacit
“Socializing is the process of sharing experiences thus creating tacit
knowledge…” [87]. Also Tacit knowledge can be acquired without using
language such as when an apprentice observing and imitating a master
craftsman. A specific Japanese example are Honda Motors and the
“brainstorming camps” it has developed enabling its employees to meet in an
informal setting in order to solve difficult problems [87]. It is interesting to note
that although not directly stated by the authors, based on our research into the
communications aspect of knowledge transfer, we found that what Nonaka and
Takeuchi present here is essentially a concept of Conversation Analytics
communication theory.
Externalization : Tacit Explicit
“Externalization is a process of articulating tacit knowledge into explicit concepts”
[87]. This is “…typically seen in the process of concept creation…”[87], and very
much integrated into product innovation. Ideas, concepts, images, hypotheses
are “hammered-out” into articulated knowledge in various forms such as writing,
instructions, diagrams, etc. According to the authors, when this is too difficult to
do directly thru analytical methods, externalization can take place thru metaphor
and / or analogy [87]. Canon copiers is a good example of this. It analogized a
disposable copier cartridge with a beer can thus creating the first disposable
aluminum copier cartridge.
Combination : Explicit Explicit
“Combination is a process of systemizing concepts into a knowledge system” [87].
Various forms of training, instruction and formal education fall under this type of
knowledge conversion.
Internalization : Explicit Tacit
According to Nonaka and Takeuchi, “Internalization is a process of incorporating
explicit knowledge into tacit knowledge. It is closely related to learning by doing”
[87]. For explicit knowledge to become tacit there are 2 steps involved. The
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knowledge should first be verbalized or recorded into documents, manuals, etc.
(Externalization). We can say that this “standardizes” the knowledge. The next
step is for this material to be used by individuals in order to create and expand
their personal tacit knowledge (Internalization). If this is done on a wide-basis
within an organization, and from the same “standardized” foundation of explicit
knowledge, the individual tacit knowledge that is created by the employees
becomes part of the organizational culture. Honda and Sony are prime examples.
According to Nonaka and Takeuchi’s research, “…among the 4 modes of knowledge
conversion, externalization holds the key to knowledge creation, because it creates
new explicit concepts from tacit knowledge” [87]. This allows for these to be shared
more easily. And, it is this type of process which a significant number of Japanese
companies utilize based on the socio-cultural origins of their views on knowledge and
learning. One of the areas our research will focus on is the tacit to explicit
( Externalization ) creation and transfer which we contend is central to successful
knowledge transfer between parent and subsidiary and in fact one of the central
hypotheses for the Nonaka and Takeuchi text in the way how Japanese companies
create knowledge. Our research will extend Nonaka’s and Takeuchi’s in the sense that it
will focus on the relationship between parent and subsidiary something that was not
directly addressed in prior research.
Table 2-1 : Four Modes of Knowledge Conversion ( This table is a variation of Figure 3-2 in Nonaka and Takeuchi [87] )
TO : Tacit Knowledge Explicit Knowledge
Tacit Knowledge Socialization Externalization FROM :
Explicit Knowledge Internalization Combination
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Nonaka and Takeuchi’s research outlined 5 conditions required in an organization in
order to promote the knowledge transfer process : intention, autonomy, fluctuation (or
creative chaos), redundancy, and requisite variety. We will show how these relate
within the scope of our investigation specifically for the parent-subsidiary operational set-
up and relationship. Further, one of the first requisite steps that the authors identify in
creating and sharing knowledge is sharing tacit knowledge. They also admit that this is
probably the most difficult step as well since tacit knowledge can not be communicated
of transferred easily and depends on individual background, personal perspective, inner-
motivation and emotions, feelings, etc. [87]. Our research and investigative approach
will extend this concept by considering and integrating facets of communication theory.
Once again, extending the potential established by Nonaka and Takeuchi.
A further interesting point by the authors is the concept of middle-up-down
management which, they contend, Japanese companies follow and is responsible for
an improved knowledge creation and transfer [87]. Essentially this is an iterative process
where it’s the middle-management organizational structure that drives the critical
knowledge process both downward to the rank and file, and upward to top level
management. According to Nonaka and Takeuchi, this factor emphasizing the
importance of middle-management is the distinguishing factor between Japanese and
Western management. [87] The authors propose the following Table 2-2 as a
comparison of 3 management models regarding knowledge creation and transfer. This is
relevant for our research in the sense that it relates management structure and
organizational culture with knowledge transfer which we believe is integral to
establishing and maintaining success not only with projects and project teams but for
subsidiary performance overall.
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Table 2-2 : Comparison of 3 Management Models Regarding Knowledge Creation ( This table is a variation of Figure 5-1 in Nonaka and Takeuchi [87] )
Top-Down Bottom-Up Middle-Up-Down
Agent of Knowledge Creation
Top Management Entrepreneurial Individual
Team
Top Management Role
Commander Sponsor / Mentor Catalyst
Who
Middle Management Role
Information Processor
Autonomous Entrepreneur
Team Leader
Accumulated Knowledge
Explicit Tacit Explicit and Tacit What
Knowledge Conversion
Partial Partial Full
Where Knowledge Storage Computerized, Database, Manuals
Individuals Organizational
Organization Hierarchical Project Hierarchical Task Force
Communication Orders / Instructions
Self-Organizing Dialogue
Tolerance for Ambiguity
Low Some High
How
Weakness Strong dependence on Top Management
Time-consuming and cost of coordinating individuals
Human Exhaustion and Redundancies
Finally the authors provide a set of guidelines for enabling organizations to create a
knowledge “spiral” of knowledge creation and transfer : “…create a knowledge vision;
develop a knowledge crew; build a high-density field of interaction at the front line;
piggyback on the new-product development process; adopt middle-up-down
management; switch to a hypertext organization; construct a knowledge network with
the outside world…” [87].
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Beyond Nonaka’s and Takeuchi’s work, we have seen a significant amount of research
the past 15 to 20 years in knowledge management and a subset of that discipline –
knowledge transfer.
According to Joshi et al. “…Initial work on knowledge transfer has focused on
international technology…”[66]. Additionally, research into knowledge transfer has
focused on corporate governance in relation to such areas as strategic alliances,
mergers, and corporate acquisitions. However according to Joshiet al. [66] very little
research has been pursued in the understanding of the factors affecting knowledge
transfer within teams. The researchers have focused on knowledge transfer and a
communication-based approach in their paper : “Knowledge Transfer within Information
Systems Development Teams : Examining the Role of Knowledge Source Attributes"
[66], however the research is based on Information Systems development with a primary
focus on the source’s mechanisms in transferring knowledge.
In 1998 Thomas H. Davenport’s and Laurence Prusak’s, published Working
Knowledge : How Organizations Manage What they Know [31]. Their work provides a
more “hands-on” practical approach on how Knowledge Management and Knowledge
Transfer have been successfully integrated into core business processes, has become
part of the business strategy, culture and behavior of successful organizations. This is
interesting for us because of our discovery that in the industry within the scope of our
research there is virtually no such initiative to really integrate these into the core
business. Many of the companies we surveyed seemed to be struggling to understand :
(1) what they know now; (2) what they need to know to survive; and (3) what they
need to do about it. The research we conducted is in an industry in which tacit
20
knowledge is slowly disappearing instead of being captured; this is primarily due to the
overall graying of the workforce in this industry.
According to Davenport and Prusak the primary aim of their research is to provide an
“…understanding of what knowledge is within organizations…how is it different from
data and information… who has it… where is it… who uses it…” [31]. They argue that it
is important to build a link between knowledge management and transfer with the actual
knowledge work process this knowledge is designed to support. They go on to outline
these linkages as taking the form of people whose job is to-and-from front line processes
to the core of the organization; and project management approaches where proactive
reviews take place of what has actually been learned at each phase [31]. The authors
also outline the importance of creating a corporate culture that values the creation,
sharing, and use of knowledge. We will demonstrated that in the scope of our research
we have found that our survey companies do in fact profess such leanings but
unfortunately very few actually take any active measures to put these into place.
Furthermore based on our investigation we will demonstrate that very few companies
within the industry demonstrate a such a conducive corporate culture for this to take
place.
Davenport and Prusak provide some good definitions that remain useful for our research
and should be noted throughout. These definitions below are taken from Working
Knowledge: How Organizations Manage What they Know [31]. We have paraphrased
the definitions for Information and Knowledge.
Data – “…a set of discrete, objective facts about events… structured
records of transactions... there is no inherent meaning in data” [31].
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Information – data with meaning and some form of added value thru
contextualization, categorization, calculation, correction, and perhaps
summarization to a communicated message [31].
Knowledge – information that is put to work, utilized; it develops over time
from experience and contains judgment [31].
It is interesting to further consider the authors’ definition of knowledge in the sense that
“…knowledge contains judgment” [31]. Based on our research, the question that can be
asked and should be considered is who’s judgment needs to be considered – that of
the parent company, or that o the subsidiary, or both ? Judgment also is based on
values and beliefs which, once again, we must consider exactly who’s values and beliefs
within the parent-subsidiary relationship may take precedent. Beyond making the
argument that companies in the future must differentiate themselves within the global
economy based on what they know, the authors, clearly state that “…in a global
economy knowledge may be a company’s greatest competitive advantage” [31]. In a
sense this is a reiteration of what Nonaka and Takeuchi [87] presented as their central
theme and its what we are proposing for the more complex model of the parent-
subsidiary relationship and function of success.
An interesting model created by the authors and one which relates to our notion of
communication being a key factor in our research, is that of the “Knowledge Market”
complete with its buyers, sellers, brokers, political influences and dynamics, and its price
system. This price system is interesting because its based on 3 significant factors of
“…reciprocity, repute, and altruism…” [31]. Essentially, the authors contend that
knowledge transfer takes place based on a perceived self-interest, based on the
reputation of the source, and / or based on the “…natural impulse to help others…and
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for the “good of the firm” [31]. This is interesting because, although not acknowledge by
Davenport and Prusak, it relates directly to our research into Social Exchange
Communication Theory.
The authors also go on to outline 3 key factors for “Knowledge Market” inefficiency :
(1) incompleteness of information; (2) asymmetry of knowledge; and (3) localness of
knowledge. All of these were further investigated within the scope of our research; for
example, the incompleteness of information is directly related to language limitations
between parent-subsidiary communications; the asymmetry of knowledge and its
localness also play a huge role in how international parent-subsidiaries handle
knowledge transfer depending on parent subsidiary age, country of origin, and
organizational culture. However, Davenport and Prusak do ultimately conclude that
trust is the key for their “Knowledge Market” model to operate efficiently. In fact the level
of trust within the parent subsidiary relationship is a key factor which we surveyed in our
own research and will present here.
According to Davenport and Prusak, “…spontaneous, unstructured knowledge transfer is
vital to a firm’s success” [31]. And this transfer usually takes the form of both structured
as well as unstructured communication. The authors maintain that having personal
interaction is a key factor, but one which must be considered within the culture of the
organization. The authors contend that in recent years and with the evolution of
corporations to a more isolationist operational model where talk is not considered real
work, there is a danger that knowledge transfer will be threatened [31]. Language is
another major variable for knowledge transfer success. According to Davenport and
Prusak “…a shared language is essential to productive knowledge transfer. Without it,
individuals will neither understand nor trust one another” [31]. This is a key factor for
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our research which we will explore. Davenport and Prusak propose the following transfer
equation : Transfer = Transmission + Absorption
This is similar to several communication models which will be discussed. The authors go
on to describe some methods used to maintain a high-level of transfer by Japanese
companies; these include “talk rooms” that encourage exchange, as well as the familiar
after-work social gathering that has become famous in Japan for fostering relationships
and communication.
Davenport and Prusak’s research identified several key “frictions” that inhibit knowledge
transfer. The authors also provide potential solutions. These are reference in Table 2-3.
Table 2-3 : Frictions and Potential Solutions to Knowledge Transfer ( This table is a variation of the table on page 97 of Davenport and Prusak [31] )
Friction Possible Solution
Lack of Trust Build relationships and trust thru face-to-face meetings
Different Cultures, Vocabularies, Frames of Reference
Create common ground through education, discussion, publications, teaming, job rotation
Lack of time and meeting places; narrow idea of productive work
Establish times and places for knowledge transfers : talk-rooms, conferences, reports
Status and rewards go to knowledge owners
Evaluate performance and provide incentives based on sharing
Lack of absorptive capacity in recipients
Educate employees for flexibility; provide time for learning; hire for openness to ideas
Belief that knowledge is prerogative of particular groups, not-in-vented-here syndrome
Encourage nonhierarchical approach to knowledge; quality of ideas more important than status of source
Intolerance for mistakes or need for help
Accept and reward creative errors and collaboration; no loss of status from not knowing everything
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Beyond the basic Knowledge Management foundation material mentioned, there has
been additional research in associating knowledge transfer and culture by : Karlsen and
Gottschalk’s "An Empirical Evaluation of Knowledge Transfer Mechanisms for It
Projects” [67], and "Factors Affecting Knowledge Transfer in It Projects" [68]. Karlsen
and Gottschalk discuss five types of knowledge transfer : Serial, Near, Far, Strategic,
Expert. Their research methodology was similar to what we utilized, namely a Likert
scale type survey of 51 questions conducted in Norway in 2002. They had a fairly low
response rate of 6.5% but concluded that there was no significant non-response bias
[67]. But their focus was on Information (IT) Systems and the development of IT projects.
They do focus on project success and make the connection of knowledge transfer to
success but under a different set of circumstances within the IT industry and not within
multinational teams. They focus on culture more from the corporate point of view rather
than the national or multinational company within an industrial manufacturing setting.
We will indirectly extend the notion of Serial, Near, Far, Strategic, and Expert
Knowledge Transfer and how these relate within the scope of our research.
Additionally, Lin, Geng, and Whinston’s "A Sender-Receiver Framework for Knowledge
Transfer" [74] presents a sender-receiver approach to compensating an incomplete
knowledge transfer scenario under four different type of information structures :
Symmetric Complete, Sender-Advantage Asymmetric, Symmetric Incomplete,
Receiver-Advantage Asymmetric. This has direct similarities to a communication
theoretical framework which is important in knowledge transfer. Again the research is
focused on IT within inter-organizational communication but not within international or
multinational companies. Also the communication aspect is not widely mentioned and
fully integrated in the Lin, Geng, and Whinston research.
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There have been numerous studies done on knowledge transfer and organizational
learning, among them Elias G. Carayannis’ “Knowledge Transfer Through
Technological Hyperlearning in Five Industries” [17] which proposes a four-level and
four-mode structured approach of a system which could serve as “…a major source of
sustainable competitive advantage for an organization” [17]. This particular study is
mentioned because of the direct implication of company success based on successful
organizational learning by way of a certain knowledge transfer structure.
Soderquist’s "Organizing Knowledge Management and Dissemination in New Product
Development." [111] does in fact consider tacit knowledge and cross-functional team
collaboration in 12 global manufacturing companies and identifies 3 organizational
structures for knowledge management. His research is based on American, German,
French, and Japanese companies. But the research is lacking in identifying specific
factors in project success. So, whereas it is significant in the discipline of knowledge
transfer and culture and does demonstrate a positive correlation; there is little if any
tying-in of this result into specific project management success factors identification in
this research.
Another researcher has done work in the area of KM and more specific knowledge flow
is Juan Roman-Velázquez. In his dissertation "An Empirical Study of Knowledge
Management in the Government and Nonprofit Sectors: Organizational Culture
Composition and Its Relationship with Knowledge Management Success and the
Approach for Knowledge Flow [99] at The George Washington University in 2004, he
presented a detailed statistical analysis of knowledge flow based on 4 cultural types :
Clan, Adhocracy, Market, Hierarchy. His approach shows close parallel to what we
are proposing in our research based on survey and the gathering of data. The difference
26
here is that Roman-Velázquez focuses on the government and non-profit sectors and he
is another researcher which does not directly link the study to project success.
MIT’s Paul Carlile in his 2 papers "Transferring, Translating, and Transforming : An
Integrative Relational Approach to Sharing and Assessing Knowledge across
Boundaries" [19] and
"A Pragmatic View of Knowledge and Boundaries: Boundary Objectives in New Product
Development" [18] focuses on the transfer of knowledge by international companies
and teams but looks at this from a generalized strategic level as opposed to an
operational project-oriented approach, again tied into project success. In the later work
he outlines several approaches at this strategic level such as Syntactic (language),
Semantic (interpretation), and Pragmatic (consequences) [18].
Past research has also focused on knowledge transfer from customer to supplier [93]
and has considered further cultural ties to knowledge transfer such as Aleksandra
Hauke’s “Impact of Cultural Differences on Knowledge Transfer in British, Hungarian,
and Polish Enterprises” [55] published in 2006 which focuses on a study done among
British, Hungarian, and Polish companies. Hauke’s investigation integrated Geert
Hofstede’s [58] landmark research on culture and organizations originally done in the
1960s and which has been refined by the author ever since. It is interesting to note
Hauke’s main argument is that of the need for trust and the fact that managers play a
very important role in developing and nurturing this trust. This concept will be a central
theme in our research as well. The central concept of trust in knowledge management
has been researched and discussed extensively by Davenport and Prusak [31], Goh and
Swee [47], and others.
27
One interesting study has been conducted and presented by Michael D. Santoro and
Shanthi Gopalakrishnan’s "The Institutionalization of Knowledge Transfer Activities
within Industry-University Collaborative Ventures” [104]. It focuses on the relationship
and knowledge transfer activities and processes between industry and academia. The
study was based on 189 companies and 21 US universities and established that culture
plays a key-role and directly impacts the success of the transfer when there is a stable
direction-oriented approach and firms are more trusting. There study focused on
industrial companies in the US.
2.2 Culture
According to Grisham [50] it is usually sociologists, anthropologists, and psychologists
that normally research and investigate culture. Engineers and Engineering-related
managers have paid little attention to the topic in the past twenty years. Although
culture plays a very important role in all these fields; a role which continues to grow as
borders essentially dissolve.
The quintessential research conducted on national culture remains that done by Dr.
Geert Hofstede, professor of Organizational Anthropology and International
Management at Maastricht University in the Netherlands. Hofstede conducted his
original study in 1968 and a follow-up study in 1972. His research was published in
1980 as “Culture’s Consequences : International Differences in Work-Related Values”
[58] Hofstede defines culture as “the collective programming of the mind; which
manifests itself not only in values, but in more superficial ways : in symbols (metaphors),
heroes, and rituals” [58]. Hofstede contends that a person’s behavioral patterns of
thinking, feeling, and acting are based partially on mental programs, the source of which
28
lie within the social environments in which one grew up and collected their life
experiences. According to Hofstede “…programming starts within the family; it
continues within the neighborhood, at school, in youth groups, at the workplace, and in
both the local and extended living community” [58]. Hofstede contends that this
programming extends thru several “layers” of culture at various levels : national, regional,
ethnic, gender, generational, social class, and for those employed – organizational,
corporate, and departmental. We will investigate this aspect further in subsequent
sections in the dissertation regarding Engineering and Corporate culture.
According to Hofstede, culture is a collective phenomenon; a “…collective programming
of the mind that distinguishes the members of one group or category of people from
others” [58]. As such, it is important to realize that applying the norms of one
person, group, or society to another is not a good approach. This of course is important
for our research because of the fact that the national cultures we are interested in seem
to be very far from each other in terms of the definitions outlined above although the
basic scope of work or field we are studying is the same (large industrial gear production
and Project Management). This is a unique opportunity in which extensive research has
not been conducted; therefore it is interesting to consider Hofstede research and
theories within the context of our own dissertation scope.
2.2.1 National Culture
Nations have essentially evolved and developed fairly recently. They are political
constructs which we all belong to and associate with in some form or another as
Americans, Japanese, Greeks, Italians, and so forth. Distinguishing culture among
nations is in fact not strictly correct but for the sake of this research and others that
29
have been done, we will continue to use the term “National Culture.” We are
justified to a point in that within nations there always seems to be a strong force to
integrate societies – the classic example being the United States. However we do
remain cognizant of the fact that terms such as “typically American,” “typically
Japanese,” rightly or wrongly are used but need to be taken with a deeper
understanding according to Hofstede [58].
Hofstede’s extensively-validated research and conclusions are summarized below.
Appendix A provides a summary of Hofstede’s research for further reference.
1. Power Distance – “…the extent to which the less powerful members of
institutions and organizations within a country expect and accept that power is
distributed unequally” [58]. A Low Power Distance Index (PDI) signifies
decentralization of authority such as a flat organization where individuals essentially
consider themselves equal; while a high PDI indicates a more rigid hierarchical
working environment.
2. Individualism vs. Collectivism – the degree to which individuals are supposed
to look after themselves or remain integrated into groups (as in family), institutions,
organizations. In individualistic societies the ties between individuals are loose. In
collectivistic societies people are “…integrated into strong, cohesive in-groups…
protect their members…in exchange for unquestioning loyalty” [58]. A low
Individualism Index (IDV) indicates collectivism and confrontation avoidance; while
a high IDV indicates individualism and a tendency not to back away from
confrontation. Low IDV / collectivistic cultures usually utilize high-context (implied)
communication; whereas high IDV / individualistic cultures rely on low-context
(explicit) communication.
3. Masculinity / Femininity – the distribution of emotional roles between genders -
from tough, assertive, and materially-focused masculine to modest, tender and
quality-of-life-oriented feminine [58]. The measure for this dimension is Hofstede’s
masculinity index (MAS).
30
4. Uncertainty Avoidance – “…the extent to which the members of a culture feel
threatened by ambiguous or unknown situations” [58]. “The degree to which people
try to control the uncontrollable, and their resistance to change” [50]. Hofstede
uses the Uncertainty Avoidance Index (UAI) to measure this dimension. A low UAI
indicates trust, less resistance to change and low stress / anxiety. A high UAI
indicates distrust of others, high anxiety, higher uncontrolled emotions and
resistance to change. It should be noted that Uncertainty Avoidance is not the
same as Risk Avoidance; there is a subtle difference. The former deals with a
situation in which anything (unknown) can happen; while the latter by associating
risk, it is not an unknown any further. [58]
5. Long / Short Term Orientation – “…extent to which a culture programs its
members to accept delayed gratification of their material, social, and emotional
needs” [50]. Hofstede established the Long-Term Orientation Index (LTO) to
measure this dimension a low LTO (short-term-oriented) indicates the “right-here-
right-now” leanings of Western cultures and business where performance is
measured quarterly; while data clearly shows that a high LTO is associated with
East Asian cultures / countries such as China, Taiwan, Japan, Korea, Vietnam and
others; where time is provided for someone to make their contribution.
Hofstede’s research has been replicated and thus validated several times. C.L.
Scott’s research, summarized in the 1980 article : “Interpersonal Trust : A
Comparison of Attitudinal and Situational Factors” showed a very interesting result
for us in that “… trust varied more on the basis of the trustee’s attributes rather
than the trustor’s propensity to trust” [50]. This will be discussed within our
research because it has wide implications in regards to establishing effective
knowledge transfer structures between parent and subsidiary. Interestingly enough
Scott further “…hypothesized that integrity and ability (technical, interpersonal,
etc.) predicted trust better than simple benevolence…” [50].
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In 1990 Edward Twitchell Hall described an interesting way to understand cultures
thru effective communication [50]. One particularly interesting concept he proposed
is that of high and low context cultures. “High context cultures like the Japanese,
rely heavily on relationships while low context cultures like Americans rely more on
contracts” [50]. Hall discussed space which is the subset theory of Proxemics, as
well as time which various cultures have a monochronic (linear) approach while
others have a polychronic (multi-parallel) disposition.
In relating culture to international projects, one interesting research conducted in
2005 and published in the International Journal of Project Management was that of
Shore and Cross. They indicate that the relationship between project management
and national culture has generally not received the emphasis it deserves in the
literature. The authors pose a number of questions which specifically address
Project Management and which were paraphrased by Grisham. These are noted
here because they relate directly to our scope : “Is the study of national culture
relevant to Project Management ?”…”Which cultural dimensions are likely to affect
the management process ?”... “Which management issues are linked to the
influence of culture ?”... “Does culture affect project outcomes ?” [50].
An interesting factor to consider is the concept of cultural distance discussed in
Trenholm [118]. Trenholm defines cultural distance as “…the extent two cultures
differ” [118]. It will be important for our dissertation because we are considering
the relationship between cultural pairs of foreign parent company overseas with
local subsidiary in the United States. Recent work on this topic was conducted by
Antia, Lin, and Pantzalis in their 2005 paper : “Cultural Distance and Valuation of
Multinational Corporations” [5]. Their findings indicated that cultural distance
32
factors do in fact have a negative effect on firm valuation [5]. This is interesting
because it could potentially indicate a less than optimum operations strategy being
affected by the cultural distance factors and in turn affecting the overall company
valuation, profit, performance, etc. Antia, Lin, and Pantzalis go on to point out in
their conclusions that “…the notion of cultural distance does in fact seem to impede
the transfer of intangibles…” [5], such as knowledge thus leading to the negative
effect on valuation. The Antia, Lin, Pantzalis paper essentially expanded the
previous (1997) work of Gomez-Mejia and Palich : “Cultural Diversity and the
Performance of Multinational Firms” [49].
It is interesting to note that according to some researchers, among them Larry
Samovar and Richard Porter, based on their published material in “Intercultural
Communications” 8th edition (1997), Japan and the United States stand at the very
maximum in terms of cultural distance. We content that on the surface Japanese
culture seems to be very Western-oriented especially with the younger generation,
however there are deep-rooted differences which in fact do make this pairing one of
the most culturally distant. We shall now examine this further from a knowledge
management perspective.
According to Nonaka and Takeuchi [87], the Western tradition on knowledge,
learning, and reasoning has a long history going back to classical Greece and even
further, while there is almost none to speak of in Japan. In Western tradition the 2
dominant approaches are rationalism (mathematics is a good example) and
empiricism (experimental data-based science) [87]. Paraphrasing Nonaka and
Takeuchi - the “Japanese” approach to knowledge, corporate management practice,
as well as everyday life in general, integrates : Shinto, Confucianism, Buddhism,
33
Taoism, and Western Scientific Materialism [87]. The Japanese value system itself
stems from these 5 areas, greatly influencing corporate culture and thought.
According to Nonaka and Takeuchi, these make up the so-called “Japanese ethic”
which is a very important aspect to consider in terms of culture [87].
Shinto emphasizes harmony of elements and holds that Japanese race is
descended from gods. Thus the overwhelming concept of harmony in all
surroundings and situations and the traditional belief of superiority of the Japanese
race is a long-standing tradition.
Confucianism was brought to Japan from China approximately 2,500 years ago and
is more of a social code of rules of behavior rather than a religion. Confucianism
identifies types of relationships with distinctly clear patterns of behavior that govern
each. We contend that this distinct social code is easily transferable to Japanese
corporations (especially the very conservative companies) in relation to their
seniority system.
Like Confucianism, Buddhism and Taoism also originated in China and were
originally brought to Japan approximately 1,000 years ago. Japanese society
developed its own mixture of these two concepts calling the result Zen Buddhism.
Zen stresses meditation and concentration and actually reinforces Shinto [87]. In
modern Japan, traditionalists still practice these concepts.
According to the well-known author on Japan Boye Lafayette De Mente, an
additional and interesting basis for modern day Japanese values and behavior is
the notion of wet-rice farming. De Mente supports the claim of several historians
34
that the introduction of fairly complicated wet-rice farming to Japan from China
created a lifestyle that instilled the people of Japanese with qualities of patience,
perseverance, diligence, cooperation, and group dependence. Maintaining wet-rice
farming systems is virtually impossible for one individual or even one family, and
requires those qualities mentioned above. The fact that Japan is an isolated country
of which the majority of the terrain is very rugged and natural resources are
relatively scares, only adds to the difficulty. In Japan the saying goes “eating rice
from the same pot” meaning : we, the Japanese, are all in it together. This “group
think” plays an important role in knowledge creation and use. It is the idea that the
group is more important than the individual which enables many Japanese
companies to create and disseminate much information to all in the company
instead of keeping information compartmentalized.
From the above descriptions we can say that for the Japanese, knowledge means
wisdom that is acquired from the perspective of the whole personality; knowledge
that develops from relationships; and knowledge through flexibility. This is one of
the central themes of Nonaka and Takeuchi [87]. According to Nonaka and
Takeuchi, “In Zen Buddhist training students are required to devote themselves to
the world of ‘non-logic’ throughout their learning process” [87]. This is virtually
opposite of rationalism in the West. This emphasizes direct personal and physical
experience over intellectualism and logic of the West. Furthermore and according
to Nonaka and Takeuchi, “…while most Western views of human relationships are
atomistic and mechanistic, the Japanese view is collective and organic…” [87].
Thus the main distinction between Western and Japanese thought on knowledge is
one of the scientific vs. the humanistic approach.
35
In the early part of the 19th Century the well-known sociologist Frederick W. Taylor
attempted to “manage by science.” He prescribed certain scientific methods to
organize and operate work. Scientific Management was “…an attempt to formalize
workers’ experiences and tacit skills into objective and scientific knowledge...” [87],
according to Nonaka and Takeuchi. This approach did not lend itself to
personalization whatsoever.
In the 1920s and 1930s a group of management academics at Harvard headed by
the well-known George Mayo conducted experiments that established relationships
between employee morale, employee sense of belonging, and constructs based on
high levels of personalization (in effect the opposite of Taylor). Mayo went on to
develop a new management theory of “human relations” which presented
individuals as social creatures inherently linked to their social structure both in and
out of the workplace. Mayo’s theory touches upon the Japanese way of
management and group culture.
On the surface one may consider that the value system in Germany is similar to
Japan’s. German’s have an innate desire to seek consensus and a strong respect
for maintaining order. This is reflected in the German phrase : “Ordnung muss sein”
(there must be order !) [85]. One expects the same sense of group identity as
found in Japan, to also exist in Germany. Decisions are made based on one’s ties
to society, company, and family, though not necessarily in that order; and any
actions or decisions that disrupt the social order are seen as inherently wrong.
Furthermore, according to Morrison and Conaway [85], Germans do demonstrate
substantial individual freedom which is based on their ability to compartmentalize
36
and distinctly separate norms of behavior accordingly. Therefore as long as one
satisfies the requirements to their group, personal behavior may have some latitude.
The author of this dissertation personally witnessed a relatively minor act while on a
German train which somewhat supports this concept.
“While traveling on a train outside Berlin in 1999, we saw 4 German youths
around the ages of 15 to 20 years old sitting on the train seat with their feet,
punk-type leather boots and all, on the seats opposite. The interesting point was
that all of them had placed newspaper on the seats so that they would not dirty
these seats having their feet up.” ( Author’s personal observation )
Of course this is of minor consequence and one small observation, but it somewhat
crystallizes the idea noted above, namely that Germans value their individuality and
personal freedom as long as social obligations and requirements are satisfied.
Along with order, punctuality is key in Germany. According to Morrison and
Conaway, Germans can be “…very risk-averse and cautious about making
decisions… and they are more oriented toward near-term issues…” [85] (as has
also been substantiated by Hofstede’s LTO or Long-Term Orientation Index).
Germany has historically been closed to outside information and overall variation.
According to Hofstede, in German schools, the curriculum favored is a highly-
structured approach with distinct objectives to be met . Hofstede goes on to say that
“German students are brought up in the belief that anything which is easy enough
for them to understand is dubious and probably unscientific” [58]. Teachers and
knowledgeable elders are shown respect and this sense of mentorship and
development can also be seen in the country’s apprentice program which, although
37
becoming less and less popular in Germany, still remains a major structured
conduit to the country’s skilled workforce.
The concept of knowledge and knowledge transfer is treated differently in Germany
than Japan. While Japan may focus on the human side of this transfer; Germans
tend to focus on the technological side or information-management “tools.”
Interestingly-enough Germany ranks very high in the development of such tools,
especially for business. While the United States and to a lesser extent, the United
Kingdom, have focused research in these primarily revolving around security, it is
Germany who in effect has been gaining ground in such tools as ERP and CRM
systems (arguably a kind of knowledge management systems). One of the most
popular system currently is SAP.
One can make the case that in Japan the sense of obligation to the group is the
central focus. In German culture a sense of structured-order is the key. In Italian
culture its relationships. The sense of relationship to family as well as regional
culture is very important. Establishing strong, trusting human relationships is key
and there is a strong sense of loyalty to one’s family, and close regional and
professional associates.
According to Morrison and Conaway [85], the cognitive style of Italian culture is
based on readily accepting information that may be provided by a relatively
knowledgeable source. However, the processing of this information is very
subjective and associative according to Morrison and Conway. “Subjective feelings
are more important than faith in an ideology or objective facts in deciding what s
true” [85].
38
This is different than the Germans who are analytic and objective; but it’s somewhat
similar to the Japanese who are themselves subjective in their thinking but who do
in fact put much more emphasis on traditional values than either the Italians or
Germans. Furthermore, according to Morrison and Conaway, Italian culture is very
diverse but at the same time there is a sense of “…cultural resilience and
continuity” [85]. This is something similar to the Japanese.
2.2.2 Corporate / Organizational Culture
According to Eisenberg, Goodall, and Trethewey, there are 3 broad perspectives
that categorize recent organizational culture research : practical, interpretive, and
critical-postmodern. The practical approach views an organization’s culture as
another “feature” of that organization that can be created by management and
utilized in order to improve the effectiveness of the organization. According to the
authors, this approach was hypothesized and described by Terrence Deal and Allan
Kennedy in their 1982 text : “Corporate Cultures : The Rites and Rituals of
Corporate Life.” [as referenced in 37] Furthermore, the popular text “In Search of
Excellence : Lessons from America’s Best-Run Corporations” by Peters and
Waterman [as referenced in 37] also subscribe to this view.
The interpretive view essentially contends that culture is too complex to be
managed by one or several individuals of a company. According to Eisenberg,
Goodall, and Trethewey, the interpretive view treats culture as a socially-
constructed entity, one which is always in flux and based on the everyday
communicative behaviors among the members of an organization [37]. This
39
approach to understanding culture, according to Eisenberg, Goodall and Trethewey,
has shifted our focus in recent times towards understanding how people
communicate and create meaning within their communication. This is important in
knowledge management and transfer, specifically in tacit knowledge transfer.
Finally the critical-postmodern view of organizational culture supported by the
researchers Stanley Deetz and Joanne Martin, considers degrees of integration,
differentiation, and fragmentation in describing organizational culture.
Although recent work in organizational culture has experienced a revival primarily
due to globalization and the need for multicultural management, organizational
culture research is actually not a new discipline. Research in organizational culture
has been conducted since Max Weber’s Theory of Bureaucracy. A comprehensive
review of Weber’s original theories can be found in The Theory of Social and
Economic Organizations. In the early 1930s the well-known Hawthorne studies at
Western Electric Company in Chicago provided additional insight the field of
organizational culture [96]. For our research our focus will be on organizational
culture and how it relates to communication and knowledge transfer.
Although there have been numerous definitions of organizational culture in the
literature, we focus on theories of organizational culture which emphasize the ways
“…people construct (a shared) organizational reality…” [75], essentially identifying
what its members consider meaningful and valuable. John Van Maanen and
Stephen Barley’s 1985 work entitled “Cultural Organization: Fragments of a
Theory,” outline four domains of organizational culture which are relevant to our
research in considering culture in relation to communication; these are
paraphrased here : the Ecological Context – deals with the surroundings or
40
physical world within which the organization operates; Differential Interaction –
establishes and describes the networks of the organization; Collective
Understanding – identifies the content of the culture of the organization such as
values, ideals, ideas, beliefs, practices; Individual Domain – the practices and
actions of the individuals within the organization [75].
As one can easily interpret based on these domains, organizational cultures are
always in a state of flux based on a continuously-changing environment.
Furthermore Van Maanen and Barley identify the fact that a single culture within an
organization is almost impossible; with the exception perhaps of IBM in the 1960
and 1970s (author’s personal note). They contend that often subcultures identified
with particular groups, departments, sections, functions, processes, systems will
emerge. This will be a key point in the research of this dissertation and one which
has not been investigated to a great extent. Another key area which has only
recently been considered for in-depth research is the fact that there is a
fundamental shift in the overall research in organizational culture with a greater
emphasis of this idea of flux tied into communication and the notion of shared
meaning and understanding emerging from communication theory – a central
aspect of the research in this dissertation also directly related to the concept of
shared meaning within the context of tacit knowledge. According to Littlejohn and
Foss :
“…recent work on organizational culture has marked an
important shift from functionalism to interpretation – from the
assumption that an organization has pre-existing elements that
act together in a predictable manner, to the assumption that
there is a constantly-changing set of meanings constructed
through communication” [75].
41
According to Michael Pacanowsky’s and Nick O’Donnell-Trujillo’s 1983 work
“Organizational Communication as Cultural Performance,” [as referenced in 75],
organizational culture is something which is “…created, maintained, and
consistently modified thru daily interaction within the organization” [75]. Their work
extended that of Victor Turner’s 1974 “Dramas, Fields, and Metaphors.”
There is a tremendous amount of research on organizational culture but the focus
of this dissertation must evolve around previous and specific research in
conjunction with communication. The basic concept that we would like to identify is
that organizational culture, and in fact, organizations themselves are created thru
communication which is a core tool in the transfer of knowledge, specifically tacit
knowledge. Since our research is international in nature which involves certain
aspects of Japanese organizations some review and discussion can be made on
certain aspects of Japanese corporate culture as it relates to knowledge
management and transfer.
According to Chen [21] as with Japanese society in general, Japanese companies
are fairly rigidly organized and very hierarchical. He contends that, “although
companies promote a sense of equality through equal compensation and wage
parity this is true only within each specific level of the organization, that is, these
concepts are valid horizontally not vertically” [21]. At the top of the organizational
structure is the kaicho (chairman), who is followed by the shacho (president). In
most companies however the vast majority of the actual work is accomplished by
the kacho (department manager). This is important as we will see later.
42
Leaders in Japan tend to be generalists and not so much specialists in something.
Their main responsibility is to maintain the morale of their workers, who do the
actual work and keep the company functioning. Furthermore there is a strong
tendency for Japanese people to choose their leaders with personal qualities rather
than particular set of skills, experience or some specific knowledge. Younger new
employees are observed in a very systematic manner usually by their direct
supervisors and the very strong HR department which many bigger Japanese
corporations maintain. As these younger employees are developed and come up
the ranks their futures within the company are being planned. These employees are
likely to be good listeners and good harmonizers working towards group cohesion.
Above all wa or harmony is of prime importance to both Japanese society as well
as to the Japanese organization, especially the more traditional companies. The
Japanese try to promote wa in all social situations of their daily lives. Harmony is
the single key for maintaining face for Japanese and many Asian cultures. The goal
for Japanese managers is to maintain group togetherness.
According to Nonaka and Takeuchi [87] Japanese managers see themselves as
humanists with a primary focus on their group. However, Japanese humanism is
not the same as Western humanism. IN the West the focus is on the individual, in
Japan its on relationships between an individual and a group [87]. Japanese strive
to develop a self that is in harmony with the surroundings while in the West the
exact opposite occurs. Westerners strive to express a unique personal character
that sets them apart individually.
We have seen that harmony and relationships are very important. One method
promoting these is Ringi seido a commonly-used formal procedure of
43
management by group consensus. A ringisho is a proposal that originates in one
section, and is forwarded to all relevant sections on the same level, the section
heads, the managers, the directors and the president of the company [21]. The
ultimate purpose of this system is to eliminate dissension and get general
agreement on a proposal. This system provides for greater participation in the
decision-making process within the Japanese company. Essentially any decision
adopted through this method has already been agreed upon. An added benefit of
this system is the fact that many individuals throughout the company gain a wide-
range of information and valuable knowledge on certain particular important
aspects and decisions of the corporation; thus better, more informed decisions can
be made leading to greater innovation; and, according to Nonaka and Takeuchi, a
spreading of knowledge within the company takes place.
According to Nonaka and Takeuchi, in Japanese corporations, middle managers
are at the very center of knowledge management. Although Japanese companies
are very structured and hierarchical, much weight and decision-making takes place
at the mid-management level. This is unlike the West which has adopted primarily a
Top-Down approach or more recently a Bottom-Up approach with empowerment
and other similar programs.
As described by Nonaka and Takeuchi, the Top-Down approach is the
quintessential hierarchical model. In terms of knowledge creation, this occurs within
an information-processing approach. Basic information is filtered upward to the top
management who then use this to create plans and orders which are then passed
down the pyramid to those assigned to carry them out. Top management concepts
become the operational conditions for middle managers who must decide how to
44
make them happen. The middle managers then make the operational plans for the
“front-line” employees who must implement them. The Top-Down approach is well-
suited for dealing with explicit knowledge. But, essentially in controlling knowledge
creation from the top, it tends to neglect the development of tacit knowledge that
occurs on the “front-lines” [87].
In the Western Top-Down model, middle managers process much information but,
they tend not to have a major role in creating information. As stated above this
approach can be said to be more information processing (flow) instead of
knowledge creation and management.
The Bottom-Up approach is centered on autonomy which, according to Nonaka and
Takeuchi, is something that enhances tacit knowledge. Top management serves as
sponsor of entrepreneurially minded front-line employees. But, a negative aspect of
this model is that more autonomy and less interaction takes place within the
organization; a kind of “every-man for himself” mentality. Thus knowledge is created
individually and not necessarily optimized by interaction (culture and
communication), and in many cases not shared or disseminated within the
company as it should be.
According to Nonaka and Takeuchi [87], in both Top-Down and Bottom-Up,
knowledge conversion is not optimized but limited. suggests a third approach
focused at the middle. It is the middle managers which create knowledge and
generate what they refer to a “double knowledge spiral,” involving both top
management and front-line employees. These middle managers are usually the
leaders of development teams, self-organized task forces, and other such intra-
45
departmental groups. Thus, according to the authors, they are at the “…very center
of knowledge management, positioned at the intersection of both vertical and
horizontal flows of information within the company” [87]. As paraphrased from
Nonaka and Takeuchi - these managers are the so called “knot” that binds top
management with the front-line or the “bridge” between visionary ideals formed at
the top and the often chaotic reality which exists at the bottom front-lines. These
middle managers are the so called true “knowledge engineers” in Japanese
corporations [87].
