Master Thesis - Tom Bongers
description
Transcript of Master Thesis - Tom Bongers
Eindhoven, April 2011
BSc Industrial Engineering and Management Science — TU/e 2008
Student identity number 0634889
in partial fulfilment of the requirements for the degree of
Master of Science
in Operations Management and Logistics
Supervisors:
Dr. ir. P.A.M. Kleingeld, TU/e, HPM
Dr. T. Bipp, TU/e, HPM
Dhr. J.V. Meuldijk, Keurwerk
Critical Competencies of Self-employed Workers: Development and Validation of a Survey Instrument
by
T.H.P. Bongers
TUE. Department Industrial Engineering & Innovation Sciences
Series Master Theses Operations Management and Logistics
Subject headings: Behavior Event Interview (BEI), Competencies, Critical Incidents, Customer
satisfaction, Self-employed workers, Survey.
III
Abstract
This master thesis project investigates which competencies determine if customers will do repeated
business with self-employed workers. Behavioral Event Interviews (BEI’s) were held with customers of
self-employed workers to investigate which experiences had an impact on the customers’ satisfaction with
the self-employed worker. Next, the behavior of self-employed workers was transformed to questionnaire
items to validate the competencies that were mentioned at the BEI’s; the questionnaire was returned by
400 customers of self-employed workers. Finally, the competencies that related significant to satisfaction
were determined and used to compose a measurement instrument.
In order to increase general satisfaction, a self-employed worker is recommended to pay attention to every
mentioned competency. The four competencies that related significantly to general satisfaction were (1)
empathy, (2) customer focus, (3) enthusiasm and (4) proactive mentality. The company Keurwerk can use
these findings to provide specific advice to self-employed workers about their behavior.
IV
Preface
This master thesis project is composed at the faculty of Industrial Engineering and Innovation Sciences of
the Eindhoven University of Technology. The project is conducted in the field of Operations Management
and Logistics (OML) at the Human Performance Management (HPM) group and is the result of six
months research at the company “Keurwerk”.
I would like to use this opportunity to express my gratitude to my supervisors. This project would not
have been possible without the support of my company supervisor and founder of the project, Jan-Volkert
Meuldijk. I appreciate the time and effort he spent in the project and I would like to thank him for all the
advice. His enthusiasm and knowledge stimulated me to great efforts. Next, I want to thank Ad Kleingeld,
my first supervisor and mentor during the master thesis project. His feedback was instant, sharp and
constructive, and had a great contribution to my master thesis project. Meetings with him were always
pleasant and really helped me moving on during the project. I would also like to thank my second
supervisor Tanja Bipp for her assistance and her feedback on the final report.
I want to thank all the people I have interviewed for their time and response. Without them it was not
possible to gather different behavior about the self-employed workers. Furthermore, I would like to thank
all respondents of the quantitative questionnaire and the people who helped me with their network
increasing the response rate.
Finally, I want to thank my family and friends for their support during my study. Thanks to my friends
from university for the necessary distraction and their weekly electronic motivating messages.
Furthermore, I want to thank my girlfriend for always creating a delicate atmosphere when I came home.
Last but not least, a special word of thanks goes to my parents for their support during the entire study.
Due to their unconditional confidence, I had the opportunity to become who I am now.
Tom Bongers
Eindhoven, April 2011
V
Management summary
Context
There are various explanations why some self-employed workers are more successful than others.
According to the company Keurwerk, their success may be determined by the general satisfaction that
customers have about a self-employed worker. In this master thesis project, a validated questionnaire (i.e.
an instrument) is designed in order to investigate which particular competencies of self-employed workers
are the best predictors of general customer satisfaction.
Research objectives
The focus of the study is to measure competencies of independent self-employed workers who work in a
business to business environment. A competency is defined as a set of behaviors that influence the
achievement of specific results or outcomes (Kurz and Bartram, 2002). Although other factors (e.g. price,
quality, expertise, etc.) may also influence the general satisfaction of customers, in this research the
influences of competencies are of interest. Therefore, the following research question is answered in this
study: “Which competencies of self-employed workers significantly influence the general impression of
customers and are quantitatively measurable?”
Methodology
The methodology of the study was based on the competency study design of Spencer and Spencer (1993)
and consists of four main phases. In the first phase of the study, 22 Behavior Event Interviews (BEI’s)
were held by telephone to identify competencies that may influence the general satisfaction of customers.
In total, 314 usable Critical Incidents were identified and clustered in categories. These categories were
based on the 112 competency components of the Great Eight competency model of Bartram (2005). In the
second phase, the clustered Critical Incidents were used to compose a quantitative questionnaire in order
to validate the results of the BEI’s. Only the 89 most relevant Critical Incidents were included in the
questionnaire. Moreover, six questions about general satisfaction were obtained from literature and
formed the dependent variable. Although it was not the main goal of the study, five self-defined questions
about the price/quality of the self-employed worker were included to determine if this factor had an
influence on the dependent variable. The quantitative questionnaire was executed online in the third phase
of the study to measure the degree to which self-employed workers exhibit each competency identified in
the previous phase, as well as the “general impression”. The questionnaires were analyzed in SPSS using
hierarchical multiple regression and correlation analyses to establish which competencies were related to
the dependent variable. In the final phase of the study, the validated instrument that can be used by
Keurwerk was defined. The items that had the highest association with the outcome variable were
selected for use in this final instrument to offer an independent assessment of the competencies of self-
employed workers.
VI
Findings
In total, 400 customers of self-employed workers filled in the online questionnaire completely. After
analyzing the questionnaire, the outcome of the factor analysis was not in conformity with the
categorization that had been executed in advance. Therefore, it was decided to use the scales that were
provided by the factor analysis, rather than the predefined scales. The scales and their (in)direct
relationship with the dependent variable is depicted in Figure 1.
Figure 1: Competencies with a direct and indirect influence on general satisfaction
The correlations between the competencies of self-employed workers and general satisfaction were all
greater than .58 (significant at the .01 level), which represents a large effect. The competencies empathy
(r = .86), proactive mentality (r = .82) and enthusiasm (r = .79) were most strongly positively related to
general satisfaction. Four background variables (i.e. sector, contract duration, hired by respondent and
contact with multiple self-employed workers) were weakly associated with general satisfaction (r ≤ .11; p
< .05). A distinction was made between two sectors; the correlation analysis showed that customers from
self-employed workers working as a professional in the service industry were in general more satisfied
compared to customers from self-employed workers who worked as a specialized worker. Strikingly,
other background variables (e.g. contact frequency) did not show a significant relationship with general
satisfaction.
A hierarchical multiple regression analysis was executed to obtain the relative importance of the
competencies in the prediction of general satisfaction. The outcome showed a R² of .82 indicating that a
high amount of variance was explained by the model. The competency empathy was the strongest
predictor of general satisfaction (β = .32; p < .01). This means that if the empathy of the self-employed
worker towards the customer increases, the general satisfaction of the customer about the self-employed
worker is also likely to increase. The second strongest predictor was a proactive mentality (β = .27; p <
.01). Other significant predictors were customer focus (β = .16; p < .01), enthusiasm (β = .15; p < .01) and
the price/quality ratio (β = .08; p < .05). The regression results suggested that the other competencies did
not make a significant contribution to the prediction equation.
VII
Since not all competencies contributed significantly to the regression equitation, it was investigated if
they may demonstrate a mediating relationship with the general satisfaction. The approach posed by
Baron and Kenny (1986) was used and a mediating effect was found. As illustrated in Figure 1, the
competencies empathy, customer focus, enthusiasm and proactive mentality have a direct influence on
general satisfaction. These four competencies also mediate between four competencies (i.e. professional
appearance, process communication, availability and professional disposition) and general satisfaction.
The suggested relations were to a large degree confirmed by a more advanced Structural Equation
Modeling (SEM) analysis. Therefore, the final instrument contained questions about all eight
competencies. It was decided to include three or four questions per competency in order to prevent the
final instrument for becoming too extensive. For every competency, the means and standard deviations
were calculated based on the sample of 400, to serve as guidelines for the advice that can be provided by
Keurwerk to self-employed workers.
For both sectors (i.e. professionals in the service industry and specialized workers), a separate hierarchical
multiple regression analysis was executed to discover if there were differences in the prediction equation.
The results showed that only the competency enthusiasm was no longer a significant predictor among
professionals in the service industry; the other predictors were equal in both sectors.
Discussion
The correlation matrix indicated that all competencies correlated significantly with general satisfaction.
However, an alternative explanation is that this is due to the influence of a general evaluation on specific
judgments (Murphy, Jako and Anhalt, 1993). When a self-employed worker is rated on multiple
performance dimensions, the customer’s overall satisfaction or evaluation is thought to strongly influence
ratings of specific attributes; this phenomenon is referred to as halo effect (Murphy et al., 1993). It is
likely to assume that the halo effect has affected the results of the analyses, because all correlations were
high and there were on average no extreme differences between the competencies. Furthermore, it was
remarkable that the price/quality ratio was not the strongest predictor of general satisfaction. According to
the hierarchical multiple regression analysis, it was more important to possess the crucial competencies.
This finding emphasizes the importance of the competencies and can be used by Keurwerk to implement
the final instrument in the market.
Limitations and suggestions for future research
Besides the two sectors that are investigated in this study, also other differentiations can be made or other
self-employed workers can be investigated in order to implement the final instrument in a larger market.
The outcome of the analyses suggested that the halo effect had a large influence on the results. The
influence can be further investigated and can also be compared to the influence of a halo effect in other
studies.
VIII
Table of Contents
Abstract .......................................................................................................................................... III
Preface ........................................................................................................................................... IV
Management summary .................................................................................................................... V
List of Figures ................................................................................................................................. X
List of Tables .................................................................................................................................. X
1 Introduction .............................................................................................................................. 1
2 The research setting ................................................................................................................. 2
2.1 The company Keurwerk ................................................................................................... 2
2.2 Origin of the problem ....................................................................................................... 2
2.3 Defining the Self-employed workers ............................................................................... 4
2.4 The Great Eight competency model ................................................................................. 7
2.5 Research objectives .......................................................................................................... 9
3 Definition ............................................................................................................................... 11
3.1 Methodology for collecting the Critical Incidents ......................................................... 11
3.2 Application of BEI in this study .................................................................................... 12
3.3 Outcome of the BEI’s beyond boundaries of MTP ........................................................ 14
4 Identification .......................................................................................................................... 15
4.1 Categorization methodology including reliability and validity check ........................... 15
4.2 Application of CI’s in this study .................................................................................... 16
4.3 Including CI’s in questionnaire ...................................................................................... 16
4.4 Process from BEI to questionnaire ................................................................................. 19
4.5 Composition of the questionnaire .................................................................................. 21
4.6 Hypotheses ..................................................................................................................... 22
5 Validation ............................................................................................................................... 23
5.1 Data collection ............................................................................................................... 23
5.2 Examining the data ........................................................................................................ 24
5.2.1 Missing data, outliers and descriptive statistics ..................................................... 24
5.2.2 Normality and Linearity ......................................................................................... 25
5.2.3 Factor analysis and reliability of the scales ............................................................ 25
5.2.4 Definition of the scales .......................................................................................... 27
5.3 Results ............................................................................................................................ 29
5.3.1 Inter correlations among study variables ............................................................... 29
5.3.2 Predicting general satisfaction ............................................................................... 31
5.3.3 Testing for mediating effects ................................................................................. 32
5.3.4 Explaining the relationships among the variables .................................................. 35
5.3.5 Comparison between two sectors ........................................................................... 37
5.3.6 Underlying characteristics of competencies ........................................................... 39
6 Implementation ...................................................................................................................... 43
6.1 Introduction .................................................................................................................... 43
6.2 Final instrument ............................................................................................................. 43
6.3 Recommendations for self-employed workers............................................................... 44
7 Discussion .............................................................................................................................. 48
IX
7.1 Overview of the results .................................................................................................. 48
7.2 Recommendations .......................................................................................................... 49
7.3 Limitations and suggestions for future research ............................................................ 51
7.3.1 Evaluation of the final instrument .......................................................................... 51
7.3.2 Limitations ............................................................................................................. 52
7.3.3 Suggestions for future research .............................................................................. 53
8 References .............................................................................................................................. 55
Appendix I: The Great Eight competencies ................................................................................... 59
Appendix II: BEI (in Dutch) .......................................................................................................... 61
Appendix III: Calculation of Fleiss Kappa .................................................................................... 63
Appendix IV: Final questionnaire (in Dutch) ................................................................................ 65
Appendix V: Correlation matrix of the original scales .................................................................. 66
Appendix VI: Factor Analysis ....................................................................................................... 68
Appendix VII: Sobel test for mediating mechanisms .................................................................... 71
Appendix VIII: Structural Equation Model on latent level ............................................................ 73
Appendix IX: Final instrument (in Dutch) ..................................................................................... 74
X
List of Figures
Figure 1: Competencies with a direct and indirect influence on general satisfaction ................................. VI
Figure 2: Influencing factors on maintaining the customer .......................................................................... 3
Figure 3: Relationship between behavior and the outcome variable ............................................................ 4
Figure 4: The focus of the master thesis project ........................................................................................... 6
Figure 5: Steps in the master thesis project ................................................................................................. 10
Figure 6: Planning process .......................................................................................................................... 18
Figure 7: The mediating effect .................................................................................................................... 33
Figure 8: Competencies with a direct and indirect influence on general satisfaction ................................. 33
Figure 9: The architecture model of competencies (Roe, 2002) ................................................................. 40
Figure 10: Underlying characteristics of competencies (Spencer and Spencer, 1993) ............................... 41
Figure 11: Example of a feedback graph .................................................................................................... 45
Figure 12: Random page of the final questionnaire .................................................................................... 65
Figure 13: The mediating effect .................................................................................................................. 71
List of Tables
Table 1: Self-employed workers by occupational groups (Houtman, 2006) ................................................ 6
Table 2: The Great Eight competency model (Bartram, 2005) ..................................................................... 8
Table 3: Occupation of the self-employed workers described by respondents ........................................... 13
Table 4: Interpretation of Fleiss Kappa (Landis and Koch, 1977) .............................................................. 15
Table 5: Calculated Fleiss Kappa values .................................................................................................... 16
Table 6: Categorization process .................................................................................................................. 17
Table 7: Most important competency components according to categorization ......................................... 17
Table 8: Example of the realization of a questionnaire scale ...................................................................... 20
Table 9: Independent variables including sample question ........................................................................ 26
Table 10: Pearson correlation coefficients .................................................................................................. 30
Table 11: Hierarchical multiple regression analysis ................................................................................... 32
Table 12: Testing the best mediators .......................................................................................................... 34
Table 13: Testing mediating effect with multiple mediators ...................................................................... 35
Table 14: Path coefficients and fit indices .................................................................................................. 36
Table 15: Hierarchical multiple regression analysis for professionals in the service industry ................... 37
Table 16: Hierarchical multiple regression analysis for specialized workers ............................................. 38
Table 17: Underlying characteristics of competencies ............................................................................... 42
Table 18: Means and Standard Deviations per sector ................................................................................. 44
Table 19: Relationship between stanine scores and normal distribution .................................................... 46
Table 20: Suggestions to improve Empathy ............................................................................................... 46
Table 21: Pearson correlation coefficients .................................................................................................. 66
Table 22: Regression analysis for relationship c......................................................................................... 71
Table 23: Regression analysis for relationship a......................................................................................... 71
Table 24: Regression analysis for relationship b ........................................................................................ 71
Table 25: Regression analysis for relationship c while controlling for b .................................................... 72
1
1 Introduction
A self-employed worker can deliver decent work, but if customers go to the competitor, he or she
becomes unemployed in the long run. Therefore, it is important that customers of the self-employed
worker are satisfied, in order to come back for repeated business. To emphasize the importance of
customer satisfaction, the findings of Anderson, Fornell and Lehmann (1994) supported that customer
satisfaction has a positive impact on profitability. Until now, it was unknown which factors determine
whether self-employed workers maintain their customers. This master thesis project explored
competencies that influences if customers come back to the same self-employed worker.