Finally in considering the question : “Why is culture so important for a
organization ?” We can consider the following by William Schneider as outlined in
the 2001 Doctoral dissertation of Vincent Michel Ribiere [96] but slightly modified by
the author. Culture is important because :
“…it provides consistency for the organization and its people; it provides
order and structure for activity within the organization; it establishes and
internal way of life for members; it determines conditions for effectiveness; it
strongly influences how an organization is structured; it sets the patterns for
internal relationships among members; it defines effective and ineffective
performance; it anchors an organization’s approach to management; it
provides the boundaries for strategy and strategic planning” [96].
2.3 Communication : Methodologies, Mechanisms, and Tools
“Communication is at the heart of all organizational operations and international
relations. It is the most important tool we have for getting things done. It is the
basis for understanding, cooperation, and action. Yet communication is both
hero and villain – it transfers information, meets people’s needs, and gets
things done, but far too often it also distorts messages, causes frustration, and
renders people and organizations ineffective ” [53].
46
Excerpted is the transcript of Avianca Flight 52 from Bogotá Columbia to JFK
New York. The flight ran out of fuel, crashing in Long Island in Jan. 1990; killing
73 passengers. ________________________________________________________________________________________
Captain to Copilot : “tell them we are in emergency”
Copilot to Air-Traffic Controller : “we are running out of fuel…l”
Air-Traffic Controller : “climb and maintain 3,000”
Copilot to Air-Traffic Controller : “uh…we’re running out of fuel”
Air-Traffic Controller : “I’m going to bring you about 15 miles northeast and then turn you back……is that fine with you and your fuel ?”
Copilot : “I guess so…..” ________________________________________________________________________________________
Taken from Exhibit 2-1 in Harris and Moran’s Managing Cultural Differences [53].
2.3.1 Theoretical Basis
We contend that one cannot maintain nor even initiate any form of meaningful
knowledge transfer without utilizing various forms of communication. As with
considering the cultural aspect of knowledge and knowledge transfer,
communication also is fundamental. How does one define “communication” ?
Certainly it is not an easy task since “communication” and the verb “communicate”
are two of the most overworked terms in the English language according to
Theodore Clevenger in his 1991 work “Can One Not Communicate?: A Conflict of
Models.” Frank Dance’s paper “The Concept of Communication” published in
1970 in the Journal of Communication, provided a major step forward in defining
communication within 3 basic dimensions : level of observation, intentionality,
and judgment. Furthermore scholars have also begun to distinguish between
Eastern and Western traditions in defining communication. While “…Eastern
theories focus on wholeness and unity…” Western norm is to focus on the parts,
packets, essentially the fragmented portions of communication… “without
47
necessarily being overly concerned with the integration or unification of those parts”
[75]. Sarah Trenholm in her text “Thinking Through Communication: An
Introduction to the Study of Human Communication” proposes several practical
definitions. It is noteworthy to paraphrase these here : “a process of acting on
information”; “…a process through which we make sense out of the world and
share this sense with others…” ; “ a process in which a source transmits a
message to a receiver with conscious intent to affect the receivers behavior…” ;
“the transmission of information, ideas, emotions, skills, etc., by use of words,
symbols, pictures, figures, graphs, etc.” [118].
All of the above definitions play some role within the context of knowledge transfer,
for example it is critical when transferring tacit knowledge to be able to define the
background meaning of that knowledge. It is certainly not simple data and
information which one can argue is not even considered explicit, let alone tacit
knowledge. In order for us to make the connection between communication and
knowledge transfer we can consider three different models of understanding
regarding communication : Communication as action, interaction, and transaction.
In 1949 Charles Shannon from MIT and Bell Labs described communication as a
linear process comprised of several key elements : source, message, receiver,
channel and noise [118]. This linear action model takes a fairly narrow and
simplistic view in that it suggests that a person is only a sender or a receiver. It
does not fit our concept within the scope of knowledge transfer. In 1954 Wilbur
Schramm proposed that the relationship between sender and receiver be
considered. Certainly this is a step in the right direction regarding our concept with
knowledge transfer simply due to the fact that within a company one must take into
48
account the relationship between the parties involved in the transfer, along with the
protocols, processes, procedures, and norms depending on how the company is
structured, whether rigid or loose hierarchical, flat or cross-functional. This concept
of relationship was utilized in establishing portions of our survey. Schramm
proposed a circular interactional model of communication which emphasized
two-way interaction not seen in Shannon’s earlier linear model. An additional
important feature of this model that we are interested in is that it takes into account
a person’s field of experience or how a person’s culture, experiences, and heredity
influence that person’s ability to communicate [124]. This of course now ties in the
very important culture variable.
A similar concept is presented in Littlejohn and Foss’ text “Theories of Human
Communication” [75] which propose an interesting basic three-stage model of
inquiry as a starting point for understanding communication. According to the
authors “…the first stage is asking questions, …the second stage is observation,
…and the third stage is constructing answers” [75]. This parallels to some degree
Dance’s three basic dimensions of observation, intentionality, and judgment
mentioned earlier. Even though this may seem fairly straight-forward, the important
point that the researchers make is that inquiry is not linear but a circular,
interactional model similar to Schramm’s.
It is these ideas from basic communication theory that take us one step closer to
applying the concept to knowledge transfer, however, we are not there yet and
need to go even beyond both the linear and the circular models and consider a third
transactional communication model initially proposed by D.C. Barnlund in his
1970 paper : “A Transactional Model of Communication.” This model emphasizes
49
the simultaneous and continuous sending and receiving of messages in a
cooperative manner in which the sender and receiver are mutually responsible for
the effect and effectiveness of the communication. In the linear model meaning is
sent from one person to the other; in the circular model meaning is achieved thru
feedback; but in the transactional model the participants “build shared meaning”
[124]. This is directly related to our concept of successfully managing knowledge
transfer especially with tacit knowledge. The three basic models discussed here
are shown in Figure 2-1 below.
Figure 2-1 : Three Basic Models of Communication. ( These are variations by the author of Fig. 1.3, 1.4, and 1.5 in West and Turner [124] )
50
An additional factor to consider is the context or environment in which
communication takes place. This is situational and essentially has 6 levels :
Interpersonal, Small Group, Organizational, Intercultural, Public or Rhetorical,
and Mass. There is a wide range of research that has gone into each context
including relationship maintenance strategies, group decision-making,
organizational hierarchy and power, employee morale, culture and rule-setting,
ethnocentrism, to name just a few. Based on our dissertation’s scope we will
consider Interpersonal, Small Groups, Organizational, and Intercultural
communications.
Table 2-4a summarizes the mapping of the various communication theories
researched based on the holistic approach of Robert Craig’s work “Communication
Theory as a Field.” Craig divides the world of communication theory into the
following six traditions.
Semiotic – “…based on signs which can be considered stimuli designating some
other condition(s)… and symbols which usually designate complex signs and
where meaning arises from the relationship among an object, a person, and a
sign...” [75].
Phenomenological – “this tradition concentrates on the conscious experience of
the person ….and how individuals actively interpret their experiences and
come to understand their surroundings…” [75]. Stanley Deetz summarizes
the three basic principles of this tradition : “…knowledge is found directly in
conscious experience; meaning is based on potential, basically how we relate
to something or someone determines meaning for us; language is the vehicle
of meaning” [75]. It is worthy to note the indirect ties with the field of tacit
51
knowledge and its transfer, especially within the context of mutual language –
something that will be explored within our research.
Cybernetic – based on “…complex systems in which many interacting elements
influence one another” [75]; the idea of “system” and “networks” are central
themes to this particular tradition.
Sociopsychological – based on Western thought of the individual being the
central focus, including “social behavior, psychological variables, individual
effects, personality traits, and perceptions and cognition” [75]. Key questions
that can be established based on some of the key themes of the
Sociopsychological tradition are : (1) How can individual knowledge transfer
behavior be predicted ? (2) How does an individual take into account and
accommodate different knowledge transfer situations ? (3) How do
communicators adapt their behaviors to one another regarding the sharing of
knowledge ? (4) How is information assimilated, organized, and used in
ultimately deriving knowledge and leading to successful project strategies
and plans ? (5) How is information integrated to form beliefs and attitudes
affecting project success ? (6) How are expectations formed in interactions
with others primarily within international project teams ? These are
paraphrased based on the original text in Littlejohn and Foss’ “Theories of
Human Communication” [75].
Sociocultural – this tradition is culturally-centric and based on Eastern thought of
the Group being the central focus and “…how people together create the
realities of their social groups, organizations, and cultures” [75]. Research
here focuses on how identities are established thru the social group.
Needless to say this is a central theme of the Japanese culture.
52
Critical – based on the themes of privilege and power which are central to
hierarchical organizations. Concerned with the understanding of power
structures, beliefs, and ideologies, and how interests are served within these
structures. [75]
Table 2-4a below is originally constructed based on the general content structure
found in Littlejohn and Foss’ “Theories of Human Communication” [75]. It serves as
the starting point for our identification of potential gaps in past literature which we
need to address in our research.
53
54
We would like to better-define and refine our communication theory mapping and
identify which theories relate to our dissertation scope in the closest manner. The
first step in doing this is to eliminate the Semiotic, Phenomenological, and Critical
traditions since, based on our detailed review, they do not relate very directly to the
three areas of our theoretical construct, namely : (1) Knowledge Management /
Knowledge Transfer, (2) Project Management, and (3) Culture. Once this is done,
we also code the remaining theories based on their relationship to our three
construct areas and we obtain Table 2-4b shown below. This is an originally-
constructed table from 2-4a.
55
We next eliminate those remaining theories within the 3 remaining traditions that we
the
wn
could not directly associate with any of the three areas of our construct and maintain
those in which we could directly associate with KM / KT, Project Management, and
Culture. We also identify the major gaps in the remaining map, noting that these
seem to exist primarily in the Message and Communicator topic areas as well as
Culture section. All of which offer opportunities for research segments within our
framework from the communication topic point of view. The remaining map is sho
in Table 2-4c below. This is an originally-constructed table from 2-4b.
56
As a final refinement in our mapping, we replace the 3 tradition-identifying columns
(Cybernetic, Sociopsychological, Sociocultural) with the three constructs associated
to our framework / dissertation (KM / KT, PM, Culture) and align the theories we
associated closely with each construct (per the color coding) in rows across the 6
communication topic areas. By doing this we can identify more specifically which
relationships between our construct areas and the general areas of communication
theory still maintain a deficiency in terms of theoretical background. We therefore
can identify more specific focus areas of our research and further justify the overall
theoretical framework we created. This is an originally-constructed table from 2-4c.
57
This final Table 2-4d now exposes some key points. KM / KT can be related to
almost all of the 6 topic areas of communication. The only one in which we found
specific and direct communication theory relating to KM / KT was in the area of
Culture which we note with the Gap notation. In effect we have mapped nine
established communication theories linking the main communication topic are
Knowledge Transfer. We have also identified seven communication theories closely
linked to Project Management which address four out of six communication topic
areas. It is logical to see that the majority of these theories, four out of seven relat
closely to Group communications. It is interesting once again to see that there is
some deficiency in the area of Culture, but also in the area of Organizational
Communication. What this indicates, surprisingly, is that there is little direct
theoretical basis and research done on how Project Management fits betwee
Organization and also the culture of that organization – therefore PM, Organization
Culture, and National Culture is a logical research linkage we can pursue. This is
very interesting because it does present a focus on a key area of our research and
further justifies our theoretical construct which overall seeks to link Knowledge
Transfer with Project Success (PM) / International Engineering Team success
(Culture).
no
as with
e
n the
al
.3.2 Groups and Teams
ased on our dissertation focus on knowledge transfer and international
reas of
can
2
B
engineering team and project success we must consider research in the a
team and group communications since it has been stated that “…the key to
successful… groups is effective communication” [54]. Team communication
58
be defined for our purposes as “…..the transactional process of using symbolic
behavior to achieve shared meaning among members over a period of time…” [54].
In 2001 S.L. Tubbs published “A Systems Approach to Small Group Interaction” in
which certain characteristics of complex systems were applied to group interaction
and dynamics. The reason for his approach was the fact that communication within
groups is often disorderly, chaotic, discontinuous, and constantly evolving. Although
the research encompassed a general holistic view of group communications, it was
not focused on aspects of international engineering teams. The concepts developed
can be applied to our research as well but we feel that our work will go beyond and
focus on specific conditional interaction of specialized teams with subtle
communication patterns and characteristics.
One researcher which has considered group functioning within a multicultural
scope is John Oetzel and the development of his Effective Intercultural Work
Group Theory [as referenced in 75] He proposed 3 important cultural differences
Clusters : (1) individualism vs. collectivism – similar to the work of Hofstede in that
it considers and gages a culture’s tendency towards individualism vs. the group;
(2) self-construal - demonstrating “…how members think about themselves…”[75];
and (3) face concerns – “…how group members manage personal image…in terms
of self-face, other-face, and mutual-face…” [75] Oetzel realized that “…cultural
differences necessitate effective communication but also make it difficult” [75].
Unfortunately this dilemma is very much still evident today.
In relating a team’s or group’s role normative role within an overall organization, the
1969 work of E.H. Schein, “Process Consultation: Its Role in Organizational
Development” stands out. Schein researched the collective values of groups, how
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these are formed, and how they relate and are prescribed by an organizational
culture or an underlying understanding of how groups are expected to operate. This
is interesting because it serves as a linking components of our research which does
consider the role of the organization and its overall structure.
Additional research on roles and there function in teams has been done by A.P
Hare, Griffin, Bales, Bochner, and others as referenced in Harris and Sherblom [54].
Overall the research in this area has been undertaken from a higher-level
perspective and what we propose in our dissertation is to apply some of the
concepts within a detailed extension of our framework of international engineering
project teams which seems to not have been researched to a great extent.
Table 2-5a below summarizes the overall mapping of group role behavior that has
been researched. This table is a modified version found in Harris and Sherblom [54].
This is presented here for 2 reasons : (1) so that we can present a more visual
approach in identifying key areas related to our research as done similarly with the
communication theory mapping above and furthermore integrating and
complimenting the mapping above in coming to a final “gap analysis” conclusion
that will be addressed by our research; and (2) presenting one possible ideal role
structure for teams which can be referenced by what we conclude within our
research in terms of what companies within our scope are doing and what they are
not doing in support of our conclusions.
Table 2-5a below is a modified version of Table 3.1 found in Harris and Sherblom’s Small Group and Team Communications [54]
60
As done previously with communication theory mapping we identify and code those
roles in Table 2-5a which directly contribute and relate to Knowledge Management
/ Knowledge Transfer, Project Management, and Culture. The same color coding
scheme is used. The resulting Table 2-5b highlights the relationship between our
three constructs and Group Task vs. Group Maintenance Roles. Table 2-5b is an
originally-constructed table from 2-5a.
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Considering our refinement one step further, we can eliminate the Negative Roles /
Self-Oriented Behaviors column, focusing only on those characteristics we would
like to enforce and group these roles together while still maintaining them under
their respective column labeling. This is shown in Table 2-5c. What is made
immediately clear is the fact that the majority of Group Task Roles fall under a
Project Management and KM / KT orientation while the Group Maintenance Roles
are more oriented towards culture and maintaining a positive and efficient group
relationship. The benefit we can obtain from performing such visual mapping
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manipulation is that the process can indicate some strong (and not so strong)
relationships based on previous research. It can also indicate a direction in which
current and / or future research can focus in order to optimize and establish some
reasonable and expected results. With the particular method of organization of
Table 2-5c, we can focus on particular roles within the Project Management portion
of the construct and its impact on the overall Group Tasking process, the Cultural
portion of the construct and its impact on the Group Maintenance portion while
noting and taking into account some dual characteristic of the KM / KT related roles
which fall under both, although primarily under Tasking. The key is that we establish
a relationship with key areas of our proposed theoretical construct and tied them
into previous research, specifically in areas where there either is a lack of a
complete theoretical basis or there are some “gaps.”
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An additional area to note is the research done on group cohesiveness by Griffin
in 2005 and also noted in Harris and Sherblom [54]. It is worthy to note this
particular characteristic because it relates directly to one of research focal points,
namely the importance within the Japanese natural schema of behavior based both
on culture as well as the particular organization one belongs to. Cohesiveness is
essentially “…the extent to which members are loyal and committed to the
group…”[54], they identify with in various situations. One area that will be studied
within the researched proposed in this dissertation and which has not seen recent
research is that of groupthink as it manifests itself from excessive cohesiveness.
We will argue and propose a direct case study to demonstrate the real pitfalls
associated with this within the scope of our research.
2.3.3 International / Intercultural Communications
“The roots of the study of intercultural communication can be traced to the post -
World War II era when the United States came to dominate the world stage” [77].
In 1946 the Foreign Service Act was passed which established the Foreign Service
Institute (FSI). It was at the FSI that Edward Twitchell Hall initially pioneered his
systematic study of culture and communications [77].
According to Martin and Nakayama [77], there are three contemporary approaches
to studying intercultural communications : (1) the Social Science or Functionalist
approach, (2) the Interpretive approach, and (3) the Critical approach. Interestingly-
enough each approach differs in its theory integrating culture and communication.
The Social Science / Functionalist approach maintains that communication is
influenced by culture. The Interpretive approach theorizes that culture is created
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and maintained by communication. The Critical approach states that culture is a site
of power struggles and communication is a medium for this.
William Gudykunst, a leading communications researcher added to the research
done by Hofstede regarding individualistic vs. collectivistic cultures. In his paper :
“A Model of Uncertainty Reduction in Intergroup Encounters” published in the
Journal of Language and Social Psychology in 1985, Gudykunst found that different
culture, depending on their orientation, will approach a communication encounter
either directly or indirectly with the desire to either “get-the-job-done” or establish an
initial relationship beforehand. Gudykunst later extended his theory to include the
element of anxiety by introducing his Anxiety Uncertainty Management Theory
which explains the role of anxiety and uncertainty in individuals’ communicating
across cultural lines [77].
Additional work in the culture / communication arena has been conducted by Stella
Ting-Toomey in 1985 and in 2005 with Gao, Trubisky, Yang, Kim, et al. in the
development of Face Negotiation Theory [77]. We content that this is an important
aspect we have seen within the scope of our research as well.
In the area of conversational strategies and cultural differences, Min-Sun Kim in her
work : “Cross-Cultural Comparisons of the Perceived Importance of Conversational
Constraints” published in 1994, and again in 2005 with “Culture-Based
Conversational Constraints Theory,” attempts to explain how and why people make
particular conversational choices. Similar studies have been conducted by Gallois,
Giles, Jones, et al., as referenced in Martin and Nakayama [77].
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This is by no means an exhaustive listing on theories and research within this
particular area of communication. The key concept is the understanding that there
is no single theory which can be considered without limitation. All these works have
been useful in identifying variations in cultural patterns which manifest themselves
with communication but all are limited in some form or another. The reason for this
is the simple fact that the research lies across two very complex and huge areas of
study : Culture and Communication. There are many variables that simply cannot
be identified and many scholars increasingly believe that “…communication is
often more creative than predictable” [77]. Our research will focus on a particular
aspect of various theories as they apply to Knowledge transfer for which
communication is a tool, with the goal of establishing a relationship with project
management. Thus we limit our scope to these particular areas in which
interestingly-enough not much research has taken place. The key for us to utilize
those specific areas and concepts within the overall bodies of knowledge in Culture,
Communication, etc. and fit them into our construct to develop an innovative idea
within our scope.
2.3.4 Communications by Engineers
Elizabeth Varnes’ 1993 dissertation, “A Sociotechnical Approach to the Study of
Semiautonomous Work Group Communication in Technical Organizations” [121]
presented research done to understand how team members define effective group
communications. The research was undertaken using a socio-technical approach
examining the adequacy of the social system encompassing the teams, in relation
to the actual tasks that have to be performed and the technologies used to carry
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out these tasks [121]. Varnes’ research is an extension of W.A. Pasmore’s 1988
work “Designing Effective Organizations: The Sociotechnical Systems Perspective”
Within this Sociotechnical approach Varnes’ found a need and desire of team
members to utilize more effective communication tools in order to improve their
technical work. This may not seem like such a profound finding however it directly
relates to our research within our particular scope. We will demonstrate that this
same desire is expressed by technical teams within our research scope and within
the industry under investigation in general, however few companies have taken up
the call to improve their communication tools and we will show that this does impact
overall performance. We content that this is extremely important in the area of
technical communications and specification management because of the
complicated nature of the project work under investigation.
In 2000 Myra Lynette Corrello published her dissertation “Communication and the
Engineering Profession : Perspectives from the Field” [24] in which she discusses
how “…engineers perceive the role of communication in their profession and how
the phenomenon of Communication Apprehension affects their perception” [24].
She contends that “…Engineers are increasingly expected to be both effective
engineers but also marketers and that communication is becoming increasingly
important in their daily work especially when technology tools are alleviating some
of the workload pressures on the technical side of their work…” [24]. Corrello
references eight formal studies conducted from 1974 thru 1996 investigating
communication within the engineering profession.
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In 2005 Colleen Garside’s dissertation “A Qualitative Analysis of Verbal Interaction
in Mechanical Engineering Design Teams : Genres of Practice” [43] researched the
concept that “each community has its own cultural values… and these are linked to
judgments of situational appropriateness…and so does mechanical engineering as
a discipline, processes a cultural outlook on communication…” [43].
Garside’s research did take into account the specific discipline in which we are
interested in, however she approached her research from a daily work perspective
specific to Design Engineering Teams rather than large Industrial Project Teams
managed by a group / team of international engineers.
In reviewing the literature overall regarding Engineering communication we have
discovered several areas where we see some deficiencies and where we hope to
address these within the scope of our research. There has been very little research
done focusing on Project Engineering / Management and small technical /
engineering group communication. There are limitations in the research in the
areas of communication and engineering team-leadership and motivation; and in
the area of multinational engineering teams. We contend that these are
increasingly important areas especially as business is becoming global in nature
and, as Corrello correctly stated in her research, Engineers are being asked to
handle more and more non-engineering tasks. It is also important within our
context within the scope of project success and international team effectiveness.
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2.4 Project Management
Along with Dr. John Saee, as outlined in his paper : “Best Practices in Project
Management in Contemporary Global Economy,” [102] we contend that there are
essentially three interacting forces involved when we discuss Project Management.
These are paraphrased here as : (1) the overwhelming global expansion and ever-
increasing flux of knowledge; (2) the growing demand for complex, sophisticated,
customized goods and services; and (3) the continued expansion of intense global
competition. [102]
According to Vladimir Mikheev and David Pells’ “The 3rd Wave – A New Management
Paradigm for Project and Program Management,” basic Project Management “…is
maturing in most industries including energy, oil & gas, petrochemicals, pharmaceuticals,
automotive, and certain heavy industries…” [81]. Unfortunately it’s not the case in the
machinery industry which relates to our research. Mikheev and Pells describe their
concept of the maturation of project management and related research. What they call
the 1st Wave occurred from the 1950s thru about 1980 and was based on much
development that was done for World War II and the computer age. This period was
strongly focused on process development and improvement.
The 2nd Wave took place in the 1980s thru the turn of the century, 2000 and focused on
people and the criticality of leadership to project success. A defining moment in this
development was PMI’s Project Management Body of Knowledge publication in 1987
and the initiation of the Project Management Professional Certification program. The 3rd
Wave according to Mikheev and Pells [81] began in 2000 and focuses on a strategic
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global perspective, where organizations come to understand the value of Project
Management as a competitive resource that is closely tied to knowledge management.
2.4.1 Communicating Effective Project Management
The importance of communication in projects, in particular its influence on the
acceptance of change and something new is well-documented as outlined in Saee’s
paper “Best Practice in Project Management in Contemporary Global Economy” [102].
“Lack of communication has been cited as the biggest reason for project failures...” [102]
One of the key points in relating communication with project management and eventual
project success is what we refer to as “communication logistics” - quantity, quality, and
timing.
Diallo and Thuillier’s work published in 2004 – “The Success of International
Development Projects, Trust and Communication : An African Perspective” [33] as well
as Loosemore and Muslmani’s “Construction Project Management in the Persian Gulf :
Inter-Cultural Communications” [76] focus on the need to establish and maintain trust in
order to have effective communications and thus create a higher probability that a
project (in these case in Sub-Saharan Africa and the Middle East) will be successful.
Diallo and Thuillier specifically identified a strong correlation between the quality of
communication among members of the project team and success of a project within
their research scope. Muslmani and Loosemore integrated Hofstede’s dimensions and
analyzed actual communication patterns in the Arabic language; patterns which
demonstrate similarities to our research in the Japanese culture.
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Further cultural and communication research related to Project Management and Project
Success has been published by Henrie [57]; Zwikael, Shimizu, and Globerson [129];
Jansen [63]; and Riemer and Jansen [97]. Riemer and Jansen incorporate so called
emotional intelligence (EQ) factors which are directly associated with cultural differences
which is part of our research focus. The key point to be made and expanded upon from
this research is that empathy, self-awareness, and intercultural awareness, unfortunately
are qualities which are lacking in many “global engineers” and something which must be
investigated within our particular research framework and scope. The 2007 text :
“Emotional Intelligence for Project Managers” by Anthony Mersino [80] , provides a
comprehensive overview of this particular topic. The only slight drawback with this
reference however is that it does not provide a rigorous quantitative approach to
establish any relationship with EQ and project success.
Moenaert, Caeldries, Lievens, and Wauters of the University of Ghent, Belgium
published a paper in 2000 titled “Communication Flows in International Product
Innovation Teams” [83] in which they identified 5 requirements that determine the
effectiveness and efficiency of communication in international product development
teams : transparency, knowledge codification, knowledge credibility, communication cost,
and secrecy [83]. This particular research does provides some good insight into the
relationship between knowledge, specifically the codification of knowledge, that is, the
process of structuring tacit into explicit, and success of international teams. It also
touches on the effects of organizational and national culture and the socio-cultural
qualities that every organization develops. The limitation of the research however is that
it focuses on European R&D-based companies and functions; whereas our research is
based on daily operational projects which are not considered R&D initiatives
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2.4.2 The Successful Project
According to Dr. Lynn Crawford a long-time researcher in Project Management, the 1974
work of Murphy, Baker, and Fischer remains “…one of the most extensive and
authoritative research on the factors contributing to project success” [26]. They used
data from 650 aerospace and construction projects to identify 10 factors that strongly
related to perceived project success. They also identified 23 project manager
characteristics that were necessary for perceived success [86]. These are fairly heavily
focused on people and having the right team which can affect and ensure the right
processes and systems are integrated to the extent that a project will (most likely) be
successful. Furthermore, Crawford’s 2004 paper : “Senior Management Perceptions of
Project Management Competence” [27] in the International Journal of Project
Management focuses on the skills and competencies required of project management
leadership. Crawford lists 13 variables analyzed thru logistic regression analysis which
are associated with project success and project management top performers. Out of
these 13 variables, 4 relate either directly or indirectly to communication, and 5 relate to
organizational structure including impact by a parent organization [27]. This lends
support to our particular research framework.
In the 1980s several studies drew on and extended the work of Murphy, Baker and
Fischer, specifically those of Pinto and Slevin which used a sample of 418 PMI members
responding to questions asking them to rate the relevance to project implementation
success of ten critical success factors as previously identified by Murphy, Baker, and
Fischer. [26] , [91] The following factors where identified as critical by Pinto and Slevin
to the success of projects : Project Mission, Top Management Support, Project Plan,
Customer Consultation of Project Requirements, Recruitment, Selection, Training of
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Project Personnel, Technical Tasks, Customer Agreement / Acceptance, Project
Monitoring / Feedback, Communication, Trouble-Shooter. They are documented based
on Crawford’s research papers [25], [26], [27], and Pinto et al [91].
Further significant research done with project management and project success in the
1990s include that of Ashley [6], Geddes [45], Jiang [65], Zimmerer [128], Whittaker
[125], and Clark [23] . However one of the key difficulties in this area of research
remains - how to reasonably quantify the concept of project success with a formalized
universal set of criteria that can be agreed upon by general group of practitioners. In
effect, project success however has maintained a definition based on a case-by-case
situational basis. It remains subjective. This particular issue has been addressed
recently by various researchers such as Rad, Koelmans, Altman, Dvir, and others. The
most recent study has been by Lee-Kelley and Sankey. "Global Virtual Teams for Value
Creation and Project Success : A Case Study" [72] They identify key factors affecting
success; they include “…time zone and cultural differences in particular, affect
communication and team relations…” [72]. The researchers also describe effects from
diverging management agendas, leadership styles (again related to culture), and role
uncertainty, something we feel also relates to culture as per the research conducted by
Hofstede. Although they touch upon communication, the research does not delve into
actual knowledge transfer and the communications structure as tool for this transfer.
Yu, Flett, and Bowers’ “Developing a Value-Centered Proposal for Assessing Project
Success” [127] propose a value-centered approach to measuring project success. They
develop and define two key concepts in their study : Net Project Execution Cost
(NPEC) and Net Product Operation Value (NPOV). Along with these they conclude 12
possible project outcomes based on the values of NPEC and NPOV and compare final
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outcome to initial estimates. In their studies they do not directly take into account
knowledge transfer in any of their variables.
Other researchers including Dr. David Bryde’s work “Methods for Managing Different
Perspectives of Project Success” [16] have developed Key Performance Indicators
(KPI) to measure project success in this area, once again knowledge transfer is hardly
mentioned. A significant paper in the area of project functions and their impact to project
success has been written by Jha and Iyer "Critical Determinants of Project Coordination"
[64] for the International Journal of Project Management in 2005. They have outlined 20
important coordination activities that relate to project coordination and overall success.
They subsequently found that only 6 of these 20 factors were “statistically significant”
and of these only 2 were “very significant” [64]. A key area to focus on would be on how
knowledge transfer relates to these two activities that the researchers identified as
important : (1) estimation of optimum resources required; (2) agreement on detailed
methods of construction [64]. We feel (2) is of primary interest because it relates more
directly to the overall knowledge transfer function in terms of the industry we are
considering (complex machinery, assembly, setup, and start-up.
Dov Dvir and Aaron Shenhar, two key researchers in project management, have
collaborated on several occasions with Asher Tishler, Stanislav Lipovetsky, and others
to publish various works on quantifying project success. In 1998 they presented their
work - “In Search of Project Classification: A Non-Universal Approach to Project
Success Factors” [35] which concluded that the shortcomings of past research prior to
that time has been the tendency to try to provide a universal approach to quantifying
project success. They argue that project success determination is not universalistic and
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there should not be such an all-encompassing approach. They employ a linear
discriminant analysis methodology in order to first classify projects and then determine
factors for success. In their study, they identify several managerial and organizational
variables, some of which relate directly to communication style, project control, and
reporting; in additional to technical requirements definition, technical and operational
specs and capacity to meet specs. These are the areas which knowledge transfer as a
whole is important although they do not take the actual knowledge transfer into account,
rather they focus on a multitude of factors. One very surprising aspects of their 1998
research is the conclusion that “learning capability” is only a weak predictor of success.
This would be contrary to what would be expected and it is mentioned as such in their
conclusion. They propose future research into this area. We feel that our research will
relate to this more directly.
A 2002 work from virtually the same research team of Shenhar, Tishler, Dvir, Lipovetsky
and Lechler, attempts to refine the previous research into project management success
by using a multivariate, typological approach with a strict statistical methodology in
identifying the key variables. "Refining the Search for Project Success Factors : A
Multivariate, Typological Approach." [108] They concede that still no conclusive
evidence or common agreement on project success / failure measurements exists and
they attempt to further refine their previous research with additional data and variable
identification. Unfortunately (or fortunately for our research) again there is no direct
investigation of the knowledge transfer and project success relationship. This is the crux
of our research.
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2.5 Literature Review Summary & Research Potential
The research team of Dvir and Shenhar recently published their latest paper "Project
Management Research: The Challenge and Opportunity" [107] in the June 2007 edition
of the Project Management Journal, in which they identify key areas of future research
potential. This paper directs future studies of project management in several key areas
which we feel we are addressing with our research. One of these areas is the need to
provide integrative research into project management; that is, the challenge to combine
research from other disciplines. This is exactly what we are aiming to do, provide a
holistic approach utilizing research from Knowledge Management, knowledge
transfer utilizing communication methods and processes and combining these
with a cultural aspect of companies (both corporate and national) in order to
identify key success factors in project management. According to Dvir and Shenhar,
“…..this multidisciplinary approach represents a unique challenge to researchers….”
[107]. Essentially the “hole we are trying to fill” with our proposed research is that of
past research not integrating knowledge transfer processes and relating these to project
management success. In certain isolated cases, it has been attempted for IT projects
and but nothing further. In other cases, industrial projects have been considered but not
from a multinational company perspective. We focus on integrating these into a single
research target of multinational industrial companies, structuring their knowledge
transfer processes to provide the optimum probability of project success, once we
identify what constitutes project success within our scope.
As is readily apparent past research associated with the components of our current
research has been quit extensive, the problem is however this holistic approach (of
these components) that Dvir and Shenhar mention has not taken place within the
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important areas we are considering. Based on our extensive literature review, we did not
find any specific research that integrated the components we require for our research
and within the scope study we are considering. This concept can be shown in Figure 2-2
which can be considered an interim precursor to our overall research framework.
Our research is based overall on a management problem; more specifically a technical
and engineering management problem since we focus on knowledge transfer of
engineering and industrial manufacturing projects. From a higher level point of view this
is an issue of how international companies with subsidiaries in the United States
manage their operations. This will involve research in international business which as a
discipline began to develop in the 1970s in conjunction with the expansion of
international business itself. Cross-culture management research, however, was very
limited throughout the 1970s and 1980s [15]. Only in the 1990s with continued
internationalization did interest and deeper research began to emerge and take shape.
Furthermore, according to Briscoe and Schuler [15] “…much of the published research
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is based on an American perspective done by American or America-trained
researchers…research published by non-western scholars or in non-English sources
has gone virtually unnoticed…” [15], by both the academic and business world in the
United States.
As outlined in this chapter there has been significant research in project management
and what constitutes project success under various conditions. However there is no
agreement on a universal set of criteria for success. It remains subjective even after the
fundamental work of Murphy, Baker, and Fischer. Furthermore there seems to be no
significant and recent research of knowledge transfer associated with project
management success except some research in IT and civil projects. There seems to be
nothing on industrial machinery projects managed by multinational manufacturing
companies. Once again our focus is in this area because this industry is critical and
involved in practically every other type of heavy industrial, infrastructure, even
commercial segment. Also according to Henrie, “while project management literature
discusses and proposes that culture is an influence on projects, a clear theory of what
this influence is, is lacking” [57]. The area where there is a clear lack of research seems
to be in the communication structure between headquarters and subsidiary and how this
is utilized as a tool within the knowledge transfer function and how culture plays a role.
Our research will seek to realize these areas within a common framework of industrial
manufacturers and how they operate their business units / subsidiaries in the United
States and the effect this has on project success. Identifying the attributes of these
relationship for this success. Figure 2-3 provides a more refined graphical interpretation
of our research focus as developed over this chapter. This was established as an
original model for our research.
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The significance of having the right people in Project Management roles is emphasized
by several researchers including Bresnen et al. [14] Their conclusion was to create a
key role, namely that of REM Regional Engineering Manager that would coordinate and
facilitate communication and knowledge transfer. In effect these “knowledge brokers”
would be the nodes in the communication structure of international project teams
hopefully improving the probability of project success. This is an interesting concept
because it identifies with one of our own models, namely the so-called one-to-one or
point-to-point structure (See Figure 2-4 below). Unfortunately the scope of Bresnen’s
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research does not cover the particular parent subsidiary relationship which for us is a
central theme for which we have devised several higher tier communication structures
(in addition to Bresnen’s REM concept). Bresnen’s research most closely identifies with
our “point-to-point” model. Based on our research, we content that there are situations
where the other models must be considered as better optimized under certain conditions.
Figure 2-4 : Higher-Tier Knowledge Transfer Models for Parent-Subsidiary
Finally a core reference that was discovered within our research is Stock, Greis, and
Dibner’s 1996 research publication appearing in the IEEE Transactions of Engineering
Management, and titled “Parent-Subsidiary Communication in International
Biotechnology R&D” [114] This research has some close parallels to what we are
proposing, namely in the areas of parent-subsidiary communications between European
and Japanese multinational companies and their subsidiaries in the United States.
Stock, Greis, and Dibner’s research examines the flow of technical communication and
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how this is transmitted to and from parent firms. The paper presents a close parallel also
to our own methodology and this is why it is mentioned here prior to the next chapter.
However, once again this previous research does not consider the important aspect of
knowledge transfer and more importantly the transfer of tacit knowledge into something
that can be usable at either location (parent or subsidiary) in improving the chances of
project success of international teams.
Based on our extensive literature review, we can confirm that the particular research
framework, under our defined scope, we have undertaken is in fact something which has
not been researched previously and can provide both scholarly and business benefits as
outlined in Chapter 1.
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CHAPTER 3 – RESEARCH DESIGN and METHODOLOGY
The research was conducted with a survey instrument used to gather data on which a
correlational analytical methodology was utilized. “The correlational approach is effective
in determining whether, and to what extent, a relationship exists between 2 or more
quantifiable variables” [44]. The overall methodology was modeled after Dr. Vincent
Michel Ribiere’s research approach in a similar investigation conducted in 2000-2001. In
addition to this particular approach we researched and analyzed an actual detailed case
which is used as a specific illustrative example of the principles developed. The case
example content is located in Appendix D. Although our case example is used to
confirm some of our findings we realize that it does not, by any means, incorporate a full
confirmation of the theoretical construct established. This approach however is typically
considered as “…an appropriate methodology in an initial research effort that is intended
to develop some theoretical understanding…” [57]. This multi-method, or what is
referred to as triangulation has also been successfully utilized in research conducted
by Stock [114] and Jansen [63]. For our research this methodology was appropriate
and applicable since the intent was to establish an understanding of the relationship
between knowledge transfer attributes and international team project success.
3.1 Research Objectives – Hypotheses Mapping
The primary assumption going forward is that there is in fact a correlation among the
way foreign company expats and local representatives working in a subsidiary in the U.S.
and within an engineering and manufacturing function in our study population are
managed and the way communication flows between them and headquarters
(knowledge transfer). There does exist a relationship that can be identified and used to
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model and describe a knowledge transfer function or process; and this can be related to
project success.
The research objectives as initially outlined in Chapter 1 are :
Establish what is the most meaningful concept of project success to the target
study companies. How do they measure success and what are the similarities in
measuring project success among them. Establish these common factors for
success that can then be used to further the investigation.
Identify specific knowledge transfer attributes and descriptive variables of
multinational industrial manufacturing companies with foreign headquarters and U.S.
subsidiaries involved in international projects (our target companies). Make a
preliminary judgment on how these attributes and descriptive variables are
related, if at all, to the company’s project management successes; what is important,
what is not important, etc.
Identify key correlations in knowledge transfer processes between the 3 culturally
diverse groups of companies that make up the majority of our target industrial
manufacturers (German, Italian, Japanese); identify communication attributes that
related to the companies’ corporate and national culture and how these establish a
tool link with the knowledge transfer function.
Establish a final correlated relationship between knowledge transfer factors and
project success; conclude a final relationship among the attributes and variables of
knowledge transfer and project success, and establish a conceptual model for this.
Our underlying hypothesis is that there exists a correlation between how knowledge
transfer takes place within our population and the success of the population companies’
international projects. Identifying the attributes of successful knowledge transfer,
identifying the attributes of project success and establishing a correlation or relationship
between the two is essentially the higher-level goal.
This is illustrated simply in Figure 3-1.
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Figure 3-1 : Higher Level Research Objective
Knowledge Transfer
Attributes International Team / Project
Success Attributes
What is the Relationship ?
Based on this overall objective, the formal directional hypothesis is defined as :
H1 : There is a relationship between successful knowledge transfer between parent – subsidiary and organizational project success.
The overall null hypothesis of course is the logical opposite and defined as :
H0 : There is no a relationship between successful knowledge transfer between parent – subsidiary and organizational project success.
From this we begin the process of establishing the important sub hypotheses which
frame the research hypothesis. These sub hypotheses are integral to our overall
directional hypothesis above because of the various research - associated factors and
variables as demonstrated in the extensive Literature Review Section (Chapter 2). Here
we will establish a map between the objectives of the research and the established sub
hypotheses thus creating the foundation for our formal directional hypothesis defined
above. It should be noted that these relate to our target research population.
Sub hypotheses are broken down into three main groups (in addition to the
demographics portion) : (1) Headquarters and Subsidiary Communications; (2)
Headquarters and Subsidiary Knowledge Transfer and Corporate Culture; and (3)
Project Success Characteristics and Interpretation. This is the general structure of our
survey tool as well. This will be discussed further below.
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Based on our Literature Review and the different attributes under consideration, we
anticipate that trust plays a crucial role in how communication channels within the
organization are structured. It is anticipated that these semi-formal channels in fact arise
and take shape from the daily communication “work” and interaction that takes place
both within the subsidiary and between subsidiary and parent headquarters. A key point
is that this communication, whether the daily interaction at the subsidiary or the more
formal communication structure between subsidiary and parent, in which we contend
that knowledge transfer takes place, is established with little to no consideration of the
communication concepts outlined in Chapter 2. However since these concepts create
the building blocks of this communication; and in turn the communication establishes the
conduits of knowledge transfer of which trust is of the utmost importance, and
furthermore, trust is in our opinion a key factor in morale; we hypothesize the following
sub hypotheses Cluster B :
HB1 : There is a positive relationship between the way technical communications are handled on a daily basis and trust
HB2 : There is a positive relationship between how technical communication channels are modeled between subsidiary and headquarters and trust
HB3 : There is a positive relationship between how technical communication channels are modeled between subsidiary and headquarters and establishing a truly shared meaning in succesful knowledge transfer .