As a final product, the company Keurwerk wanted to have an instrument that consists of a quantitative
questionnaire that measures the competencies of a self-employed worker. After this model is filled in by
customers of the self-employed worker, Keurwerk has insights in the strong and weak points of the self-
employed workers and can give advice accordingly.
This study describes the study that leads to this final product. It starts with the research setting of the
master thesis project, including the origin of the problem, the research question and background
information about self-employed workers. Chapter three provides information about how the behavior
that may influence general satisfaction is collected. The next chapter selects the competencies that most
likely have an influence on the general satisfaction of self-employed workers. The most important
competencies were extracted with an online questionnaire, which is also explained in chapter four. All
analyses of the online questionnaire are described in chapter five. The next chapter depicts the final
instrument to measure general satisfaction of customers. Finally, chapter seven discusses the results
including limitations and suggestions for future research.
2
2 The research setting
This chapter starts with a small description of the company that initiated the master thesis project. Next,
the origin of the problem is explained and the self-employed workers are defined. Subsequently, the
research objectives are formulated including the research question. Finally, the different phases of the
study are described in order to give an overview of the steps that were executed to answer the research
question.
2.1 The company Keurwerk
The master thesis project is commissioned by Keurwerk. Keurwerk is a virtual organization, which
consists of a small number of self-employed workers. The number of self-employed workers changes
over time, but consists at the moment of a part time website developer and a communication specialist.
The initiator of Keurwerk has experience as a self-employed worker by combining expertise and
entrepreneurship. Like most other small entrepreneurs, he gained experience in entrepreneurship by trial
and error. In his opinion, there should be a way to make the process around entrepreneurship more
efficient. Therefore, the initiator of Keurwerk involved also people from other fields into his company
(i.e. marketing, ICT, communication, graphical designers, etc.) to extent the knowledge about
entrepreneurship. The goal of Keurwerk is to provide self-employed workers with a method to enhance
their entrepreneurial skills, by giving them insight in the opinion of customers about their behavior.
Keurwerk is established for this master thesis project and intends to implement the results of the master
thesis project in the market.
2.2 Origin of the problem
Some self-employed workers are more successful than others. This can have several causes, for instance
the market in which they operate, their education, expertise, knowledge, skills or their motivation to
become a self-employed worker (Boyatzis, 2008; Hoekstra and van Sluijs, 2003). Some of the success
factors are fixed in a certain field while others are subject to influences. One of the factors that can be
influenced are competencies (e.g. Boyatzis, 2008; Hoekstra and van Sluijs, 2003). In short, competencies
consist of sets of behaviors that influence the achievement of specific results or outcomes (Kurz and
Bartram, 2002; Landy and Conte, 2004). Paragraph 2.4 will discuss competencies in detail. The next
paragraph will describe the competency model that will be used to relate behaviors of self-employed
workers to competencies. Keurwerk would like to have answers to questions like for instance: which
characteristics of a self-employed worker motivate a customer to come back to the same self-employed
worker? The assumption made by Keurwerk is that the motivation of a customer to go back to the same
self-employed worker does not only depend on price or quality of the work, but also on other factors. One
of these factors is the general impression that self-employed workers leave. To determine the general
impression of customers about self-employed workers, the general satisfaction of customers will be
measured; therefore, the terms impression and satisfaction are used interchangeably throughout the study.
The main goal of the master thesis project is to establish which way of doing business is most profitable
for the self-employed worker, in terms of maintaining the customer. Figure 2 depicts some factors that
may have an influence on maintaining the customer.
3
Within the master thesis project, the general
satisfaction of the self-employed worker will
be the outcome variable. Keurwerk has
noticed that this is a factor in which the self-
employed worker has a lack of knowledge and
experience. A proven method to establish
what the determinants of a general impression
are is by making use of competencies (e.g.
Bartram, 2005; Woodruffe, 1993).
Figure 2: Influencing factors on maintaining the customer
Figure 3 depicts graphically the relationship between behavior and the outcome variable of the master
thesis project, which is the general impression of the self-employed worker. Individual differences are
related to behavior of self-employed workers and can be divided in three main fields: ability (i.e.
cognitive- and physical ability), motivation and personality (O’Reilly and Chatman, 1994).
The colored dots in Figure 3 represent different behaviors. In the first phase of the master thesis project, it
will be investigated which behaviors are exhibited by self-employed workers in their interaction with
customers. Some of these behaviors are related to competencies. The double arrow represents a two sided
effect. In other words, the specific competencies are also related to behavior. In the second phase, it will
be investigated which competencies are recognized by customers. Consequently, these competencies
relate to the general impression of self-employed workers. Not every behavior of the self-employed
worker is observed by the customers. This is visualized in Figure 3 by the decreasing amount of colored
dots. If the general impression is positive, the customers are satisfied and there is an increased probability
that they will do repeated business with the self-employed worker. On the other hand, if the customer is
dissatisfied, the self-employed worker should change his behavior in order to leave a good impression.
Maintaining the customer
Price Quality
Other
factors
General
impression
4
Individual
differences
PersonalityAbility
Behavior of a self-employed worker
General satisfaction
Dissatisfied
customer
Satisfied
customer
Using the self-employed worker
again
Phase 1
Phase 2
Interpreted behavior by customers
Competencies
Motivation
Figure 3: Relationship between behavior and the outcome variable
2.3 Defining the Self-employed workers
Because the goal of the master thesis project is to obtain more insight in the functioning of self-employed
workers, this paragraph provides more information about these kinds of workers. Connelly and Gallagher
(2004) defined two main work arrangements which account for most workers. The first one is the
“normal” or “standard” work arrangement that (a) is performed full time, (b) continuous indefinitely and
(c) is performed at the “employer’s” place of business under the supervision of a manager. On the other
hand, there is a more alternative way of working which is called “contingent work”. A commonly use
definition of contingent work is: “any job in which an individual does not have an explicit or implicit
contract for long-term employment or one in which the minimum hours worked can vary in a
nonsystematic manner” (Polivka and Nardone, 1989, p. 11).
5
The group of contingent workers is not homogenous. In fact, four broad groupings of work arrangement
were defined by Connelly and Gallagher (2004) that fit into Polivka and Nardone’s (1989) definition.
These groups are graphically depicted in Figure 4. The first group is called “temporary staffing agencies”
or “temporary-help service firms”. Among the temporary-help service firms, there is an almost
universally explicit understanding that the contract has a fixed duration. A good example of such a
company who provides temporary-help services is Manpower (Connelly and Gallagher, 2004). A second
category of contingent workers is most often found in large organizations where irregular staffing
requirements result in the frequent use of workers for short-term assignments. This arrangement is called
“in-house” or “direct hire”. The difference with the previous arrangement is that the workers are now
directly hired, instead of only using the services of a temporary-help service firm. In the Netherlands, a
variation of the direct-hire arrangement is referred to as “zero-hour” contracts, where working hours are
only made available when a definite demand exists for such labor (Sparrow, 1998). The third category of
contingent workers also includes workers who are directly hired by an organization. However, the
workers are now hired based on a seasonal contract (e.g., resorts, tourism, etc.) where there is an absence
of a long-term contract. Matusik and Hill (1998) found evidence that many firms use contingent workers
as “technical experts” on important projects.
The focus of the master thesis lies on the fourth category, which consists of workers with “independent
contractor” or “contract” status. These independent contractors or “freelancers” are often defined as self-
employed workers. According to Connelly and Gallagher (2004), a key characteristic of the self-
employed worker is that they sell their services to client organizations on a fixed-term or a project basis.
The use of this kind of workers has become very visible in knowledge-based occupations, especially the
information technology (IT). Vroonhof et al. (2001) add to this key characteristic that self-employed
workers do not conduct their activities on their own initiative, but only after an order is distributed to
them. Furthermore, they do not receive a fixed salary, but get paid per assignment. In general, the self-
employed workers do not have their own company building. They operate from their home, or they are
located at the company they are working for (Vroonhof et al., 2001). Ho, Ang and Straub (2003)
discovered that companies occasionally terminate “standard” contracts of permanent workers and hire
these employee’s as self-employed workers in order to increase the flexibility.
Boheim and Muehlberger (2006) analyzed the characteristics of workers who provide work on the basis
of a civil or commercial contract, but who are dependent on or integrated into the firm for which they
work. Boheim and Muehlberger (2006, p. 2) define the dependent self-employed worker as: “workers
who provide work or perform services to other persons within the legal framework of a civil or
commercial contract, but who in fact are dependent on or integrated into the firm for which they perform
the work or provide the service in question.” These are also called “economically dependent workers”
because they are formally self-employed but depend on a single employer for their income. As depicted in
Figure 4 the focus of the master thesis project lies on the independent self-employed workers. More
information about contingent workers can be found in the literature study of Bongers (2010).
6
Figure 4: The focus of the master thesis project
Based on recent numbers of the CBS, there are approximately 708,000 self-employed workers in the
Netherlands (CBS, 2011). It is unknown how this number is distributed between dependent- and
independent self-employed workers. From now on, the term self-employed workers will be used in the
master thesis report to mention independent self-employed workers. The focus of the research is on self-
employed workers who act in the B2B market and have a higher education level. Examples of
occupations in this field are website developers, graphical designers, event organizers, actors and coaches.
The different occupational groups of the self-employed workers are listed in Table 1. Although the
information originates from 2006, the percentages give at least an indication about the distribution of self-
employed workers within occupational groups. Table 1 depicts that relatively many self-employed
workers in the Netherlands work as a craftsmen or industry worker, markets sales worker, technician,
associate professional, agricultural and fishery worker (Houtman, 2006).
Table 1: Self-employed workers by occupational groups (Houtman, 2006)
Occupational Group Percentage
Craftsmen and industry workers 13.9%
Transportation workers 1.9%
Clerks 3.7%
Trade and shop and market sales workers 15.9%
Service workers 7.7%
Health care professionals 6.6%
Educational professions 3.4%
Technicians and associate professionals 17.8%
Agricultural and fishery workers 17.6%
Managers and officials 1.1%
Other Professions 10.4%
Total 100.0%
7
2.4 The Great Eight competency model
The literature distinguishes several definitions of a competency, but there are two frequently used
definitions that also fit into the design of this study. Kurz and Bartram (2002, p. 229) define competencies
as: “A set of behaviors that are instrumental in the delivery of desired results or outcomes.” Hoekstra and
van Sluijs (2003, p. 33) define a competency as: “The ability to perform effectively in a specific task
situation or in a specific problem situation.” According to Kurz and Bartram (2002), a competency based
approached is based on measuring individual differences in terms of specific work related constructs that
are relevant to successful job performance. There are several models that describe and list competencies
(e.g. Hoekstra and van Sluijs, 2003; Kurz and Bartram, 2002; Spencer and Spencer, 1993). However, not
all models can be used for the development of an instrument to identify crucial competencies of self-
employed workers. According to Bongers (2010), the main reasons for the exclusion of competency
models for the master thesis project are:
• The competency model is not suitable for self-employed workers, because it is written for other
specialism’s (e.g. managers, service workers, etc.).
• The competency model does not include a comprehensive overview of competencies to compare
the characteristics of self-employed workers to.
• The overview of competencies is not complete.
The easiest way to relate self-employed workers’ characteristics to competencies is to compare the
characteristics with an extensive competency list. The competency model of Bartram (2005) has three
levels and describes a lot of details. This competency model is called “The Great Eight” and provides a
criterion-centric model that has emerged from factor analyses and multidimensional scaling analyses of
self- and manager ratings of workplace performance (Bartram, 2005). Because this competency model is
validated, it is likely that it has a high quality and predicts performance across a wide variety of jobs. The
model distinguishes 20 competency dimensions containing 112 component competencies at a detailed
level (see Appendix I). The titles and high-level definitions of the great eight competencies are depicted
in Table 2. Bartram (2005) showed that the Big Five of personality factors, motivation and ability
relationships relate to the Great Eight in the manner as described in Table 2. According to Bartram (2005)
the factors of the Great Eight appear to occupy a position within the work performance domain similar to
the Big Five in the personality predictor domain. With the validated model of Bartram (2005) it is also
possible to connect personality factors of self-employed workers to specific competencies. However, this
will not be part of the master thesis project.
8
Table 2: The Great Eight competency model (Bartram, 2005)
Factor Competency
domain title
Competency domain definition Big Five, motivation, and
ability relationships
1 Leading and
Deciding
Takes control and exercises leadership.
Initiates action, gives direction, and takes
responsibility.
Need for power and
control, extraversion
2 Supporting and
Cooperating
Supports others and shows respect and
positive regard for them in social situations.
Puts people first, working effectively with
individuals and teams, clients, and staff.
Behaves consistently with clear personal
values that complement those of the
organization.
Agreeableness
3 Interacting and
Presenting
Communicates and networks effectively.