Furthermore, we hypothesize that based on various demographic factors of the
organization, in fact the “best” model for knowledge transfer is the many-to-many
concept at the higher tier. This leads to :
HB4 : Organizations that implement a many -to-many technical communication channel model are more likely to establish and maintain a truly learning and trusting relationship
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Utilizing the link to employee morale but within an operational framework in which
organizational structure and the relationship between subsidiary and parent
headquarters is considered, we anticipate a link between morale (at the subsidiary) with
the level of perceived satisfaction at headquarters. Here we must be careful to
emphasize that this is in fact a perception of satisfaction at headquarters. By
constructing the research from survey question to sub hypotheses in such a way we
focus on the attitudes and dispositions of the personnel at the subsidiary operation
something which we are emphasizing with this research. We are now in the position to
consider how this relates to project success. We contend two points : (1) that there
exists a relationship between the perception of headquarters satisfaction with its
subsidiary and project success, (i.e., if there is a multitude of successful projects that the
subsidiary has accomplished, then it would seem almost a given that perception would
be that headquarters has a high satisfaction rating of its subsidiary); (2) that there is a
strong positive relationship between subsidiary employee morale and project success;
once again this would seem intuitive. This rationale is outlined in sub hypothesis
Cluster E :
HE1 : There is a positive relationship between subsidiary employee morale and project success.
HE2 : There is a positive relationship between parent headquarters satisfaction and project success
HE3 : There is a positive relationship between parent headquarters satisfaction and subsidiary employee morale
If we consider once again our Literature Review in Chapter 2, we saw from a
communications point of view and from the discussion regarding Hofstede’s research
[58] that certain circumstances, scenarios, and situations, give rise to an internal /
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innate need to understand personal position within an organization. We have seen this in
several references and past research. There is a propensity for individuals (some
cultures more than others in fact) for face to be maintained during interaction,
uncertainty to be avoided to some practical degree; we anticipate that these cultural
considerations in fact relate to the degree in which an employee has direct input into
decisions that affect him or her. Furthermore, from groups, teams, and technical
communication, as well as thru our project success literature review, we hypothesize
that there is a positive relationship between certain fairly structured operational
standards in handling projects, but within the appropriate level of communication
pertinent to each situation (basically understanding and allowing for the various
communication factors), and project success. This rationale outlined above regarding
employees’ abilities to have direct input to decisions, and the need for a structure
environment which would allow for a greater probability of project success, form 2
additional sub hypotheses shown here :
HD1 : There is a positive relationship between proactively conducting and managing a system for post-project reviews and lessons -learned meetings and project success.
HD2 : There is a positive relationship between employees having a direct input into decisions that affect them and project success.
It should be noted that HD2 stems directly from both E and B Clusters previously
mentioned, namely the discussion on personnel morale (directly from HE1) and our
contention that the many-to-many knowledge transfer model (HB3) is the optimum
structure for establishing true knowledge transfer and learning. This should be fairly
intuitive when we consider that HD2 deals with employees making their own decisions –
the morale issue; and employees establishing direct links to headquarters as opposed to
having single individual acting as “gate-keepers” in communication and knowledge
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transfer between subsidiary and parent headquarters. We further contend that HD1 and
HD2 affect directly project success factors and measures as outlined in our subsequent
sub hypothesis shown here.
HD3 : Organizations focus on delivery and performance , more so than cost , recurring business, and knowledge -gain, as the key measures for project success.
The progression of the sub hypotheses development above thru Clusters B, D, and E
has enabled us to address our first research objective, namely to identify the most
meaningful concept of project success for our target population. In effect we contend
that delivery and performance is of the utmost importance, outweighing price and other
factors such as corporate learning.
As outlined previously, the key to knowledge transfer is establishing a shared meaning
primarily with trying to convey and transfer tacit knowledge. This was discussed in detail
by Nonaka and Takeuchi [87], as well as Davenport’s and Prusak [31]. Extending the
framework from our sub hypotheses Cluster B (HB3 and HB4) which hypothesizes the
relationship among communication channels, shared meaning , and our many-to-many
concept, we can derive a conceptual relationship and formulate a 4th Cluster C which
relates shared meaning and employees’ direct decision-making abilities, which relate to
an organization’s structure HC1 ; technology tools as a means of easing cooperation and
collaboration HC2, ; leading to the formulation of sub- hypothesis HC3 which we stipulate
a relationship between trust and successful knowledge transfer. This Cluster is mapped
to our second research objective discussing knowledge transfer attributes for which we
contend that trust is a primary attribute that unfortunately may be lacking as researched
in previous studies. We need to identify the relationship for our target population.
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HC1 : There is a positive relationship between employees having a direct input into decisions that affect them and establishing a truly shared meaning in succesful knowledge transfer.
HC2 : There is a positive relationship between the availability of technology tools and a true spirit of cooperation / collaboration between subsidiary and headquarters .
HC3 : There is a positive relationship between trust and knowledge transfer that occurs in both directions between headquarters and subsidiary .
Finally, we must consider the demographic data which we obtained and outline how
specific characteristics of an organization, its structure, that is, how rigidly hierarchical it
is, or not, its size, maturity (age), as well as how many expats are working in the
organization and what is their level of project management experience; all these factors
should be taken into account and related to our third research objective which considers
attributes and variables regarding corporate culture and structure. It should be noted
also that from a national culture point of view we will be considering these sub
hypotheses individually as well; that is individually within the framework of America,
German, Italian, and Japanese companies. Any similarities will be noted and any
differences will be examined in detail. This, along with our entire data set will be
presented and analyzed in the next chapter. Below is Cluster A relating to demographics.
The input into Cluster A is a logical extension of Cluster B primarily dealing with
communications. Figure 3-2 shows the Cluster Inter-Relationships leading to the
research objectives and Figure 3-3 shows the actual sub hypotheses.
HA1 : There is a positive relationship between the size of the subsidiary and headquarters and how technical communication channels are modeled
HA2 : There is a positive relationship between the age of the subsidiary and headquarters and how technical communication channels are modeled
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HA3 : There is a positive relationship between organizational culture and structure and establishing a truly shared meaning in succesful knowledge transfer
HA4 : There is a positive relationship between the number of expats in the subsidiary and establishing a truly shared meaning in succesful knowledge transfer
90
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3.2 Method
In following a correlational approach, we model our analysis in a similar way as Vincent
Michel Ribiere’s 2000-2001 research [96]. This methodology, as previously utilized by
Gay, “attempts to determine whether, and to what degree, a relationship exists between
two or more quantifiable variables…prediction of some outcome or hypothesis
confirmation is based on a strong relationship between the variables…” [44]. Based on
our conceptual framework shown in Chapter 1 Figure 1-2, we establish the following
relationships :
Per our Literature Review and our Research Structure we define the following moving
forward :
Corporate Culture Independent Variables / Attributes. Parent – Dependent vs. Independent, Parent – Integrated vs. Non-Integrated, Hierarchically Rigid vs. Loose, Democratic vs. Autocratic, Trusting vs. Holdback, Degree of Social and Cultural Empathy to Parent
National Culture Independent Variables / Attributes.
Hofstede [58] Set : Power Distance, Individualism vs. Collectivism, Masculinity / Femininity, Uncertainty Avoidance, Long / Short-Term Orientation, Trust, Degree of Ethnocentrism
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Basic Communication Theory Independent Variables / Attributes. Modified Hall [51] Set : Transmission = f (Speed, Context, Space, Time, Flow, Sequence) ; Absorption, Trust
International Communication Independent Variables / Attributes.
Language, Degree of Technology Usage, Time Lag & Time Difference, Degree of Feedback, Degree of Integration into both Parent and Subsidiary Strategic Initiative
Groups & Teams Communication Independent Variables / Attributes.
Individualism vs. Collectivism, Degree of Self-Construal & Face-Concern (in relation to Role Behavior Characteristics of Teams, See Table 2-5c), Trust
Project Success Dependent Variables / Attributes.
Delivery, Budget, Technical Performance, Market-Share Expansion / Growth, Employee Morale, Knowledge-Gained / Lessons-Learned.
3.3 Population
The survey instrument distribution population will be world-wide gear and machinery
manufacturers, consultants, and academic personnel associated with our target industry,
including those international manufacturers having operations in the United States.
Table 3-1 provides a summary of the target population overall available pool / potential.
The target population was identified thru several means including personal experience
and associations in the industry for 15 years as well as the well-documented AGMA
(American Gear Manufacturers Association) 2007 Members Directory utilizing the proper
industrial and geographical categories and filtering . It should be noted that this directory
is international and not limited to specifically - American gear manufacturers. A
comprehensive list of the entire detailed potential survey distribution population pool is
located in Appendix G for reference. This pool contains approximately 870 specifically-
identified individuals which make up the greater available potential population.
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The survey will be addressed to specific individuals; it will not be distributed “blindly.”
We refined this overall list of 870 or so and targeted a specific population of 168
individuals which fit our particular job classification criteria and fit the scope of the
research in terms of specific function within the overall industrial gear industry. This was
verified to a great extent by initial contact via telephone. We avoided a “shotgun”
approach to the survey and focused on a tightly targeted group of Project Managers /
Engineers, Application Managers / Engineers, Product Managers / Engineers, Sales
Managers or Engineer, Purchasing Managers / Engineer, Design Managers / Engineers,
R&D Managers or Engineers.
These specific job classifications were established based on our experience in the
industry of corporate structure in terms of what personnel is involved in large scale
projects such as those within our scope. It is these individuals holding these positions
that also maintain communications channels to and from parent and subsidiary. In the
possible case that the company is fairly small and such communications are handled at
a higher executive level, as is the case sometimes, we left an open-ended question in
terms of job-title position. We did not restrict our study to any particular organizational
size, history, or whether public or private. We did focus on those particular companies
dealing with large-scale projects within our scope and with national orientations we are
researching, in particular : American / Canadian, German, Swiss, Italian, Japanese; and
secondary : Other European and Other Asian.
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Table 3-1 : Overall Population Potential Target Pool Job Function / Position of Potential Respondents
Sector
Location Potential
DestinationsPotential
Respondents
1
2
3
4
5
6
7
8
USA and Canada
110 ~ 400
Europe, East & West
36 ~ 160
Asia Including Australia & India
43 ~ 170
Industry
and Corporate
Other 14 ~ 20 203 750
USA and Canada
29 ~ 70
Europe, East & West
2 ~ 5
Asia Including Australia & India
3 ~ 5
Consulting
Other 2 ~ 2
36 82
USA and Canada
10 ~ 12
Europe, East & West
6 ~ 19
Asia Including Australia & India
6 ~ 8
Academic
Other 2 ~ 2
24 41
Job Function Codes 1 = Project Manager or Engineer 2 = Application Manger or Engineer 3 = Product Manager or Engineer 4 = Sales Manager or Engineer 5 = Purchasing Manager or Engineer 6 = Design Manager or Designer 7 = R&D Manager or Engineer 8 = Other (to be specified in the survey)
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As mentioned previously we refined our target population to 168 individuals from the
870+ available pool / potential. This refinement was based on a 2nd phase confirmation
of updated information from the AGMA web site (see figure 3-4) and a more in-depth
investigation of specific target companies dealing directly and primarily within our scope
as one of their core businesses and /or job functions. We feel that by doing this we have
significantly improved both survey response levels and data quality. The specific target
population is shown in abbreviated format in Table 3-2 and listed by ID#, company and
operations locations only. Names of individuals which the survey was sent to, are
omitted in order to maintain anonymity. This final list makes up our single-stage
sampling population.
Figure 3-4 American Gear Manufacturers Association Web Site www.agma.org ( used with permission from AGMA )
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3.4 Instrument / Cross-Cultural Survey Research Design
The research instrument utilized consists of a self-administered questionnaire designed
and optimized to collect our required data. The questionnaire or survey is the preferred
type of data collection instrument for our particular research because it provided for an
economical and fast way for obtaining our data. This is true especially since data was
required from international sources outside the United States.
Our survey was cross-sectional and based on the well-known Tailored Design Method
a four-phase administration process outlined in Dr. Don Dillman’s text : Mail and Internet
Surveys: The Tailored Design Method [34]. Essentially the methodology focuses on
carefully constructed and repetitive communications emphasizing a survey’s usefulness
and the importance of a response from each person in the sample. This is done thru a
structured procedure of continued communication with the target group and as much on
an individual basis as possible emphasizing “…survey response as a sort of social
intellectual exchange…” [34]. And according to Dillman this approach has the goal of
“…minimizing survey error which typically takes the form of sampling, coverage,
measurement, and nonresponsive errors respectively” [34].
Of particular importance in this survey is the fact that the research will be focusing on
manufacturers in various countries but primarily from Japan, Italy, Germany and to some
extent Switzerland. We realize that conducting surveys is a rather difficult endeavor and
conducting international surveys makes things even more complicated, however, based
on the Tailored Design Method discussed above as well as guidelines and procedures
presented in the foremost text on international surveys : Cross-Cultural Survey Methods,
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by Dr. Janet Harkness, Dr. Fons Van de Vijver, and Dr. Peter Mohler [52] , we were
able to obtain an excellent return rate of 41%.
It should also be noted that the survey was designed in such as way as to obtain
additional data for future expanded research. The questionnaire, as will be discussed
below, was designed solely for this research but also provides data for further research
namely in analyzing in greater detail attitudes of respondents vs. actual organization
processes and systems. It collects data of what is actually being done in organizations
but it also collects data on what personnel feel is important on how things should be
done. Some of this data will be analyzed and used in support of our specific hypotheses
but it will also be available for future research. The questionnaire was purposely and
specifically designed in such a manner.
In addition to utilizing the Tailored Design Methodology, two additional key actions
were taken to further confirm an optimum understanding and response to the
questionnaire : (1) establish one “universal” survey in which all necessary translations
are immediately available on the instrument itself; and (2) conduct a preliminary pilot
survey so that questions can be better- finalized and clarified. These key points along
with all additional guidelines related to the survey are discussed in further detail below.
3.4.1 Basic Principles and Best Practices
There are 3 basic techniques for collecting primary data : survey research, direct
measurement, and observation [95]. “Survey research provides a proven
methodology for determining information with a known accuracy-level about a larger
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population” [95]. Furthermore, there are essentially 5 general methods in collecting
survey data : mailings, web-based, telephone, in-person interviews, and intercept.
Our primary and initial distribution method was a mass-mailing of a printed survey
questionnaire followed by several timed email follow-up contacts. The advantages
of this methodology are numerous, including cost savings, convenience, timing,
anonymity, reduced interviewer-induced bias, and the opportunity for visual
enhancement to clarify any complexities. In developing the questionnaire, we
maintained a focus on objectivity, avoiding leading and loaded questions and kept
an eye on potential built-in assumptions. We tried to keep questions and
expressions simple, direct, and as familiar as possible and practical and
maintaining a specificity in the nature of the questions, that’s is asking precise
questions.
“One of the most popular ways of asking a subjective question is to use ratings
scales, that is a single, well-defined continuum in which the answer is expected to
be placed” [62]. For our survey we utilized a 9-position or category Likert Scale
shown in Figure 3-5 below. “Although…scales can include 12 categories or more, it
is preferable to use between 5 and 9 categories” [62]. Furthermore, various
research shows that “…scales intended to measure bipolar concepts should use
negative - to - positive values…” [62], preferably labeling only the extreme values
and the mid-point. This is what we used as a governing guideline in our scaling.
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Three key areas need to be considered in survey design : question wording,
question coding, and survey appearance including flow. During the overall
development of the survey, from textural, structural, and visual points of view the
following guidelines below were applied. These are found in various forms in
several references [95], [62], [28], [34], [99] but we primarily utilized Harkness,
Van de Vijver, Mohler [52] with some slight modifications. These are considered
survey / questionnaire best practices and good design principles to be used to
minimize bias. The list below is primarily from Harkness, Van de Vijver, and
Mohler’s “Cross Cultural Survey Methods” [52] with some modifications by the
author.
Introduce the study in a cover page with a simple and clear explanation of purpose
Provide simple and complete instructions located where they are needed and visually distinguish them as instructions
Utilize appropriate spacing, alignment, color coding, fonts, emphasis, and visual queues
Utilize sequential and consistent numbering throughout
Group questions into fairly logical sections with similar qualities and relevance
Make choices that are mutually exclusive to maximize accuracy
Short, simple sentences with 25 or less words each
Use active rather than passive voice
Repeat nouns instead of using pronouns
Avoid metaphors and colloquialisms
Avoid the subjective which may introduce bias
Avoid negative or double negative expressions
Provide context where required for key items
Provide redundancy for key items
Avoid possessive forms
Use specific rather than general terms
Avoid terms leading to vagueness (such as probably, maybe, perhaps)
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3.4.2 Pilot Study Program
In order for us to confirm that we did in fact have an optimized survey tool for our
research, we conducted a two-phased pilot study which culminated into the final
questionnaire that was actually used in the data gathering and which is also
documented in Appendix B. The pre-testing of the questionnaire was conducted
using the conventional method approach in which respondents are given the
opportunity to complete the survey followed by a structured interview session.
Phase 1 of the pilot study / survey was conducted on Monday and Tuesday, Nov.
5th and 6th 2007 with various respondents from Sumitomo Drive Technologies; a
Japanese heavy machinery manufacturer located in Virginia, United States. In
addition, the preliminary survey was also provided to mG miniGears Inc., an Italian
precision gear component manufacturer in Virginia, USA, and Stihl Inc. a German
company who is not directly involved in the gear industry, but does utilize geared
parts and machinery. It was hypothesized that the technical nature of this German
manufacturer (Stihl Inc.) and the fact that we discussed our questionnaire with
German Engineers working at its plant in Virginia, will nevertheless assist us in our
survey finalization. The pilot survey was given to 10 individuals (between the 3
companies) with the following job titles : Project Manager, Senior Project Manager,
Application Engineer, Product Engineer, Sales Engineer, VP of Sales, After-Market
Coordinator. In this round, we tested our survey questions primarily in English as
well as the initial translations into Italian, German, and Japanese languages. The
thought was that the respective non-American technical personnel would provide
input into our translations.
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From Phase 1 we identified some poorly-phrased questions – some that where
unclear and somewhat difficult to understand exactly what was being asked. We
focused on improving both questionnaire quality and comprehensiveness since in
fact we did miss a very important question in the initial pre-test, namely asking the
respondent to identify their company’s overall successful project percentage. This
fundamental question was in fact inadvertently omitted initially but was identified by
the Phase 1 pre-test process. Phase 1 also tested questionnaire acceptability in
terms of length of the survey, privacy, ethical, and moral issues and standards.
There were no findings or concerns in these areas.
Phase 2 of the pilot study program was initiated after the basic Phase 1
modifications were completed. The basic concept of Phase 2 was to utilize
respondents outside of the United States who would bear a reasonable
resemblance to our population for the purpose of identifying any unique reading,
translation, question clarity, and assumption issues. Phase 2 involved actual on-
site visits to 6 target machinery companies in Switzerland and Germany between
Nov. 14 ~ 22, 2007. Manufacturers and project Managers in Oerlikon, Wil, Uzwil,
and Winterthur, Switzerland (near Zurich), as well as in Friedrichshafen (Germany)
were given our refined survey and interviewed. In this final Phase 2 of the pilot
study the final translations were confirmed and we were provided with some useful
information for improving our questions – hypotheses links.
Between Phase 1 and Phase 2 of the pilot study, we confirmed our research
instrument using 9 companies (3 in the U.S., 6 abroad) and 24 individuals (10 in the
U.S., 12 abroad) who we feel closely represented our target population. These
individuals were not utilized again for the actual survey but others in their
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organizations were, with the exception of Stihl Inc. which we determined to omit out
completely due to its non-exact organizational match to our scope. The overall pilot
study program / protocol is outlined in Figure 3-6. A modified version of Iarossi’s
[62] methodology was used.
Figure 3-6 : Pilot Program / Protocol Considerations ( Modified version of Box 3.1 in Giuseppe Iarossi’s “The Power of Survey Design” [62] )
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3.4.3 Cross-Cultural Survey Limitations & Difficulties
In addition to what has been mentioned previously regarding survey research, best-
practices, guidelines and structure required in order to obtain usable data; there is
another aspect to our research that makes the survey process somewhat more
difficult specifically in this case. The fact that the survey will be sent internationally
to recipients in Japan, Germany, Italy, Switzerland, and other European and Asian
countries establishes this as a cross-cultural type survey inherent with its own
difficulties revolving around language, translation, and actual meaning.
Cross-national or cross-cultural type research comes at somewhat of a price. It can
be expensive and time-consuming if not managed correctly. It can be difficult to
carry-out and may raise more questions than answers [52]. However there is a real
and increasing need to expand cross-national or cross-cultural research simply due
to the fact that the world is getting smaller. Globalization, internationalization, global
trade, global practices, standards, and procedures are increasingly becoming the
norm. All these are impacting different countries and cultures throughout the world
and the fact is that we must consider expanding our horizons in terms of
understanding and empathy to other cultures. The need for more cross-cultural
research can be found throughout the research literature. It is no loner feasible to
considering everything from a Western frame of reference.
According to Harkness, Van de Vijner, and Mohler “…the most commonly adopted
approach in conducting culturally-comparative research is to decide on a survey
design and to replicate / implement this as best as possible in each of the
populations involved in the project” [52]. And, this is in fact what we did within our
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research methodology. The key objective in doing this however is to ensure that we
maintain a “ask-the-same question” (ASQ) approach when replication does take
place. What this means is to make sure that our translation is not so much a literal
translation or transliteration of the words as opposed to conveying actual meaning
and being able to effectively maintain equivalence across the different cultural
groups in terms of concept (conceptual equivalence) as well as measurement and
scalar equivalence during analysis. “What this scalar equivalence means is
essentially that a well-translated indicator (question) can still generate certain non-
equivalent response patterns from different cultures” [52].
According to Harkness, Van de Vijner, and Mohler [52], when developing new
material in cross-cultural surveys there are 3 structural approaches in questionnaire
design : sequential, parallel, and simultaneous. As one can infer the most common
approach is sequential, that is, the source questionnaire is developed and then
“adapted to another culture” by translation. This is the approach we took. The
difficulty once again is to make sure that there is equivalence and the ASQ
approach is maintained most importantly from a meaning point of view. How we
overcame this difficulty is to implement an iterative translation process utilizing
professional translators in tune and knowledgeable with the technical jargon used.
This was done with all 3 of our languages – Japanese, Italian, and German (other
than English). The advantage of this approach is the potential to develop high
cultural context suitability within the survey thus leading to a decrease in potential
concept inadequacy or bias and in effect creating a “good” tool for the research.
The disadvantages to this methodology however, according to Harkness, Van de
Vijner, and Mohler are high development costs and potential for cross-cultural
suitability not being optimized if the survey tool is not pre-tested. [52] As a matter
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of fact however, our survey development process took these potential pitfalls into
account.
A translated question must ask the same question as the original source question
(English) both linguistically and pragmatically; essentially we must consider….is the
concept we are trying to convey thru our question the same for the different cultures
we are interested in ?
Several strategies were utilized in order for us to assure that our translations were
adequate :
Professional translators were utilized whose native language
was the language we were seeking.
Independent translation reviewers were utilized to check the initial
translation and for the most part these reviewers were engineers and
deeply knowledge about the concepts we were trying to convey.
In addition to the initial professional translators, the reviewers
themselves maintained the target language as their native language.
Translators had direct contact with the researcher so that an iterative
process of shared meaning could be established during the translation
process. Thus translations were fully integral to the development
process and never an afterthought.
Finally, a rigorous Two-Phased Pilot Study and pre-test were utilized
with independent target language speakers most of which were also
engineers and familiar with our concepts and which enabled a “3rd filter
pass” in terms of language translation and fine-tuning.
Based on the above points, we feel confident that our translated cross-cultural
survey is in fact more than adequate and suitable for our research.
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From a structural layout point of view we originally considered having all 3
translations for each question in the immediate vicinity of that question, this is
what is sometimes referred to as the EU Metrics model. However we soon
discovered that this would not be very practical and became increasingly
unwieldy and cluttered our overall format.
In keeping with our objective of maintaining only one survey instead of multiple
translated versions being sent-out independently, we decide to construct a
single questionnaire with 4 main sections identifying the 4 languages : English,
German, Japanese, and Italian. The recipient can receive the survey and
quickly go to the section they feel most comfortable in to proceed with the
questions. If for some reason there may be an issue in interpretation due to
translation, the recipient can always refer to another section to read the same
question in another language and perhaps obtain a better understanding of
what is being asked, if needed. Finally Likert Scales and other non-verbal
visual guides were consistently used in an effort to provide an optimum
instrument across all language sections. The final survey instrument is fully
documented in its entirety in Appendix B. Figure 3-7 demonstrates some of
the concepts described. It shows the first, introductory / instruction page of the
survey.
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Figure 3-7 : Survey Instrument Front Cover / Instructions Page
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3.4.4 Final Question Development and Mapping
“Two basic rules make good questions : Relevance and Accuracy. Relevance is
achieved when the questionnaire designer is familiar with the questions, knows
exactly each question’s objective(s), and the type of information needed” [62].
While accuracy relates to “…the collection of the information in a reliable and valid
manner” [62]. Furthermore, and based on Dr. Don Dillman’s [34] approach some
general criteria should considered in assessing survey questions, such as : Does
the question require an answer ? To what extent do survey recipients already have
an accurate, and ready answer for the question being asked ? Is the respondent
willing to reveal the requested information ? Will the respondent feel motivated to
answer each question ?
In addition to the front multi-translated cover page providing the introduction and
instructions, and shown in previous Figure 3-7, the research questionnaire consists
of 5 main sections :
A. Basic Information – incorporating the survey respondents job position,
experience, the company situation, ownership, structure, size, and other
various demographics
B. Headquarters and Subsidiary Communication – this portion surveys the basic
communication situation at the subsidiary.
C. Headquarters and Subsidiary Knowledge Transfer and Corporate Culture –
this portion surveys the situation, attitudes, trust issues, relating to knowledge
transfer between the subsidiary and the headquarters parent company.
D. What is Project Success ? – this portion of the survey solicits the respondents
input on project success as they may define it as well as how their company
usually defines it.
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E. Project Success at Your Company – this portion of the questionnaire solicits a
value percentage of some key project characteristics and employee morale
levels both at the subsidiary and headquarters.
Dr. Linda Henderson’s paper : “Encoding and Decoding Communication
Competencies in Project Management – an Exploratory Study,” [56] served as a
central reference in establishing the survey questions primarily in Section B :
Headquarters and Subsidiary Communications; and Section D : What is Project
Success ? of our survey instrument. A good number of our questions are
modified constructs based on Dr. Henderson’s questions on communicator
competence, team satisfaction, team effectiveness and productivity. Questionnaire
Section B also utilized modified versions of questions developed by Gregory N.
Stock, Noel Greis, and Mark Dibner’s : “Parent-Subsidiary Communication in
International Biotechnology R&D.” [114] In addition some question development
utilized Manuel Sosa, Steven Eppinger, Michael Pich, et.al : “Factors That
Influence Technical Communication in Distributed Product Development: An
Empirical Study in the Telecommunications Industry.” [112] For the most part
questions in Sections C : Headquarters and Subsidiary Knowledge Transfer and
Corporate Culture and to a lesser extent, Section D : What is Project Success ?
were developed from Dr. Jan Terje Karlsen’s and Petter Gottschalk’s 2003
research : “An Empirical Evaluation of Knowledge Transfer Mechanisms for IT
Projects.” [67] Further references to our questions can be found also in Karlsen’s
and Gottschalk’s 2004 paper : “Factors Affecting Knowledge Transfer in IT
Projects.” [68]
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Table 3-3 below summarizes each of the major questions in the survey noting
factors such as relevance, accuracy, related variables, question objective(s), link to
hypotheses, and references.
112
113
114
115 115
Figure 3-8 shows the overall mapping from past research referenced in basic question
development, to actual questionnaire questions (shown numerically), to our research
objectives and hypotheses, and finally linked to our original conceptual model framework.
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3.5 Validation & Reliability
Within our research context and specifically with our survey instrument, validation refers
to the steps required to ensure that we measure what we need to measure; that our
methodology meets the requirements and objectives of the research. Validation is
evolutionary and iterative to a point where final verification can occur. For our research
as a whole a portion of the validation process occurs thru the in-depth literature review
process. This is due to the fact that the first step in the validation process is to determine
actual requirements of the research. This occurs in part based on what has been
researched prior and where the research gaps exist. Following this thorough Literature
Review as outlined in Chapter 2, part of our validation process throughout this evolution,
occurred in monthly follow-up meetings with our local GWU advisor, Dr. Frank Allario.
Additionally there were several meetings with the entire group of advisors and
dissertation directors : Dr. Thomas Mazzuchi, and Dr. Shahram Sarkani, in addition to Dr.
Allario.
A fairly general definition of reliability is - the probability that something such as a system,
product, process, etc., will accomplish its designated purpose satisfactorily. In relation to
our research and in the survey instrument in particular, reliability can refer to “…the
accuracy and precision of a data collection procedure” [96].
In addition to the comments made in the immediate previous sections regarding the
survey instrument, questions were validated based on their use in part or in whole in
previous research. This is outlined in Section 3.4.4. where question mapping is shown.
Questions were finalized for our particular population in a Two-Phase Pilot Study : (1)
an initial pre-test was conducted utilizing 3 local international manufacturers : Sumitomo
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Drive Technologies (Japanese), Stihl Inc. (German), and mG miniGears (Italian); this
was done on from November 5th and 6th 2007; (2) to obtain a more refined instrument
and process, from November 14th – 22nd 2007, the survey was provided to several
manufacturers in Switzerland and Germany, along with conducting follow-up interviews.
Thru this refinement process of taking questions which had previously been utilized and
validated, and refining them to specific target population; we feel that validation was
assured. Table 3-4 shows the overall timeline for data collection.
Table 3-4 : Data Collection Timeline
1. Potential Gross Population Pool Identified : August 2007
2. Refinement to Actual Target Survey Population : September 2007
3. Pre-Test Pilot Study Phase 1 : ( 3 Local Companies : German, Italian, Japanese )
November 5th – 6th 2007
4. Pretest Pilot Study Phase 2 : ( 6 Companies in Switzerland )
November 14th – 22nd 2007
Tailored Design Method A ~ D Our Research Timeline Misc Notes
A 1st Contact Prenotice Letter
January 30th – 31st 2008 Utilized email only, not hardcopy letter.
B 2nd Contact Cover Letter & Survey
February 5th 2008
February 8th 2008
February 15th 2008
February 19th 2008 February 22nd 2008
Hardcopies via post :
133 surveys sent out
16 additional surveys sent out
2 additional contacts identified, surveys sent out (internationally)
17 final surveys distributed (locally)
C 3rd Contact Thank You & Reminder
February 17th – 22nd 2008 Utilized email only; attached replacement survey
D 4th Contact Letter & Replacement Survey
February 27th – 29th 2008 Utilized email only; attached replacement survey
5. Last survey ( #69 ) received from Japan March 30th 2008 ( approx. 1 month after deadline)
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3.6 Analysis Approach
The general approach for this research will be that of a correlation analytical
methodology applied to data obtained from a survey instrument. This approach is
effective “…in determining whether, and to what extent, a relationship exists between 2
or more quantifiable variables” [44]. Prediction of outcome or hypothesis confirmation
will be based on a strong relationship between the variables and will utilize ANOVA.
Microsoft Excel® and MiniTab® will be software that will be utilized.
Furthermore we researched and analyzed an actual detailed case which is used as a
specific illustrative example of the principles developed. The case example content is
located in Appendix D. Although our case example is used to confirm some of our
findings we realize that it does not incorporate a full confirmation of the theoretical
construct established. This approach however is typically considered as “…an
appropriate methodology in an initial research effort that is intended to develop some
theoretical understanding” [57]. This multi-method, or what is referred to as
triangulation has also been successfully utilized in research conducted by Stock [14]
and Jansen [63]. For our research this methodology was appropriate and applicable
since the intent was to establish an understanding of the relationship between
knowledge transfer attributes and international team project success. The case evolved
around an organization faced with an actual problem related directly to the scope and
concepts addressed in our research. Since the case is currently still in progress and
involves some legal issues we would like to note that the information in Appendix D has
been edited to some extent.
The purpose of sampling thru our survey instrument is to be able to correctly make
certain generalizations about our population. We will estimate a true mean and standard
119
deviation of our overall population by analyzing the probability of our sample’s likelihood
of approximating the true sample mean. Sampling and survey response qualifications
will be conducted thru response bias and basic wave analysis. Actual sample size will be
determined and confirmed using internal scale variable analysis. Sampling frames will
be evaluated for appropriateness but, we are considering a simple random sampling
approach which we feel will give us adequate representation within the entire population.
Descriptive statistics will be utilized on dependent and independent variables quantified
thru the survey instrument, where appropriate. This analysis will include quantifying and
selecting the most appropriate measure of central tendency such as mode, median, and
arithmetic mean; and the relationship to skewness. This appropriate selection is required
when these measures are relatively close to each other which we suspect. Due to the
utilization of our Likert Scale, scaled frequency distributions and factor analysis will be
considered and analyzed under appropriate situations. Additionally, measures of
dispersion such as range and standard deviation will be commonly applied techniques
to the data.
Going beyond the fundamental descriptive statistics which can be limiting when
multivariate relationships are present, we will be utilizing cross-tabulated contingency
tables that will depict the relationship between two or more of our variables and provide
the foundation for further analysis. This analysis will take the form of multiple regression
and correlation, tests for statistical significance such as chi-square ( χ2 ) and ANOVA, as
previously mentioned. Hypothesis testing based on our samples will be utilized; while a
number of output representations is considered. Relationships among the data will be
concluded, thus leading to attribute determination and final research conclusions and
thus satisfying our objectives, will be established.
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CHAPTER 4 – RESULTS & DATA ANALYSIS
4.1 Survey Results
As mentioned in the previous chapter, surveys were sent to 168 specifically targeted
individuals from a greater potential pool of 870+. Based on this highly-selective and
targeted population, a 95% confidence level, and a selected margin of error of +/- 10%,
a minimum sample size return rate of 62 was calculated to be appropriate. We received
69 returned surveys giving us a return rate of approximately 41% thus falling within the
minimum required sample size for this study. This was a good sampling representative
of the overall population. Return rates were fairly comparable across the three areas :
USA, Europe (Mainly Germany and Italy), and Asia (mainly Japan). Figure 4-1
graphically represents returned surveys vs. not-returned.
Figure 4-1 : Surveys Returned
99
69
Surveys Not ReturnedSurveys Returned
Out of the 69 returned surveys, 45 were returned in English even though some of these
were returned from abroad. 10 surveys were returned in German and an almost equal
number (9) were returned in the Japanese language. Approximately half of this number
(5) came back in Italian. The majority of the surveys that were returned in a language
other than English came from abroad. Response rates were captured by week and in
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order to measure bias, we performed a simple wave analysis based on the change of
the mean on randomly selected questions in the survey. We did not distinguish any
variations based on return timing nor on return survey language or even based on
geographic area. We concluded that our survey response characteristics were sound.
Some of this information is shown in the figures below.
Figure 4-2 : Survey Language
4510
95
Returned English Language SurveyReturned German Language SurveyReturned Japanese Language SurveyReturned Italian Language Suvey
Figure 4-3 : Geographic Location of Respondent Company
29
11
9
9
9 2JapanItalyUSAGermanyOther EuropeanOther Asia
It is noteworthy to mention that the response rate from Asia, specifically from Japan (at
65%) was more than twice as great as that of either the United States ( at 31%) or
Europe (at 29%). This is shown in Figure 4-4. It is hypothesized that the name-
recognition of the researcher’s place of employment which was mentioned in the survey
(Sumitomo) may have played a role in this particular instance, perhaps motivating Asian
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and specifically Japanese respondents a greater deal than their counterparts from the
United States and Europe. Any bias based on this will be analyzed and reported. As
mentioned, there was no bias based on response rates from a time point of view – when
surveys were returned / received. Number of returns per week are shown in Figure 4-5.
Simple wave analysis confirmed no adverse affect. Note surveys were sent out the first
week of February 2008.
0%
10%
20%
30%
40%
50%
60%
70%
Asia USA Europe
Figure 4-4 : Response Rates by Region
0
10
20
30
40
week o
f 2/11
week o
f 2/18
week o
f 2/25
week o
f 3/3
week o
f 3/10
week o
f 3/17
week o
f 3/24
week o
f 3/31
Figure 4-5 : Number of Returned Surveys by Week
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4.1.1 Basic Information / Demographics
Approximately 59% of the respondents classified themselves as either Project,
Application, Product, and/or Sales Engineers or Managers directly handling major
project business, which is the focus of this research. 22% listed themselves as
Design and/or R&D Engineers and Managers indirectly associated with project
business providing technical support. The remaining 19% were usually at a higher
executive level in the company structure and provided multi-project strategic
management. 59% of the respondents indicate they had more than 20 years
experience in their industry and about half of those respondents indicated more
than 20 years of specific project management experience. 23% indicated between
11 and 20 years industry experience. Figure 4-6 provides some additional detail on
job classifications by country of respondent. Figure 4-6 : Job Classification by Target Country
TOTAL
5
14
1210
05
10
13
Project ManagementApplication Eng.Product Eng.SalesPurchasingDesignR&DOther
Japan3
6
17
03
3
5
Germany
05
4100
2
2
Italy
0 2
300
1
1
1
USA1
1
31000
3
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Approximately 62% worked at their company’s subsidiary in the United States,
while the remaining 38% worked either at a U.S. headquarters of the American
company or abroad at the foreign company’s overseas headquarters usually
located in Germany, Japan, or Italy. 86% of the respondents indicated that their
company had one or more corporate expats working on major project business at
the subsidiary while 40% of the respondents indicated there were subsidiary
personnel working as expats at the foreign headquarters. 62% of the responses
indicated they worked at a publicly-traded company while 29% indicated a private
company, while 8% were not sure. 58% of the companies had more than 1000
employees; of these particularly large companies more than 70% had significantly
large subsidiaries of 100+ employees.
Figure 4-7 is a representation of 3 variables that will be useful for us. It is
informationally interesting because it compares company size (personnel), age, and
expat situation both at the subsidiary level as well as at the parent headquarters
level. This represents the typical profile of our target companies both here and in
their home countries.
We can see that the “oldest” companies in our research are in fact Japanese and
German with an average age of about 65 years. American companies come in 2nd
at an average age of about 55 to 60 years old (headquarters). Italian companies are
younger at an average age of about 45 years old. Furthermore we can easily see
that the Japanese companies seem to be the largest. This is confirmed when we
consider such large heavy industrial companies such as Sumitomo, Mitsubishi,
Kawasaki, and others. When we consider these companies’ subsidiaries in the USA,
we see that overall subsidiary size is comparable – typically it ranges at somewhere
of about 100 to 300 employees. Once again, mirroring the trend of their
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headquarters, the subsidiaries also vary in age, with the Japanese subsidiaries
having been in the U.S. the longest (oldest) at about 30 to 35 years; the Germans
are a close 2nd with an average age of their presence in the U.S. of about 25 years,
and again the Italian companies seem to be the relative newcomers with their
presence in the U.S. at less than 10 years on average. However, interesting as
these figures may be the additional 3rd variable represented by this “bubble” graph
is the expat situation both at headquarters and at the subsidiary; specifically, how
many cross-over expats are at each others location, Americans at abroad and
foreign expats here.
We can clearly see that American companies have the most expats on average
(14) than the others. The Japanese have the lowest number averaging only one
U.S. expat at their headquarters in Japan. This is interesting and will be discussed
later. The German and Italian company headquarters in their respective countries
do not do much better and on average maintain two U.S. expat employees at their
European headquarters. All 3 however – Japanese, German, and Italian companies
do maintain on average three employees from headquarters in their U.S.
subsidiaries. This is also interesting and will be discussed later.
Figure 4-7 : Company Size / Age / Expat Situation Profile
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2
1
14
3
33
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
2,200
0 10 20 30 40 50 60 70 8Company Age
Com
pany
Siz
e (P
erso
nnel
)
0
ITALIANSubsidiary
GERMANSubsidiary
AMERICANSubsidiary
ITALIANPARENT
JAPANESESubsidiary
JAPANESEPARENTAMERICAN
PARENT
GERMANPARENT
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The remainder of the data results is presented here utilizing cross-tabulated
contingency tables. This is done because this methodology is powerful in
presenting and establishing a starting point for simultaneous analysis of more than
one variable which we will consider in the following section : 4.2 Data Analysis /
Hypotheses Testing. Furthermore, since we are “…interested in the relationship
and influence of one variable over another, the use of contingency tables is
appropriate” [95]. According to Rea and Parker these tables add an explanatory
dimension to simple frequency distributions. Finally, all survey basic raw data is
readily available in Appendix C.
4.1.2 Headquarters & Subsidiary Communication
f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 0 0.0% 0 0.0% 1 8.3% 1 11.1% 0 0.0% 2 2.9% 0 0.0% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 2 3.0%
+3 2 6.9% 2 25.0% 5 41.7% 0 0.0% 2 20.0% 11 16.2% 0 0.0% 3 37.5% 3 27.3% 0 0.0% 2 20.0% 8 11.9%+2 7 24.1% 1 12.5% 0 0.0% 0 0.0% 0 0.0% 8 11.8% 0 0.0% 0 0.0% 4 36.4% 0 0.0% 2 20.0% 6 9.0%+1 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9% 2 6.9% 1 12.5% 0 0.0% 0 0.0% 0 0.0% 3 4.5%
Neutral 0 0 0.0% 0 0.0% 0 0.0% 2 22.2% 3 30.0% 5 7.4% 4 13.8% 0 0.0% 1 9.1% 1 11.1% 1 10.0% 7 10.4%-1 3 10.3% 0 0.0% 2 16.7% 0 0.0% 0 0.0% 5 7.4% 4 13.8% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 6 9.0%-2 6 20.7% 4 50.0% 2 16.7% 2 22.2% 1 10.0% 15 22.1% 7 24.1% 1 12.5% 1 9.1% 5 55.6% 2 20.0% 16 23.9%-3 3 10.3% 0 0.0% 1 8.3% 1 11.1% 3 30.0% 8 11.8% 5 17.2% 3 37.5% 0 0.0% 0 0.0% 2 20.0% 10 14.9%
Completely Disagree -4 7 24.1% 1 12.5% 1 8.3% 2 22.2% 1 10.0% 12 17.6% 7 24.1% 0 0.0% 0 0.0% 1 11.1% 1 10.0% 9 13.4%
TOTALS : 29 100.0% 8 100.0% 12 100.0% 9 100.0% 10 100.0% 68 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0%
Table 4-1 : One-on-One Communication Structure
Survey Question 12 13Survey Question Japan Germany Italy USA Other Total Japan Germany Italy USA Other Total
Question 12 : At my company the technical communication channel between our subsidiary and our headquarters is one-to-one. This means there is a single person at the subsidiary talking with a single person at headquarters. They both then distribute the information to others at their respective locations. Question 13 : A one-to-one communication channel set-up is optimum for coordinating tech info and knowledge transfer.
More than 65% of Japanese companies do not agree with a 1-to-1 communication
structure at their operation and almost 90% personally feel that it is not the best
approach in setting communications and a knowledge transfer structure. This is an
interesting result because there have been cases where this is exactly how such
structures are in fact constructed in many Japanese companies. German and Italian
127
respondents seem split on both questions if this is in fact the structure at their
organizations and if this is the optimum set-up.
f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 3.0% 0 0.0% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 1 1.5%
+3 2 6.9% 0 0.0% 6 54.5% 0 0.0% 0 0.0% 8 11.9% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%+2 7 24.1% 1 12.5% 2 18.2% 2 22.2% 0 0.0% 12 17.9% 1 3.4% 0 0.0% 1 9.1% 2 22.2% 0 0.0% 4 6.0%+1 4 13.8% 3 37.5% 2 18.2% 1 11.1% 1 10.0% 11 16.4% 2 6.9% 1 12.5% 2 18.2% 1 11.1% 0 0.0% 6 9.0%
Neutral 0 1 3.4% 0 0.0% 1 9.1% 1 11.1% 4 40.0% 7 10.4% 6 20.7% 0 0.0% 1 9.1% 1 11.1% 2 20.0% 10 14.9%-1 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 20.0% 2 3.0% 4 13.8% 0 0.0% 3 27.3% 0 0.0% 2 20.0% 9 13.4%-2 4 13.8% 3 37.5% 0 0.0% 0 0.0% 1 10.0% 8 11.9% 5 17.2% 5 62.5% 3 27.3% 1 11.1% 5 50.0% 19 28.4%-3 3 10.3% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 4 6.0% 5 17.2% 2 25.0% 1 9.1% 0 0.0% 1 10.0% 9 13.4%
Completely Disagree -4 7 24.1% 1 12.5% 0 0.0% 3 33.3% 2 20.0% 13 19.4% 5 17.2% 0 0.0% 0 0.0% 3 33.3% 0 0.0% 8 11.9%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0%
Table 4-2 : One-to-Many Communication Structure
Survey Question 14 15Survey Question Other TotalJapan GermanyItaly USA Italy USAOther TotalJapan Germany
Question 14 : At my company the technical communication channel between our subsidiary and our headquarters is one-to-many. This means there is a single person at the subsidiary talking with multiple / many people at headquarters. That single person then distributes the information at the subsidiary accordingly to who needs it. Question 15 : A one-to-many communication channel set-up is optimum for coordinating tech. info and knowledge transfer.
Results indicate essentially a split in Japanese company response on this particular
communication structure and its usage within their organizations. German
companies also are somewhat split on this structure as well, while interestingly
results indicate that Italian companies, by a majority 90%, do in fact practice this
type of structure. It is hypothesized that perhaps this is the case for Italian
manufacturers due to the relative younger age of their subsidiaries in the USA as
well as the fact that these companies also tend to be smaller in size tan their
German and Japanese counterparts. Results on question 15 indicate that a majority
of Japanese respondents (more than 85%) indicate that a 1-to-many scenario is not
considered optimum, even though its actual utilization is confirmed by Question 14.
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f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 0 0.0% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 2 3.0% 0 0.0% 1 12.5% 0 0.0% 0 0.0% 0 0.0% 1 1.5%
+3 3 10.3% 2 25.0% 3 27.3% 0 0.0% 0 0.0% 8 11.9% 1 3.4% 1 12.5% 4 40.0% 0 0.0% 0 0.0% 6 9.1%+2 4 13.8% 1 12.5% 0 0.0% 1 11.1% 0 0.0% 6 9.0% 3 10.3% 1 12.5% 0 0.0% 1 11.1% 0 0.0% 5 7.6%+1 5 17.2% 0 0.0% 0 0.0% 0 0.0% 2 20.0% 7 10.4% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 10.0% 2 3.0%
Neutral 0 1 3.4% 1 12.5% 0 0.0% 1 11.1% 3 30.0% 6 9.0% 6 20.7% 1 12.5% 0 0.0% 1 11.1% 4 40.0% 12 18.2%-1 1 3.4% 1 12.5% 0 0.0% 1 11.1% 1 10.0% 4 6.0% 3 10.3% 0 0.0% 0 0.0% 0 0.0% 1 10.0% 4 6.1%-2 1 3.4% 2 25.0% 1 9.1% 0 0.0% 2 20.0% 6 9.0% 2 6.9% 1 12.5% 1 10.0% 2 22.2% 1 10.0% 7 10.6%-3 6 20.7% 0 0.0% 3 27.3% 2 22.2% 0 0.0% 11 16.4% 5 17.2% 3 37.5% 2 20.0% 1 11.1% 2 20.0% 13 19.7%
Completely Disagree -4 8 27.6% 1 12.5% 2 18.2% 4 44.4% 2 20.0% 17 25.4% 8 27.6% 0 0.0% 3 30.0% 4 44.4% 1 10.0% 16 24.2%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0% 29 100.0% 8 100.0% 10 100.0% 9 100.0% 10 100.0% 66 100.0%
Table 4-3 : Many-to-One Communication Structure
Italy USASurvey Question 16 17Survey Question
Japan GermanyJapan Germany Italy USA Other Total Other Total
Question 16 : At my company the technical communication channel between our subsidiary and our headquarters is many-to-one. This means there many at the subsidiary talking with a single person at headquarters. The single person coordinates information with others at headquarters as needed. Question 17 : A many-to-one communication channel set-up is optimum for coordinating tech info and knowledge transfer.
Results indicate that Japanese, German, and Italian companies are basically split
almost evenly on this question regarding agreement or disagreement. This would
indicate that this type of structure does indeed exist in their corporations. Most likely
this would involve some kind of international planning department with a specified
manager handling inquiries from the subsidiaries. This is in fact practiced but tends
to slow down communications and affects the transmission factors of speed,
context (depending on language capabilities of this Department), and it could also
affect trust in such a way as to have headquarters dependent on their International
Planning or Support Department to deal with the subsidiaries instead of cross-
communication across all departments. Also, once again whereas German and
Italian respondents were split on how favorable they saw this structure personally;
Japanese respondents overwhelmingly felt that this was not optimum.
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f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 3 10.3% 1 12.5% 0 0.0% 1 11.1% 2 20.0% 7 10.4% 7 24.1% 1 12.5% 3 27.3% 1 11.1% 1 10.0% 13 19.4%
+3 8 27.6% 0 0.0% 2 18.2% 1 11.1% 1 10.0% 12 17.9% 8 27.6% 0 0.0% 2 18.2% 3 33.3% 2 20.0% 15 22.4%+2 0 0.0% 3 37.5% 2 18.2% 0 0.0% 2 20.0% 7 10.4% 3 10.3% 0 0.0% 0 0.0% 0 0.0% 2 20.0% 5 7.5%+1 1 3.4% 0 0.0% 2 18.2% 0 0.0% 1 10.0% 4 6.0% 2 6.9% 3 37.5% 0 0.0% 0 0.0% 0 0.0% 5 7.5%
Neutral 0 1 3.4% 0 0.0% 0 0.0% 2 22.2% 2 20.0% 5 7.5% 2 6.9% 0 0.0% 0 0.0% 2 22.2% 1 10.0% 5 7.5%-1 2 6.9% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 3 4.5% 0 0.0% 0 0.0% 1 9.1% 1 11.1% 3 30.0% 5 7.5%-2 5 17.2% 0 0.0% 0 0.0% 1 11.1% 1 10.0% 7 10.4% 2 6.9% 1 12.5% 2 18.2% 0 0.0% 0 0.0% 5 7.5%-3 8 27.6% 4 50.0% 5 45.5% 1 11.1% 0 0.0% 18 26.9% 3 10.3% 1 12.5% 3 27.3% 0 0.0% 0 0.0% 7 10.4%
Completely Disagree -4 1 3.4% 0 0.0% 0 0.0% 2 22.2% 1 10.0% 4 6.0% 2 6.9% 2 25.0% 0 0.0% 2 22.2% 1 10.0% 7 10.4%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 10 100.0% 67 100.0%
Table 4-4 : Many-to-Many Communication Structure
Survey Question 18 19Survey Question Italy USA Other TotalJapan Germany Italy USA Other Total Japan Germany
Question 18 : At my company the technical communication channel between our subsidiary and our headquarters is many-to-many. This means that multiple / many people at our subsidiary talk with multiple / many people at headquarters as required. There is no real formal channels of communication. Question 19 : A many-to-many communication channel set-up is optimum for coordinating tech info and knowledge transfer.
Almost 70% of Japanese respondents indicated that they consider the many-to-
many model the optimum structure for communications and knowledge transfer
even though there is disagreement on this structure as the actual mechanism in
their corporations. This agreement that this many-to-many structure, by far,
surpassed both German and Italian responses that ranged only between 37~40%
agreement.
f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 5 17.2% 0 0.0% 0 0.0% 3 33.3% 0 0.0% 8 11.8% 9 31.0% 0 0.0% 0 0.0% 5 55.6% 1 9.1% 15 22.1%
+3 9 31.0% 2 25.0% 0 0.0% 1 11.1% 6 54.5% 18 26.5% 5 17.2% 1 12.5% 10 90.9% 2 22.2% 6 54.5% 24 35.3%+2 9 31.0% 5 62.5% 3 27.3% 2 22.2% 3 27.3% 22 32.4% 11 37.9% 3 37.5% 0 0.0% 0 0.0% 2 18.2% 16 23.5%+1 5 17.2% 1 12.5% 1 9.1% 2 22.2% 0 0.0% 9 13.2% 3 10.3% 4 50.0% 0 0.0% 1 11.1% 0 0.0% 8 11.8%
Neutral 0 1 3.4% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 3 4.4% 0 0.0% 0 0.0% 1 9.1% 1 11.1% 2 18.2% 4 5.9%-1 0 0.0% 0 0.0% 1 9.1% 0 0.0% 0 0.0% 1 1.5% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-2 0 0.0% 0 0.0% 6 54.5% 0 0.0% 1 9.1% 7 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-5 : Written / Documented Communications
Survey Question 20 21Survey Question Japan Germany Italy USA Other Total Japan Germany Italy USA Other Total
Question 20 : At my company we handle technical communications between subsidiary and headquarters in a formal documented way using e-mail, fax, or other structured means. We do things in writing. Question 21 : The best way for handling technical communication between subsidiary and headquarters is in writing, by e-mail, fax, and / or other structured documented means.
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Virtually all (at 96%) Japanese respondents indicate that handling communications
in writing is the best way and this is how it’s done at their companies. This is
interesting in 2 ways, first it indicates that written communication is preferred
because it may be easier for headquarters personnel to review and respond. It is
fairly well-known that many individuals prefer written communication as opposed to
on-the-spot verbal communication because of fear and other factors associated
with their level of knowledge of that foreign language, and for the Japanese its no
different; in fact it is even more desired due to the emphasis on written over verbal
foreign language instruction within the Japanese education system.
Secondly, we must also consider the time-difference and the difficulty in
coordinating verbal communications whether by phone or video conference when
the time difference between subsidiary and headquarters is 12 to 13 hours.
Germans as well prefer written communications and it’s hypothesized that this may
be due to the precise and low context nature of the culture. Perhaps not surprisingly,
more than half of the respondents from Italian manufacturers indicate that this is not
the way it’s done at their company. Once again it is felt that the relatively young age
of subsidiaries within the U.S. may play a role in the fact that such formalized
systems perhaps have not been fully implemented.
f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 0 0.0% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 2 2.9% 4 13.8% 2 25.0% 2 18.2% 1 11.1% 0 0.0% 9 13.2%
+3 1 3.4% 0 0.0% 2 18.2% 1 11.1% 1 9.1% 5 7.4% 10 34.5% 2 25.0% 4 36.4% 1 11.1% 0 0.0% 17 25.0%+2 4 13.8% 3 37.5% 2 18.2% 0 0.0% 4 36.4% 13 19.1% 4 13.8% 2 25.0% 0 0.0% 0 0.0% 4 36.4% 10 14.7%+1 3 10.3% 4 50.0% 1 9.1% 0 0.0% 1 9.1% 9 13.2% 5 17.2% 2 25.0% 0 0.0% 1 11.1% 4 36.4% 12 17.6%
Neutral 0 1 3.4% 0 0.0% 1 9.1% 3 33.3% 0 0.0% 5 7.4% 1 3.4% 0 0.0% 1 9.1% 3 33.3% 0 0.0% 5 7.4%-1 6 20.7% 1 12.5% 1 9.1% 2 22.2% 2 18.2% 12 17.6% 0 0.0% 0 0.0% 4 36.4% 1 11.1% 1 9.1% 6 8.8%-2 7 24.1% 0 0.0% 2 18.2% 2 22.2% 1 9.1% 12 17.6% 3 10.3% 0 0.0% 0 0.0% 2 22.2% 1 9.1% 6 8.8%-3 5 17.2% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 7 10.3% 2 6.9% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 2.9%
Completely Disagree -4 2 6.9% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 3 4.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 1 1.5%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-6 : Verbal, Face-to-Face Communications
Survey Question 22 23Survey Question Other TotalJapan GermanyItaly USA Italy USAOther TotalJapan Germany
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Question 22 : At my company we handle technical communications between subsidiary and headquarters, by phone, video conference, or face-to-face meetings whenever possible. We try to speak to each other instead of writing. Question 23 : The best way for handling technical communication between subsidiary and headquarters is by phone or video conference. It is preferable to look and directly speak to and hear the other person while discussing technical issues.
Not surprisingly and in conjunction with the results from Questions 20 and 21,
Japanese respondents do not agree with face-to-face and/or verbal
communications. They indicate by a majority of about 68% that this is normally not
how it’s done at their corporations. German respondents however indicate that in
fact this does take place in German parent-subsidiary communications, this is
indicated by a majority 87% of respondents. Italian respondents are essentially split
almost evenly. Interestingly enough however both German and Japanese
respondents indicated that they would prefer to communicate (more) in a verbal,
face-to-face manner, by video conference, and the like. 100% of German
respondents either Agree or Completely Agree with this idea, while about 75% of
Japanese also fall in this category.
4.1.3 Headquarters & Subsidiary KT and Corporate Culture
f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 0 0.0% 1 11.1% 0 0.0% 2 22.2% 0 0.0% 3 4.3% 8 27.6% 1 12.5% 1 9.1% 3 33.3% 0 0.0% 13 19.1%
+3 2 6.9% 2 22.2% 0 0.0% 4 44.4% 2 18.2% 10 14.5% 7 24.1% 2 25.0% 8 72.7% 4 44.4% 5 45.5% 26 38.2%+2 1 3.4% 2 22.2% 0 0.0% 1 11.1% 1 9.1% 5 7.2% 5 17.2% 5 62.5% 2 18.2% 0 0.0% 3 27.3% 15 22.1%+1 2 6.9% 1 11.1% 0 0.0% 0 0.0% 3 27.3% 6 8.7% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 18.2% 2 2.9%
Neutral 0 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 2 2.9% 2 6.9% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 2.9%-1 0 0.0% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 2 2.9% 5 17.2% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 5 7.4%-2 13 44.8% 1 11.1% 5 45.5% 0 0.0% 1 9.1% 20 29.0% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 2 2.9%-3 8 27.6% 2 22.2% 6 54.5% 1 11.1% 1 9.1% 18 26.1% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%
Completely Disagree -4 2 6.9% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 3 4.3% 0 0.0% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 2 2.9%
TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-7 : Trust
Italy USASurvey Question 24 25Survey Question
Japan GermanyJapan Germany Italy USA Other Total Other Total
Question 24 : At my company there is an open and sharing of technical information and knowledge. Nothing is held back from each other by either subsidiaries nor headquarters. There is trust. We are a learning organization, an environment of continuous improvement. This is encouraged by management.
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Question 25 : The best approach in terms of knowledge sharing between headquarters and subsidiary is openness, full-sharing, and trust. You should not keep information from others as an advantage for yourself.
Almost 80% of Japanese respondents indicate disagreement with the statement
that there is open, sharing of information and trust. This is a significant result
because it indicates a presence of distrust within their organizations. Italian
companies also overwhelmingly at 99% seem to share the same kind of sense of
mistrust, no sharing, no openness. In contrast, both German and U.S. companies
indicate agreement that this sense of trust and openness and sharing does in fact
exist. However we need to consider this information with some care. Across the
board all respondents agreed that this however is required and the best approach.
f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 3 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 3 4.4% 3 10.3% 0 0.0% 1 9.1% 3 33.3% 1 9.1% 8 11.6%
+3 0 0.0% 2 25.0% 2 18.2% 0 0.0% 1 9.1% 5 7.4% 11 37.9% 2 22.2% 9 81.8% 0 0.0% 1 9.1% 23 33.3%+2 1 3.4% 1 12.5% 3 27.3% 0 0.0% 1 9.1% 6 8.8% 9 31.0% 0 0.0% 1 9.1% 1 11.1% 2 18.2% 13 18.8%+1 0 0.0% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 2 2.9% 0 0.0% 2 22.2% 0 0.0% 0 0.0% 1 9.1% 3 4.3%
Neutral 0 2 6.9% 0 0.0% 2 18.2% 1 11.1% 2 18.2% 7 10.3% 1 3.4% 0 0.0% 0 0.0% 1 11.1% 4 36.4% 6 8.7%-1 4 13.8% 0 0.0% 1 9.1% 0 0.0% 3 27.3% 8 11.8% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.4%-2 12 41.4% 2 25.0% 2 18.2% 1 11.1% 1 9.1% 18 26.5% 2 6.9% 3 33.3% 0 0.0% 0 0.0% 0 0.0% 5 7.2%-3 6 20.7% 2 25.0% 1 9.1% 3 33.3% 2 18.2% 14 20.6% 2 6.9% 1 11.1% 0 0.0% 1 11.1% 2 18.2% 6 8.7%
Completely Disagree -4 1 3.4% 1 12.5% 0 0.0% 3 33.3% 0 0.0% 5 7.4% 0 0.0% 1 11.1% 0 0.0% 3 33.3% 0 0.0% 4 5.8%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0% 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%
Table 4-8 : Hold-Back of Information Either by Headquarters or Subsidiary - 1
Survey Question 26 27Survey QuestionUSA Other TotalGermany Italy USA ItalyOther TotalJapan Japan Germany
Question 26 : At my company for whatever reason the subsidiary does hold back from headquarters some technical information, knowledge and know-how acquired from local market experience and customers. Question 27 : At my company for whatever reason headquarters does hold back from the subsidiary some centrally-based core technical information, knowledge and know-how.
Results indicate that the majority of Japanese, German, and American respondents
feel that at their company there is no holding back of information by the subsidiary
for any reason. Italian respondents are split. Surprisingly enough, however, almost
80% of Japanese respondents indicate that headquarters in fact does hold back
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information from the subsidiary. More surprisingly even though there was a split in
responses from Italian companies on whether the subsidiary holds back, the
majority (more than 90%) indicate that their headquarters does in fact hold back
information. This is an interesting result in that it relates to trust issues between
headquarters and the subsidiaries. There seems to be an aspect of “us vs. them”
which can lead to morale issues and be unproductive in the operation of the
subsidiary. Furthermore this can then it can spiral back to headquarters and create
a negative situation there as well eventually leading to a self-fulfilling prophecy of
inefficiency and poor morale which can impact project success.
f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%
+3 1 3.4% 1 12.5% 1 9.1% 0 0.0% 1 9.1% 4 5.9%+2 8 27.6% 0 0.0% 1 9.1% 1 11.1% 0 0.0% 10 14.7%+1 2 6.9% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 3 4.4%
Neutral 0 2 6.9% 0 0.0% 0 0.0% 2 22.2% 4 36.4% 8 11.8%-1 0 0.0% 0 0.0% 1 9.1% 0 0.0% 1 9.1% 2 2.9%-2 1 3.4% 1 12.5% 1 9.1% 1 11.1% 0 0.0% 4 5.9%-3 6 20.7% 5 62.5% 7 63.6% 1 11.1% 3 27.3% 22 32.4%
Completely Disagree -4 8 27.6% 1 12.5% 0 0.0% 4 44.4% 1 9.1% 14 20.6%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-9 : Hold-Back of Information Either by Headquarters or Subsidiary - 2
Survey Question 28Japan Germany Italy USA Other Total
Question 28 : It is acceptable for either headquarters or the subsidiary to hold back information from time to time in order to gain some real or perceived advantage. Critical information is a source of power that can be used.
Results indicate a split between agreement and disagreement within Japanese
companies on whether its OK to hold back. The rest of the respondents disagree
with holding back information. Again, the results are interesting from a trust point of
view. We will see later in the report that these attitudes of withholding information
whether by subsidiary or parent company and whether true or simply perceived do
reflect an aspect of culture whether Indo-European, Asian, and the like.
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f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9%
+3 6 20.7% 4 44.4% 6 54.5% 1 11.1% 2 18.2% 19 27.5%+2 4 13.8% 3 33.3% 3 27.3% 3 33.3% 2 18.2% 15 21.7%+1 1 3.4% 1 11.1% 1 9.1% 0 0.0% 0 0.0% 3 4.3%
Neutral 0 3 10.3% 0 0.0% 0 0.0% 0 0.0% 2 18.2% 5 7.2%-1 2 6.9% 0 0.0% 0 0.0% 1 11.1% 4 36.4% 7 10.1%-2 7 24.1% 1 11.1% 1 9.1% 3 33.3% 1 9.1% 13 18.8%-3 5 17.2% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 5 7.2%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%
Table 4-10 : Technical Project Specs. & Customer Knowledge
Survey Question 29Other TotalJapan Germany Italy USA
Question 29 : At my company we usually do not have any problems with customers transferring their Technical Project Specifications to us. Our customers are knowledgeable, they know what they want, and what is available in the market.
Japanese respondents to this Question 29 are split almost evenly in indicating
problems with customer transfer of technical project specifications. Since the
majority of German, Italian and most U.S. companies seem to feel that this is not a
problem for them; we think that perhaps this relates to language issues with
Japanese companies.
f % f % f % f % f % f %Completely Agree +4 0 0.0% 1 12.5% 0 0.0% 2 22.2% 0 0.0% 3 4.4%
+3 4 13.8% 2 25.0% 5 45.5% 2 22.2% 2 18.2% 15 22.1%+2 4 13.8% 4 50.0% 0 0.0% 1 11.1% 4 36.4% 13 19.1%+1 1 3.4% 1 12.5% 0 0.0% 1 11.1% 3 27.3% 6 8.8%
Neutral 0 3 10.3% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 5 7.4%-1 4 13.8% 0 0.0% 3 27.3% 0 0.0% 1 9.1% 8 11.8%-2 6 20.7% 0 0.0% 2 18.2% 1 11.1% 1 9.1% 10 14.7%-3 6 20.7% 0 0.0% 1 9.1% 0 0.0% 0 0.0% 7 10.3%
Completely Disagree -4 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Survey Question 30Japan Germany Italy USA Other Total
Table 4-11 : Technology Tools
Question 30 : At my company we use fairly new technology tools to facilitate knowledge transfer and sharing between headquarters and the subsidiaries. We keep up with technology.
German respondents indicate significant usage of technology tools. 100% response
from German companies indicates agreement with the survey Question / Statement
30; whereas a strong portion of Japanese respondents (about 59%) indicate no
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such usage or minimal usage of technology regarding knowledge transfer
facilitation.
f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9% 8 27.6% 4 50.0% 1 9.1% 4 44.4% 2 18.2% 19 27.9%
+3 1 3.4% 5 55.6% 2 18.2% 1 11.1% 6 54.5% 15 21.7% 18 62.1% 4 50.0% 7 63.6% 2 22.2% 6 54.5% 37 54.4%+2 7 24.1% 0 0.0% 2 18.2% 3 33.3% 3 27.3% 15 21.7% 1 3.4% 0 0.0% 3 27.3% 2 22.2% 2 18.2% 8 11.8%+1 2 6.9% 1 11.1% 1 9.1% 0 0.0% 0 0.0% 4 5.8% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%
Neutral 0 3 10.3% 0 0.0% 0 0.0% 3 33.3% 1 9.1% 7 10.1% 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 2 2.9%-1 6 20.7% 3 33.3% 0 0.0% 0 0.0% 0 0.0% 9 13.0% 0 0.0% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 1 1.5%-2 8 27.6% 0 0.0% 4 36.4% 1 11.1% 1 9.1% 14 20.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-3 1 3.4% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 3 4.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-12 : Cooperation & Collaboration / Culture
Survey Question 31 32Survey Question Japan Germany Italy USA Other Total Japan Germany Italy USA Other Total
Question 31 : At my company cooperation and collaboration is critical to our success and strong within our culture; everyone understands and practices this for mutual benefit both within the subsidiary and between headquarters and subsidiary. Question 32 : A spirit of true cooperation and collaboration is the most important aspect of knowledge transfer.
Japanese respondents seem to disagree with this particular statement on
cooperation and collaboration existing between parent and subsidiary entities at
their corporations. About 60% indicate that there may be problems with true
cooperation and collaboration. German and Italian responses indicate a split.
However all respondents across the board overwhelmingly indicate that a spirit of
cooperation and collaboration is in fact critical and the most important aspect of
knowledge transfer. It just seems from the responses that even though individual
may feel this way, it is lacking in practice.
f % f % f % f % f % f %Completely Agree +4 0 0.0% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 1 1.4%
+3 2 6.9% 1 11.1% 0 0.0% 0 0.0% 2 18.2% 5 7.2%+2 11 37.9% 2 22.2% 1 9.1% 4 44.4% 1 9.1% 19 27.5%+1 1 3.4% 1 11.1% 0 0.0% 2 22.2% 4 36.4% 8 11.6%
Neutral 0 1 3.4% 2 22.2% 0 0.0% 2 22.2% 3 27.3% 8 11.6%-1 4 13.8% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 6 8.7%-2 6 20.7% 3 33.3% 8 72.7% 0 0.0% 0 0.0% 17 24.6%-3 3 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 3 4.3%
Completely Disagree -4 1 3.4% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 2 2.9%
TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%
Table 4-13 : Structure of Decision-Making and Processes
Survey Question 33Japan Germany Italy USA Other Total
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Question 33 : At my company there is a high level of agreement about how things are done; we have a fairly strong structure where each and every one follows strict guidelines on doing things.
Japanese and German responses indicate a split between agreement and
disagreement with this Question / Statement; Italian respondents however indicate
that such structure really does not exists; thus they overwhelmingly disagree at
about 90% rate. This could once again indicate the relatively young age of Italian
subsidiaries compared to both German and Japanese companies. The fact could
be that Italian subsidiaries in the U.S. could still be maturing and creating these
needed structures within their operations while both Japanese and German
companies have evolved these systems already.
f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9%
+3 1 3.4% 2 22.2% 0 0.0% 1 11.1% 2 18.2% 6 8.7%+2 2 6.9% 6 66.7% 0 0.0% 2 22.2% 1 9.1% 11 15.9%+1 3 10.3% 0 0.0% 0 0.0% 0 0.0% 2 18.2% 5 7.2%
Neutral 0 1 3.4% 1 11.1% 0 0.0% 3 33.3% 2 18.2% 7 10.1%-1 11 37.9% 0 0.0% 0 0.0% 0 0.0% 2 18.2% 13 18.8%-2 8 27.6% 0 0.0% 3 27.3% 2 22.2% 2 18.2% 15 21.7%-3 0 0.0% 0 0.0% 7 63.6% 0 0.0% 0 0.0% 7 10.1%
Completely Disagree -4 2 6.9% 0 0.0% 1 9.1% 0 0.0% 0 0.0% 3 4.3%
TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%
Table 4-14 : Employee Input Into Decision-Making
Survey Question 34Japan Germany Italy USA Other Total
Question 34 : At my company most employees have direct input into decisions that affect them.
Most Japanese companies (about 70%) disagree and indicate that employees do
not have a strong sense of direct input into decisions that may affect them. The
same holds true and to a greater extent at about 90% for Italian companies. It
would seem that employees in both Japanese and Italian manufacturers at least in
this industry) are not directly influential in decision-making. On the other hand
German companies seem to provide more leeway and opportunity in their
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employees having more direct input. They overwhelmingly answered in the positive
at about 88% in agreement with survey Question 34.
f % f % f % f % f % f %Completely Agree +4 0 0.0% 1 12.5% 0 0.0% 1 11.1% 0 0.0% 2 2.9%
+3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 1 1.5%+2 0 0.0% 0 0.0% 0 0.0% 3 33.3% 2 18.2% 5 7.4%+1 3 10.3% 4 50.0% 0 0.0% 2 22.2% 2 18.2% 11 16.2%
Neutral 0 1 3.4% 0 0.0% 0 0.0% 2 22.2% 3 27.3% 6 8.8%-1 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-2 11 37.9% 1 12.5% 3 27.3% 0 0.0% 2 18.2% 17 25.0%-3 10 34.5% 2 25.0% 6 54.5% 1 11.1% 1 9.1% 20 29.4%
Completely Disagree -4 4 13.8% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 6 8.8%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-15 : Shared-Meaning Between Headquarters and Subsidiary
Survey Question 35Japan Germany Italy USA Other Total
Question 35 : There is true shared-meaning between our company’s headquarters and subsidiaries. We really do understand each other.
Corresponding to previous results, once again Japanese and Italian company
respondents seem to feel that there is no shared-meaning between headquarters
and subsidiary; that there is no true understanding.
4.1.4 What is Project Success
f % f % f % f % f % f % f % f % f % f % f % f %Completely Agree +4 7 24.1% 1 11.1% 4 28.6% 4 44.4% 1 9.1% 17 23.6% 8 27.6% 1 12.5% 1 9.1% 3 33.3% 3 27.3% 16 23.5%
+3 10 34.5% 5 55.6% 3 21.4% 2 22.2% 6 54.5% 26 36.1% 12 41.4% 7 87.5% 8 72.7% 3 33.3% 6 54.5% 36 52.9%+2 3 10.3% 3 33.3% 2 14.3% 0 0.0% 2 18.2% 10 13.9% 6 20.7% 0 0.0% 2 18.2% 2 22.2% 2 18.2% 12 17.6%+1 2 6.9% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 4 5.6% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
Neutral 0 3 10.3% 0 0.0% 0 0.0% 1 11.1% 2 18.2% 6 8.3% 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9%-1 3 10.3% 0 0.0% 4 28.6% 0 0.0% 0 0.0% 7 9.7% 2 6.9% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 2 2.9%-2 1 3.4% 0 0.0% 1 7.1% 0 0.0% 0 0.0% 2 2.8% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 9 100.0% 14 100.0% 9 100.0% 11 100.0% 72 100.0% 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-16 : Project Success : Time, Budget, Performance
Survey Question 36 37Survey QuestionJapan Germany Italy USA Other Total Japan Germany Italy USA Other Total
Question 36 : At my company we measure Project Success as completing a project on-time, on-budget, and meeting all technical performance specifications in terms of function and quality. Question 37 : The best measure of project success is by means of delivery, budget, and performance.
Essentially the majority of respondents regardless of company nationality indicated
that delivery, price, and technical performance are in fact key measures of project
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success. Across the board Japanese ( 75% ), German ( 100% ), Italian ( 64% ), and
American ( 66% ) companies in this industry still measure project success based on
these original factors.
f % f % f % f % f % f %Completely Agree +4 1 3.4% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 3 4.3%
+3 2 6.9% 1 11.1% 0 0.0% 1 11.1% 0 0.0% 4 5.8%+2 1 3.4% 0 0.0% 0 0.0% 1 11.1% 2 18.2% 4 5.8%+1 1 3.4% 1 11.1% 0 0.0% 1 11.1% 3 27.3% 6 8.7%
Neutral 0 1 3.4% 0 0.0% 0 0.0% 1 11.1% 3 27.3% 5 7.2%-1 4 13.8% 3 33.3% 0 0.0% 1 11.1% 0 0.0% 8 11.6%-2 10 34.5% 0 0.0% 2 18.2% 2 22.2% 1 9.1% 15 21.7%-3 7 24.1% 3 33.3% 7 63.6% 1 11.1% 1 9.1% 19 27.5%
Completely Disagree -4 2 6.9% 1 11.1% 2 18.2% 0 0.0% 0 0.0% 5 7.2%
TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%
Table 4-17 : Post-Project Reviews
Survey Question 38Japan Germany Italy USA Other Total
Question 38 : At my company we conduct fairly structured post-project reviews and lessons-learned sessions. These are important to identify and understand ways to improve our project capabilities. Virtually no majority, whether Japanese, German, Italian, nor American, conducts
structured post-project reviews and lessons-learned sessions.
f % f % f % f % f % f %Completely Agree +4 3 10.3% 1 12.5% 5 45.5% 1 11.1% 1 9.1% 11 16.2%
+3 11 37.9% 1 12.5% 0 0.0% 1 11.1% 5 45.5% 18 26.5%+2 2 6.9% 6 75.0% 3 27.3% 2 22.2% 4 36.4% 17 25.0%+1 5 17.2% 0 0.0% 1 9.1% 3 33.3% 0 0.0% 9 13.2%
Neutral 0 5 17.2% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 6 8.8%-1 0 0.0% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 1 1.5%-2 3 10.3% 0 0.0% 0 0.0% 0 0.0% 1 9.1% 4 5.9%-3 0 0.0% 0 0.0% 2 18.2% 0 0.0% 0 0.0% 2 2.9%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-18 : Employee Morale, Satisfaction, and Project Success
Survey Question 39Japan Germany Italy USA Other Total
Question 39 : Employee morale and satisfaction at the subsidiary is an important measure of project success even though there may be no direct impact at all on cost, delivery and performance.
Results indicate consistently that almost all respondents regardless of company
nationality feel that employee morale, satisfaction is an important measure of
project success. How important compared to price, delivery and performance,
unfortunately was not indicated in any particular individual survey question but will
be analyzed within this research. It is interesting that respondents overwhelmingly
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consider the typical project success factors but also consider employee morale and
satisfaction. This was a result that was not really expected within this fairly mature
and some would consider “old-fashioned” industry.
f % f % f % f % f % f %Completely Agree +4 9 31.0% 1 12.5% 3 27.3% 1 11.1% 3 27.3% 17 25.0%
+3 10 34.5% 4 50.0% 7 63.6% 4 44.4% 3 27.3% 28 41.2%+2 8 27.6% 3 37.5% 1 9.1% 2 22.2% 3 27.3% 17 25.0%+1 1 3.4% 0 0.0% 0 0.0% 2 22.2% 2 18.2% 5 7.4%
Neutral 0 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-1 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-2 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%-3 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-19 : Customer Satisfaction and Repeat Business, and Project Success
Survey Question 40Japan Germany Italy USA Other Total
Question 40 : Fully satisfied customers leading to repeat business is the most important measure of project success. This means also eliminating after-market repairs and problems. Results indicate a strong agreement to the statement on satisfied customers and
repeat business being an indicator of project success. Virtually all responses
indicated a 90%n or greater agreement rate.
f % f % f % f % f % f %Completely Agree +4 3 10.3% 0 0.0% 1 9.1% 2 22.2% 1 9.1% 7 10.1%
+3 9 31.0% 3 33.3% 9 81.8% 3 33.3% 5 45.5% 29 42.0%+2 7 24.1% 3 33.3% 1 9.1% 2 22.2% 3 27.3% 16 23.2%+1 3 10.3% 2 22.2% 0 0.0% 1 11.1% 2 18.2% 8 11.6%
Neutral 0 3 10.3% 1 11.1% 0 0.0% 1 11.1% 0 0.0% 5 7.2%-1 3 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 3 4.3%-2 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.4%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 9 100.0% 11 100.0% 9 100.0% 11 100.0% 69 100.0%
Table 4-20 : Financial and Commercial Gains, Increase Market Share, and Project Success
Survey Question 41Japan Germany Italy USA Other Total
Question 41 : My company measures project success based on what was achieved commercially, financially, increase market share.
As with Question / Comment 40, again there was strong agreement with
commercial and financial indicators of project success. American and Italian
responses indicated a stronger more complete agreement as opposed to Japanese
and German whose responses are more spread. We hypothesize that this relates to
the desire to increase market share by relatively newer Italian manufacturers both
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in the United States and globally. Along those lines this would also indicate the
desire for American manufacturers in this industry to perhaps regain some market
share lost to foreign competitors. Japanese respondents were more spread which
would indicate perhaps some stability in their situation in the industry.
f % f % f % f % f % f %Completely Agree +4 3 10.3% 0 0.0% 1 9.1% 1 11.1% 3 27.3% 8 11.8%
+3 6 20.7% 4 50.0% 5 45.5% 1 11.1% 3 27.3% 19 27.9%+2 8 27.6% 4 50.0% 4 36.4% 3 33.3% 3 27.3% 22 32.4%+1 4 13.8% 0 0.0% 1 9.1% 1 11.1% 2 18.2% 8 11.8%
Neutral 0 1 3.4% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 2 2.9%-1 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-2 3 10.3% 0 0.0% 0 0.0% 2 22.2% 0 0.0% 5 7.4%-3 3 10.3% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 3 4.4%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-21 : Risk Management and Project Success
Survey Question 42Japan Germany Italy USA Other Total
Question 42 : A very important aspect of project success is how effectively you deal with the inevitable problems that arise during the project; in other words, Risk Management.
A good majority, as indicated by the results, feels that risk management is also a
measure of project success although Japanese respondents do not have a very
strong preference for this particular measure.
f % f % f % f % f % f %Completely Agree +4 5 17.2% 0 0.0% 1 9.1% 3 33.3% 2 18.2% 11 16.2%
+3 14 48.3% 3 37.5% 7 63.6% 0 0.0% 3 27.3% 27 39.7%+2 6 20.7% 4 50.0% 2 18.2% 4 44.4% 1 9.1% 17 25.0%+1 2 6.9% 0 0.0% 0 0.0% 2 22.2% 2 18.2% 6 8.8%
Neutral 0 0 0.0% 1 12.5% 1 9.1% 0 0.0% 3 27.3% 5 7.4%-1 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-2 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-22 : Projects and Opportunity for Knowledge Creation
Survey Question 43Japan Germany Italy USA Other Total
Question 43 : The unique nature of projects means that there are many opportunities for knowledge creation both at the subsidiary and at headquarters.
Results show that Japanese respondents tend to value to a somewhat greater
extent than their counterparts the opportunity for knowledge creation within the
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context of new projects. Although both German and Italian respondents agree that
this is an important factor and measure, Japanese response indicates a complete
agreement at more than 17%. However interestingly enough American respondents
also strongly agree at more than 33% that there is opportunity for knowledge
creation within projects. It would seem that Japanese companies, in addition to their
American counterparts, understand a little bit better the relationship in knowledge
creation with new experiences such as projects. This goes back Nonaka and
Takeuchi’s [87] concepts in creating knowledge.
f % f % f % f % f % f %Completely Agree +4 5 17.2% 0 0.0% 3 27.3% 2 22.2% 3 27.3% 13 19.1%
+3 8 27.6% 3 37.5% 5 45.5% 0 0.0% 5 45.5% 21 30.9%+2 9 31.0% 5 62.5% 3 27.3% 4 44.4% 1 9.1% 22 32.4%+1 4 13.8% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 6 8.8%
Neutral 0 0 0.0% 0 0.0% 0 0.0% 1 11.1% 1 9.1% 2 2.9%-1 2 6.9% 0 0.0% 0 0.0% 1 11.1% 0 0.0% 3 4.4%-2 1 3.4% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 1 1.5%-3 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
Completely Disagree -4 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0%
TOTALS : 29 100.0% 8 100.0% 11 100.0% 9 100.0% 11 100.0% 68 100.0%
Table 4-23 : Project Success and Successful Knowledge Transfer
Survey Question 44Japan Germany Italy USA Other Total
Question 44 : Successful Knowledge transfer among all parties involved in a project : headquarters, subsidiary, customer, final end-user, is an important measure of project success even though there may be no direct impact at all on cost, delivery, and performance.
Results indicate that Japanese, German, and Italian respondents agree that
knowledge transfer is in fact an important measure of project success. American
response indicates a wider spread and not such a strong agreement as the others.
4.1.5 Project Success at Your Company
The results specific to project success evaluation at the respondents’ companies
are shown in Figures 4-8 thru 4-13 in frequency distribution graphs in order to
better-distinguish some differences between company nationalities.
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02468
10
121416
f
0% 20% 40% 60% 80% 100%
4-8a : Question 45 Percentage of projects delayed due to poor delivery performance. All
0123456789
f
0% 20% 40% 60% 80% 100%
4-8b : Question 45 Percentage of projects delayed due to poor
delivery performance.
USA
EuropeAsia
0
2
4
6
8
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f
0% 20% 40% 60% 80% 100%
4-9a : Question 46 Percentage of projects experiencing cost overruns leading to decreased margins. All
0
1
2
3
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5
6
7
f
0% 20% 40% 60% 80% 100%
4-9b : Question 46 Percentage of projects experiencing cost
overruns leading to decreased margins.