Successfully persuades and influences
others. Relates to others in a confident,
relaxed manner.
Extraversion, general
mental ability
4 Analyzing and
Interpreting
Shows evidence of clear analytical
thinking. Gets to the heart of complex
problems and issues. Applies own expertise
effectively. Quickly takes on new
technology. Communicates well in writing
General mental ability,
openness to new
experience
5 Creating and
Conceptualizing
Works well in situations requiring openness
to new ideas and experiences. Seeks out
learning opportunities. Handles situations
and problems with innovation and
creativity. Thinks broadly and strategically.
Supports and drives organizational change.
Openness to new
experience, general
mental ability
6 Organizing and
Executing
Plans ahead and works in a systematic and
organized way. Follows directions and
procedures. Focuses on customer
satisfaction and delivers a quality service or
product to the agreed standards.
Conscientiousness, general
mental ability
7 Adapting and
Coping
Adapts and responds well to change.
Manages pressure effectively and copes
well with setbacks.
Emotional stability
8 Enterprising and
Performing
Focuses on results and achieving personal
work objectives. Works best when work is
related closely to results and the impact of
personal efforts is obvious. Shows an
understanding of business, commerce, and
finance. Seeks opportunities for self-
development and career advancement.
Need for achievement,
negative
agreeableness
9
2.5 Research objectives
Keurwerk would like to have a tool for self-employed workers to give them more insights in the
competencies they need to have in order to improve their general impression and to be successful. As
Figure 3 already showed, the competency on its own is not the only thing which is important in this study.
The way in which customers experience the actions of the self-employed worker is also an important
factor. For instance, a self-employed worker can try to act reliable, but customers may experience
something else. Therefore, it is important for self-employed workers that they have insight in how their
behavior is actually interpreted by customers. As a result, the first research objective is the development
and validation of an instrument to measure the crucial competencies of self-employed workers that satisfy
customers. Next, guidelines for the use of this validated instrument will be provided. The implementation
will be the main goal of Keurwerk after the master thesis project is finished.
The main research was a collaboration between the student and Keurwerk. The research question can be
formulated as:
“Which competencies of self-employed workers significantly influence the general impression of
customers and are quantitatively measurable?”
To answer the research question, the assessment process of the master thesis project is outlined in a
flowchart (see Figure 5) which is based on the competency study design of Spencer and Spencer (1993).
This flowchart can be interpreted as the framework of the master thesis project; every step is discussed in
a separate chapter.
10
Figure 5: Steps in the master thesis project
In the definition phase, Behavior Event Interviews (BEI’s) are held by telephone to identify
competencies that may influence the general satisfaction of customers. In the identification phase, the
Critical Incidents that are deduced from the BEI’s are clustered in categories. These categories are based
on the 112 competency components of the Great Eight competency model of Bartram (2005). The
clustered Critical Incidents lead to the composition of the quantitative questionnaire that validates the
results of the BEI’s. The quantitative questionnaire is executed in the validation phase to measure the
degree to which the self-employed worker exhibits each competency identified in the previous phase, as
well as the “general impression”.
Next, the outcomes of the questionnaire are analyzed in SPSS. Correlation and regression analysis are
executed to establish which competencies are related to the outcome variable (general impression of the
self-employed worker). The Implementation phase of this master thesis project is the design of the
validated instrument. The questions that have the highest association with the outcome variable are
selected to use in this final instrument. This instrument offers an independent judgment about the self-
employed worker according to his or her competencies.
11
3 Definition
This chapter is divided in three sections and provides information about how the Critical Incidents were
collected. The first section describes how the Behavioral Event Interviews (BEI’s) were executed to
identify Critical Incidents and gain insight in the customer perception after a self-employed worker had
finished his work. Next, the results were used to develop the final questionnaire about behaviors of self-
employed workers that influence the general impression of customers. The final section describes
additional information that was provided by respondents to support self-employed workers in their
customer interaction.
3.1 Methodology for collecting the Critical Incidents
In the first phase, questions were developed for the BEI. From now on, the first qualitative interview will
be called BEI to prevent confusion through mixing up terms. The in-depth BEI do not directly measure
competencies of self-employed workers, but measured the experiences of customers with the self-
employed worker. The BEI is derived from Flanagan’s (1954) Critical Incident Method (Spencer and
Spencer, 1993). Most important difference is that the Critical Incident Method identifies aspects of the
job. On the other hand, the BEI method identifies the competencies needed to do the job well (Spencer
and Spencer, 1993). Furthermore, the BEI asks people to identify and describe the most critical situations
they have encountered. The objective of the BEI is to get detailed behavioral descriptions of how a
customer thinks about the way people execute their work. The interviewer’s job is to keep pushing for
complete stories that describe the specific behaviors, thoughts, and actions that people show in actual
situations (Spencer and Spencer, 1993). Due to this interview technique also the probability to discover
unknown unknown’s increases. According to Mullins (2007), the “unk-unks” are things that people do
not know they do not know. Initially customers of self-employed workers may for instance say that they
only care about the quality of the delivered work. However, when they are describing their collaboration
with the self-employed worker, they may come to the conclusion that they also valued a smooth
collaboration. These underlying thoughts can be discovered using BEI’s.
Spencer and Spencer (1993) describe some aspects of the BEI which explains why this interview
technique outperforms the traditional interviewing method. First of all, traditional interviewing methods
are unable to identify competencies, because they ask directly to them (e.g. what is your greatest
strength?). The problem with this interviewing technique is that people do not know what their
competencies, strengths or weaknesses really are. Therefore, it is better to ask the interviewee to describe
several situations and deduct the competencies from these behavioral events. Second, the interviewee is in
traditional interviews not able to reveal their real competencies, due to leading interview questions
(Hodgson, 1987). As a result, the interviewee gives a “socially desirable” answer or an answer what they
think the interviewer wants to hear. These answers are not reliable, because they do not describe the
interviewee’s real preferences or opinions. Third, what people think or say about their competencies is not
credible, only what they actually do, in the most Critical Incidents they have faced, is to be believed
(Spencer and Spencer, 1993). This is accomplished with the BEI method, because people are asked to
describe how they actually behaved in specific incidents.
12
According to Spencer and Spencer (1993), a BEI contains five steps. Most of the interview should focus
on step 3; however, the other steps will also be explained. The questions are based on the literature about
BEI (Spencer and Spencer, 1993) and the Critical Incident Technique (Flanagan, 1954; Latham and
Wexley, 1982), but also on literature about competencies that determine the satisfaction of customers (e.g.
Rackham et al., 1996; Schaffer, 2002; Stumpf, 2009). The five steps of the BEI are briefly mentioned
below; the entire interview questions are described in Appendix II.
• Step 1: Introduction and Explanation
• Step 2: Job Responsibilities
• Step 3: Behavioral Events
• Step 4: Characteristics Needed to do the job
• Step 5: Conclusion and summary
To obtain at least 300 Critical Incidents, Latham and Wexley (1982) recommend that at least 30 people
should be interviewed.