USAEurope
Asia
0
5
10
15
20
f
0% 20% 40% 60% 80% 100%
4-10a : Question 47 Percentage of recurring project business due to good customer satisfaction. All
0123456789
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f
0% 20% 40% 60% 80% 100%
4-10b : Question 47 Percentage of recurring project business
due to good customer satisfaction.USAEurope
Asia
0246
1012141618
8f
0% 20% 40% 60% 80% 100%
4-11a : Question 48 Percentage of overall successful projects is…..
All
0
2
4
6
8
10
12
f
0% 20% 40% 60% 80% 100%
4-11b : Qestion 48 Percentage of overall successful projects
is…..USA
Europe
Asia
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0
5
Overall, frequency distribution tabulation and subsequent statistical analyses
indicate that in terms of structuring communication channels, smaller companies
and subsidiaries tend to prefer one-to-one relationships and communication
channels between subsidiary and parent. This typically results in a 56% success
rate on major projects for all companies surveyed. When companies start evolving
into bigger entities, there is increasing disagreement with this one-to-one
relationship and the tendency is for the parent to encourage multilateral
communication channels which tend to slightly increase the success rate of projects
to approximately 68% for all companies surveyed. The potential for increased
resources as the entity grew bigger was considered only in terms of communication
and personnel instead of other material resources, with the exception of
technological communication tools such as video conferencing.
10
15
20
f
0% 20% 40% 60% 80% 100%
4-12a : Question 49 Percentage of subsidiary employees with a generally positive outlook and work morale. All
012345678
f
0% 20% 40% 60% 80% 100%
4-12b : Question 49 Percentage of subsidiary employees with a
generally positive outlook and work morale.
USA
Europe
Asia
0
5
10
15
20
f
0% 20% 40% 60% 80% 100%
4-13a : Question 50 Percentage of dissatisfaction from our parent headquarters is about….. All
012345678
f
0% 20% 40% 60% 80% 100%
4-13b : Question 50 Percentage of dissatisfaction from our
parent headquarters is about…..
USA
Europe
Asia
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The vast majority of companies in this industry maintain the classical definition of
project success of : on-time delivery, on-budget, and meeting all performance
specifications but a significant proportion, over 67% indicated that delivery from
their parent company was the key success factor for these major projects.
4.2 Data Analysis / Hypotheses Testing
Measures of central tendency and dispersion, which we initially consider in our analysis,
“…constitute the fundamental elements of descriptive statistics” [95]. They describe and
summarize a large amount of data typically obtained thru survey methodologies such as
with our own specific research. These analyses are fairly simple and elegant because
they provide description thru single statistical values.
Initial analysis was conducted on all fundamental survey questions in order to obtain a
baseline of our data. This is important because the next step is establishing an analysis
on the relationship among the data, specifically the relationship between variable
established from the various questions. Therefore an understanding of the initial data
disposition prior to initiating such a relational analysis is important. If there already exists
some initial relationship prior to our correlational methodology, it needs to be identified
and accounted for within the subsequent analysis we are most interested in below.
The simple arithmetic mean was calculated to identify data located above and below the
central point in addition to providing a relative distance of the data to that point. This is
important in order to establish the baseline for each survey question from which
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subsequent analyses such as ANOVA will be handled. The median also was calculated
to provide an additional measure comparable to the arithmetic mean. According to Rea
and Parker [95] when working with cross-tabulated contingency tables, “…it is normal
not to expect the median and the mean to coincide or even be close in magnitude to
each other based on a scaled frequency distribution used such as a Likert Scale…” [95].
Based on Rea and Parker’s “Designing and Conducting Survey Research” [95] the
arithmetic mean seems to be the most appropriate measure to consider. We calculated
and documented both this and the median.
The additional measure of central tendency is the mode which is useful in identifying the
particular category (in ordinal scaled surveys) which is “most popular” with respondents,
or most “typical” of the population surveyed. This calculation will help identify some
beliefs and trends and add to our discussion and conclusions from an overall
perspective.
The well-known standard deviation measure was individually calculated in order to
provide a good measure of dispersion that does not eliminate any outliers or extreme
values yet is not overly influenced by them. Finally we included a simple chi-square
calculation (χ2 ) for all the distribution function data obtained for each survey question
so that we could confirm that no initial relationship exists prior to initiating our
correlational analysis relating to our hypotheses.
Our initial analysis is summarized in tabular form in Table 4-23.
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mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr. mean median mode std.dev chi-sqr.
x m M s χ2 x m M s χ2 x m M s χ2 x m M s χ2 x m M s χ2 x m M s χ2
1. Question 12 -1.07 15.00 0.00 2.49 0.30 -0.50 4.50 0.00 2.55 0.65 0.50 6.50 1.00 2.78 0.20 -1.11 5.00 1.00 2.47 0.26 -0.90 5.50 0.00 2.39 0.09 -0.71 34.50 2.00 2.60 -2. Question 13 -2.03 15.00 0.00 1.56 0.20 -0.13 4.50 0.00 2.71 0.14 1.18 6.00 0.00 1.75 0.03 -0.67 5.00 0.00 2.67 0.01 -0.40 5.50 2.00 2.58 0.87 -0.85 34.00 6.00 2.40 -3. Question 14 -0.59 15.00 1.00 2.70 0.76 -0.63 4.50 0.00 2.00 0.29 2.18 6.00 0.00 1.03 0.00 -0.67 5.00 1.00 2.94 0.65 -1.10 5.50 0.00 1.64 0.00 -0.22 34.00 2.00 2.56 -4. Question 15 -1.45 15.00 5.00 1.89 0.80 -1.88 4.50 0.00 1.17 0.42 -0.73 6.00 0.00 1.48 0.77 -0.56 5.00 1.00 2.87 0.03 -1.50 5.50 0.00 0.92 0.73 -1.27 34.00 1.00 1.87 -5. Question 16 -1.07 15.00 1.00 2.64 0.69 -0.13 4.50 1.00 2.42 0.52 -0.18 6.00 0.00 3.33 0.05 -2.33 5.00 0.00 2.05 0.75 -1.10 5.50 0.00 1.76 0.17 -0.99 34.00 6.00 2.65 -6. Question 17 -1.52 15.00 1.00 2.19 0.91 -0.25 4.50 1.00 2.73 0.21 -0.80 5.50 0.00 3.16 0.07 -2.33 5.00 0.00 2.00 0.74 -1.20 5.50 1.00 1.60 0.52 -1.32 33.50 - 2.41 -7. Question 18 -0.10 15.00 1.00 2.82 0.48 -0.25 4.50 0.00 2.82 0.18 -0.27 6.00 0.00 2.56 0.33 -0.78 5.00 1.00 2.70 0.26 1.00 5.50 1.00 2.45 0.45 -0.07 34.00 7.00 2.76 -8. Question 19 1.34 15.00 2.00 2.71 0.89 -0.75 4.50 0.00 2.73 0.05 0.36 6.00 0.00 3.02 0.36 0.44 5.00 0.00 2.87 0.46 0.70 5.50 1.00 2.37 0.15 0.72 34.00 5.00 2.82 -9. Question 20 2.41 15.00 0.00 1.07 0.57 2.13 4.50 0.00 0.60 0.61 -0.55 6.00 0.00 1.78 0.00 2.33 5.00 0.00 1.41 0.30 2.00 6.00 0.00 1.54 0.33 1.82 34.50 0.00 1.67 -
10. Question 21 2.59 15.00 0.00 1.22 0.11 1.63 4.50 0.00 0.70 0.01 2.73 6.00 0.00 0.86 0.01 3.00 5.00 0.00 1.41 0.17 2.36 6.00 0.00 1.23 0.27 2.51 34.50 0.00 1.21 -11. Question 22 -1.00 15.00 1.00 1.95 0.72 1.13 4.50 0.00 0.93 0.09 0.00 6.00 2.00 2.22 0.87 0.11 5.00 0.00 1.97 0.06 0.73 6.00 1.00 2.30 0.62 -0.16 34.50 5.00 2.13 -12. Question 23 1.62 15.00 4.00 2.11 0.61 2.50 4.50 0.00 1.12 0.86 1.45 6.00 0.00 2.10 0.05 0.33 5.00 1.00 1.94 0.12 0.45 6.00 0.00 1.88 0.05 1.34 34.50 6.00 2.07 -13. Question 24 -1.66 15.00 2.00 1.86 0.54 0.78 5.00 1.00 2.57 0.63 -2.55 6.00 0.00 0.50 0.31 2.00 5.00 0.00 2.26 0.01 0.09 6.00 1.00 2.23 0.19 -0.72 35.00 3.00 2.47 -14. Question 25 1.83 15.00 5.00 2.13 0.21 2.50 4.50 0.00 0.71 0.42 2.91 6.00 0.00 0.51 0.61 1.78 5.00 0.00 3.12 0.04 1.91 6.00 0.00 1.44 0.08 2.09 34.50 2.00 1.96 -15. Question 26 -1.24 15.00 0.00 2.11 0.28 -0.75 4.50 0.00 1.41 0.62 0.36 6.00 0.00 2.06 0.31 -2.44 5.00 0.00 1.71 0.06 -0.45 6.00 1.00 1.83 0.54 -0.96 34.50 5.00 2.25 -16. Question 27 1.79 15.00 0.00 2.01 0.50 -0.56 5.00 0.00 2.45 0.01 3.00 6.00 0.00 0.43 0.13 -0.11 5.00 0.00 3.48 0.01 0.55 6.00 1.00 2.10 0.06 1.23 35.00 6.00 2.48 -17. Question 28 -0.93 15.00 1.00 2.75 0.39 -2.25 4.50 0.00 2.05 0.59 -1.73 6.00 0.00 2.09 0.30 -2.11 5.00 0.00 2.13 0.60 -0.91 6.00 1.00 2.02 0.20 -1.37 34.50 4.00 2.45 -18. Question 29 0.00 15.00 1.00 2.36 0.47 1.89 5.00 0.00 1.52 0.63 2.09 6.00 0.00 1.44 0.40 0.67 5.00 0.00 2.26 0.51 0.36 6.00 0.00 1.72 0.11 0.72 35.00 5.00 2.20 -19. Question 30 -0.59 15.00 4.00 2.21 0.38 2.38 4.50 0.00 0.86 0.34 0.45 6.00 0.00 2.39 0.29 1.67 5.00 2.00 1.94 0.16 1.27 6.00 0.00 1.48 0.35 0.53 34.50 - 2.27 -20. Question 31 -0.07 15.00 1.00 1.87 0.46 1.44 5.00 0.00 1.83 0.06 -0.27 6.00 0.00 2.34 0.22 1.22 5.00 0.00 1.75 0.17 2.00 6.00 0.00 1.54 0.24 0.59 35.00 15.00 2.08 -21. Question 32 3.07 15.00 0.00 0.87 - 3.50 4.50 0.00 0.50 - 2.82 6.00 0.00 0.57 - 2.78 5.00 0.00 1.55 - 2.73 6.00 0.00 1.05 - 2.99 34.50 0.00 0.98 -22. Question 33 0.00 15.00 1.00 2.15 0.40 0.22 5.00 0.00 1.81 0.93 -1.45 6.00 0.00 1.16 0.03 1.56 5.00 0.00 1.17 0.12 0.73 6.00 0.00 1.81 0.03 0.12 35.00 8.00 2.00 -23. Question 34 -0.72 15.00 1.00 1.82 0.09 2.00 5.00 0.00 0.82 0.00 -2.82 6.00 0.00 0.57 0.00 0.78 5.00 0.00 1.99 0.21 0.36 6.00 2.00 1.72 0.65 -0.33 35.00 7.00 2.12 -24. Question 35 -2.24 15.00 0.00 1.38 - 0.00 4.50 0.00 2.29 - -2.91 6.00 0.00 0.67 - 1.00 5.00 0.00 1.83 - 0.18 6.00 0.00 1.80 - -1.26 34.50 6.00 2.13 -25. Question 36 2.10 15.00 3.00 1.81 0.99 2.78 5.00 0.00 0.63 0.38 1.64 7.50 0.00 2.22 0.17 2.67 5.00 0.00 1.49 0.17 2.36 6.00 0.00 1.23 0.49 2.21 36.50 0.00 1.72 -26. Question 37 2.69 15.00 0.00 1.34 - 3.13 4.50 0.00 0.33 - 2.91 6.00 0.00 0.51 - 2.78 5.00 0.00 1.23 - 3.09 6.00 0.00 0.67 - 2.85 34.50 0.00 1.06 -27. Question 38 -1.38 15.00 1.00 2.06 0.83 -1.33 5.00 0.00 2.11 0.43 -3.00 6.00 0.00 0.60 0.16 0.22 5.00 1.00 2.30 0.89 0.55 6.00 1.00 1.83 0.02 -1.12 35.00 4.00 2.22 -28. Question 39 1.66 15.00 0.00 1.79 0.15 2.38 4.50 0.00 0.70 0.13 1.91 6.00 0.00 2.54 0.00 1.44 5.00 1.00 1.42 0.17 2.27 6.00 0.00 1.48 0.60 1.85 34.50 - 1.78 -29. Question 40 2.76 15.00 0.00 1.38 0.70 2.75 4.50 0.00 0.66 0.63 3.18 6.00 0.00 0.57 0.35 2.44 5.00 0.00 0.96 0.33 2.64 6.00 0.00 1.07 0.51 2.76 34.50 0.00 1.13 -30. Question 41 1.76 15.00 3.00 1.63 0.61 1.89 5.00 0.00 0.99 0.80 3.00 6.00 0.00 0.43 0.25 2.44 5.00 0.00 1.26 0.90 2.45 6.00 0.00 0.89 0.92 2.17 35.00 0.00 1.35 -31. Question 42 1.17 15.00 3.00 2.18 0.74 2.50 4.50 0.00 0.50 0.62 2.55 6.00 0.00 0.78 0.87 1.11 5.00 1.00 1.97 0.52 2.64 6.00 0.00 1.07 0.72 1.78 34.50 8.00 1.83 -32. Question 43 2.52 15.00 0.00 1.35 0.60 2.13 4.50 0.00 0.93 0.60 2.64 6.00 0.00 0.98 0.75 0.00 5.00 0.00 2.71 0.16 1.91 6.00 0.00 1.50 0.18 2.38 34.50 1.00 1.28 -33. Question 44 2.14 15.00 0.00 1.50 0.81 2.38 4.50 0.00 0.48 0.51 3.00 6.00 0.00 0.74 0.79 1.78 5.00 0.00 1.55 0.38 2.73 6.00 0.00 1.21 0.54 2.35 34.50 0.00 1.34 -
OTHER
Table 4-23 : Descriptive Statistics Analysis Summary for Survey Questions - Sections B, C, D, E
TOTALJAPAN GERMANY ITALY USA
147
4.2.1 Targeted Correlational Analysis
The analysis presented in this and the following section was done utilizing the
software MiniTab® (ver.14). Additionally, Microsoft’s Visio® was used to graphically
consolidate and represent the material in a consistent manner within this report.
24-US
20-U
S
43210
3.0
2.5
2.0
1.5
1.0
0.5
0.0
S 1.15617R-Sq 6.4%R-Sq(adj) 0.0%
Fitted Line Plot20-US = 0.7857 + 0.2143 24-US
24-IT
20-I
T
6543210
6
5
4
3
2
1
0
S 1.99256R-Sq 17.2%R-Sq(adj) 5.3%
Fitted Line Plot20-IT = 0.7967 + 0.3481 24-IT
24-GR
20-G
R
2.01.51.00.50.0
5
4
3
2
1
0
S 1.45023R-Sq 35.7%R-Sq(adj) 26.5%
Fitted Line Plot20-GR = - 0.2778 + 1.167 24-GR
24-JP
20-J
P
14121086420
9
8
7
6
5
4
3
2
1
0
S 3.77087R-Sq 16.7%R-Sq(adj) 4.9%
Fitted Line Plot20-JP = 4.386 - 0.3611 24-JP
20, 22, 24
HB1 Daily communication method and trust.Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
As. Primary Attrib. Set(s) :
Basic and International Communication, Corporate and National Culture
Correlations: 20-JP, 24-JP Pearson correlation of 20-JP and 24-JP = -0.409P-Value = 0.274
Correlations: 20-GR, 24-GR Pearson correlation of 20-GR and 24-GR = 0.597P-Value = 0.089
Regression Analysis: 20-JP versus 24-JP The regression equation is20-JP = 4.39 - 0.361 24-JPPredictor Coef SE Coef T PConstant 4.386 1.594 2.75 0.02824-JP -0.3611 0.3043 -1.19 0.274S = 3.77087 R-Sq = 16.7% R-Sq(adj) = 4.9%Analysis of VarianceSource DF SS MS F PRegression 1 20.02 20.02 1.41 0.274Residual Error 7 99.54 14.22Total 8 119.56
Regression Analysis: 20-GR versus 24-GR The regression equation is20-GR = - 0.278 + 1.17 24-GRPredictor Coef SE Coef T PConstant -0.2778 0.7643 -0.36 0.72724-GR 1.1667 0.5921 1.97 0.089S = 1.45023 R-Sq = 35.7% R-Sq(adj) = 26.5%Analysis of VarianceSource DF SS MS F PRegression 1 8.167 8.167 3.88 0.089Residual Error 7 14.722 2.103Total 8 22.889
Correlations: 20-IT, 24-IT Pearson correlation of 20-IT and 24-IT = 0.414P-Value = 0.267
Correlations: 20-US, 24-US Pearson correlation of 20-US and 24-US = 0.254P-Value = 0.510
Regression Analysis: 20-IT versus 24-IT The regression equation is20-IT = 0.797 + 0.348 24-ITPredictor Coef SE Coef T PConstant 0.7967 0.7522 1.06 0.32524-IT 0.3481 0.2889 1.20 0.267S = 1.99256 R-Sq = 17.2% R-Sq(adj) = 5.3%Analysis of VarianceSource DF SS MS F PRegression 1 5.763 5.763 1.45 0.267Residual Error 7 27.792 3.970Total 8 33.556
Regression Analysis: 20-US versus 24-US The regression equation is20-US = 0.786 + 0.214 24-USPredictor Coef SE Coef T PConstant 0.7857 0.4940 1.59 0.15624-US 0.2143 0.3090 0.69 0.510S = 1.15617 R-Sq = 6.4% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.643 0.643 0.48 0.510Residual Error 7 9.357 1.337Total 8 10.000
148
24-US
22-U
S
43210
3.0
2.5
2.0
1.5
1.0
0.5
0.0
S 1.19095R-Sq 0.7%R-Sq(adj) 0.0%
Fitted Line Plot22-US = 1.071 - 0.0714 24-US
24-IT
22-I
T
6543210
2.0
1.5
1.0
0.5
0.0
S 0.757473R-Sq 27.7%R-Sq(adj) 17.4%
Fitted Line Plot22-IT = 1.002 + 0.1799 24-IT
24-GR
22-G
R
2.01.51.00.50.0
4
3
2
1
0
S 1.61344R-Sq 3.5%R-Sq(adj) 0.0%
Fitted Line Plot22-GR = 0.5556 + 0.3333 24-GR
24-JP
22-J
P
14121086420
7
6
5
4
3
2
1
0
S 2.00617R-Sq 40.8%R-Sq(adj) 32.3%
Fitted Line Plot22-JP = 2.077 + 0.3553 24-JP
20, 22, 24
HB1 Daily communication method and trust.Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
As. Primary Attrib. Set(s) :
Basic and International Communication, Corporate and National Culture
Correlations: 22-US, 24-US Pearson correlation of 22-US and 24-US = -0.085P-Value = 0.829
Correlations: 22-IT, 24-IT Pearson correlation of 22-IT and 24-IT = 0.526P-Value = 0.145
Correlations: 22-GR, 24-GR Pearson correlation of 22-GR and 24-GR = 0.188P-Value = 0.628
Correlations: 22-JP, 24-JP Pearson correlation of 22-JP and 24-JP = 0.638P-Value = 0.064
Regression Analysis: 22-IT versus 24-IT The regression equation is22-IT = 1.00 + 0.180 24-ITPredictor Coef SE Coef T PConstant 1.0023 0.2860 3.51 0.01024-IT 0.1799 0.1098 1.64 0.145S = 0.757473 R-Sq = 27.7% R-Sq(adj) = 17.4%Analysis of VarianceSource DF SS MS F PRegression 1 1.5392 1.5392 2.68 0.145Residual Error 7 4.0164 0.5738
Regression Analysis: 22-US versus 24-US The regression equation is22-US = 1.07 - 0.071 24-USPredictor Coef SE Coef T PConstant 1.0714 0.5088 2.11 0.07324-US -0.0714 0.3183 -0.22 0.829S = 1.19095 R-Sq = 0.7% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.071 0.071 0.05 0.829Residual Error 7 9.929 1.418Total 8 10.000
Regression Analysis: 22-GR versus 24-GR The regression equation is22-GR = 0.556 + 0.333 24-GRPredictor Coef SE Coef T PConstant 0.5556 0.8504 0.65 0.53424-GR 0.3333 0.6587 0.51 0.628S = 1.61344 R-Sq = 3.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.667 0.667 0.26 0.628Residual Error 7 18.222 2.603Total 8 18.889
Regression Analysis: 22-JP versus 24-JP The regression equation is22-JP = 2.08 + 0.355 24-JPPredictor Coef SE Coef T PConstant 2.0774 0.8481 2.45 0.04424-JP 0.3553 0.1619 2.19 0.064S = 2.00617 R-Sq = 40.8% R-Sq(adj) = 32.3%Analysis of VarianceSource DF SS MS F PRegression 1 19.383 19.383 4.82 0.064Residual Error 7 28.173 4.025Total 8 47.556
149
24-US
12-U
S
43210
2.0
1.5
1.0
0.5
0.0
S 0.699854R-Sq 42.9%R-Sq(adj) 34.7%
Fitted Line Plot12-US = 1.429 - 0.4286 24-US
24-IT
12-I
T
6543210
5
4
3
2
1
0
S 1.68873R-Sq 0.2%R-Sq(adj) 0.0%
Fitted Line Plot12-IT = 1.299 + 0.0280 24-IT
24-GR
12-G
R
2.01.51.00.50.0
4
3
2
1
0
S 1.42539R-Sq 4.5%R-Sq(adj) 0.0%
Fitted Line Plot12-GR = 0.5556 + 0.3333 24-GR
24-JP
12-J
P
14121086420
7
6
5
4
3
2
1
0
S 2.81127R-Sq 13.0%R-Sq(adj) 0.5%
Fitted Line Plot12-JP = 2.476 + 0.2315 24-JP
12, 14, 16, 18, 24
HB2 Communication channel between subsidiary and parent company; and trust
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
International Communication and Corp. CultureAs. Primary
Attrib. Set(s) :
Correlations: 12-JP, 24-JP Pearson correlation of 12-JP and 24-JP = 0.360P-Value = 0.341
Correlations: 12-GR, 24-GR Pearson correlation of 12-GR and 24-GR = 0.212P-Value = 0.585
Correlations: 12-IT, 24-IT Pearson correlation of 12-IT and 24-IT = 0.043P-Value = 0.912
Correlations: 12-US, 24-US Pearson correlation of 12-US and 24-US = -0.655P-Value = 0.056
Regression Analysis: 12-US versus 24-US The regression equation is12-US = 1.43 - 0.429 24-USPredictor Coef SE Coef T PConstant 1.4286 0.2990 4.78 0.00224-US -0.4286 0.1870 -2.29 0.056S = 0.699854 R-Sq = 42.9% R-Sq(adj) = 34.7%Analysis of VarianceSource DF SS MS F PRegression 1 2.5714 2.5714 5.25 0.056Residual Error 7 3.4286 0.4898Total 8 6.0000
Regression Analysis: 12-IT versus 24-IT The regression equation is12-IT = 1.30 + 0.028 24-ITPredictor Coef SE Coef T PConstant 1.2991 0.6375 2.04 0.08124-IT 0.0280 0.2449 0.11 0.912S = 1.68873 R-Sq = 0.2% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.037 0.037 0.01 0.912Residual Error 7 19.963 2.852Total 8 20.000
Regression Analysis: 12-GR versus 24-GR The regression equation is12-GR = 0.556 + 0.333 24-GRPredictor Coef SE Coef T PConstant 0.5556 0.7512 0.74 0.48424-GR 0.3333 0.5819 0.57 0.585S = 1.42539 R-Sq = 4.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.667 0.667 0.33 0.585Residual Error 7 14.222 2.032Total 8 14.889
Regression Analysis: 12-JP versus 24-JP The regression equation is12-JP = 2.48 + 0.232 24-JPPredictor Coef SE Coef T PConstant 2.476 1.188 2.08 0.07624-JP 0.2315 0.2269 1.02 0.341S = 2.81127 R-Sq = 13.0% R-Sq(adj) = 0.5%Analysis of VarianceSource DF SS MS F PRegression 1 8.233 8.233 1.04 0.341Residual Error 7 55.323 7.903Total 8 63.556
150
24-IT
14-I
T
6543210
6
5
4
3
2
1
0
S 1.99122R-Sq 12.0%R-Sq(adj) 0.0%
Fitted Line Plot14-IT = 1.568 - 0.2827 24-IT
24-US
14-U
S
43210
3.0
2.5
2.0
1.5
1.0
0.5
0.0
S 0.989743R-Sq 14.3%R-Sq(adj) 2.0%
Fitted Line Plot14-US = 1.286 - 0.2857 24-US
24-GR
14-G
R
2.01.51.00.50.0
3.0
2.5
2.0
1.5
1.0
0.5
0.0
S 1.35693R-Sq 0.0%R-Sq(adj) 0.0%
Fitted Line Plot14-GR = 0.8889 + 0.0000 24-GR
24-JP
14-J
P
14121086420
7
6
5
4
3
2
1
0
S 2.66647R-Sq 3.5%R-Sq(adj) 0.0%
Fitted Line Plot14-JP = 2.875 + 0.1078 24-JP
12, 14, 16, 18, 24
HB2 Communication channel between subsidiary and parent company; and trust
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
International Communication and Corp. CultureAs. Primary
Attrib. Set(s) :
Correlations: 14-US, 24-US Pearson correlation of 14-US and 24-US = -0.378P-Value = 0.316
Correlations: 14-IT, 24-IT Pearson correlation of 14-IT and 24-IT = -0.347P-Value = 0.360
Correlations: 14-GR, 24-GR Pearson correlation of 14-GR and 24-GR = 0.000P-Value = 1.000
Correlations: 14-JP, 24-JP Pearson correlation of 14-JP and 24-JP = 0.186P-Value = 0.632
Regression Analysis: 14-JP versus 24-JP The regression equation is14-JP = 2.87 + 0.108 24-JPPredictor Coef SE Coef T PConstant 2.875 1.127 2.55 0.03824-JP 0.1078 0.2152 0.50 0.632S = 2.66647 R-Sq = 3.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 1.785 1.785 0.25 0.632Residual Error 7 49.771 7.110Total 8 51.556
Regression Analysis: 14-GR versus 24-GR The regression equation is14-GR = 0.889 + 0.000 24-GRPredictor Coef SE Coef T PConstant 0.8889 0.7152 1.24 0.25424-GR 0.0000 0.5540 0.00 1.000S = 1.35693 R-Sq = 0.0% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.000 0.000 0.00 1.000Residual Error 7 12.889 1.841Total 8 12.889
Regression Analysis: 14-IT versus 24-IT The regression equation is14-IT = 1.57 - 0.283 24-ITPredictor Coef SE Coef T PConstant 1.5678 0.7517 2.09 0.07524-IT -0.2827 0.2887 -0.98 0.360S = 1.99122 R-Sq = 12.0% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.801 3.801 0.96 0.360Residual Error 7 27.755 3.965Total 8 31.556
Regression Analysis: 14-US versus 24-US The regression equation is14-US = 1.29 - 0.286 24-USPredictor Coef SE Coef T PConstant 1.2857 0.4229 3.04 0.01924-US -0.2857 0.2645 -1.08 0.316S = 0.989743 R-Sq = 14.3% R-Sq(adj) = 2.0%Analysis of VarianceSource DF SS MS F PRegression 1 1.1429 1.1429 1.17 0.316Residual Error 7 6.8571 0.9796Total 8 8.0000
151
24-IT
16-I
T
6543210
3.0
2.5
2.0
1.5
1.0
0.5
0.0
S 1.28927R-Sq 14.2%R-Sq(adj) 1.9%
Fitted Line Plot16-IT = 0.9766 + 0.2009 24-IT
24-US
16-U
S
43210
4
3
2
1
0
S 1.32095R-Sq 12.8%R-Sq(adj) 0.3%
Fitted Line Plot16-US = 1.357 - 0.3571 24-US
24-GR
16-G
R
2.01.51.00.50.0
2.0
1.5
1.0
0.5
0.0
S 0.835711R-Sq 0.0%R-Sq(adj) 0.0%
Fitted Line Plot16-GR = 0.8889 - 0.0000 24-GR
24-JP
16-J
P
14121086420
9
8
7
6
5
4
3
2
1
0
S 2.91353R-Sq 0.2%R-Sq(adj) 0.0%
Fitted Line Plot16-JP = 3.127 + 0.0297 24-JP
12, 14, 16, 18, 24
HB2 Communication channel between subsidiary and parent company; and trust
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
International Communication and Corp. CultureAs. Primary
Attrib. Set(s) :
Correlations: 16-JP, 24-JP Pearson correlation of 16-JP and 24-JP = 0.048P-Value = 0.903
Correlations: 16-GR, 24-GR Pearson correlation of 16-GR and 24-GR = 0.000P-Value = 1.000
Correlations: 16-IT, 24-IT Pearson correlation of 16-IT and 24-IT = 0.376P-Value = 0.318
Correlations: 16-US, 24-US Pearson correlation of 16-US and 24-US = -0.357P-Value = 0.345
Regression Analysis: 16-US versus 24-US The regression equation is16-US = 1.36 - 0.357 24-USPredictor Coef SE Coef T PConstant 1.3571 0.5644 2.40 0.04724-US -0.3571 0.3530 -1.01 0.345S = 1.32095 R-Sq = 12.8% R-Sq(adj) = 0.3%Analysis of VarianceSource DF SS MS F PRegression 1 1.786 1.786 1.02 0.345Residual Error 7 12.214 1.745Total 8 14.000
Regression Analysis: 16-IT versus 24-IT The regression equation is16-IT = 0.977 + 0.201 24-ITPredictor Coef SE Coef T PConstant 0.9766 0.4867 2.01 0.08524-IT 0.2009 0.1870 1.07 0.318S = 1.28927 R-Sq = 14.2% R-Sq(adj) = 1.9%Analysis of VarianceSource DF SS MS F PRegression 1 1.920 1.920 1.16 0.318Residual Error 7 11.636 1.662Total 8 13.556
Regression Analysis: 16-GR versus 24-GR The regression equation is16-GR = 0.889 - 0.000 24-GRPredictor Coef SE Coef T PConstant 0.8889 0.4405 2.02 0.08324-GR -0.0000 0.3412 -0.00 1.000S = 0.835711 R-Sq = 0.0% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.0000 0.0000 0.00 1.000Residual Error 7 4.8889 0.6984Total 8 4.8889
Regression Analysis: 16-JP versus 24-JP The regression equation is16-JP = 3.13 + 0.030 24-JPPredictor Coef SE Coef T PConstant 3.127 1.232 2.54 0.03924-JP 0.0297 0.2351 0.13 0.903S = 2.91353 R-Sq = 0.2% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.135 0.135 0.02 0.903Residual Error 7 59.420 8.489Total 8 59.556
152
24-IT
18-I
T
6543210
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2
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S 1.59428R-Sq 24.5%R-Sq(adj) 13.7%
Fitted Line Plot18-IT = 0.7967 + 0.3481 24-IT
24-US
18-U
S
43210
2.0
1.5
1.0
0.5
0.0
S 0.749149R-Sq 1.8%R-Sq(adj) 0.0%
Fitted Line Plot18-US = 1.071 - 0.0714 24-US
24-GR
18-G
R
2.01.51.00.50.0
4
3
2
1
0
S 1.23764R-Sq 43.2%R-Sq(adj) 35.1%
Fitted Line Plot18-GR = - 0.2778 + 1.167 24-GR
24-JP
18-J
P
14121086420
9
8
7
6
5
4
3
2
1
0
S 2.79606R-Sq 27.6%R-Sq(adj) 17.2%
Fitted Line Plot18-JP = 2.035 + 0.3683 24-JP
12, 14, 16, 18, 24
HB2 Communication channel between subsidiary and parent company; and trust
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
International Communication and Corp. CultureAs. Primary
Attrib. Set(s) :
Correlations: 18-US, 24-US Pearson correlation of 18-US and 24-US = -0.134P-Value = 0.732
Correlations: 18-IT, 24-IT Pearson correlation of 18-IT and 24-IT = 0.495P-Value = 0.176
Correlations: 18-GR, 24-GR Pearson correlation of 18-GR and 24-GR = 0.658P-Value = 0.054
Correlations: 18-JP, 24-JP Pearson correlation of 18-JP and 24-JP = 0.525P-Value = 0.147
Regression Analysis: 18-JP versus 24-JP The regression equation is18-JP = 2.04 + 0.368 24-JPPredictor Coef SE Coef T PConstant 2.035 1.182 1.72 0.12924-JP 0.3683 0.2256 1.63 0.147S = 2.79606 R-Sq = 27.6% R-Sq(adj) = 17.2%Analysis of VarianceSource DF SS MS F PRegression 1 20.830 20.830 2.66 0.147Residual Error 7 54.726 7.818Total 8 75.556
Regression Analysis: 18-GR versus 24-GR The regression equation is18-GR = - 0.278 + 1.17 24-GRPredictor Coef SE Coef T PConstant -0.2778 0.6523 -0.43 0.68324-GR 1.1667 0.5053 2.31 0.054S = 1.23764 R-Sq = 43.2% R-Sq(adj) = 35.1%Analysis of VarianceSource DF SS MS F PRegression 1 8.167 8.167 5.33 0.054Residual Error 7 10.722 1.532Total 8 18.889
Regression Analysis: 18-IT versus 24-IT The regression equation is18-IT = 0.797 + 0.348 24-ITPredictor Coef SE Coef T PConstant 0.7967 0.6019 1.32 0.22724-IT 0.3481 0.2312 1.51 0.176S = 1.59428 R-Sq = 24.5% R-Sq(adj) = 13.7%Analysis of VarianceSource DF SS MS F PRegression 1 5.763 5.763 2.27 0.176Residual Error 7 17.792 2.542Total 8 23.556
Regression Analysis: 18-US versus 24-US The regression equation is18-US = 1.07 - 0.071 24-USPredictor Coef SE Coef T PConstant 1.0714 0.3201 3.35 0.01224-US -0.0714 0.2002 -0.36 0.732S = 0.749149 R-Sq = 1.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.0714 0.0714 0.13 0.732Residual Error 7 3.9286 0.5612Total 8 4.0000
153
35-US
12-U
S
3.02.52.01.51.00.50.0
2.0
1.5
1.0
0.5
0.0
S 0.918073R-Sq 1.7%R-Sq(adj) 0.0%
Fitted Line Plot12-US = 1.100 - 0.1000 35-US
35-IT
12-I
T
6543210
5
4
3
2
1
0
S 1.68978R-Sq 0.1%R-Sq(adj) 0.0%
Fitted Line Plot12-IT = 1.356 - 0.0188 35-IT
35-GR
12-G
R
43210
4
3
2
1
0
S 1.42622R-Sq 4.4%R-Sq(adj) 0.0%
Fitted Line Plot12-GR = 1.075 - 0.2090 35-GR
35-JP
12-J
P
121086420
7
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1
0
S 2.83405R-Sq 11.5%R-Sq(adj) 0.0%
Fitted Line Plot12-JP = 2.518 + 0.2185 35-JP
12, 14, 16, 18, 35
HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
As. Primary Attrib. Set(s) :
International Communication; Corp. and National Culture
Correlations: 12-JP, 35-JP Pearson correlation of 12-JP and 35-JP = 0.340P-Value = 0.371
Correlations: 12-GR, 35-GR Pearson correlation of 12-GR and 35-GR = -0.209P-Value = 0.590
Correlations: 12-IT, 35-IT Pearson correlation of 12-IT and 35-IT = -0.025P-Value = 0.949
Correlations: 12-US, 35-US Pearson correlation of 12-US and 35-US = -0.129P-Value = 0.741
Regression Analysis: 12-US versus 35-US The regression equation is12-US = 1.10 - 0.100 35-USPredictor Coef SE Coef T PConstant 1.1000 0.4218 2.61 0.03535-US -0.1000 0.2903 -0.34 0.741S = 0.918073 R-Sq = 1.7% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.1000 0.1000 0.12 0.741Residual Error 7 5.9000 0.8429Total 8 6.0000
Regression Analysis: 12-IT versus 35-IT The regression equation is12-IT = 1.36 - 0.019 35-ITPredictor Coef SE Coef T PConstant 1.3563 0.6612 2.05 0.07935-IT -0.0188 0.2834 -0.07 0.949S = 1.68978 R-Sq = 0.1% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.013 0.013 0.00 0.949Residual Error 7 19.988 2.855Total 8 20.000
Regression Analysis: 12-GR versus 35-GR The regression equation is12-GR = 1.07 - 0.209 35-GRPredictor Coef SE Coef T PConstant 1.0746 0.5779 1.86 0.10535-GR -0.2090 0.3696 -0.57 0.590S = 1.42622 R-Sq = 4.4% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.650 0.650 0.32 0.590Residual Error 7 14.239 2.034Total 8 14.889
Regression Analysis: 12-JP versus 35-JP The regression equation is12-JP = 2.52 + 0.219 35-JPPredictor Coef SE Coef T PConstant 2.518 1.198 2.10 0.07435-JP 0.2185 0.2287 0.96 0.371S = 2.83405 R-Sq = 11.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 7.333 7.333 0.91 0.371Residual Error 7 56.223 8.032Total 8 63.556
154
35-IT
14-I
T
6543210
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4
3
2
1
0
S 1.94466R-Sq 16.1%R-Sq(adj) 4.1%
Fitted Line Plot14-IT = 1.684 - 0.3781 35-IT
35-US
14-U
S
3.02.52.01.51.00.50.0
3.0
2.5
2.0
1.5
1.0
0.5
0.0
S 1.00712R-Sq 11.3%R-Sq(adj) 0.0%
Fitted Line Plot14-US = 0.7000 + 0.3000 35-US
35-GR
14-G
R
43210
3.0
2.5
2.0
1.5
1.0
0.5
0.0
S 1.11541R-Sq 32.4%R-Sq(adj) 22.8%
Fitted Line Plot14-GR = 0.4179 + 0.5299 35-GR
35-JP
14-J
P
121086420
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3
2
1
0
S 2.63302R-Sq 5.9%R-Sq(adj) 0.0%
Fitted Line Plot14-JP = 2.770 + 0.1404 35-JP
12, 14, 16, 18, 35
HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
As. Primary Attrib. Set(s) :
International Communication; Corp. and National Culture
Correlations: 14-JP, 35-JP Pearson correlation of 14-JP and 35-JP = 0.242P-Value = 0.530
Correlations: 14-GR, 35-GR Pearson correlation of 14-GR and 35-GR = 0.569P-Value = 0.109
Correlations: 14-IT, 35-IT Pearson correlation of 14-IT and 35-IT = -0.401P-Value = 0.284
Correlations: 14-US, 35-US Pearson correlation of 14-US and 35-US = 0.335P-Value = 0.378
Regression Analysis: 14-US versus 35-US The regression equation is14-US = 0.700 + 0.300 35-USPredictor Coef SE Coef T PConstant 0.7000 0.4627 1.51 0.17435-US 0.3000 0.3185 0.94 0.378S = 1.00712 R-Sq = 11.3% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.900 0.900 0.89 0.378Residual Error 7 7.100 1.014Total 8 8.00
Regression Analysis: 14-IT versus 35-IT The regression equation is14-IT = 1.68 - 0.378 35-ITPredictor Coef SE Coef T PConstant 1.6844 0.7610 2.21 0.06235-IT -0.3781 0.3261 -1.16 0.284S = 1.94466 R-Sq = 16.1% R-Sq(adj) = 4.1%Analysis of VarianceSource DF SS MS F PRegression 1 5.084 5.084 1.34 0.284Residual Error 7 26.472 3.782Total 8 31.556
Regression Analysis: 14-GR versus 35-GR The regression equation is14-GR = 0.418 + 0.530 35-GRPredictor Coef SE Coef T PConstant 0.4179 0.4520 0.92 0.38635-GR 0.5299 0.2891 1.83 0.109S = 1.11541 R-Sq = 32.4% R-Sq(adj) = 22.8%Analysis of VarianceSource DF SS MS F PRegression 1 4.180 4.180 3.36 0.109Residual Error 7 8.709 1.244Total 8 12.889
Regression Analysis: 14-JP versus 35-JP The regression equation is14-JP = 2.77 + 0.140 35-JPPredictor Coef SE Coef T PConstant 2.770 1.113 2.49 0.04235-JP 0.1404 0.2125 0.66 0.530S = 2.63302 R-Sq = 5.9% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.026 3.026 0.44 0.530Residual Error 7 48.530 6.933Total 8 51.556
155
35-US
16-U
S
3.02.52.01.51.00.50.0
4
3
2
1
0
S 1.39386R-Sq 2.9%R-Sq(adj) 0.0%
Fitted Line Plot16-US = 1.200 - 0.2000 35-US
35-IT
16-I
T
6543210
3.0
2.5
2.0
1.5
1.0
0.5
0.0
S 1.18322R-Sq 27.7%R-Sq(adj) 17.4%
Fitted Line Plot16-IT = 0.8250 + 0.3250 35-IT
35-GR
16-G
R
43210
2.0
1.5
1.0
0.5
0.0
S 0.669150R-Sq 35.9%R-Sq(adj) 26.7%
Fitted Line Plot16-GR = 1.194 - 0.3433 35-GR
35-JP
16-J
P
121086420
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3
2
1
0
S 2.81076R-Sq 7.1%R-Sq(adj) 0.0%
Fitted Line Plot16-JP = 2.686 + 0.1664 35-JP
12, 14, 16, 18, 35
HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
As. Primary Attrib. Set(s) :
International Communication; Corp. and National Culture
Correlations: 16-JP, 35-JP Pearson correlation of 16-JP and 35-JP = 0.267P-Value = 0.487
Correlations: 16-GR, 35-GR Pearson correlation of 16-GR and 35-GR = -0.599P-Value = 0.088
Correlations: 16-IT, 35-IT Pearson correlation of 16-IT and 35-IT = 0.526P-Value = 0.145
Regression Analysis: 16-JP versus 35-JP The regression equation is16-JP = 2.69 + 0.166 35-JPPredictor Coef SE Coef T PConstant 2.686 1.188 2.26 0.05835-JP 0.1664 0.2268 0.73 0.487S = 2.81076 R-Sq = 7.1% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 4.253 4.253 0.54 0.487Residual Error 7 55.302 7.900Total 8 59.556