3.2 Application of BEI in this study
The first respondents of the BEI’s were invited by a letter in which they were asked to participate in the
study. Using a snowball approach, other respondents were contacted. The questions of the BEI’s were
asked by telephone to a total of 22 customers of different self-employed workers and recorded on tape to
simplify the processing of the Critical Incidents. Confidentiality was guaranteed and only the researchers
had access to the tapes. Detailed sub questions were asked to validate if the answers are interpreted on
the right way. In addition to the BEI, a semi-standardized qualitative technique called laddering
(Reynolds and Gutman, 1988) is used to collect Critical Incidents. The laddering technique leads to deep
and focused results, because it constantly asks why a specific behavior is important (Gruber et al., 2008).
As a result, the underlying thoughts behind the answers were explored.
As explained before, to obtain a comprehensive sample of incidents, at least 30 people should be
interviewed (Latham and Wexley, 1982). However, only asking respondents about competencies while
disregarding the quality, price and content of their work, strongly limits the variation and number of
Critical Incidents. Hence, 22 customers of self-employed workers are interviewed telephonically to obtain
answers to the BEI questions that are depicted in Appendix II. Because in the last five interviews no
radical new Critical Incident categories showed up, it is likely to assume that all relevant behavior is
described by these 22 respondents. To validate this assumption, 10% of the Critical Incidents is set aside
and examined after the categorization to see if any of them describes behaviors that has not yet appeared
(Latham and Wexley, 1982).
13
Most of the respondents worked with different self-employed workers. As a result, they could describe
behavior of multiple self-employed workers. This positively affected the study, because the number of
Critical Incidents increased and the behavior of different self-employed workers was described, which
gave a more complete picture. Furthermore, the respondents were also asked to describe negative
behavior of self-employed workers. Especially if a respondent rejected the offer of the self-employed
worker, it was interesting to know the reason behind it. The 22 respondents produced a total of 525 useful
Critical Incidents. The Critical Incidents that were mentioned more than ones are combined, resulting into
a total of 314 unique items. Table 3 depicts the occupations of the self-employed workers that are
described by the respondents. Although the sample of respondents is quite diverse, their Critical Incidents
were less dispersed. A first impression of the Critical Incidents showed that there seems to be no strong
impact of occupation on the type of behavior that is valued as important. Examples of Critical Incidents
that are mentioned by respondents are discussed in chapter 4. This is realized according to the thematic
analysis of Spencer and Spencer (1993). The thematic analysis is the process of identifying themes or
patterns in raw data (Spencer and Spencer, 1993). This means that all the Critical Incidents are filtered out
of the BEI and all statements made during the interviews are examined and converted into items
describing only one issue (Vliegen et al., 2010).
Table 3: Occupation of the self-employed workers described by respondents
Occupation of the self-employed worker Number of respondents Percentage
Website developer 8 17.5%
Graphical designer 6 13%
Actor 5 10.9%
Photographer 5 10,9%
Trainer 5 10,9%
Coach 3 6.5%
Event organizer 2 4.3%
Interim manager 2 4.3%
Photo reviser 2 4.3%
Teacher 2 4.3%
Text writer 2 4.3%
Advisor 1 2.2%
Artist 1 2.2%
Career mentor 1 2.2%
Plumber 1 2.2%
Total 46* 100% *This number is higher than 22 because some respondents described behavior of multiple self-employed workers.
The target group for executing the master thesis project is defined by some aspects. First of all, the self-
employed worker should have the ability and the knowledge to enhance his or her daily work.
Furthermore, he or she should be willing to evaluate his or her functioning. It is likely to assume that
these are self-employed workers with a higher education. Secondly, customers should be willing to
evaluate the self-employed workers. This means that the customers should have close ties or a business
connection with the self-employed worker; otherwise they are not able to give a fair opinion. Because the
customer did business with the self-employed worker, it is likely to assume that their knowledge about the
self-employed worker is good enough to participate in the questionnaire. Thirdly, it is assumed that the
study will have the biggest impact in a business to business (B2B) relationship.
14
3.3 Outcome of the BEI’s beyond boundaries of MTP
During the interviews, many behaviors with respect to the content of the occupation were mentioned by
the respondents. Although these Critical Incidents are not part of the master thesis project, they are now
mentioned briefly because they are assumed to play an important role in the general satisfaction of
customers. Furthermore, additional information given by the respondents that is not related to general
customer satisfaction, but can improve the development of self-employed workers will also be mentioned
in this section.
According to almost all respondents, the most important characteristic of a self-employed worker should
be his knowledge about the subject. Self-employed workers are hired by customers due to their ability in a
specific field. Therefore, they have to show that they possess all the skills, expertise and capabilities to
perform well. Furthermore, there should be a clear difference between being a self-employed worker or
an employee. For instance, some self-employed workers require their customers to pay for additional skill
training. This demand would have been justified if they worked as an employee for a fixed salary.
However, self-employed workers made the choice to become independent which also includes keeping
their own knowledge on the desired level. Finally, some customers demand explicitly for a registration at
the chamber of commerce.
Some of the respondents work in a large company as an intermediary and hire self-employed workers to
work for their customers. Hiring self-employed workers to work for one’s customers exposes the risk that
the self-employed worker takes over the customer. This seriously harms the relationship between the
intermediary and the self-employed worker. As a result, the self-employed worker is strongly advised to
communicate with their customers via the intermediary about prices or other intimate information.
Furthermore, the intermediary entrusts the self-employed worker with his customers. Therefore, a good
business relationship between the customers and the self-employed worker will also be appreciated by the
intermediary.
Since self-employed workers do not have employees, valuable information about projects may be lost if
the self-employed worker is involved in for instance a serious car accident. In that case, some respondents
of the interviews mentioned that they appreciated the fact that they have their own access to relevant
project information.
In case a self-employed worker has multiple customers, the customers appreciate it when the self-
employed worker does not talk about them to competitors. Respondents of the interviews also recommend
self-employed workers not to inform them about competitors, because this can harm the mutual
confidence. Finally, the respondents gave some additional advice to self-employed workers, and
recommend them to:
• Build a network, so self-employed workers can acquire their own customers
• Have some good references, so customers know who they are working with.
• Define a Unique Selling Point (USP), so the self-employed worker distinguishes from
competitors.
• Know other self-employed workers with competencies beyond their own. When outsourcing
work to them, chances increase that they also outsource work to you.
4 Identification
In this phase, the Critical Incidents that are deduced from the BEI
categories. Based on the categorization and the frequency the CI are mentioned by customers, it is
decided which categories to include in the questionnaire.
the outcome of the questionnaire.
4.1 Categorization methodology including
Categorizing CI’s in one of the competency components means that
CI’s in the competency component that has the highest overlap with respect to content. In this
categorization process it was not allowed to classify a CI in multiple competency components.
reliability of the categorization is assessed by establishing the inter
statistical measure for calculating inter
can be defined as: (P – Pe) / (1 – Pe).
above chance, and (P – Pe) gives the degree of agreement actually achieved above chance. However,
Cohen’s kappa measures agreement between two raters only. Therefore, Fleiss kappa
similar measure of agreement, because there
calculation of Fleiss kappa, including the formulas that
and Koch (1977) formulated guidelines to interpret
Table 4: Interpretation of Fleiss Kappa (Landis and Koch, 1977)
Interpretation
<0 Poor agreement
0.0 – 0.20 Slight agreement
0.21 – 0.40 Fair agreement
0.41 – 0.60 Moderate agreement
0.61 – 0.80 Substantial agreement
0.81 – 1.00 Almost perfect agreement
The degree to which the items constitute a representative sample of the competencies that are related to
the general impression of self-employed workers (i.e. the content validity of the categorization) is verified
by categorizing the 10% that was initiall
to be met in order to conclude that the categorization was valid (Latham and Wexley, 1982):
• It was not allowed to create new categories.
• No more than two new behavioral items under an existing category
If these conditions are not met, new BEI should be organized, because apparently not all important
Critical Incidents have been collected (
discussed in the next section.
15
In this phase, the Critical Incidents that are deduced from the BEI are analyzed and
. Based on the categorization and the frequency the CI are mentioned by customers, it is
decided which categories to include in the questionnaire. Finally, hypotheses were formulated to predict
methodology including reliability and validity check
Categorizing CI’s in one of the competency components means that an individual categorizer
CI’s in the competency component that has the highest overlap with respect to content. In this
gorization process it was not allowed to classify a CI in multiple competency components.
reliability of the categorization is assessed by establishing the inter-rater agreement (Cohen, 1960). A
statistical measure for calculating inter-rater agreement is Cohen’s Kappa (Cohen, 1960). The kappa (
Pe). The factor (1–Pe) gives the degree of agreement that is attainable
gives the degree of agreement actually achieved above chance. However,
en’s kappa measures agreement between two raters only. Therefore, Fleiss kappa
similar measure of agreement, because there were more than two raters (Fleiss,
calculation of Fleiss kappa, including the formulas that were used can be found in Appendix
and Koch (1977) formulated guidelines to interpret values. These guidelines are depicted in Table 4.
: Interpretation of Fleiss Kappa (Landis and Koch, 1977)
Moderate agreement
Substantial agreement
Almost perfect agreement
The degree to which the items constitute a representative sample of the competencies that are related to
employed workers (i.e. the content validity of the categorization) is verified
by categorizing the 10% that was initially set aside. While categorizing these 31 items, two conditions had
to be met in order to conclude that the categorization was valid (Latham and Wexley, 1982):
not allowed to create new categories.
No more than two new behavioral items under an existing category were allowed to be created.
If these conditions are not met, new BEI should be organized, because apparently not all important
Critical Incidents have been collected (Latham and Wexley, 1982). The outcome of the validity check is
analyzed and clustered in
. Based on the categorization and the frequency the CI are mentioned by customers, it is
formulated to predict
check
categorizer classifies a
CI’s in the competency component that has the highest overlap with respect to content. In this
gorization process it was not allowed to classify a CI in multiple competency components. The
rater agreement (Cohen, 1960). A
is Cohen’s Kappa (Cohen, 1960). The kappa ( ),
gives the degree of agreement that is attainable
gives the degree of agreement actually achieved above chance. However,
en’s kappa measures agreement between two raters only. Therefore, Fleiss kappa was used for a
more than two raters (Fleiss, 1971). The exact
used can be found in Appendix III. Landis
values. These guidelines are depicted in Table 4.
The degree to which the items constitute a representative sample of the competencies that are related to
employed workers (i.e. the content validity of the categorization) is verified
y set aside. While categorizing these 31 items, two conditions had
to be met in order to conclude that the categorization was valid (Latham and Wexley, 1982):
allowed to be created.
If these conditions are not met, new BEI should be organized, because apparently not all important
2). The outcome of the validity check is
16
4.2 Application of CI’s in this study
The 314 Critical Incidents were categorized by the student in one of the 112 competency components of
Bartram’s (2005) Great Eight competency model. To validate the categorization, two other independent
raters (i.e. the supervisor of Keurwerk and a graduate) were also asked to categorize the items of the
Critical Incidents. All competencies were translated accurately into Dutch, to prevent language errors and
to make the categorization process easier. The clustered competencies led to the composition of the
quantitative questionnaire that validates the results of the BEI’s.
The calculated Fleiss Kappa after the categorization of the 314 items in one of the 112 competency
components was 0.56. Furthermore, Fleiss Kappa values for the 20 competency dimension and the 8
domain competencies were calculated1. The results, which are depicted in Table 5, show that every
categorization has at least moderate agreement.
Table 5: Calculated Fleiss Kappa values
314 items Agreement
8 Competency domains 0.68 Substantial
20 competency dimensions 0.64 Substantial
112 competency components 0.56 Moderate
Although there were differences in the categorization, the most important CI’s (i.e. CI’s that are
mentioned more than three times) were almost always categorized two or more times in the same
competency component. Subsequently, there was no reason to discuss the final categorization with the
supervisor of Keurwerk and the graduate.
The conditions of the content validity check defined by Latham and Wexley (1982) were both met.
Therefore, it is most likely that a sufficient number of important Critical Incidents that determine the
satisfaction of customers were taken into account (Latham and Wexley, 1982).
4.3 Including CI’s in questionnaire
All 314 Critical Incidents are categorized into competency components by three independent raters (i.e.
the researcher, a graduate and the supervisor of Keurwerk). Table 6 depicts the categorization process of
Critical Incidents in competency component 2.1.2 “Adapting to the Team”. This competency component
is discussed in more detail in section 4.4. The other Critical Incidents are categorized in a similar way into
the competency components. The most important competency components are summarized in Table 7.
1 Because not all 314 items were included in the final questionnaire, Fleiss Kappa values were also calculated
separately for the 89 items that appeared in the questionnaire. The values are respectively 0.75, 0.73 and 0.65 for the
competency domains, competency dimensions and competency components.
17
Table 6: Categorization process
Categorizer Categorized Critical Incidents
Researcher 43 45 115 135 138 157 180 225 254 314
Graduate 43 45 115 135 138 157 180 225 254 312 313 314
Supervisor 43 115 135 157 190 216 225 314
Critical Incident numbers 135, 157, 254 and 314 were included in the questionnaire
The numbers in the table refer to the following Critical Incidents; all Critical Incidents start with the phrase: “The self-
employed worker…” 43 Fits within the organization; 45 Has a close relationship to the environment; 115 Is flexible to get
on with; 135 Is able to collaborate with other people and is able to give and receive feedback; 138 Has a well developed
corporal awareness and is aware of his non-verbal communication; 157 Is able to work in a team; 180 Is able to work in a
team, able to give feedback to customers and able to receive feedback from customers; 190 Is able to deal with other
people; 216 Shares characteristics with the customer (e.g. being informal, reliable, etc.); 225 Fits to the organization and
meets the needs of the customer; 254 Is able to collaborate and able to work together to a result; 312 Is able to adjust to
the needs of the initiator; 313 Is able to adjust to customers; 314 Is able to adjust to the customers demand.
Table 7: Most important competency components according to categorization
Competency component with
corresponding number
*Number of
items
**Number of
different CI’s
Multi-
plication
3.1.1. Building Rapport † 23 16 368
3.3.5. Projecting Credibility † 19 17 323
4.1.4. Targeting Communication † 19 15 285
2.1.7. Communicating Proactively † 18 15 270
1.1.2. Taking Responsibility † 18 14 252
8.1.2. Working Energetically and
Enthusiastically † 16 15 240
1.1.3. Acting with Confidence † 11 14 151
2.1.2. Adapting to the Team † 10 13 130
2.1.12. Developing and Communicating Self-
knowledge and Insight † 11 10 110
4.1.4. Acting on Own Initiative † 10 10 100
6.2.7. Driving Projects to Results 8 8 64
3.1.2. Networking 7 9 63
7.1.1. Adapting † 6 9 54
6.1.2. Planning 6 5 30
6.2.1. Focusing on Customer Needs and
Satisfaction 6 5 30
7.1.3. Adapting Interpersonal Style 4 5 20
4.2.1. Applying Technical Expertise 4 4 16
1.1.6. Taking Calculated Risks 5 3 15
7.2.5. Handling Criticism 4 3 12
8.2.2. Identifying Business Opportunities 4 3 12 * Number of items that are at least categorized by two raters in the same competency component.