Regression Analysis: 16-GR versus 35-GR The regression equation is16-GR = 1.19 - 0.343 35-GRPredictor Coef SE Coef T PConstant 1.1940 0.2711 4.40 0.00335-GR -0.3433 0.1734 -1.98 0.088S = 0.669150 R-Sq = 35.9% R-Sq(adj) = 26.7%Analysis of VarianceSource DF SS MS F PRegression 1 1.7546 1.7546 3.92 0.088Residual Error 7 3.1343 0.4478Total 8 4.8889
Regression Analysis: 16-IT versus 35-IT The regression equation is16-IT = 0.825 + 0.325 35-ITPredictor Coef SE Coef T PConstant 0.8250 0.4630 1.78 0.11835-IT 0.3250 0.1984 1.64 0.145S = 1.18322 R-Sq = 27.7% R-Sq(adj) = 17.4%Analysis of VarianceSource DF SS MS F PRegression 1 3.756 3.756 2.68 0.145Residual Error 7 9.800 1.400Total 8 13.556
Regression Analysis: 16-US versus 35-US The regression equation is16-US = 1.20 - 0.200 35-USPredictor Coef SE Coef T PConstant 1.2000 0.6404 1.87 0.10335-US -0.2000 0.4408 -0.45 0.664S = 1.39386 R-Sq = 2.9% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.400 0.400 0.21 0.664Residual Error 7 13.600 1.943Total 8 14.000
156
35-US
18-U
S
3.02.52.01.51.00.50.0
2.0
1.5
1.0
0.5
0.0
S 0.665475R-Sq 22.5%R-Sq(adj) 11.4%
Fitted Line Plot18-US = 1.300 - 0.3000 35-US
35-IT
18-I
T
6543210
5
4
3
2
1
0
S 1.50461R-Sq 32.7%R-Sq(adj) 23.1%
Fitted Line Plot18-IT = 0.6531 + 0.4656 35-IT
35-GR
18-G
R
43210
4
3
2
1
0
S 1.63223R-Sq 1.3%R-Sq(adj) 0.0%
Fitted Line Plot18-GR = 0.7761 + 0.1269 35-GR
35-JP
18-J
P
121086420
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S 2.91702R-Sq 21.2%R-Sq(adj) 9.9%
Fitted Line Plot18-JP = 2.182 + 0.3227 35-JP
12, 14, 16, 18, 35
HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
As. Primary Attrib. Set(s) :
International Communication; Corp. and National Culture
Correlations: 18-JP, 35-JP Pearson correlation of 18-JP and 35-JP = 0.460P-Value = 0.213
Correlations: 18-GR, 35-GR Pearson correlation of 18-GR and 35-GR = 0.113P-Value = 0.773
Correlations: 18-IT, 35-IT Pearson correlation of 18-IT and 35-IT = 0.572P-Value = 0.108
Regression Analysis: 18-JP versus 35-JP The regression equation is18-JP = 2.18 + 0.323 35-JPPredictor Coef SE Coef T PConstant 2.182 1.233 1.77 0.12035-JP 0.3227 0.2354 1.37 0.213S = 2.91702 R-Sq = 21.2% R-Sq(adj) = 9.9%Analysis of VarianceSource DF SS MS F PRegression 1 15.993 15.993 1.88 0.213Residual Error 7 59.563 8.509Total 8 75.556
Regression Analysis: 18-GR versus 35-GR The regression equation is18-GR = 0.776 + 0.127 35-GRPredictor Coef SE Coef T PConstant 0.7761 0.6614 1.17 0.27935-GR 0.1269 0.4230 0.30 0.773S = 1.63223 R-Sq = 1.3% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.240 0.240 0.09 0.773Residual Error 7 18.649 2.664Total 8 18.889
Regression Analysis: 18-IT versus 35-IT The regression equation is18-IT = 0.653 + 0.466 35-ITPredictor Coef SE Coef T PConstant 0.6531 0.5888 1.11 0.30435-IT 0.4656 0.2523 1.85 0.108S = 1.50461 R-Sq = 32.7% R-Sq(adj) = 23.1%Analysis of VarianceSource DF SS MS F PRegression 1 7.709 7.709 3.41 0.108Residual Error 7 15.847 2.264Total 8 23.556
Regression Analysis: 18-US versus 35-US The regression equation is18-US = 1.30 - 0.300 35-USPredictor Coef SE Coef T PConstant 1.3000 0.3058 4.25 0.00435-US -0.3000 0.2104 -1.43 0.197S = 0.665475 R-Sq = 22.5% R-Sq(adj) = 11.4%Analysis of VarianceSource DF SS MS F PRegression 1 0.9000 0.9000 2.03 0.197Residual Error 7 3.1000 0.4429Total 8 4.0000
157
24-US
18-U
S
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2.0
1.5
1.0
0.5
0.0
S 0.749149R-Sq 1.8%R-Sq(adj) 0.0%
Fitted Line Plot18-US = 1.071 - 0.0714 24-US
24-IT
18-I
T
6543210
5
4
3
2
1
0
S 1.59428R-Sq 24.5%R-Sq(adj) 13.7%
Fitted Line Plot18-IT = 0.7967 + 0.3481 24-IT
24-GR
18-G
R
2.01.51.00.50.0
4
3
2
1
0
S 1.23764R-Sq 43.2%R-Sq(adj) 35.1%
Fitted Line Plot18-GR = - 0.2778 + 1.167 24-GR
24-JP
18-J
P
14121086420
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2
1
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S 2.79606R-Sq 27.6%R-Sq(adj) 17.2%
Fitted Line Plot18-JP = 2.035 + 0.3683 24-JP
18, 24
HB4 Many-to-many subsidiary communication channel and learning / trusting relationship
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
As. Primary Attrib. Set(s) :
International Communication; Corp. and National Culture; trust (as a major subset attribute)
Correlations: 18-JP, 24-JP Pearson correlation of 18-JP and 24-JP = 0.525P-Value = 0.147
Correlations: 18-GR, 24-GR Pearson correlation of 18-GR and 24-GR = 0.658P-Value = 0.054
Regression Analysis: 18-JP versus 24-JP The regression equation is18-JP = 2.04 + 0.368 24-JPPredictor Coef SE Coef T PConstant 2.035 1.182 1.72 0.12924-JP 0.3683 0.2256 1.63 0.147S = 2.79606 R-Sq = 27.6% R-Sq(adj) = 17.2%Analysis of VarianceSource DF SS MS F PRegression 1 20.830 20.830 2.66 0.147Residual Error 7 54.726 7.818Total 8 75.556
Regression Analysis: 18-GR versus 24-GR The regression equation is18-GR = - 0.278 + 1.17 24-GRPredictor Coef SE Coef T PConstant -0.2778 0.6523 -0.43 0.68324-GR 1.1667 0.5053 2.31 0.054S = 1.23764 R-Sq = 43.2% R-Sq(adj) = 35.1%Analysis of VarianceSource DF SS MS F PRegression 1 8.167 8.167 5.33 0.054Residual Error 7 10.722 1.532Total 8 18.889
Correlations: 18-IT, 24-IT Pearson correlation of 18-IT and 24-IT = 0.495P-Value = 0.176
Regression Analysis: 18-IT versus 24-IT The regression equation is18-IT = 0.797 + 0.348 24-ITPredictor Coef SE Coef T PConstant 0.7967 0.6019 1.32 0.22724-IT 0.3481 0.2312 1.51 0.176S = 1.59428 R-Sq = 24.5% R-Sq(adj) = 13.7%Analysis of VarianceSource DF SS MS F PRegression 1 5.763 5.763 2.27 0.176Residual Error 7 17.792 2.542Total 8 23.556
Correlations: 18-US, 24-US Pearson correlation of 18-US and 24-US = -0.134P-Value = 0.732Regression Analysis: 18-US versus 24-US The regression equation is18-US = 1.07 - 0.071 24-USPredictor Coef SE Coef T PConstant 1.0714 0.3201 3.35 0.01224-US -0.0714 0.2002 -0.36 0.732S = 0.749149 R-Sq = 1.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.0714 0.0714 0.13 0.732Residual Error 7 3.9286 0.5612Total 8 4.0000
158
35-US
34-U
S
3.02.52.01.51.00.50.0
3.0
2.5
2.0
1.5
1.0
0.5
0.0
S 1.09545R-Sq 16.0%R-Sq(adj) 4.0%
Fitted Line Plot34-US = 0.6000 + 0.4000 35-US
35-IT
34-I
T
6543210
7
6
5
4
3
2
1
0
S 0.470562R-Sq 96.6%R-Sq(adj) 96.1%
Fitted Line Plot34-IT = - 0.1375 + 1.112 35-IT
35-GR
34-G
R
43210
6
5
4
3
2
1
0
-1
S 1.98931R-Sq 13.4%R-Sq(adj) 1.1%
Fitted Line Plot34-GR = 1.478 - 0.5373 35-GR
35-JP
34-J
P
121086420
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8
6
4
2
0
S 3.97364R-Sq 0.9%R-Sq(adj) 0.0%
Fitted Line Plot34-JP = 2.959 + 0.0818 35-JP
34, 35
HC1Employees having direct input to decisions affecting them and shared meaning in succesful KTHypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
Corporate culture, Groups and Teams Communication, trust as a major attribute subset
As. Primary Attrib. Set(s) :
Correlations: 34-JP, 35-JP Pearson correlation of 34-JP and 35-JP = 0.096P-Value = 0.806
Correlations: 34-GR, 35-GR Pearson correlation of 34-GR and 35-GR = -0.367P-Value = 0.332
Correlations: 34-IT, 35-IT Pearson correlation of 34-IT and 35-IT = 0.983P-Value = 0.000
Correlations: 34-US, 35-US Pearson correlation of 34-US and 35-US = 0.400P-Value = 0.286
Regression Analysis: 34-US versus 35-US The regression equation is34-US = 0.600 + 0.400 35-USPredictor Coef SE Coef T PConstant 0.6000 0.5033 1.19 0.27235-US 0.4000 0.3464 1.15 0.286S = 1.09545 R-Sq = 16.0% R-Sq(adj) = 4.0%Analysis of VarianceSource DF SS MS F PRegression 1 1.600 1.600 1.33 0.286Residual Error 7 8.400 1.200Total 8 10.00
Regression Analysis: 34-IT versus 35-IT The regression equation is34-IT = - 0.137 + 1.11 35-ITPredictor Coef SE Coef T PConstant -0.1375 0.1841 -0.75 0.48035-IT 1.11250 0.07892 14.10 0.000S = 0.470562 R-Sq = 96.6% R-Sq(adj) = 96.1%Analysis of VarianceSource DF SS MS F PRegression 1 44.006 44.006 198.73 0.000Residual Error 7 1.550 0.221Total 8 45.556
Regression Analysis: 34-GR versus 35-GR The regression equation is34-GR = 1.48 - 0.537 35-GRPredictor Coef SE Coef T PConstant 1.4776 0.8060 1.83 0.10935-GR -0.5373 0.5156 -1.04 0.332S = 1.98931 R-Sq = 13.4% R-Sq(adj) = 1.1%Analysis of VarianceSource DF SS MS F PRegression 1 4.299 4.299 1.09 0.332Residual Error 7 27.701 3.957Total 8 32.000
Regression Analysis: 34-JP versus 35-JP The regression equation is34-JP = 2.96 + 0.082 35-JPPredictor Coef SE Coef T PConstant 2.959 1.680 1.76 0.12235-JP 0.0818 0.3207 0.25 0.806S = 3.97364 R-Sq = 0.9% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 1.03 1.03 0.07 0.806Residual Error 7 110.53 15.79Total 8 111.56
159
31-US
30-U
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3.02.52.01.51.00.50.0
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1.5
1.0
0.5
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Fitted Line Plot30-US = 0.5833 + 0.4167 31-US
31-IT
30-I
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Fitted Line Plot30-IT = 0.7071 + 0.4214 31-IT
31-GR
30-G
R
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Fitted Line Plot30-GR = 0.7735 + 0.1154 31-GR
31-JP
30-J
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Fitted Line Plot30-JP = 1.981 + 0.3851 31-JP
30, 31
HC2Technology tools , and true spirit of cooperation and collaboration between subsidiary , parent headquartersHypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
International Communication, National Culture, Trust
As. Primary Attrib. Set(s) :
Correlations: 30-JP, 31-JP Pearson correlation of 30-JP and 31-JP = 0.532P-Value = 0.141
Correlations: 30-GR, 31-GR Pearson correlation of 30-GR and 31-GR = 0.152P-Value = 0.695
Correlations: 30-IT, 31-IT Pearson correlation of 30-IT and 31-IT = 0.329P-Value = 0.388
Correlations: 30-US, 31-US Pearson correlation of 30-US and 31-US = 0.589P-Value = 0.095
Regression Analysis: 30-JP versus 31-JP The regression equation is30-JP = 1.98 + 0.385 31-JPPredictor Coef SE Coef T PConstant 1.9814 0.9931 2.00 0.08631-JP 0.3851 0.2319 1.66 0.141S = 1.96193 R-Sq = 28.3% R-Sq(adj) = 18.0%Analysis of VarianceSource DF SS MS F PRegression 1 10.611 10.611 2.76 0.141Residual Error 7 26.944 3.849Total 8 37.556
Regression Analysis: 30-GR versus 31-GR The regression equation is30-GR = 0.774 + 0.115 31-GRPredictor Coef SE Coef T PConstant 0.7735 0.5574 1.39 0.20831-GR 0.1154 0.2827 0.41 0.695S = 1.44137 R-Sq = 2.3% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.346 0.346 0.17 0.695Residual Error 7 14.543 2.078Total 8 14.889
Regression Analysis: 30-IT versus 31-IT The regression equation is30-IT = 0.707 + 0.421 31-ITPredictor Coef SE Coef T PConstant 0.7071 0.8213 0.86 0.41831-IT 0.4214 0.4575 0.92 0.388S = 1.80447 R-Sq = 10.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 2.763 2.763 0.85 0.388Residual Error 7 22.793 3.256Total 8 25.556
Regression Analysis: 30-US versus 31-US The regression equation is30-US = 0.583 + 0.417 31-USPredictor Coef SE Coef T PConstant 0.5833 0.3298 1.77 0.12031-US 0.4167 0.2159 1.93 0.095S = 0.748013 R-Sq = 34.7% R-Sq(adj) = 25.4%Analysis of VarianceSource DF SS MS F PRegression 1 2.0833 2.0833 3.72 0.095Residual Error 7 3.9167 0.5595Total 8 6.0000
160
26-US
24-U
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Fitted Line Plot24-US = 1.500 - 0.5000 26-US
26-IT
24-I
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Fitted Line Plot24-IT = 0.895 + 0.2674 26-IT
26-GR
24-G
R
2.01.51.00.50.0
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1.5
1.0
0.5
0.0
S 0.724807R-Sq 38.7%R-Sq(adj) 30.0%
Fitted Line Plot24-GR = 0.4839 + 0.5806 26-GR
26-JP
24-J
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Fitted Line Plot24-JP = 0.055 + 0.9830 26-JP
24, 26, 27
HC3 Trust and knowledge holdback by either subsidiary and / or parent headquarters
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
International Communication, Trust (as a major attribute subset)
As. Primary Attrib. Set(s) :
Correlations: 24-JP, 26-JP Pearson correlation of 24-JP and 26-JP = 0.860P-Value = 0.003
Correlations: 24-GR, 26-GR Pearson correlation of 24-GR and 26-GR = 0.622P-Value = 0.074
Correlations: 24-IT, 26-IT Pearson correlation of 24-IT and 26-IT = 0.120P-Value = 0.759
Correlations: 24-US, 26-US Pearson correlation of 24-US and 26-US = -0.463P-Value = 0.210
Regression Analysis: 24-US versus 26-US The regression equation is24-US = 1.50 - 0.500 26-USPredictor Coef SE Coef T PConstant 1.5000 0.5528 2.71 0.03026-US -0.5000 0.3619 -1.38 0.210S = 1.25357 R-Sq = 21.4% R-Sq(adj) = 10.2%Analysis of VarianceSource DF SS MS F PRegression 1 3.000 3.000 1.91 0.210Residual Error 7 11.000 1.571Total 8 14.000
Regression Analysis: 24-IT versus 26-IT The regression equation is24-IT = 0.90 + 0.267 26-ITPredictor Coef SE Coef T PConstant 0.895 1.338 0.67 0.52526-IT 0.2674 0.8371 0.32 0.759S = 2.58767 R-Sq = 1.4% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.683 0.683 0.10 0.759Residual Error 7 46.872 6.696Total 8 47.556
Regression Analysis: 24-GR versus 26-GR The regression equation is24-GR = 0.484 + 0.581 26-GRPredictor Coef SE Coef T PConstant 0.4839 0.3444 1.40 0.20326-GR 0.5806 0.2762 2.10 0.074S = 0.724807 R-Sq = 38.7% R-Sq(adj) = 30.0%Analysis of VarianceSource DF SS MS F PRegression 1 2.3226 2.3226 4.42 0.074Residual Error 7 3.6774 0.5253Total 8 6.0000
Regression Analysis: 24-JP versus 26-JP The regression equation is24-JP = 0.05 + 0.983 26-JPPredictor Coef SE Coef T PConstant 0.055 1.067 0.05 0.96026-JP 0.9830 0.2204 4.46 0.003S = 2.38944 R-Sq = 74.0% R-Sq(adj) = 70.3%Analysis of VarianceSource DF SS MS F PRegression 1 113.59 113.59 19.90 0.003Residual Error 7 39.97 5.71Total 8 153.56
161
27-US
24-U
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S 1.41000R-Sq 0.6%R-Sq(adj) 0.0%
Fitted Line Plot24-US = 1.083 - 0.0833 27-US
27-IT
24-I
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Fitted Line Plot24-IT = 1.458 - 0.1933 27-IT
27-GR
24-G
R
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0.5
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Fitted Line Plot24-GR = 0.8000 + 0.2000 27-GR
27-JP
24-J
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Fitted Line Plot24-JP = 3.713 - 0.1524 27-JP
24, 26, 27
HC3 Trust and knowledge holdback by either subsidiary and / or parent headquarters
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
International Communication, Trust (as a major attribute subset)
As. Primary Attrib. Set(s) :
Correlations: 24-JP, 27-JP Pearson correlation of 24-JP and 27-JP = -0.139P-Value = 0.721
Correlations: 24-GR, 27-GR Pearson correlation of 24-GR and 27-GR = 0.258P-Value = 0.502
Correlations: 24-IT, 27-IT Pearson correlation of 24-IT and 27-IT = -0.234P-Value = 0.545
Correlations: 24-US, 27-US Pearson correlation of 24-US and 27-US = -0.077P-Value = 0.844
Regression Analysis: 24-JP versus 27-JP The regression equation is24-JP = 3.71 - 0.152 27-JPPredictor Coef SE Coef T PConstant 3.713 2.035 1.82 0.11127-JP -0.1524 0.4107 -0.37 0.721S = 4.63822 R-Sq = 1.9% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 2.96 2.96 0.14 0.721Residual Error 7 150.59 21.51Total 8 153.56
Regression Analysis: 24-GR versus 27-GR The regression equation is24-GR = 0.800 + 0.200 27-GRPredictor Coef SE Coef T PConstant 0.8000 0.4110 1.95 0.09327-GR 0.2000 0.2828 0.71 0.502S = 0.894427 R-Sq = 6.7% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.4000 0.4000 0.50 0.502Residual Error 7 5.6000 0.8000Total 8 6.0000
Regression Analysis: 24-IT versus 27-IT The regression equation is24-IT = 1.46 - 0.193 27-ITPredictor Coef SE Coef T PConstant 1.4585 0.9228 1.58 0.15827-IT -0.1933 0.3039 -0.64 0.545S = 2.53425 R-Sq = 5.5% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 2.599 2.599 0.40 0.545Residual Error 7 44.957 6.422Total 8 47.556
Regression Analysis: 24-US versus 27-US The regression equation is24-US = 1.08 - 0.083 27-USPredictor Coef SE Coef T PConstant 1.0833 0.6218 1.74 0.12527-US -0.0833 0.4070 -0.20 0.844S = 1.41000 R-Sq = 0.6% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.083 0.083 0.04 0.844Residual Error 7 13.917 1.988Total 8 14.000
162
48-US
38-U
S
2.01.51.00.50.0
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1.5
1.0
0.5
0.0
S 0.501876R-Sq 11.8%R-Sq(adj) 0.0%
Fitted Line Plot38-US = 1.132 - 0.2368 48-US
48-IT
38-I
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S 1.65149R-Sq 56.2%R-Sq(adj) 49.9%
Fitted Line Plot38-IT = - 0.6068 + 0.6859 48-IT
48-GR
38-G
R
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0.5
0.0
S 0.959338R-Sq 46.3%R-Sq(adj) 38.6%
Fitted Line Plot38-GR = 0.1282 + 0.3269 48-GR
48-JP
38-J
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Fitted Line Plot38-JP = 2.165 + 0.3525 48-JP
38, 48
HD1 Post-project review and lessons-learned and project success
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
Project Success, Group / Team CommunicationAs. Primary
Attrib. Set(s) :
Correlations: 38-JP, 48-JP Pearson correlation of 38-JP and 48-JP = 0.426P-Value = 0.253
Correlations: 38-GR, 48-GR Pearson correlation of 38-GR and 48-GR = 0.681P-Value = 0.044
Correlations: 38-IT, 48-IT Pearson correlation of 38-IT and 48-IT = 0.749P-Value = 0.020
Correlations: 38-US, 48-US Pearson correlation of 38-US and 48-US = -0.344P-Value = 0.365
Regression Analysis: 38-JP versus 48-JP The regression equation is38-JP = 2.16 + 0.352 48-JPPredictor Coef SE Coef T PConstant 2.165 1.344 1.61 0.15148-JP 0.3525 0.2830 1.25 0.253S = 3.12592 R-Sq = 18.1% R-Sq(adj) = 6.4%Analysis of VarianceSource DF SS MS F PRegression 1 15.156 15.156 1.55 0.253Residual Error 7 68.400 9.771Total 8 83.556
Regression Analysis: 38-US versus 48-US The regression equation is38-US = 1.13 - 0.237 48-USPredictor Coef SE Coef T PConstant 1.1316 0.2154 5.25 0.00148-US -0.2368 0.2442 -0.97 0.365S = 0.501876 R-Sq = 11.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.2368 0.2368 0.94 0.365Residual Error 7 1.7632 0.2519Total 8 2.0000
Regression Analysis: 38-IT versus 48-IT The regression equation is38-IT = - 0.607 + 0.686 48-ITPredictor Coef SE Coef T PConstant -0.6068 0.8222 -0.74 0.48448-IT 0.6859 0.2290 2.99 0.020S = 1.65149 R-Sq = 56.2% R-Sq(adj) = 49.9%Analysis of VarianceSource DF SS MS F PRegression 1 24.464 24.464 8.97 0.020Residual Error 7 19.092 2.727Total 8 43.556
Regression Analysis: 38-GR versus 48-GR The regression equation is38-GR = 0.128 + 0.327 48-GRPredictor Coef SE Coef T PConstant 0.1282 0.4776 0.27 0.79648-GR 0.3269 0.1330 2.46 0.044S = 0.959338 R-Sq = 46.3% R-Sq(adj) = 38.6%Analysis of VarianceSource DF SS MS F PRegression 1 5.5577 5.5577 6.04 0.044Residual Error 7 6.4423 0.9203Total 8 12.0000
163
48-IT
34-I
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S 1.61561R-Sq 59.9%R-Sq(adj) 54.2%
Fitted Line Plot34-IT = - 0.7094 + 0.7244 48-IT
48-US
34-U
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0.5
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S 1.06022R-Sq 21.3%R-Sq(adj) 10.1%
Fitted Line Plot34-US = 1.395 - 0.7105 48-US
48-GR
34-G
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Fitted Line Plot34-GR = 1.923 - 0.3462 48-GR
48-JP
34-J
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Fitted Line Plot34-JP = 0.7140 + 0.8361 48-JP
34, 48
HD2 Employees having direct input into decisions and project success
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
Corporate Culture and Project Success, Teams.As. Primary
Attrib. Set(s) :
Correlations: 34-JP, 48-JP Pearson correlation of 34-JP and 48-JP = 0.874P-Value = 0.002
Correlations: 34-GR, 48-GR Pearson correlation of 34-GR and 48-GR = -0.441P-Value = 0.234
Correlations: 34-IT, 48-IT Pearson correlation of 34-IT and 48-IT = 0.774P-Value = 0.014
Regression Analysis: 34-US versus 48-US The regression equation is34-US = 1.39 - 0.711 48-USPredictor Coef SE Coef T PConstant 1.3947 0.4550 3.07 0.01848-US -0.7105 0.5160 -1.38 0.211S = 1.06022 R-Sq = 21.3% R-Sq(adj) = 10.1%Analysis of VarianceSource DF SS MS F PRegression 1 2.132 2.132 1.90 0.211Residual Error 7 7.868 1.124Total 8 10.000
Regression Analysis: 34-IT versus 48-IT The regression equation is34-IT = - 0.709 + 0.724 48-ITPredictor Coef SE Coef T PConstant -0.7094 0.8043 -0.88 0.40748-IT 0.7244 0.2240 3.23 0.014S = 1.61561 R-Sq = 59.9% R-Sq(adj) = 54.2%Analysis of VarianceSource DF SS MS F PRegression 1 27.284 27.284 10.45 0.014Residual Error 7 18.271 2.610Total 8 45.556
Regression Analysis: 34-GR versus 48-GR The regression equation is34-GR = 1.92 - 0.346 48-GRPredictor Coef SE Coef T PConstant 1.9231 0.9552 2.01 0.08448-GR -0.3462 0.2661 -1.30 0.234S = 1.91868 R-Sq = 19.5% R-Sq(adj) = 8.0%Analysis of VarianceSource DF SS MS F PRegression 1 6.231 6.231 1.69 0.234Residual Error 7 25.769 3.681Total 8 32.000
Regression Analysis: 34-JP versus 48-JP The regression equation is34-JP = 0.714 + 0.836 48-JPPredictor Coef SE Coef T PConstant 0.7140 0.8331 0.86 0.42048-JP 0.8361 0.1754 4.77 0.002S = 1.93748 R-Sq = 76.4% R-Sq(adj) = 73.1%Analysis of VarianceSource DF SS MS F PRegression 1 85.279 85.279 22.72 0.002Residual Error 7 26.277 3.754Total 8 111.556
Correlations: 34-US, 48-US Pearson correlation of 34-US and 48-US = -0.462P-Value = 0.211
164
44-US
36-U
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Fitted Line Plot36-US = 0.8571 + 0.1429 44-US
44-IT
36-I
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Fitted Line Plot36-IT = 0.8985 + 0.5376 44-IT
44-GR
36-G
R
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Fitted Line Plot36-GR = 0.2727 + 0.8182 44-GR
44-JP
36-J
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Fitted Line Plot36-JP = 1.123 + 0.6515 44-JP
36, 44
HD3 OTD, Cost, Performance as project success factors vs. recurring business, knowledge gained
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
Project Success, Basic Communication as it relates directly to KT
As. Primary Attrib. Set(s) :
Correlations: 36-US, 44-US Pearson correlation of 36-US and 44-US = 0.134P-Value = 0.732
Correlations: 36-IT, 44-IT Pearson correlation of 36-IT and 44-IT = 0.594P-Value = 0.092
Correlations: 36-GR, 44-GR Pearson correlation of 36-GR and 44-GR = 0.832P-Value = 0.005
Correlations: 36-JP, 44-JP Pearson correlation of 36-JP and 44-JP = 0.688P-Value = 0.041
Regression Analysis: 36-JP versus 44-JP The regression equation is36-JP = 1.12 + 0.651 44-JPPredictor Coef SE Coef T PConstant 1.123 1.198 0.94 0.38044-JP 0.6515 0.2600 2.51 0.041S = 2.56767 R-Sq = 47.3% R-Sq(adj) = 39.8%Analysis of VarianceSource DF SS MS F PRegression 1 41.405 41.405 6.28 0.041Residual Error 7 46.150 6.593Total 8 87.556
Regression Analysis: 36-GR versus 44-GR The regression equation is36-GR = 0.273 + 0.818 44-GRPredictor Coef SE Coef T PConstant 0.2727 0.4007 0.68 0.51844-GR 0.8182 0.2062 3.97 0.005S = 1.06904 R-Sq = 69.2% R-Sq(adj) = 64.8%Analysis of VarianceSource DF SS MS F PRegression 1 18.000 18.000 15.75 0.005Residual Error 7 8.000 1.143Total 8 26.000
Regression Analysis: 36-IT versus 44-IT The regression equation is36-IT = 0.898 + 0.538 44-ITPredictor Coef SE Coef T PConstant 0.8985 0.6018 1.49 0.17944-IT 0.5376 0.2753 1.95 0.092S = 1.49668 R-Sq = 35.3% R-Sq(adj) = 26.0%Analysis of VarianceSource DF SS MS F PRegression 1 8.542 8.542 3.81 0.092Residual Error 7 15.680 2.240Total 8 24.222
Regression Analysis: 36-US versus 44-US The regression equation is36-US = 0.857 + 0.143 44-USPredictor Coef SE Coef T PConstant 0.8571 0.6401 1.34 0.22244-US 0.1429 0.4004 0.36 0.732S = 1.49830 R-Sq = 1.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.286 0.286 0.13 0.732Residual Error 7 15.714 2.245Total 8 16.000
165
48-IT
49-I
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Fitted Line Plot49-IT = 0.7817 + 0.6690 48-IT
48-US
49-U
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Fitted Line Plot49-US = 0.7326 + 0.1047 48-US
48-GR
49-G
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Fitted Line Plot49-GR = 0.7817 + 0.6690 48-GR
48-JP
49-J
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Fitted Line Plot49-JP = 1.474 + 0.4408 48-JP
48, 49
HE1 Subsidiary employee morale and project successHypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
Project Success, Corporate culture, trust as a subset
As. Primary Attrib. Set(s) :
Correlations: 49-JP, 48-JP Pearson correlation of 49-JP and 48-JP = 0.591P-Value = 0.055
Correlations: 49-GR, 48-GR Pearson correlation of 49-GR and 48-GR = 0.648P-Value = 0.031
Correlations: 49-IT, 48-IT Pearson correlation of 49-IT and 48-IT = 0.648P-Value = 0.031
Correlations: 49-US, 48-US Pearson correlation of 49-US and 48-US = 0.174P-Value = 0.608
Regression Analysis: 49-US versus 48-US The regression equation is49-US = 0.733 + 0.105 48-USPredictor Coef SE Coef T PConstant 0.7326 0.2850 2.57 0.03048-US 0.1047 0.1971 0.53 0.608S = 0.779253 R-Sq = 3.0% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.1712 0.1712 0.28 0.608Residual Error 9 5.4651 0.6072Total 10 5.6364
Regression Analysis: 49-IT versus 48-IT The regression equation is49-IT = 0.782 + 0.669 48-ITPredictor Coef SE Coef T PConstant 0.7817 0.9376 0.83 0.42648-IT 0.6690 0.2619 2.55 0.031S = 2.10391 R-Sq = 42.0% R-Sq(adj) = 35.6%Analysis of VarianceSource DF SS MS F PRegression 1 28.889 28.889 6.53 0.031Residual Error 9 39.838 4.426Total 10 68.727
Regression Analysis: 49-GR versus 48-GR The regression equation is49-GR = 0.782 + 0.669 48-GRPredictor Coef SE Coef T PConstant 0.7817 0.9376 0.83 0.42648-GR 0.6690 0.2619 2.55 0.031S = 2.10391 R-Sq = 42.0% R-Sq(adj) = 35.6%Analysis of VarianceSource DF SS MS F PRegression 1 28.889 28.889 6.53 0.031Residual Error 9 39.838 4.426Total 10 68.727
Regression Analysis: 49-JP versus 48-JP The regression equation is49-JP = 1.47 + 0.441 48-JPPredictor Coef SE Coef T PConstant 1.4742 0.8693 1.70 0.12448-JP 0.4408 0.2004 2.20 0.055S = 2.28956 R-Sq = 35.0% R-Sq(adj) = 27.7%Analysis of VarianceSource DF SS MS F PRegression 1 25.366 25.366 4.84 0.055Residual Error 9 47.179 5.242Total 10 72.545
166
48-US
50-U
S
43210
4
3
2
1
0
S 1.31307R-Sq 0.8%R-Sq(adj) 0.0%
Fitted Line Plot50-US = 0.8895 - 0.0872 48-US
48-IT
50-I
T
76543210
6
5
4
3
2
1
0
S 2.33705R-Sq 6.8%R-Sq(adj) 0.0%
Fitted Line Plot50-IT = 1.925 + 0.2352 48-IT
48-GR
50-G
R
76543210
6
5
4
3
2
1
0
S 2.33705R-Sq 6.8%R-Sq(adj) 0.0%
Fitted Line Plot50-GR = 1.925 + 0.2352 48-GR
48-JP
50-J
P
121086420
9
8
7
6
5
4
3
2
1
0
S 2.24327R-Sq 7.1%R-Sq(adj) 0.0%
Fitted Line Plot50-JP = 2.118 + 0.1623 48-JP
48, 50
HE2 Parent headquarters satisfaction and project success
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
Project Success and Corporate culture As. Primary
Attrib. Set(s) :
Correlations: 50-US, 48-US Pearson correlation of 50-US and 48-US = -0.087P-Value = 0.799
Correlations: 50-IT, 48-IT Pearson correlation of 50-IT and 48-IT = 0.260P-Value = 0.440
Correlations: 50-GR, 48-GR Pearson correlation of 50-GR and 48-GR = 0.260P-Value = 0.440
Correlations: 50-JP, 48-JP Pearson correlation of 50-JP and 48-JP = 0.266P-Value = 0.430
Regression Analysis: 50-US versus 48-US The regression equation is50-US = 0.890 - 0.087 48-USPredictor Coef SE Coef T PConstant 0.8895 0.4802 1.85 0.09748-US -0.0872 0.3321 -0.26 0.799S = 1.31307 R-Sq = 0.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 0.119 0.119 0.07 0.799Residual Error 9 15.517 1.724Total 10 15.636
Regression Analysis: 50-IT versus 48-IT The regression equation is50-IT = 1.93 + 0.235 48-ITPredictor Coef SE Coef T PConstant 1.925 1.041 1.85 0.09848-IT 0.2352 0.2909 0.81 0.440S = 2.33705 R-Sq = 6.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.571 3.571 0.65 0.440Residual Error 9 49.156 5.462Total 10 52.72
Regression Analysis: 50-GR versus 48-GR The regression equation is50-GR = 1.93 + 0.235 48-GRPredictor Coef SE Coef T PConstant 1.925 1.041 1.85 0.09848-GR 0.2352 0.2909 0.81 0.440S = 2.33705 R-Sq = 6.8% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.571 3.571 0.65 0.440Residual Error 9 49.156 5.462Total 10 52.727
Regression Analysis: 50-JP versus 48-JP The regression equation is50-JP = 2.12 + 0.162 48-JPPredictor Coef SE Coef T PConstant 2.1177 0.8517 2.49 0.03548-JP 0.1623 0.1963 0.83 0.430S = 2.24327 R-Sq = 7.1% R-Sq(adj) = 0.0%Analysis of VarianceSource DF SS MS F PRegression 1 3.437 3.437 0.68 0.430Residual Error 9 45.290 5.032Total 10 48.727
167
49-US
50-U
S
2.01.51.00.50.0
4
3
2
1
0
S 1.05409R-Sq 36.0%R-Sq(adj) 28.9%
Fitted Line Plot50-US = 0.0000 + 1.000 49-US
49-IT
50-I
T
76543210
6
5
4
3
2
1
0
S 2.27245R-Sq 11.9%R-Sq(adj) 2.1%
Fitted Line Plot50-IT = 1.778 + 0.3016 49-IT
49-GR
50-G
R
76543210
6
5
4
3
2
1
0
S 2.27245R-Sq 11.9%R-Sq(adj) 2.1%
Fitted Line Plot50-GR = 1.778 + 0.3016 49-GR
49-JP
50-J
P
9876543210
9
8
7
6
5
4
3
2
1
0
S 1.90384R-Sq 33.1%R-Sq(adj) 25.6%
Fitted Line Plot50-JP = 1.303 + 0.4712 49-JP
49, 50
HE3 Parent headquarters satisfaction and subsidiary employee morale
Hypotheses :
Questions :
Variables :
JAPAN GERMANY
ITALY USA
As. Primary Attrib. Set(s) :
Project Success, Corporate culture, trust as a subset.
Correlations: 50-JP, 49-JP Pearson correlation of 50-JP and 49-JP = 0.575P-Value = 0.064
Correlations: 50-GR, 49-GR Pearson correlation of 50-GR and 49-GR = 0.344P-Value = 0.300
Correlations: 50-IT, 49-IT Pearson correlation of 50-IT and 49-IT = 0.344P-Value = 0.300
Correlations: 50-US, 49-US Pearson correlation of 50-US and 49-US = 0.600P-Value = 0.051
Regression Analysis: 50-JP versus 49-JP The regression equation is50-JP = 1.30 + 0.471 49-JPPredictor Coef SE Coef T PConstant 1.3033 0.8227 1.58 0.14849-JP 0.4712 0.2235 2.11 0.064S = 1.90384 R-Sq = 33.1% R-Sq(adj) = 25.6%Analysis of VarianceSource DF SS MS F PRegression 1 16.106 16.106 4.44 0.064Residual Error 9 32.622 3.625Total 10 48.727
Regression Analysis: 50-US versus 49-US The regression equation is50-US = 0.000 + 1.00 49-USPredictor Coef SE Coef T PConstant 0.0000 0.4827 0.00 1.00049-US 1.0000 0.4440 2.25 0.051S = 1.05409 R-Sq = 36.0% R-Sq(adj) = 28.9%Analysis of VarianceSource DF SS MS F PRegression 1 5.636 5.636 5.07 0.051Residual Error 9 10.000 1.111Total 10 15.636
Regression Analysis: 50-IT versus 49-IT The regression equation is50-IT = 1.78 + 0.302 49-ITPredictor Coef SE Coef T PConstant 1.7778 0.9779 1.82 0.10249-IT 0.3016 0.2741 1.10 0.300S = 2.27245 R-Sq = 11.9% R-Sq(adj) = 2.1%Analysis of VarianceSource DF SS MS F PRegression 1 6.251 6.251 1.21 0.300Residual Error 9 46.476 5.164Total 10 52.727
Regression Analysis: 50-GR versus 49-GR The regression equation is50-GR = 1.78 + 0.302 49-GRPredictor Coef SE Coef T PConstant 1.7778 0.9779 1.82 0.10249-GR 0.3016 0.2741 1.10 0.300S = 2.27245 R-Sq = 11.9% R-Sq(adj) = 2.1%Analysis of VarianceSource DF SS MS F PRegression 1 6.251 6.251 1.21 0.300Residual Error 9 46.476 5.164Total 10 52.727
168
4.2.2 Statistical Significance and Measures of Association
As with the previous section, we utilized MiniTab® (version 14) for the analysis in
this section as well, and with the results formatted in a Microsoft’s Visio® template.
Final results and hypotheses discussion is located at the end of this section.
4.2.2.1 Chi-square test (χ2) and Cramer’s V
The tables below outline the results and analysis from MiniTab regarding Chi-
square. As is apparent , they are categorized by company nationality (per the
original returned surveys) and follow the same organization as the correlational
analysis.
20, 22, 24
HB1 Daily communication method and trust.
Basic and International Communication, Corporate and National Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
20 -JP 24-JP Total 1 5 0 5 2 .50 2 .50 2 .500 2.500
2 9 2 11 5 .50 5 .50 2 .227 2.227
3 9 1 10 5 .00 5 .00 3 .200 3.200
4 5 2 7 3 .50 3 .50 0 .643 0.643
5 1 1 2 1 .00 1 .00 0 .000 0.000
7 0 13 13 6 .50 6 .50 6 .500 6.500
8 0 8 8 4 .00 4 .00 4 .000 4.000
9 0 2 2 1 .00 1 .00 1 .000 1.000
Total 29 29 58
Chi-Sq = 40.140, DF = 7
20 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418
2 2 2 4 1 .88 2 .12 0 .007 0.007
3 5 2 7 3 .29 3 .71 0 .883 0.785
4 1 1 2 0 .94 1 .06 0 .004 0.003
7 0 1 1 0 .47 0 .53 0 .471 0.418
8 0 2 2 0 .94 1 .06 0 .941 0.837
Total 8 9 17
Chi-Sq = 5.245, DF = 5
20 -IT 24-IT Total 3 3 0 3 1 .50 1 .50 1 .500 1.500
4 1 0 1 0 .50 0 .50 0 .500 0.500
6 1 0 1 0 .50 0 .50 0 .500 0.500
7 6 5 11 5 .50 5 .50 0 .045 0.045
8 0 6 6 3 .00 3 .00 3 .000 3.000
Total 11 11 22
Chi-Sq = 11.091, DF = 4
20 -US 24-US Total 1 3 2 5 2 .50 2 .50 0 .100 0.100
2 1 4 5 2 .50 2 .50 0 .900 0.900
3 2 1 3 1 .50 1 .50 0 .167 0.167
4 2 0 2 1 .00 1 .00 1 .000 1.000
5 1 0 1 0 .50 0 .50 0 .500 0.500
6 0 1 1 0 .50 0 .50 0 .500 0.500
8 0 1 1 0 .50 0 .50 0 .500 0.500
Total 9 9 18
Chi-Sq = 7.333, DF = 6
169
20, 22, 24
HB1 Daily communication method and trust.
Basic and International Communication, Corporate and National Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
22 -JP 24-JP Total 2 1 2 3 1 .50 1 .50 0 .167 0.167
3 4 1 5 2 .50 2 .50 0 .900 0.900
4 3 2 5 2 .50 2 .50 0 .100 0.100
5 1 1 2 1 .00 1 .00 0 .000 0.000
6 6 0 6 3 .00 3 .00 3 .000 3.000
7 7 13 20 10 .00 10 .00 0 .900 0.900
8 5 8 13 6 .50 6 .50 0 .346 0.346
9 2 2 4 2 .00 2 .00 0 .000 0.000
Total 29 29 58
Chi-Sq = 10.826, DF = 7
22 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418
2 0 2 2 0 .94 1 .06 0 .941 0.837
3 3 2 5 2 .35 2 .65 0 .178 0.158
4 4 1 5 2 .35 2 .65 1 .153 1.025
6 1 0 1 0 .47 0 .53 0 .596 0.529
7 0 1 1 0 .47 0 .53 0 .471 0.418
8 0 2 2 0 .94 1 .06 0 .941 0.837
Total 8 9 17
Chi-Sq = 8.972, DF = 6
22 -IT 24-IT Total 2 2 0 2 1 .00 1 .00 1 .000 1.000
3 2 0 2 1 .00 1 .00 1 .000 1.000
4 1 0 1 0 .50 0 .50 0 .500 0.500
5 1 0 1 0 .50 0 .50 0 .500 0.500
6 1 0 1 0 .50 0 .50 0 .500 0.500
7 2 5 7 3 .50 3 .50 0 .643 0.643
8 2 6 8 4 .00 4 .00 1 .000 1.000
Total 11 11 22
Chi-Sq = 10.286, DF = 6
22 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167
2 1 4 5 2 .50 2 .50 0 .900 0.900
3 0 1 1 0 .50 0 .50 0 .500 0.500
5 3 0 3 1 .50 1 .50 1 .500 1.500
6 2 1 3 1 .50 1 .50 0 .167 0.167
7 2 0 2 1 .00 1 .00 1 .000 1.000
8 0 1 1 0 .50 0 .50 0 .500 0.500
Total 9 9 18
Chi-Sq = 9.467, DF = 6
12, 14, 16, 18, 24
HB2 Communication channel between subsidiary and parent company; and trust
International Communication and Corp. Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
12 -JP 24-JP Total 2 2 2 4 2 .00 2 .00 0 .000 0.000
3 7 1 8 4 .00 4 .00 2 .250 2.250
4 1 2 3 1 .50 1 .50 0 .167 0.167
5 0 1 1 0 .50 0 .50 0 .500 0.500
6 3 0 3 1 .50 1 .50 1 .500 1.500
7 6 13 19 9 .50 9 .50 1 .289 1.289
8 3 8 11 5 .50 5 .50 1 .136 1.136
9 7 2 9 4 .50 4 .50 1 .389 1.389
Total 29 29 58
Chi-Sq = 16.463, DF = 7
12 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418
2 2 2 4 1 .88 2 .12 0 .007 0.007
3 1 2 3 1 .41 1 .59 0 .120 0.107
4 0 1 1 0 .47 0 .53 0 .471 0.418
7 4 1 5 2 .35 2 .65 1 .153 1.025
8 0 2 2 0 .94 1 .06 0 .941 0.837
9 1 0 1 0 .47 0 .53 0 .596 0.529
Total 8 9 17
Chi-Sq = 7.099, DF = 6
12 -IT 24-IT Total 1 1 0 1 0 .52 0 .48 0 .438 0.478
2 5 0 5 2 .61 2 .39 2 .192 2.391
6 2 0 2 1 .04 0 .96 0 .877 0.957
7 2 5 7 3 .65 3 .35 0 .747 0.815
8 1 6 7 3 .65 3 .35 1 .926 2.101
9 1 0 1 0 .52 0 .48 0 .438 0.478
Total 12 11 23
Chi-Sq = 13.840, DF = 5
12 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167
2 0 4 4 2 .00 2 .00 2 .000 2.000
3 0 1 1 0 .50 0 .50 0 .500 0.500
4 1 0 1 0 .50 0 .50 0 .500 0.500
5 2 0 2 1 .00 1 .00 1 .000 1.000
6 0 1 1 0 .50 0 .50 0 .500 0.500
7 2 0 2 1 .00 1 .00 1 .000 1.000
8 1 1 2 1 .00 1 .00 0 .000 0.000
9 2 0 2 1 .00 1 .00 1 .000 1.000
Total 9 9 18
Chi-Sq = 13.333, DF = 8
170
12, 14, 16, 18, 24
HB2 Communication channel between subsidiary and parent company; and trust
International Communication and Corp. Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
14 -JP 24-JP Total 1 1 0 1 0 .50 0 .50 0 .500 0.500
2 2 2 4 2 .00 2 .00 0 .000 0.000
3 7 1 8 4 .00 4 .00 2 .250 2.250
4 4 2 6 3 .00 3 .00 0 .333 0.333
5 1 1 2 1 .00 1 .00 0 .000 0.000
7 4 13 17 8 .50 8 .50 2 .382 2.382
8 3 8 11 5 .50 5 .50 1 .136 1.136
9 7 2 9 4 .50 4 .50 1 .389 1.389
Total 29 29 58
Chi-Sq = 15.982, DF = 7
14 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418
2 0 2 2 0 .94 1 .06 0 .941 0.837
3 1 2 3 1 .41 1 .59 0 .120 0.107
4 3 1 4 1 .88 2 .12 0 .664 0.590
7 3 1 4 1 .88 2 .12 0 .664 0.590
8 0 2 2 0 .94 1 .06 0 .941 0.837
9 1 0 1 0 .47 0 .53 0 .596 0.529
Total 8 9 17
Chi-Sq = 8.303, DF = 6
14 -IT 24-IT Total 2 6 0 6 3 .00 3 .00 3 .000 3.000
3 2 0 2 1 .00 1 .00 1 .000 1.000
4 2 0 2 1 .00 1 .00 1 .000 1.000
5 1 0 1 0 .50 0 .50 0 .500 0.500
7 0 5 5 2 .50 2 .50 2 .500 2.500
8 0 6 6 3 .00 3 .00 3 .000 3.000
Total 11 11 22
Chi-Sq = 22.000, DF = 5
14 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167
2 0 4 4 2 .00 2 .00 2 .000 2.000
3 2 1 3 1 .50 1 .50 0 .167 0.167
4 1 0 1 0 .50 0 .50 0 .500 0.500
5 1 0 1 0 .50 0 .50 0 .500 0.500
6 0 1 1 0 .50 0 .50 0 .500 0.500
8 1 1 2 1 .00 1 .00 0 .000 0.000
9 3 0 3 1 .50 1 .50 1 .500 1.500
Total 9 9 18
Chi-Sq = 10.667, DF = 7
12, 14, 16, 18, 24
HB2 Communication channel between subsidiary and parent company; and trust
International Communication and Corp. Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
16 -US 24-US Total 1 0 2 2 1 .00 1 .00 1 .000 1.000
2 0 4 4 2 .00 2 .00 2 .000 2.000
3 1 1 2 1 .00 1 .00 0 .000 0.000
5 1 0 1 0 .50 0 .50 0 .500 0.500
6 1 1 2 1 .00 1 .00 0 .000 0.000
8 2 1 3 1 .50 1 .50 0 .167 0.167
9 4 0 4 2 .00 2 .00 2 .000 2.000
Total 9 9 18
Chi-Sq = 11.333, DF = 6
16 -IT 24-IT Total 1 2 0 2 1 .00 1 .00 1 .000 1.000
2 3 0 3 1 .50 1 .50 1 .500 1.500
7 1 5 6 3 .00 3 .00 1 .333 1.333
8 3 6 9 4 .50 4 .50 0 .500 0.500
9 2 0 2 1 .00 1 .00 1 .000 1.000
Total 11 11 22
Chi-Sq = 10.667, DF = 4
16 -GR 24-GR Total 1 0 1 1 0 .47 0 .53 0 .471 0.418
2 2 2 4 1 .88 2 .12 0 .007 0.007
3 1 2 3 1 .41 1 .59 0 .120 0.107
4 0 1 1 0 .47 0 .53 0 .471 0.418
5 1 0 1 0 .47 0 .53 0 .596 0.529
6 1 0 1 0 .47 0 .53 0 .596 0.529
7 2 1 3 1 .41 1 .59 0 .245 0.218
8 0 2 2 0 .94 1 .06 0 .941 0.837
9 1 0 1 0 .47 0 .53 0 .596 0.529
Total 8 9 17
Chi-Sq = 7.634, DF = 8
16 -JP 24-JP Total 2 3 2 5 2 .50 2 .50 0 .100 0.100
3 4 1 5 2 .50 2 .50 0 .900 0.900
4 5 2 7 3 .50 3 .50 0 .643 0.643
5 1 1 2 1 .00 1 .00 0 .000 0.000
6 1 0 1 0 .50 0 .50 0 .500 0.500
7 1 13 14 7 .00 7 .00 5 .143 5.143
8 6 8 14 7 .00 7 .00 0 .143 0.143
9 8 2 10 5 .00 5 .00 1 .800 1.800
Total 29 29 58
Chi-Sq = 18.457, DF = 7
171
12, 14, 16, 18, 24
HB2 Communication channel between subsidiary and parent company; and trust
International Communication and Corp. Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
18 -JP 24-JP Total 1 3 0 3 1 .50 1 .50 1 .500 1.500
2 8 2 10 5 .00 5 .00 1 .800 1.800
3 0 1 1 0 .50 0 .50 0 .500 0.500
4 1 2 3 1 .50 1 .50 0 .167 0.167
5 1 1 2 1 .00 1 .00 0 .000 0.000
6 2 0 2 1 .00 1 .00 1 .000 1.000
7 5 13 18 9 .00 9 .00 1 .778 1.778
8 8 8 16 8 .00 8 .00 0 .000 0.000
9 1 2 3 1 .50 1 .50 0 .167 0.167
Total 29 29 58
Chi-Sq = 13.822, DF = 8
18 -GR 24-GR Total 1 1 1 2 0 .94 1 .06 0 .004 0.003
2 0 2 2 0 .94 1 .06 0 .941 0.837
3 3 2 5 2 .35 2 .65 0 .178 0.158
4 0 1 1 0 .47 0 .53 0 .471 0.418
7 0 1 1 0 .47 0 .53 0 .471 0.418
8 4 2 6 2 .82 3 .18 0 .490 0.436
Total 8 9 17
Chi-Sq = 4.825, DF = 5
18 -IT 24-IT Total 2 2 0 2 1 .00 1 .00 1 .000 1.000
3 2 0 2 1 .00 1 .00 1 .000 1.000
4 2 0 2 1 .00 1 .00 1 .000 1.000
7 0 5 5 2 .50 2 .50 2 .500 2.500
8 5 6 11 5 .50 5 .50 0 .045 0.045
Total 11 11 22
Chi-Sq = 11.091, DF = 4
18 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167
2 1 4 5 2 .50 2 .50 0 .900 0.900
3 0 1 1 0 .50 0 .50 0 .500 0.500
5 2 0 2 1 .00 1 .00 1 .000 1.000
6 1 1 2 1 .00 1 .00 0 .000 0.000
7 1 0 1 0 .50 0 .50 0 .500 0.500
8 1 1 2 1 .00 1 .00 0 .000 0.000
9 2 0 2 1 .00 1 .00 1 .000 1.000
Total 9 9 18
Chi-Sq = 8.133, DF = 7
12, 14, 16, 18, 35
HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT International Communication; Corp. and National Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
12 -US 35-US Total 1 1 1 2 1 .00 1 .00 0 .000 0.000
3 0 3 3 1 .50 1 .50 1 .500 1.500
4 1 2 3 1 .50 1 .50 0 .167 0.167
5 2 2 4 2 .00 2 .00 0 .000 0.000
7 2 0 2 1 .00 1 .00 1 .000 1.000
8 1 1 2 1 .00 1 .00 0 .000 0.000
9 2 0 2 1 .00 1 .00 1 .000 1.000
Total 9 9 18
Chi-Sq = 7.333, DF = 6
12 -IT 35-IT Total 1 1 0 1 0 .52 0 .48 0 .438 0.478
2 5 0 5 2 .61 2 .39 2 .192 2.391
6 2 0 2 1 .04 0 .96 0 .877 0.957
7 2 3 5 2 .61 2 .39 0 .142 0.155
8 1 6 7 3 .65 3 .35 1 .926 2.101
9 1 2 3 1 .57 1 .43 0 .204 0.223
Total 12 11 23
Chi-Sq = 12.084, DF = 5
12 -GR 35-GR Total 1 0 1 1 0 .50 0 .50 0 .500 0.500
2 2 0 2 1 .00 1 .00 1 .000 1.000
3 1 0 1 0 .50 0 .50 0 .500 0.500
4 0 4 4 2 .00 2 .00 2 .000 2.000
7 4 1 5 2 .50 2 .50 0 .900 0.900
8 0 2 2 1 .00 1 .00 1 .000 1.000
9 1 0 1 0 .50 0 .50 0 .500 0.500
Total 8 8 16
Chi-Sq = 12.800, DF = 6
12 -JP 35-JP Total 2 2 0 2 1 .00 1.00 1 .000 1 .000
3 7 0 7 3 .50 3.50 3 .500 3 .500
4 1 3 4 2 .00 2.00 0 .500 0 .500
5 0 1 1 0 .50 0.50 0 .500 0 .500
6 3 0 3 1 .50 1.50 1 .500 1 .500
7 6 11 17 8 .50 8.50 0 .735 0 .735
8 3 10 13 6 .50 6.50 1 .885 1 .885
9 7 4 11 5 .50 5.50 0 .409 0 .409
Total 29 29 58
Chi-Sq = 20.058, DF = 7
172
12, 14, 16, 18, 35
HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT International Communication; Corp. and National Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
14 -JP 35-JP Total 1 1 0 1 0 .50 0 .50 0 .500 0.500
2 2 0 2 1 .00 1 .00 1 .000 1.000
3 7 0 7 3 .50 3 .50 3 .500 3.500
4 4 3 7 3 .50 3 .50 0 .071 0.071
5 1 1 2 1 .00 1 .00 0 .000 0.000
7 4 11 15 7 .50 7 .50 1 .633 1.633
8 3 10 13 6 .50 6 .50 1 .885 1.885
9 7 4 11 5 .50 5 .50 0 .409 0.409
Total 29 29 58
Chi-Sq = 17.997, DF = 7
14 -GR 35-GR Total 1 0 1 1 0 .50 0 .50 0 .500 0.500
3 1 0 1 0 .50 0 .50 0 .500 0.500
4 3 4 7 3 .50 3 .50 0 .071 0.071
7 3 1 4 2 .00 2 .00 0 .500 0.500
8 0 2 2 1 .00 1 .00 1 .000 1.000
9 1 0 1 0 .50 0 .50 0 .500 0.500
Total 8 8 16
Chi-Sq = 6.143, DF = 5
14 -IT 35-IT Total 2 6 0 6 3 .00 3 .00 3 .000 3.000
3 2 0 2 1 .00 1 .00 1 .000 1.000
4 2 0 2 1 .00 1 .00 1 .000 1.000
5 1 0 1 0 .50 0 .50 0 .500 0.500
7 0 3 3 1 .50 1 .50 1 .500 1.500
8 0 6 6 3 .00 3 .00 3 .000 3.000
9 0 2 2 1 .00 1 .00 1 .000 1.000
Total 11 11 22
Chi-Sq = 22.000, DF = 6
14 -US 35-US Total 1 1 1 2 1 .00 1 .00 0 .000 0.000
3 2 3 5 2 .50 2 .50 0 .100 0.100
4 1 2 3 1 .50 1 .50 0 .167 0.167
5 1 2 3 1 .50 1 .50 0 .167 0.167
8 1 1 2 1 .00 1 .00 0 .000 0.000
9 3 0 3 1 .50 1 .50 1 .500 1.500
Total 9 9 18
Chi-Sq = 3.867, DF = 5
12, 14, 16, 18, 35
HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT International Communication; Corp. and National Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
16 -US 35-US Total 1 0 1 1 0 .50 0 .50 0 .500 0.500
3 1 3 4 2 .00 2 .00 0 .500 0.500
4 0 2 2 1 .00 1 .00 1 .000 1.000
5 1 2 3 1 .50 1 .50 0 .167 0.167
6 1 0 1 0 .50 0 .50 0 .500 0.500
8 2 1 3 1 .50 1 .50 0 .167 0.167
9 4 0 4 2 .00 2 .00 2 .000 2.000
Total 9 9 18
Chi-Sq = 9.667, DF = 6
16 -IT 35-IT Total 1 2 0 2 1 .00 1 .00 1 .000 1.000
2 3 0 3 1 .50 1 .50 1 .500 1.500
7 1 3 4 2 .00 2 .00 0 .500 0.500
8 3 6 9 4 .50 4 .50 0 .500 0.500
9 2 2 4 2 .00 2 .00 0 .000 0.000
Total 11 11 22
Chi-Sq = 7.000, DF = 4
16 -GR 35-GR Total 1 0 1 1 0 .50 0 .50 0 .500 0.500
2 2 0 2 1 .00 1 .00 1 .000 1.000
3 1 0 1 0 .50 0 .50 0 .500 0.500
4 0 4 4 2 .00 2 .00 2 .000 2.000
5 1 0 1 0 .50 0 .50 0 .500 0.500
6 1 0 1 0 .50 0 .50 0 .500 0.500
7 2 1 3 1 .50 1 .50 0 .167 0.167
8 0 2 2 1 .00 1 .00 1 .000 1.000
9 1 0 1 0 .50 0 .50 0 .500 0.500
Total 8 8 16
Chi-Sq = 13.333, DF = 8
16 -JP 35-JP Total 2 3 0 3 1 .50 1 .50 1 .500 1.500
3 4 0 4 2 .00 2 .00 2 .000 2.000
4 5 3 8 4 .00 4 .00 0 .250 0.250
5 1 1 2 1 .00 1 .00 0 .000 0.000
6 1 0 1 0 .50 0 .50 0 .500 0.500
7 1 11 12 6 .00 6 .00 4 .167 4.167
8 6 10 16 8 .00 8 .00 0 .500 0.500
9 8 4 12 6 .00 6 .00 0 .667 0.667
Total 29 29 58
Chi-Sq = 19.167, DF = 7
173
12, 14, 16, 18, 35
HB3 Communication channel between subsidiary and parent and truly shared-meaning in KT International Communication; Corp. and National Culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
18 -JP 35-JP Total 1 3 0 3 1 .50 1 .50 1 .500 1.500
2 8 0 8 4 .00 4 .00 4 .000 4.000
4 1 3 4 2 .00 2 .00 0 .500 0.500
5 1 1 2 1 .00 1 .00 0 .000 0.000
6 2 0 2 1 .00 1 .00 1 .000 1.000
7 5 11 16 8 .00 8 .00 1 .125 1.125
8 8 10 18 9 .00 9 .00 0 .111 0.111
9 1 4 5 2 .50 2 .50 0 .900 0.900
Total 29 29 58
Chi-Sq = 18.272, DF = 7
18 -GR 35-GR Total 1 1 1 2 1 .00 1 .00 0 .000 0.000
3 3 0 3 1 .50 1 .50 1 .500 1.500
4 0 4 4 2 .00 2 .00 2 .000 2.000
7 0 1 1 0 .50 0 .50 0 .500 0.500
8 4 2 6 3 .00 3 .00 0 .333 0.333
Total 8 8 16
Chi-Sq = 8.667, DF = 4
18 -IT 35-IT Total 2 2 0 2 1 .00 1 .00 1 .000 1.000
3 2 0 2 1 .00 1 .00 1 .000 1.000
4 2 0 2 1 .00 1 .00 1 .000 1.000
7 0 3 3 1 .50 1 .50 1 .500 1.500
8 5 6 11 5 .50 5 .50 0 .045 0.045
9 0 2 2 1 .00 1 .00 1 .000 1.000
Total 11 11 22
Chi-Sq = 11.091, DF = 5
18 -US 35-US Total 1 1 1 2 1 .00 1 .00 0 .000 0.000
2 1 0 1 0 .50 0 .50 0 .500 0.500
3 0 3 3 1 .50 1 .50 1 .500 1.500
4 0 2 2 1 .00 1 .00 1 .000 1.000
5 2 2 4 2 .00 2 .00 0 .000 0.000
6 1 0 1 0 .50 0 .50 0 .500 0.500
7 1 0 1 0 .50 0 .50 0 .500 0.500
8 1 1 2 1 .00 1 .00 0 .000 0.000
9 2 0 2 1 .00 1 .00 1 .000 1.000
Total 9 9 18
Chi-Sq = 10.000, DF = 8
18, 24
HB4 Many-to-many subsidiary communication channel and learning / trusting relationship International Communication; Corp. and National Culture; trust (as a major subset attribute)
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
18 -JP 24-JP Total 1 3 0 3 1 .50 1.50 1 .500 1 .500
2 8 2 10 5 .00 5.00 1 .800 1 .800
3 0 1 1 0 .50 0.50 0 .500 0 .500
4 1 2 3 1 .50 1.50 0 .167 0 .167
5 1 1 2 1 .00 1.00 0 .000 0 .000
6 2 0 2 1 .00 1.00 1 .000 1 .000
7 5 13 18 9 .00 9.00 1 .778 1 .778
8 8 8 16 8 .00 8.00 0 .000 0 .000
9 1 2 3 1 .50 1.50 0 .167 0 .167
Total 29 29 58
Chi-Sq = 13.822, DF = 8
18 -GR 24-GR Total 1 1 1 2 0 .94 1 .06 0 .004 0.003
2 0 2 2 0 .94 1 .06 0 .941 0.837
3 3 2 5 2 .35 2 .65 0 .178 0.158
4 0 1 1 0 .47 0 .53 0 .471 0.418
7 0 1 1 0 .47 0 .53 0 .471 0.418
8 4 2 6 2 .82 3 .18 0 .490 0.436
Total 8 9 17
Chi-Sq = 4.825, DF = 5
18 -IT 24-IT Total 2 2 0 2 1 .00 1 .00 1 .000 1.000
3 2 0 2 1 .00 1 .00 1 .000 1.000
4 2 0 2 1 .00 1 .00 1 .000 1.000
7 0 5 5 2 .50 2 .50 2 .500 2.500
8 5 6 11 5 .50 5 .50 0 .045 0.045
Total 11 11 22
Chi-Sq = 11.091, DF = 4
18 -US 24-US Total 1 1 2 3 1 .50 1 .50 0 .167 0.167
2 1 4 5 2 .50 2 .50 0 .900 0.900
3 0 1 1 0 .50 0 .50 0 .500 0.500
5 2 0 2 1 .00 1 .00 1 .000 1.000
6 1 1 2 1 .00 1 .00 0 .000 0.000
7 1 0 1 0 .50 0 .50 0 .500 0.500
8 1 1 2 1 .00 1 .00 0 .000 0.000
9 2 0 2 1 .00 1 .00 1 .000 1.000
Total 9 9 18
Chi-Sq = 8.133, DF = 7
174
34, 35
HC1Employees having direct input to decisions affecting them and shared meaning in succesful KT
Corporate culture, Groups and Teams Communication, trust as a major attribute subset
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
34 -JP 35-JP Total 1 1 0 1 0 .50 0 .50 0 .500 0.500
2 1 0 1 0 .50 0 .50 0 .500 0.500
3 2 0 2 1 .00 1 .00 1 .000 1.000
4 3 3 6 3 .00 3 .00 0 .000 0.000
5 1 1 2 1 .00 1 .00 0 .000 0.000
6 11 0 11 5 .50 5 .50 5 .500 5.500
7 8 11 19 9 .50 9 .50 0 .237 0.237
8 0 10 10 5 .00 5 .00 5 .000 5.000
9 2 4 6 3 .00 3 .00 0 .333 0.333
Total 29 29 58
Chi-Sq = 26.140, DF = 8
34 -GR 35-GR Total 1 0 1 1 0 .53 0 .47 0 .529 0.596
2 2 0 2 1 .06 0 .94 0 .837 0.941
3 6 0 6 3 .18 2 .82 2 .510 2.824
4 0 4 4 2 .12 1 .88 2 .118 2.382
5 1 0 1 0 .53 0 .47 0 .418 0.471
7 0 1 1 0 .53 0 .47 0 .529 0.596
8 0 2 2 1 .06 0 .94 1 .059 1.191
Total 9 8 17
Chi-Sq = 17.000, DF = 6
34 -IT 35-IT Total 7 3 3 6 3 .00 3 .00 0 .000 0.000
8 7 6 13 6 .50 6 .50 0 .038 0.038
9 1 2 3 1 .50 1 .50 0 .167 0.167
Total 11 11 22
Chi-Sq = 0.410, DF = 2
34 -US 35-US Total 1 1 1 2 1 .00 1 .00 0 .000 0.000
2 1 0 1 0 .50 0 .50 0 .500 0.500
3 2 3 5 2 .50 2 .50 0 .100 0.100
4 0 2 2 1 .00 1 .00 1 .000 1.000
5 3 2 5 2 .50 2 .50 0 .100 0.100
7 2 0 2 1 .00 1 .00 1 .000 1.000
8 0 1 1 0 .50 0 .50 0 .500 0.500
Total 9 9 18
Chi-Sq = 6.400, DF = 6
30, 31
HC2Technology tools , and true spirit of cooperation and collaboration between subsidiary , parent headquarters
International Communication, National Culture, Trust
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
30 -JP 31-JP Total 1 0 1 1 0 .50 0 .50 0 .500 0.500
2 4 1 5 2 .50 2 .50 0 .900 0.900
3 4 7 11 5 .50 5 .50 0 .409 0.409
4 1 2 3 1 .50 1 .50 0 .167 0.167
5 3 3 6 3 .00 3 .00 0 .000 0.000
6 4 6 10 5 .00 5 .00 0 .200 0.200
7 6 8 14 7 .00 7 .00 0 .143 0.143
8 6 1 7 3 .50 3 .50 1 .786 1.786
9 1 0 1 0 .50 0 .50 0 .500 0.500
Total 29 29 58
Chi-Sq = 9.209, DF = 8
30 -GR 31-GR Total 1 1 0 1 0 .47 0 .53 0 .596 0.529
2 2 5 7 3 .29 3 .71 0 .508 0.452
3 4 0 4 1 .88 2 .12 2 .382 2.118
4 1 1 2 0 .94 1 .06 0 .004 0.003
6 0 3 3 1 .41 1 .59 1 .412 1.255
Total 8 9 17
Chi-Sq = 9.259, DF = 4
30 -IT 31-IT Total 2 5 2 7 3 .50 3 .50 0 .643 0.643
3 0 2 2 1 .00 1 .00 1 .000 1.000
4 0 1 1 0 .50 0 .50 0 .500 0.500
6 3 0 3 1 .50 1 .50 1 .500 1.500
7 2 4 6 3 .00 3 .00 0 .333 0.333
8 1 2 3 1 .50 1 .50 0 .167 0.167
Total 11 11 22
Chi-Sq = 8.286, DF = 5
30 -US 31-US Total 1 2 1 3 1 .50 1 .50 0 .167 0.167
2 2 1 3 1 .50 1 .50 0 .167 0.167
3 1 3 4 2 .00 2 .00 0 .500 0.500
4 1 0 1 0 .50 0 .50 0 .500 0.500
5 2 3 5 2 .50 2 .50 0 .100 0.100
7 1 1 2 1 .00 1 .00 0 .000 0.000
Total 9 9 18
Chi-Sq = 2.867, DF = 5
175
24, 26, 27
HC3 Trust and knowledge holdback by either subsidiary and / or parent headquartersInternational Communication, Trust (as a major attribute subset)
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
24 -JP 26-JP Total 1 0 3 3 1 .50 1.50 1 .500 1 .500
2 2 0 2 1 .00 1.00 1 .000 1 .000
3 1 1 2 1 .00 1.00 0 .000 0 .000
4 2 0 2 1 .00 1.00 1 .000 1 .000
5 1 2 3 1 .50 1.50 0 .167 0 .167
6 0 4 4 2 .00 2.00 2 .000 2 .000
7 13 12 25 12 .50 12.50 0 .020 0 .020
8 8 6 14 7 .00 7.00 0 .143 0 .143
9 2 1 3 1 .50 1.50 0 .167 0 .167
Total 29 29 58
Chi-Sq = 11.992, DF = 8
24 -GR 26-GR Total 1 1 0 1 0 .53 0 .47 0 .418 0.471
2 2 2 4 2 .12 1 .88 0 .007 0.007
3 2 1 3 1 .59 1 .41 0 .107 0.120
4 1 0 1 0 .53 0 .47 0 .418 0.471
7 1 2 3 1 .59 1 .41 0 .218 0.245
8 2 2 4 2 .12 1 .88 0 .007 0.007
9 0 1 1 0 .53 0 .47 0 .529 0.596
Total 9 8 17
Chi-Sq = 3.620, DF = 6
24 -IT 26-IT Total 2 0 2 2 1 .00 1 .00 1 .000 1.000
3 0 3 3 1 .50 1 .50 1 .500 1.500
5 0 2 2 1 .00 1 .00 1 .000 1.000
6 0 1 1 0 .50 0 .50 0 .500 0.500
7 5 2 7 3 .50 3 .50 0 .643 0.643
8 6 1 7 3 .50 3 .50 1 .786 1.786
Total 11 11 22
Chi-Sq = 12.857, DF = 5
24 -US 26-US Total 1 2 0 2 1 .00 1 .00 1 .000 1.000
2 4 0 4 2 .00 2 .00 2 .000 2.000
3 1 0 1 0 .50 0 .50 0 .500 0.500
4 0 1 1 0 .50 0 .50 0 .500 0.500
5 0 1 1 0 .50 0 .50 0 .500 0.500
6 1 0 1 0 .50 0 .50 0 .500 0.500
7 0 1 1 0 .50 0 .50 0 .500 0.500
8 1 3 4 2 .00 2 .00 0 .500 0.500
9 0 3 3 1 .50 1 .50 1 .500 1.500
Total 9 9 18
Chi-Sq = 15.000, DF = 8
24, 26, 27
HC3 Trust and knowledge holdback by either subsidiary and / or parent headquartersInternational Communication, Trust (as a major attribute subset)
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
24 -US 27-US Total 1 2 3 5 2 .50 2 .50 0 .100 0.100
2 4 0 4 2 .00 2 .00 2 .000 2.000
3 1 1 2 1 .00 1 .00 0 .000 0.000
5 0 1 1 0 .50 0 .50 0 .500 0.500
6 1 0 1 0 .50 0 .50 0 .500 0.500
8 1 1 2 1 .00 1 .00 0 .000 0.000
9 0 3 3 1 .50 1 .50 1 .500 1.500
Total 9 9 18
Chi-Sq = 9.200, DF = 6
24 -IT 27-IT Total 1 0 1 1 0 .50 0 .50 0 .500 0.500
2 0 9 9 4 .50 4 .50 4 .500 4.500
3 0 1 1 0 .50 0 .50 0 .500 0.500
7 5 0 5 2 .50 2 .50 2 .500 2.500
8 6 0 6 3 .00 3 .00 3 .000 3.000
Total 11 11 22
Chi-Sq = 22.000, DF = 4
24 -GR 27-GR Total 1 1 0 1 0 .50 0 .50 0 .500 0.500
2 2 2 4 2 .00 2 .00 0 .000 0.000
3 2 0 2 1 .00 1 .00 1 .000 1.000
4 1 2 3 1 .50 1 .50 0 .167 0.167
7 1 3 4 2 .00 2 .00 0 .500 0.500
8 2 1 3 1 .50 1 .50 0 .167 0.167
9 0 1 1 0 .50 0 .50 0 .500 0.500
Total 9 9 18
Chi-Sq = 5.667, DF = 6
24 -JP 27-JP Total 1 0 3 3 1 .50 1 .50 1 .500 1.500
2 2 11 13 6 .50 6 .50 3 .115 3.115
3 1 9 10 5 .00 5 .00 3 .200 3.200
4 2 0 2 1 .00 1 .00 1 .000 1.000
5 1 1 2 1 .00 1 .00 0 .000 0.000
6 0 1 1 0 .50 0 .50 0 .500 0.500
7 13 2 15 7 .50 7 .50 4 .033 4.033
8 8 2 10 5 .00 5 .00 1 .800 1.800
9 2 0 2 1 .00 1 .00 1 .000 1.000
Total 29 29 58
Chi-Sq = 32.297, DF = 8
176
38, 48
HD1 Post-project review and lessons-learned and project success
Project Success, Group / Team Communication
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
38 -JP 48-JP Total 1 1 0 1 0 .52 0 .48 0 .449 0.482
2 2 0 2 1 .04 0 .96 0 .898 0.964
3 1 0 1 0 .52 0 .48 0 .449 0.482
4 1 3 4 2 .07 1 .93 0 .554 0.595
5 1 0 1 0 .52 0 .48 0 .449 0.482
6 4 12 16 8 .29 7 .71 2 .217 2.381
7 10 5 15 7 .77 7 .23 0 .641 0.689
8 7 3 10 5 .18 4 .82 0 .641 0.688
9 2 4 6 3 .11 2 .89 0 .394 0.424
Total 29 27 56
Chi-Sq = 13.880, DF = 8
38 -GR 48-GR Total 2 1 2 3 0 .82 2 .18 0 .040 0.015
4 1 0 1 0 .27 0 .73 1 .939 0.727
5 0 2 2 0 .55 1 .45 0 .545 0.205
6 3 5 8 2 .18 5 .82 0 .307 0.115
7 0 5 5 1 .36 3 .64 1 .364 0.511
8 3 7 10 2 .73 7 .27 0 .027 0.010
9 1 3 4 1 .09 2 .91 0 .008 0.003
Total 9 24 33
Chi-Sq = 5.817, DF = 6
38 -IT 48-IT Total 2 0 2 2 0 .63 1 .37 0 .629 0.288
5 0 2 2 0 .63 1 .37 0 .629 0.288
6 0 5 5 1 .57 3 .43 1 .571 0.720
7 2 5 7 2 .20 4 .80 0 .018 0.008
8 7 7 14 4 .40 9 .60 1 .536 0.704
9 2 3 5 1 .57 3 .43 0 .117 0.054
Total 11 24 35
Chi-Sq = 6.563, DF = 5
38 -US 48-US Total 1 1 0 1 0 .64 0 .36 0 .198 0.357
2 1 0 1 0 .64 0 .36 0 .198 0.357
3 1 0 1 0 .64 0 .36 0 .198 0.357
4 1 1 2 1 .29 0 .71 0 .063 0.114
5 1 0 1 0 .64 0 .36 0 .198 0.357
6 1 1 2 1 .29 0 .71 0 .063 0.114
7 2 1 3 1 .93 1 .07 0 .003 0.005
8 1 0 1 0 .64 0 .36 0 .198 0.357
9 0 2 2 1 .29 0 .71 1 .286 2.314
Total 9 5 14
Chi-Sq = 6.741, DF = 8
34, 48
HD2 Employees having direct input into decisions and project success
Corporate Culture and Project Success, Teams.
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
34 -US 48-US Total 1 1 0 1 0 .64 0 .36 0 .198 0.357
2 1 0 1 0 .64 0 .36 0 .198 0.357
3 2 0 2 1 .29 0 .71 0 .397 0.714
4 0 1 1 0 .64 0 .36 0 .643 1.157
5 3 0 3 1 .93 1 .07 0 .595 1.071
6 0 1 1 0 .64 0 .36 0 .643 1.157
7 2 1 3 1 .93 1 .07 0 .003 0.005
9 0 2 2 1 .29 0 .71 1 .286 2.314
Total 9 5 14
Chi-Sq = 11.096, DF = 7
34 -IT 48-IT Total 2 0 2 2 0 .63 1 .37 0 .629 0.288
5 0 2 2 0 .63 1 .37 0 .629 0.288
6 0 5 5 1 .57 3 .43 1 .571 0.720
7 3 5 8 2 .51 5 .49 0 .094 0.043
8 7 7 14 4 .40 9 .60 1 .536 0.704
9 1 3 4 1 .26 2 .74 0 .053 0.024
Total 11 24 35
Chi-Sq = 6.579, DF = 5
34 -GR 48-GR Total 2 2 2 4 1 .09 2.91 0 .758 0 .284
3 6 0 6 1 .64 4.36 11 .636 4 .364
5 1 2 3 0 .82 2.18 0 .040 0 .015
6 0 5 5 1 .36 3.64 1 .364 0 .511
7 0 5 5 1 .36 3.64 1 .364 0 .511
8 0 7 7 1 .91 5.09 1 .909 0 .716
9 0 3 3 0 .82 2.18 0 .818 0 .307
Total 9 24 33
Chi-Sq = 24.597, DF = 6
34 -JP 48-JP Total 1 1 0 1 0 .52 0 .48 0 .449 0.482
2 1 0 1 0 .52 0 .48 0 .449 0.482
3 2 0 2 1 .04 0 .96 0 .898 0.964
4 3 3 6 3 .11 2 .89 0 .004 0.004
5 1 0 1 0 .52 0 .48 0 .449 0.482
6 11 12 23 11 .91 11 .09 0 .070 0.075
7 8 5 13 6 .73 6 .27 0 .239 0.256
8 0 3 3 1 .55 1 .45 1 .554 1.669
9 2 4 6 3 .11 2 .89 0 .394 0.424
Total 29 27 56
Chi-Sq = 9.343, DF = 8
177
36, 44
HD3 OTD, Cost, Performance as project success factors vs. recurring business, knowledge gainedProject Success, Basic Communication as it relates directly to KT
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
36 -JP 44-JP Total 1 7 5 12 6 .00 6 .00 0 .167 0.167
2 10 8 18 9 .00 9 .00 0 .111 0.111
3 3 9 12 6 .00 6 .00 1 .500 1.500
4 2 4 6 3 .00 3 .00 0 .333 0.333
5 3 0 3 1 .50 1 .50 1 .500 1.500
6 3 2 5 2 .50 2 .50 0 .100 0.100
7 1 1 2 1 .00 1 .00 0 .000 0.000
Total 29 29 58
Chi-Sq = 7.422, DF = 6
36 -GR 44-GR Total 1 1 0 1 0 .53 0 .47 0 .418 0.471
2 5 3 8 4 .24 3 .76 0 .138 0.155
3 3 5 8 4 .24 3 .76 0 .360 0.405
Total 9 8 17
Chi-Sq = 1.948, DF = 2
36 -IT 44-IT Total 1 4 3 7 3 .92 3 .08 0 .002 0.002
2 3 5 8 4 .48 3 .52 0 .489 0.622
3 2 3 5 2 .80 2 .20 0 .229 0.291
6 4 0 4 2 .24 1 .76 1 .383 1.760
7 1 0 1 0 .56 0 .44 0 .346 0.440
Total 14 11 25
Chi-Sq = 5.563, DF = 4
36 -US 44-US Total 1 4 2 6 3 .00 3.00 0 .333 0 .333
2 2 0 2 1 .00 1.00 1 .000 1 .000
3 0 4 4 2 .00 2.00 2 .000 2 .000
4 2 1 3 1 .50 1.50 0 .167 0 .167
5 1 1 2 1 .00 1.00 0 .000 0 .000
6 0 1 1 0 .50 0.50 0 .500 0 .500
Total 9 9 18
Chi-Sq = 8.000, DF = 5
48, 49
HE1 Subsidiary employee morale and project success
Project Success, Corporate culture, trust as a subset
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
48 -JP 49-JP Total 3 0 1 1 0 .51 0 .49 0 .509 0.529
4 3 1 4 2 .04 1 .96 0 .454 0.472
5 0 1 1 0 .51 0 .49 0 .509 0.529
6 12 4 16 8 .15 7 .85 1 .818 1.888
7 5 8 13 6 .62 6 .38 0 .398 0.413
8 3 5 8 4 .08 3 .92 0 .284 0.295
9 4 6 10 5 .09 4 .91 0 .235 0.244
Total 27 26 53
Chi-Sq = 8.576, DF = 6
48 -GR 49-GR Total 2 2 0 2 0 .94 1 .06 1 .191 1.059
3 0 1 1 0 .47 0 .53 0 .471 0.418
4 0 2 2 0 .94 1 .06 0 .941 0.837
5 2 2 4 1 .88 2 .12 0 .007 0.007
6 5 3 8 3 .76 4 .24 0 .405 0.360
7 5 6 11 5 .18 5 .82 0 .006 0.005
8 7 6 13 6 .12 6 .88 0 .127 0.113
9 3 7 10 4 .71 5 .29 0 .618 0.550
Total 24 27 51
Chi-Sq = 7.116, DF = 7
48 -IT 49-IT Total 2 2 0 2 0 .94 1 .06 1 .191 1.059
3 0 1 1 0 .47 0 .53 0 .471 0.418
4 0 2 2 0 .94 1 .06 0 .941 0.837
5 2 2 4 1 .88 2 .12 0 .007 0.007
6 5 3 8 3 .76 4 .24 0 .405 0.360
7 5 6 11 5 .18 5 .82 0 .006 0.005
8 7 6 13 6 .12 6 .88 0 .127 0.113
9 3 7 10 4 .71 5 .29 0 .618 0.550
Total 24 27 51
Chi-Sq = 7.116, DF = 7
48 -US 49-US Total 3 0 1 1 0 .38 0 .62 0 .385 0.240
4 1 0 1 0 .38 0 .62 0 .985 0.615
5 0 1 1 0 .38 0 .62 0 .385 0.240
6 1 1 2 0 .77 1 .23 0 .069 0.043
7 1 2 3 1 .15 1 .85 0 .021 0.013
8 0 2 2 0 .77 1 .23 0 .769 0.481
9 2 1 3 1 .15 1 .85 0 .621 0.388
Total 5 8 13
Chi-Sq = 5.254, DF = 6
178
48, 50
HE2 Parent headquarters satisfaction and project success
Project Success and Corporate culture
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
48 -US 50-US Total 2 0 2 2 0 .71 1 .29 0 .714 0.397
3 0 4 4 1 .43 2 .57 1 .429 0.794
4 1 1 2 0 .71 1 .29 0 .114 0.063
6 1 1 2 0 .71 1 .29 0 .114 0.063
7 1 0 1 0 .36 0 .64 1 .157 0.643
9 2 1 3 1 .07 1 .93 0 .805 0.447
Total 5 9 14
Chi-Sq = 6.741, DF = 5
48 -IT 50-IT Total 2 2 6 8 3 .69 4 .31 0 .776 0.665
3 0 5 5 2 .31 2 .69 2 .308 1.978
4 0 2 2 0 .92 1 .08 0 .923 0.791
5 2 3 5 2 .31 2 .69 0 .041 0.035
6 5 6 11 5 .08 5 .92 0 .001 0.001
7 5 2 7 3 .23 3 .77 0 .969 0.830
8 7 3 10 4 .62 5 .38 1 .232 1.056
9 3 1 4 1 .85 2 .15 0 .721 0.618
Total 24 28 52
Chi-Sq = 12.946, DF = 7
48 -GR 50-GR Total 2 2 6 8 3 .69 4 .31 0 .776 0.665
3 0 5 5 2 .31 2 .69 2 .308 1.978
4 0 2 2 0 .92 1 .08 0 .923 0.791
5 2 3 5 2 .31 2 .69 0 .041 0.035
6 5 6 11 5 .08 5 .92 0 .001 0.001
7 5 2 7 3 .23 3 .77 0 .969 0.830
8 7 3 10 4 .62 5 .38 1 .232 1.056
9 3 1 4 1 .85 2 .15 0 .721 0.618
Total 24 28 52
Chi-Sq = 12.946, DF = 7
48 -JP 50-JP Total 1 0 3 3 1 .47 1 .53 1 .473 1.420
2 0 8 8 3 .93 4 .07 3 .927 3.787
3 0 4 4 1 .96 2 .04 1 .964 1.894
4 3 3 6 2 .95 3 .05 0 .001 0.001
5 0 3 3 1 .47 1 .53 1 .473 1.420
6 12 1 13 6 .38 6 .62 4 .946 4.769
7 5 2 7 3 .44 3 .56 0 .711 0.686
8 3 2 5 2 .45 2 .55 0 .121 0.117
9 4 2 6 2 .95 3 .05 0 .378 0.364
Total 27 28 55
Chi-Sq = 29.452, DF = 8
49, 50
HE3 Parent headquarters satisfaction and subsidiary employee morale Project Success, Corporate culture, trust as a subset.
Hypotheses :
Questions :
Variables :
JAPAN GERMANY ITALY USA
As. Primary Attrib. Set(s) :
49 -JP 50-JP Total 1 0 3 3 1 .44 1 .56 1 .444 1.341
2 0 8 8 3 .85 4 .15 3 .852 3.577
3 1 4 5 2 .41 2 .59 0 .823 0.764
4 1 3 4 1 .93 2 .07 0 .445 0.413
5 1 3 4 1 .93 2 .07 0 .445 0.413
6 4 1 5 2 .41 2 .59 1 .054 0.978
7 8 2 10 4 .81 5 .19 2 .107 1.957
8 5 2 7 3 .37 3 .63 0 .788 0.732
9 6 2 8 3 .85 4 .15 1 .198 1.112
Total 26 28 54
Chi-Sq = 23.444, DF = 8
49 -GR 50-GR Total 2 0 6 6 2 .95 3 .05 2 .945 2.840
3 1 5 6 2 .95 3 .05 1 .285 1.239
4 2 2 4 1 .96 2 .04 0 .001 0.001
5 2 3 5 2 .45 2 .55 0 .084 0.081
6 3 6 9 4 .42 4 .58 0 .455 0.439
7 6 2 8 3 .93 4 .07 1 .094 1.055
8 6 3 9 4 .42 4 .58 0 .566 0.546
9 7 1 8 3 .93 4 .07 2 .404 2.318
Total 27 28 55
Chi-Sq = 17.354, DF = 7
49 -IT 50-IT Total 2 0 6 6 2 .95 3 .05 2 .945 2.840
3 1 5 6 2 .95 3 .05 1 .285 1.239
4 2 2 4 1 .96 2 .04 0 .001 0.001
5 2 3 5 2 .45 2 .55 0 .084 0.081
6 3 6 9 4 .42 4 .58 0 .455 0.439
7 6 2 8 3 .93 4 .07 1 .094 1.055
8 6 3 9 4 .42 4 .58 0 .566 0.546
9 7 1 8 3 .93 4 .07 2 .404 2.318
Total 27 28 55
Chi-Sq = 17.354, DF = 7
49 -US 50-US Total 2 0 2 2 0 .94 1 .06 0 .941 0.837
3 1 4 5 2 .35 2 .65 0 .778 0.692
4 0 1 1 0 .47 0 .53 0 .471 0.418
5 1 0 1 0 .47 0 .53 0 .596 0.529
6 1 1 2 0 .94 1 .06 0 .004 0.003
7 2 0 2 0 .94 1 .06 1 .191 1.059
8 2 0 2 0 .94 1 .06 1 .191 1.059
9 1 1 2 0 .94 1 .06 0 .004 0.003
Total 8 9 17
Chi-Sq = 9.775, DF = 7
179
The chi-square test, such as the one conducted here using the MiniTab® software
and whose results are displayed in the previous pages, essentially seeks to identify
whether findings are appropriate and thus can be generalized to a full population, or
if the findings are simply due to sampling error [95]. However, such tests for
statistical significance determine whether a relationship exists between variables,
but they do not measure strength of such a potential relationship.
A fairly simple and versatile measure of association derived directly from the chi-
square values is Cramer’s V. This test is used extensively in survey research. The
relationship between Chi-Square and Cramer’s V is show below; where n denotes
the sample size and M the minimum number of either rows or columns (whichever
is the smaller value).
V = χ2
n ( M-1 )
We summarize our intermediate analysis results, including chi-square and Cramer’s
V below. At the end of this Chapter a comprehensive summary is also be presented.
180
Table 4-24 : Chi-Square ( χ2 ) and Cramer's V Significance and Association Summary Values and Interpretations
Hypotheses Question / Country χ2 dF χ2*.05 M n V Interpretation** of V
Japan 40.14 7 3 58 0.588 Relatively strong associationGermany 5.24 5 3 17 0.393Italy 11.09 4 3 22 0.502 Relatively strong associationUSA 7.33 6 3 18 0.451Japan 10.83 7 3 58 0.306Germany 8.97 6 3 17 0.514Italy 10.29 6 3 22 0.484USA 9.47 6 3 18 0.513Japan 16.46 7 3 58 0.377 Moderate AssociationGermany 7.10 6 3 17 0.457Italy 13.84 5 3 23 0.549 Relatively strong associationUSA 13.33 8 3 18 0.609Japan 15.98 7 3 58 0.371 Moderate AssociationGermany 8.30 6 3 17 0.494Italy 22.00 5 3 22 0.707 Strong AssociationUSA 10.67 7 3 18 0.544Japan 18.46 7 3 58 0.399 Moderate AssociationGermany 7.63 8 3 17 0.474Italy 10.67 4 3 22 0.492 Relatively strong associationUSA 11.33 6 3 18 0.561Japan 13.82 8 3 58 0.345Germany 4.82 5 3 17 0.377Italy 11.10 4 3 22 0.502 Relatively strong associationUSA 8.13 7 3 18 0.475Japan 20.06 7 3 58 0.416 Relatively strong associationGermany 12.80 6 3 16 0.632 Strong AssociationItaly 12.10 5 3 23 0.513 Relatively strong associationUSA 7.33 6 3 18 0.451Japan 17.99 7 3 58 0.394 Moderate AssociationGermany 6.14 5 3 16 0.438Italy 22.00 6 3 22 0.707 Strong AssociationUSA 3.87 5 3 18 0.328Japan 19.17 7 3 58 0.407 Relatively strong associationGermany 13.33 8 3 16 0.645Italy 7.00 4 3 22 0.399USA 9.67 6 3 18 0.518Japan 18.27 7 3 58 0.397 Moderate AssociationGermany 8.67 4 3 16 0.521Italy 11.10 5 3 22 0.502 Relatively strong associationUSA 10.00 8 3 18 0.527Japan 13.82 8 3 58 0.345Germany 4.82 5 3 17 0.377Italy 11.09 4 3 22 0.502 Relatively strong associationUSA 8.13 7 3 18 0.475Japan 26.14 8 3 58 0.475 Relatively strong associationGermany 17.00 6 3 17 0.707 Strong AssociationItaly 0.41 2 3 22 0.097USA 6.40 6 3 18 0.422Japan 9.21 8 3 58 0.282Germany 9.26 4 3 17 0.522 Relatively strong associationItaly 8.29 5 3 22 0.434USA 2.87 5 3 18 0.282Japan 11.99 8 3 58 0.321Germany 3.62 6 3 17 0.326Italy 12.86 5 3 22 0.541 Relatively strong associationUSA 15.00 8 3 18 0.645 Strong AssociationJapan 32.30 8 3 58 0.528 Relatively strong associationGermany 5.67 6 3 18 0.397Italy 22.00 4 3 22 0.707 Strong AssociationUSA 9.20 6 3 18 0.506Japan 13.88 8 3 56 0.352Germany 5.82 6 3 33 0.297Italy 6.56 5 3 35 0.306USA 6.74 8 3 14 0.491Japan 9.34 8 3 56 0.289Germany 24.60 6 3 33 0.611 Strong AssociationItaly 6.58 5 3 35 0.307USA 11.10 7 3 14 0.630Japan 7.42 6 3 58 0.253Germany 1.95 2 3 17 0.239Italy 5.56 4 3 25 0.333USA 8.00 5 3 18 0.471Japan 8.58 6 3 53 0.285Germany 7.12 7 3 51 0.264Italy 7.12 7 3 51 0.264USA 5.25 6 3 13 0.449Japan 29.45 8 3 55 0.517 Relatively strong associationGermany 12.95 7 3 52 0.353Italy 12.95 7 3 52 0.353USA 6.74 5 3 14 0.491Japan 23.44 8 3 54 0.466 Relatively strong associationGermany 17.35 7 3 55 0.397 Moderate AssociationItaly 17.35 7 3 55 0.397 Moderate AssociationUSA 9.77 7 3 17 0.536
* criteria based on Rea, Parker Reference [95], page 186 - Critical Values of the Chi-Square Distribution** criteria based on Rea, Parker Reference [95], page 189 - Interpretation of Calculated Cramer's V
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HE3 49 / 50
48 / 50
HD1
HD2
HD3
HE1
HC1
HC2
HC3
HC3
HB3
HB3
HB3
HB4
HB2
HB2
HB2
HB3
HB1 20 / 24
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HB2 12 / 24
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4.2.2.2 ANOVA Confirmation by Survey Question
Results obtained from our analysis using MiniTab® are documented in Appendix C
under the heading ANOVA Raw Data. Our final analysis results, as well as
Hypotheses disposition and discussion, are shown in the following section and in
tabulated form.
4.2.3 Analysis Summary
Based on our results and subsequent analysis including the Correlational, and
ANOVA analysis performed in MiniTab® we can establish a relational model once
we establish and conclude a final disposition on our Hypotheses; please refer to
summary Tables 4-24, 4-2, and 4-26, as well as Appendix C for ANOVA results.
We had previously established the following construct for which we now establish
the model based on our results.
Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +
…. …. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e
where fcc is the function for the corporate culture set, fnc is the function for the
national culture set, and so on. Because not all models can be ideally perfect, we
also include an error term e.
182
Table 4-25 : Analysis Results Summary and Hypotheses Disposition
Null Hypotheses ( H0... )
Associated Primary Attribs.
Pearson Correl.
r
Based on r > +/- 0.5 χ2 χ2*
.05Interpretation** of Cramer's V
Conclusion by Country
Conclusion by Set
JP -0.409 40.14 Reject Null
Reject NullReject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject NullReject Null
Reject Null
Reject Null
Reject NullReject Null
Reject NullReject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject Null
Reject NullReject Null
Reject Null
Reject Null
Reject Null Hypothesis
Reject Null Hypothesis
Reject Null Hypothesis
Reject Null Hypothesis
Reject Null Hypothesis
Reject Null Hypothesis
Reject Null Hypothesis
Reject Null Hypothesis
Reject Null Hypothesis
Relatively strong associationGR 0.597 5.24
IT 0.414 11.09 Relatively strong associationUS 0.254 7.33
JP 0.638 10.83
GR 0.188 8.97
IT 0.526 10.29
US -0.085 9.47
JP 0.360 16.46 Moderate AssociationGR 0.212 7.10
IT 0.043 13.84 Relatively strong association InconclusiveUS -0.655 13.33
JP 0.186 15.98 Moderate Association InconclusiveGR 0.000 8.30
IT -0.347 22.00 Strong AssociationUS -0.378 10.67
JP 0.048 18.46 Moderate Association InconclusiveGR 0.000 7.63
IT 0.376 10.67 Relatively strong associationUS -0.357 11.33
JP 0.525 13.82
GR 0.658 4.82
IT 0.497 11.10 Relatively strong associationUS -0.134 8.13
JP 0.340 20.06 Relatively strong associationGR -0.209 12.80 Strong Association InconclusiveIT -0.025 12.10 Relatively strong association InconclusiveUS -0.129 7.33
JP 0.242 17.99 Moderate Association InconclusiveGR 0.569 6.14
IT -0.401 22.00 Strong AssociationUS 0.335 3.87
JP 0.267 19.17 Relatively strong associationGR -0.599 13.33
IT 0.526 7.00
US -0.169 9.67
JP 0.460 18.27 Moderate AssociationGR 0.113 8.67
IT 0.572 11.10 Relatively strong associationUS -0.474 10.00
JP 0.525 13.82
GR 0.658 4.82
IT 0.495 11.09 Relatively strong association
US -0.134 8.13
JP 0.096 26.14 Relatively strong association Inconclusive
GR -0.367 17.00 Strong Association
IT 0.983 0.41
US 0.400 6.40
JP 0.532 9.21
GR 0.152 9.26 Relatively strong association Inconclusive
IT 0.329 8.29
US 0.589 2.87
JP 0.860 11.99
GR 0.622 3.62
IT 0.120 12.86 Relatively strong association InconclusiveUS -0.463 15.00 Strong AssociationJP -0.139 32.30 Relatively strong association InconclusiveGR 0.258 5.67
IT -0.234 22.00 Strong AssociationUS -0.077 9.20
JP 0.426 13.88
GR 0.681 5.82
IT 0.749 6.56
US -0.344 6.74
JP 0.874 9.34
GR -0.441 24.60 Strong Association
IT 0.774 6.58
US -0.462 11.10
JP 0.688 7.42
GR 0.832 1.95
IT 0.594 5.56
US 0.134 8.00
JP 0.591 8.58
GR 0.648 7.12
IT 0.648 7.12
US 0.174 5.25
JP 0.266 29.45 Relatively strong association InconclusiveGR 0.260 12.95
IT 0.260 12.95
US -0.087 6.74
JP 0.575 23.44 Relatively strong associationGR 0.344 17.35 Moderate Association InconclusiveIT 0.344 17.35 Moderate Association InconclusiveUS 0.600 9.77
* criteria based on Rea, Parker Reference [95], page 186 - Critical Values of the Chi-Square Distribution** criteria based on Rea, Parker Reference [95], page 189 - Interpretation of Calculated Cramer's V
Organizations focus on delivery and performance, more so than cost, recurring business, and knowledge-gain, as the key measures for project success.
Organizations DO NOT focus on delivery and performance, more so than cost, recurring business, and knowledge-gain, as the key measures for project success.
There is NO positive relationship between subsidiary employee morale and project success.
There is a positive relationship between subsidiary employee morale and project success.
There is a positive relationship between proactively conducting and managing a system for post-project reviews and lessons-learned meetings and project success.
There is NO positive relationship between proactively conducting and managing a system for post-project reviews and lessons-learned meetings and project success.
There is NO positive relationship between employees having a direct input into decisions that affect them and project success.
There is a positive relationship between employees having a direct input into decisions that affect them and project success.
There is a positive relationship between trust and knowledge transfer that occurs in both directions between headquarters and subsidiary.
There is NO positive relationship between the way technical communications are handled on a daily basis and trust.
There is NO positive relationship between how technical communication channels are modeled between subsidiary and headquarters and trust.
There is NO positive relationship between how technical communication channels are modeled between subsidiary and headquarters and establishing a truly shared meaning in succesful knowledge transfer.
There is NO positive relationship between trust and knowledge transfer that occurs in both directions between headquarters and subsidiary.
There is a positive relationship between employees having a direct input into decisions that affect them and establishing a truly shared meaning in succesful knowledge transfer.
There is NO positive relationship between employees having a direct input into decisions that affect them and establishing a truly shared meaning in succesful knowledge transfer.
There is a positive relationship between the availability of technology tools and a true spirit of cooperation / collaboration between subsidiary and headquarters.
There is NO positive relationship between the availability of technology tools and a true spirit of cooperation / collaboration between subsidiary and headquarters.
Organizations that implement a many-to-many technical communication channel model are more likely to establish and maintain a truly learning and trusting relationship.
Organizations that implement a many-to-many technical communication channel model are NOT more likely to establish and maintain a truly learning and trusting relationship.
There is a positive relationship between how technical communication channels are modeled between subsidiary and headquarters and establishing a truly shared meaning in succesful knowledge transfer.
Trust, Modified Hall Set, Language, Deg.of Feedback, Hofstede Set, Parent Dependency and Level of Integration.
Parent Dependency and Level of Integration; Degree of Hierarchical Organization; Trust; level of holdback; Degree of Social and Cultural Empathy to Parent
Parent Dependency and Level of Integration; Degree of Hierarchical Organization; Trust; level of holdback; Degree of Social and Cultural Empathy to Parent; Language; Degree of Strategic Integration
Trust; Degree of Feedback; Language; Hofstede Set;
Degree of Hierarchical Organization; Democratic vs. Autocratic
Degree of Technology Usage; Time Lag and Difference; Trust; Hofstede Set
Trust; Degree of Holdback by Subsidiary
Trust; Degree of Holdback by Parent
There is a positive relationship between how technical communication channels are modeled between subsidiary and headquarters and trust.
Delivery, Budget, Tech. Performance; Degree of Knowledge-gained & Lessons-LearnedDeg. of Hierarchical Organization; Democratic vs. Autocratic; Delivery, Budget, Tech. Perform Delivery, Budget, Tech. Performance; Deg. of Knowledge-gained & Lessons-Learned; Market Share expansion
Trust; Delivery, Budget, Tech. Performance
Degree of Social and Cultural Empathy to Parent; Delivery, Budget, Tech. Performance
Trust; Degree of Parent-Integration; Project Success Set (indirect)
Inconclusive
Associated Question
RelationshipHypotheses
There is a positive relationship between the way technical communications are handled on a daily basis and trust.
Inconclusive
Inconclusive
Inconclusive
Inconclusive
Inconclusive
Inconclusive
Inconclusive
Inconclusive
Inconclusive
Inconclusive
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HE2
HE3 49 / 50
48 / 50There is a positive relationship between parent headquarters satisfaction and project success.
There is NO positive relationship between parent headquarters satisfaction and project success.
There is NO positive relationship between parent headquarters satisfaction and subsidiary employee morale.
There is a positive relationship between parent headquarters satisfaction and subsidiary employee morale.
HD1
HD2
HD3
HE1
HC1
HC2
HC3
HC3
HB3
HB3
HB3
HB4
HB2
HB2
HB2
HB3
HB1 20 / 24
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HB2 12 / 24
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Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject Null
Fail to Reject NullFail to Reject Null
Fail to Reject Null Hypothesis
183
Once again, with the resulting analysis and results of our hypotheses testing, we
establish the appropriate influences to our model which is calculated thru
regression analysis within MiniTab®
Japan Model :
Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +
…. …. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e
Project Success(JP) = 1.79 + 0.276(JP)cc - 0.224(JP)nc + 0.276(JP)bc + 0.625(JP)ic - 0.566(JP)gt + e
German Model :
Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +
…. …. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e
Project Success(GR) = - 0.15 + 0.935(GR)cc + 1.87(GR)nc - 0.71 (GR)bc - 0.767(GR)ic - 0.116(GR)gt + e
Italy Model :
Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +
…. …. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e
Project Success(IT) = 3.89 + 2.06(IT)cc - 1.37(IT)nc + 0.478(IT)bc - 1.01(IT)ic - 0.845(IT)gt + e
Unfortunately we could not conclude anything of significance for the United States.
This is based on the fact that we did not have enough data for this subset and as is
apparent in Table 4-26, for the most part we failed to reject the Null Hypotheses
184
in regards to USA responses. Additionally our model must be further verified thru
a validation program because of the fact that there were areas were no conclusion
could be made. We feel these areas which we could not definitively establish a
conclusion regarding our Hypotheses have the potential to “water-down” or diminish
the strength of this model. However we feel confident that this is an excellent initial
theoretical construct which we had initially set out to create within the objectives of
our research. Based on the sub hypotheses analysis we reject the Null Hypotheses
and confirm that there is in fact a relationship between successful knowledge
transfer between parent and subsidiary organizational project success.
Further, qualitative, discussion is presented in Chapter 5. This is where we will
discuss further the actual attributes and their importance per the individual sets in
the model(s).
COMPOSITE Model :
Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +
….…. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + e Project Success(All) = 12.8 + 0.004(All)cc + 0.291(All)nc
- 0.053(All)bc + 0.020(All)ic - 0.790(All)gt + e
185
CHAPTER 5 – CONCLUSION
5.1 Discussion and Implications
The goal of this research was to assess the relative value of knowledge transfer
processes and their relationship to the success of international project management
teams and projects and identify attributes for success. The mathematical / quantitative
relationship was established and documented in Chapter 4. This relationship is
composed of 5 terms or what we refer to as attribute “sets” : a corporate culture
attribute set (cc); a national culture attribute set (nc); a basic communication theory
attribute set (bc); an international communication attribute set (ic); and a group / team
communication attribute set (gt). The form of the equation is shown below.
Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +
….…. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + error term
Furthermore with the relationship construct of our research that culture overall is a
function of both corporate and national cultural attributes particular to say Japanese
companies, or German companies, or rigidly hierarchical companies vs. team-oriented
organization; that communications overall is a construct of basic communication theory,
as well as international, and group / team communications; and with the concept that
knowledge transfer is in effect a construct or function of communication and culture; we
feel we have provided a good integration within our theoretical framework for which our
subsequent analysis essentially provided the weighing factors of the variables. This can
be referenced in our Variable Utilization Matrix, Table 5-1 below.
186
we get away from the analytics and discuss some of the practical implications for the
If
industry we can begin to see some real value in day-to-day potential operational process
improvements. Going from the analytics to the “practical” or going from quantitative to
qualitative we basically start looking at the individual variables which make up the sets
we described above, and which are shown in Table 5-1, and see how these (based on
responses from our survey instrument) can provide some insight within our industry.
187
One of the key areas investigated was how communication between subsidiary and
zed
iary talks to one person at headquarters
arters
d subsequent analysis on which model is best for which type of company, let
lt since
apparent discrepancy between data and real-world practice we
also
It was concluded that the one-to-one model has been optimized for those small
ls
headquarters takes place at a higher-tier level. Four models were initially conceptuali
based on real-world practice. These are :
1. one-to-one : one person at subsid
2. one-to-many : one person at subsidiary talks to many at headquarters
3. many-to-one : many persons at subsidiary talk to one person at headqu
4. many-to-many : unilateral communication across all personnel as required
The data an
alone which model is best overall, was mixed. More than 65% of Japanese companies
did not agree with a one-to-one model and more than 90% of Japanese company
respondents personally felt that this was not the best approach for a higher-tier
knowledge transfer structure. As previously mentioned this is an interesting resu
this is in fact how a good deal of Japanese companies do in fact structure their
communications and knowledge transfer systems.
In trying to identify this
finally realized the relationship not only for Japanese companies but for both German
and Italian organizations as well. The key was in several related factors such as :
company size, age, and number of expats being stationed at the subsidiary. We
investigated whether the company’s foreign expats being stationed at headquarters and
whether the company being private vs. public had an influence; but there was no such
influence based on these factors.
subsidiaries which are essentially run by a transplant from headquarters who dea
188
directly with technical matters within the large projects in question. In such cases both
explicit and tacit knowledge transfer does in fact occur very efficiently and results in an
above-average project team success rate. But, in effect, in these situations the
individual handling the transfer is also more than likely the defacto project manager of a
relatively small project team made up primarily of headquarters personnel, so therefore
not international. It is extremely difficult for such a structure to be maintained as
projects become more complex and the natural tendency is of course for the company to
expand. Therefore this model is fairly limiting and correlates to smaller company size
and limited project scope.
Similarly, Model 2 (one-to-many) is limited to smaller subsidiaries in the United States
and primarily to those that have very limited production capabilities outside their home-
country headquarters. Additionally the technical transfer conduit in this case will not be a
technically-trained engineer but will most likely be an executive level individual that has
the authority to prioritize and make requests from several areas back at headquarters.
Unfortunately in this situation there is a real danger to sub-optimize the technical
specification transfer between customer and headquarters. It was concluded that for this
type of arrangement to succeed the technological side of communication such as direct
video conferencing or face-to-face meetings amongst all parties must occur on a fairly
frequent basis in order to minimize the danger of the company not meeting project
specifications and expectations.
Model 3, stipulating many subsidiary employees communicating directly with a single
headquarters “filter” individual, on the surface may seem to provide a streamlined
approach to coordinating communication with one or more subsidiaries of a large foreign
manufacturer, however the data and the comments made during the course of the
189
research indicate that logistically this is a difficult approach in terms of workload for a
single individual at headquarters. Once again as the company grows and knowledge
transfer demands increase, the effectiveness of this approach will decrease; it is
unsustainable. Furthermore, and even though we did not investigate this concept in
great detail, we feel that in this and similar situations where the headquarters has
competing priorities between say a U.S. subsidiary and another foreign subsidiary in
China or SouthEast Asia for example, there is tendency for the headquarters to focus
more in those fast-paced growing economies even though the headquarters may be
faced with legitimate alternate areas of growth such as Latin and South America. The
data indicated that priorities (at least up to mid-2008) were in fact focused in Asia and
not the United States. We make this claim based on review of specific on-time-delivery
data. This data can be for both actual product manufactured at parent headquarters and
destined for the Americas, but for our case here we focus on on-time-delivery of
technical information from parent headquarters to U.S. subsidiary. If this
information, such as a large project proposal / quotation is done by a single individual or
is filtered thru a single individual at headquarters, on-time-delivery suffers. Response
rates have grown to several weeks in these situations and the level of service does in
fact deteriorate and leads to a morale issue in the subsidiary personnel complaining that
they can not provide adequate service to their local customers. By no stretch of the
imagination, one would also think that this would both directly and indirectly impact
project business.
Model 4, a many-to-many type of communication structure for knowledge transfer seems
to be the ideal approach favored by the majority of larger companies. A positive
correlation was analyzed and determined between this model, the personal opinion and
perspective of individuals with over 20 years experience in Project Management and
190
with larger more established companies of 500 or more employees. Furthermore we
confirmed our hypotheses that organizations that implement the many-to-many technical
communications channel model are more likely to establish and maintain a truly learning
and trusting relationship between subsidiary and parent company. This we feel is an
important finding because : (1) it enables a subsidiary to develop and mature the “right
way” and (2) it helps the parent expand globally, the “right way.” There have been
situations were a one-to-one or one-to-many filter has remained in place and,
unfortunately, adversely impacted not only the subsidiary but also the parent
organization. One specific example which relates more towards Asian rather than
European companies is in the area of language and the threat of not developing
language resources and international cross-departmental relationship because a filtered
knowledge transfer model remained in place. Perhaps the key next step (future
research) is to identify at what point in a subsidiary’s growth stage does one switch from
a one-to-one or one-to-many model to that of many-to-many structure in order to
maintain optimal operational efficiency and knowledge flow across all departments
between subsidiary and parent company.
From a national culture point of view, the research data and analysis indicated a slightly
greater tendency for Japanese as well as European companies to measure project
success in both tangible and intangible constructs. For example, delivery, price, and
performance is central to all companies but the European and Asian companies also
rated employee morale and satisfaction as a part of project success. They also agreed
that knowledge transfer is an important measure of project success as well. U.S.
companies also felt this was a factor but not to the extent of the others. Furthermore
Japanese companies seem to lead the way in terms of thinking of projects as
opportunities for further knowledge creation. This seems to confirm Nonaka and
191
Takeuchi’s [87] central theme which they presented in their text “The Knowledge-
Creating Company: How Japanese Companies Create the Dynamics of Innovation” In
his reference the concept of Knowledge Creation leading to Continuous Innovation
leading to Competitive Advantage is the key hypothesis. Although in the past 15 years
the entire idea of a Japanese miracle management system has been questioned for
various reasons outside the scope of this research, this concept that Nonaka and
Takeuchi present is valid and in fact was confirmed by a portion of our data, as stated. A
greater portion of Japanese companies place greater value on the intangibles that can
be gained thru successful projects.
As outlined in Chapter 2 Western management traditions are rooted in explicit
knowledge, that is, something clear-cut, formal, systematic. Japanese companies
however have a different understanding of knowledge based on different values and
beliefs. They do recognize the importance of explicit knowledge but to these
organizations it seems, a far more important type of knowledge is tacit knowledge.
Tacit knowledge however is “…highly personal and difficult to formalize thus making it
difficult to communicate and share with others…”[87], and, according to Nonaka and
Takeuchi, “…it includes subjective insights, intuitions, hunches and is rooted in the
individual’s experience, ideals, and values” [87]. Throughout various portions of our
data we did see a sensitivity for Japanese companies towards this sort of abstract
concept beyond the traditional ideas of project management and success.
The difficulty for Japanese companies however, we came to realize in taking a closer
look a the data, is that of language. Language falls under our international
communications attribute set and unfortunately even though it seems from a cultural and
knowledge management point of view Japanese companies may seem to have an
192
advantage as Nonaka and Takeuchi contend, their disadvantage is that in this industry
(we must qualify the statement) Japanese companies do not communicate with their
subsidiaries in an optimal manner simply because back at the parent facility their is in
fact a shortage of English speaking personnel. This also goes back to our concept of
one-to-one filtering between parent and subsidiary and the two single-multipoint variant
models. The result of this fact is that knowledge conversion, to use Nonaka and
Takeuchi’s term, between explicit and tacit, between parent and subsidiary……is
hampered and a major portion of the idea of a learning organization, even though ideally
is desired on a personal level, as is apparent from our data, in reality it is hampered.
This also relates to our data gathered on day-to-day communication and knowledge
transfer. Even though we understand that tacit knowledge may be difficult to convey by
standard means such as documentation, based on our results and analysis, an
overwhelming majority of Japanese companies (96%) indicated that they prefer written
communication over other means. We feel that this also relates to language and the fact
that writing could potentially be easier than speaking, especially when you have a 12-
hour time window between transmission as is the case between a U.S. subsidiary and a
parent in Japan. Unfortunately because of this another set of attributes can be
negatively affected. So, whereas the international communication set which includes
language can influence our model in one direction, the basic communication set in turn
may have to be adjusted say for the fact that now transmission characteristics have
changed. This of course is seen in real life when company’s rely on email versus
telephone or video conferencing.
Recently however there are initiatives within Japanese companies to greatly improve
language capabilities. Appendix E provides a representation of a multilingual process
designed to systematically translate and provide dual language capabilities that can be
193
utilized and shared between parent and subsidiary. From a technological point of view
this may not seem new at all and in fact it is not, it existed years ago, however from a
conceptual knowledge sharing, learning, trust, and communications aspect this is new
territory where parent headquarters whether in Tokyo or Berlin is actually proactively
sharing core knowledge. Unfortunately what we discovered based on our data is that
only a few companies in the industry today practice this philosophy. Again, it’s the
mentality of the organization relating language and knowledge transfer. It is not the
technology and certainly it should not be …….“how many expats can I place at my
subsidiaries to establish a suboptimal knowledge transfer and communication structure.”
The reason we go to such a great detail in our comments regarding this aspect is
because our analysis did in fact reveal a relationship between both organizational and
national culture and knowledge transfer and to a certain extent we confirmed some of
the basic concepts established by Davenport and Prusak [31]. Additionally such
interaction also starts to involve trust which we will discuss below, but suffice it to say
that it is an important component of the overall system under consideration. In fact trust
was a significant factor involved with knowledge transfer and with us rejecting the
specific null sub hypotheses in both Japanese and German companies.
As for utilizing technology tools for optimal communication and as a conduit for
knowledge transfer, unfortunately the majority in the industry regardless of company size,
or any other significant variables, rated low in the use of such technology with the
exception of German companies who based on the data seem to have embraced
technology to a greater extent compared to their counterparts. Also, survey respondents
preferred these tools but the companies themselves, again with the exception of
Germany, utilized them in a very limited manner. Although we did not delve into the
194
details, a potential future research opportunity could be to what extent does this
technology contribute to knowledge transfer.
Regarding morale and project success our results were mixed and inconclusive.
Although we could reject the null hypotheses and establish a relationship between
morale and project success, we could not fulfill the overall construct and expand it to
parent headquarters satisfaction and project success (failed to reject the null
hypotheses) and closing the circle with the final portion of parent headquarters
satisfaction and subsidiary employee morale (inconclusive). This can also be considered
an interesting area for future research – namely the relationship between subsidiary
employee morale, parent headquarters level of satisfaction, and project success,
and the interaction among these variables.
Suggested Operational Process Improvements Based on our Research :
Project success for the target companies tends to focus on delivery, meeting
performance requirements, and cost; in that order. Because of the nature in this
industry for headquarters to supply critical engineering information as well as
core and auxiliary products, it seems on-time-delivery (schedule) is the major
factor. Although data was not specifically collected on the reasons for delivery
being the critical factor, it is inferred that competing priorities at headquarters is
the main reason. It is recommended that companies either address the
underlying issues involved or place resources and emphasis on meeting
on-time delivery.
Smaller companies favor single-points of contact but realize their limitations with
both company growth as well as optimal project success. Larger more
established companies have successfully developed unilateral many-to-many
model type communication and knowledge transfer channels. The key area
that a company needs to realize and come to understand is at what point
in its, and its subsidiary’s, maturity development do the knowledge
195
transfer channels change in order to maintain operational efficiency,
otherwise there will be a deterioration in operations.
European companies seem to be leading Asian companies in successfully
transferring their knowledge from headquarters to subsidiary. An important part
of this is language and the fact that over 85% of the European companies
studied conduct their international business in English thus complimenting the
many-to-many model (Model 4) of knowledge transfer by not requiring
headquarters expats at the subsidiary to act as filters; something that Asian
companies have done in the past but recently are starting to migrate away from
this practice in a similar approach to the Europeans. According to the August
2008 issue of Talent Management Journal 25% of the world’s population
speaks English, it’s the official language of 50+ countries, 1 billion people are
learning English today and according to the British Council this number will
double by 2015. Establish English as a common business language in
order to facilitate communications and knowledge transfer.
Although realizing the potential for technology tool such as video conferencing
and other collaboration software, there was no significant use of such
technology (with the exception of the Germans) to further alleviate and
expedite knowledge transfer between headquarters and subsidiary. This is
indicative of the industry overall. Companies in this industry need to embrace
knowledge transfer and communication tools in order to stay competitive in an
increasingly global economy. There is a tendency for these companies to focus
on core business of machining steel and making machinery and not be
concerned with technology such as internet, video, collaboration software, etc.
It is recommended to invest in technological infrastructure to facilitate
communications and thus knowledge transfer.
There is an indication that there is a hold-back of certain knowledge and
product technology that does in fact take place between headquarters and
subsidiary (both ways). Respondents indicated that this is undesirable but a
certain portion did concede thru their survey data that this does take place. In
some cases our data indicated more than 90% feel either the subsidiary or
196
headquarters is withholding information from the other ! Furthermore,
subsequent analysis did indicate that this may play a role in morale, and
certainly trust issues. Top Management in these companies need to
consider how the companies operate in relation to standing orders on
information sharing both at the subsidiary level and headquarters.
Companies also need to strengthen their unilateral communication structures
amongst all project teams and members. Having single points of contact to filter
information between subsidiary and headquarters will not suffice and is
unsustainable. The additional benefit of having Model 4 unilateral
communication and knowledge transfer lines is the continued development of
parent company headquarter employees in both language and international
business practices. An interesting idea that we would like to put forth is the
following – company executives should consider a reverse migration of
subsidiary expats TO headquarters for extensive stays. Up to now we have
been discussing Japanese nationals for example staying at the subsidiary in the
U.S. while the subsidiary is established. Perhaps we have reached a maturity
level in the industry where now American subsidiary personnel should be
systematically assigned stays in Japan to affect a change at Headquarters ?
This holds true also for European companies.
There needs to be continued development of well-structured and professional
project management education within the industry in order to develop the next
generation of project managers coordinating international teams. Very few if any
respondents indicated any sort of professional project management structure
including conducting any sort of post-project reviews or lessons learned. We
recommend to strengthen the professional project management
knowledge within these companies. More and more global competition
will require improved project management skills.
Thru this continued development of project management and international
project teams, it is hoped that some of the lingering attitudes of “us vs. them”
that still appear between a subsidiary and its headquarters in a majority of
international organizations in this industry and the manufacturing sector overall,
197
will slowly evaporate; to be replaced by improved morale and true team
cooperation. In the researchers opinion, this is inevitable, it is only a mater of
facilitating and accelerating its acceptance. This is critical because if it does not
occur it can create a sort of “death spiral” effect between headquarter levels of
satisfaction and levels of employee morale at the subsidiary. Although we could
not definitively make a conclusion on this because of its fairly complex nature,
we feel it is a major factor that affects various areas and attributes in our study.
5.2 Theoretical Construct and Future Research
Our model construct is shown below; and for our overall research we established the
composite equation shown in blue text below the model.
Proj. Success = fcc [ α, β, γ…]cc + fnc [α, β, γ…]nc + fbc [α, β, γ…]bc +
…. + fic [α, β, γ… ]ic + fgc [α, β, γ… ]gt + error term Project Success(All) = 12.8 + 0.004(All)cc + 0.291(All)nc
- 0.053(All)bc + 0.020(All)ic - 0.790(All)gt + e
Our model should be further verified thru a validation program because of the fact
that there were areas were no conclusion could be made thus leaving some
variable / attribute sets with not as much weight as others and therefore not as
much influence as they potentially could have exerted. We feel the areas which we
could not definitively establish a conclusion regarding our Hypotheses have the
slight potential to “water-down” or diminish the strength of this model to some
extent. We are confident that this effect however is minimal.
Another potential limitation is that the data collected to establish the model thru our
analysis represented the perception of various individuals, as opposed to an
198
objective measure. We compensated for this by constructing our survey in such a
way as to request : (1) information from the respondent’s company and how it
operates but also request (2) input from the respondent on how they feel
themselves regarding the same issue in most cases. Although we did not apply a
full analysis in the differences in responses, this could be a next area to investigate.
In fact the way we constructed our survey will enable us to continue to utilize the
data to further expand and conduct additional research and refinement of our
hypotheses without the need for further data collection (if conducted within a
reasonable period of time). We are planning to expand this initial research and
continue to publish refinements in the coming 8 to 12 months on a post-doctoral
level.
Overall we feel confident that this is an excellent initial theoretical construct which
we had initially set out to create within the objectives of our research. Based on the
sub hypotheses analysis we reject the Null Hypotheses and confirm that there is in
fact a relationship between successful knowledge transfer between parent
and subsidiary organizational project success.
The influence of the trust attribute does merit further research. Here it was treated
in an ancillary way and based on our results we feel that there could be more to
gain from additional investigation on how trust plays a role not only in Project
Management and Knowledge Transfer, but from an overall operational
management point of view.
We are also considering a tighter integration to the Hofstede analysis utilizing his
indices in a much more integrative way so as to be able to predict the cultural
199
component and be able to assist potential users of this work in aligning
international project teams. This can be done, we feel, fairly easily by : (1)
utilizing the eigenvalues and eigenvectors within our data analysis; and (2) either
graphically “vectorizing” the Hofstede data in an appropriate way and adding the
two, or using the indices as mentioned above and mathematically establishing an
improved project team model.
Ultimately we would like to code our research methodology into a program that
could provide a computer-based approach for predicting project success within
the industry; perhaps even commercializing this if practical.
200
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Appendices
APPENDIX A : Hofstede Summary & Relational Mapping……………………. 210
APPENDIX B : Survey Instrument………………………………………………. 212
APPENDIX C : Survey Raw & Supplemental Data……………………………. 229
APPENDIX D : Illustrative Example Case……………………………………… 250
APPENDIX E : Sample Multilingual Documentation from the Industry……… 251
APPENDIX F : Photographs from the Industry………..............……………… 252
APPENDIX G : Comprehensive List of Gross Population…………………… 253
Appendices Have Been Omitted in this Version.
209