** Number of different respondents who mentioned at least one Critical Incident that fits into the corresponding
competency component. Only items that are categorized two or three times in the same competency component are taken
into account.
† Competency component included in questionnaire
18
A minimum number of questions has been established in order to prevent the questionnaire for becoming
too long, which may limit the possible respondents for participation. After analyzing Table 7, the cut-off
score for the inclusion of the competency components in the questionnaire has been set on a minimum of
6 items and at least 9 different respondents (>40% of the respondents) who mentioned at least one Critical
Incident within the component. The fourth column of Table 7 depicts the multiplication of the previous
two columns; as a consequence of previous mentioned restrictions, a multiplication score of 54 has been
used as cut-off score. There are two competency components that have a multiplication score above the
cut-off, but were not included in the final questionnaire. The first one “Driving Projects to Results” is part
of the competency dimension “Delivering Results and Meeting Customer Expectations”, which is too
closely related to the content of the job. Because the focus of this master thesis project is on general
competencies that are beyond the content of the job, this competency component was not included in the
final questionnaire. The second competency component that is not included in the final questionnaire
despite a multiplication score above the cut-off is “Networking”. Respondents mentioned this competency
mainly as an answer to the question what characteristics they think are needed to become a successful
self-employed worker. As a result, networking is interpreted as an advice to self-employed workers and
therefore explained in section 3.3 and not included in the questionnaire. Another reason for not including
networking in the questionnaire is because this competency is basically no behavior. Networking requires
other behavior such as social- and communicative skills, which are already included in the questionnaire.
Table 7 depicts that there are nine competency components left that include multiple items and are
mentioned by different respondents, but are below the cut-off score. Besides the low cut-off score,
additional reasons for excluding these competency components from the questionnaire are:
• Planning: As can be noticed in Figure 6, the self-employed worker and customer are both
involved when an appointment is made. However, the customer is not involved in the planning
process of the appointments. The third step will be visible again for both parties. As a result, all
Critical Incidents that relate to planning are not included in the final questionnaire about general
customer satisfaction, because there are no customers involved in this process. Critical Incidents
that relate to for instance keeping the appointment can be found in the competency component
“Taking Responsibility”, so all important items are included in the next step of the project.
Making the
appointment
Planning the
appointment
Following the
appointment
Self-
employed
worker
Customer
Self-
employed
worker
Self-
employed
worker
Customer
1 2 3 Figure 6: Planning process
• Focusing on Customer Needs and Satisfaction: This competency component was not included
in the final questionnaire, because it has too much overlap with the dependent variable (i.e.
general satisfaction of customers). However, some Critical Incidents that were mentioned in this
category (e.g. being customer directed) were also mentioned in the competency component
“Building Rapport”.
19
• Adapting Interpersonal Style: Items within this competency component were too vague to
include in the final questionnaire. For instance the Critical Incidents “ability to adjust to the
principal’s profile” and “equal the principal’s customer approach” were not easy to answer for
customers of self-employed workers, especially if there is no principal involvement.
• Applying Technical Expertise: This competency component had too much overlap with
competencies relating to the content of the job. Therefore, it was excluded from the general
competencies.
• Taking Calculated Risks: The interpretation of “risks” can cause confusion among the
respondents, because it can be interpreted positively and negatively. It was excluded for that
reason.
• Handling Criticism: Some of the Critical Incidents in this competency component dealt with
feedback. However, items that are related to accepting and processing feedback were already
included in the competency component “Adapting to the Team”.
• Identifying Business Opportunities: Again, this competency component is not directly visible
by the customer. If business opportunities are identified by a self-employed worker, the outcome
(i.e. taking initiative, improving existing processes) can be criticized by the customer. Therefore,
only the items that were visible for customers are included in the final questionnaire under the
competency component “Acting on Own Initiative”
Because competency components that are included in the questionnaire contain too many Critical
Incidents to include as separate questions, only the relevant Critical Incidents that had been mentioned
three or more times were retained. If the competency component did not contain enough questions for a
reliable scale, additional relevant questions were added. Finally, the list of all relevant Critical Incidents
was checked for items that had been mentioned four or more times, but had not been included in the
questionnaire. There was one item (i.e. “listening to what I really want”) meeting this requirement. Hence,
this item was added to a questionnaire category to prevent losing relevant information.
4.4 Process from BEI to questionnaire
To illustrate the way questionnaire scales were composed from BEI statements, this section provides a
complete example of how the scale of competency component number 2.1.2. (i.e. Adapting to the Team)
was composed. The CI numbers of Table 8 correspond to the numbers that were used in Table 6. The
second column depicts statements that were mentioned by the respondents during the BEI’s. Every
statement starts with the expression: “the self-employed worker”. Each letter in the third column
represents a different respondent. Hence, the total number of different respondents contributing to this
scale was 13. The item number corresponds to the items that were classified by the three categorizers. The
CI numbers above 314 are marked with † (e.g. 373, 374 and 386) because these have a large overlap with
a certain item (in this case 135). The * marked statements were transformed to questionnaire items.
Because there were five different respondents who mentioned feedback, item 135 was included in the
questionnaire. The item was divided in a question dealing with receiving feedback and an item dealing
with giving feedback. Because item nr. 157 “being able to work in a team” had a high overlap with the
competency component; it was also included in the scale. The question was negatively formulated
because every scale needs at least one reverse-phrased item to reduce response bias (Field, 2005). The **
marked statements in Table 8 were not included in the final instrument for various reasons. CI’s 43 and
20
225 were not included because they deal with an organization and a self-employed worker is not always
working for an organization. CI’s 45, 115, 138 and 180 were too restricted because they were only
mentioned by a maximum of two respondents or the statement related too strong to an existing question.
Table 8: Example of the realization of a questionnaire scale
CI
Nr.
Statement from BEI. The self-employed worker:
Mentioned by
respondent
Item
Nr.
Transformed in
questionnaire item
43 Fits within the organization ** A - B 43 Not included
45 Has a close relationship to the
environment ** C 45 Not included
115 Is flexible to get on with ** H 115 Not included
135
Is able to collaborate with other
people and is able to give and
receive feedback *
F
135
Is open to receive
feedback
373 Gives feedback † I - J
Gives constructive
feedback to other people
374 Is able to give feedback † B - C
386 Has the ability to give adequate
feedback † F
138
Has a well developed corporal
awareness and is aware of his non-
verbal communication **
F 138 Not included
157 Is able to work in a team * C 157 Is not able to work in a
team
180
Is able to work in a team, able to
give feedback to customers and able
to receive feedback from customers
**
E - J
180 Not included
398 Is able to collaborate with other
people † E
225 Fits to the organization and meets
the needs of the customer ** A - K
225 Not included
414 Fits to the organization due to his
enthusiasm † A
254 Is able to collaborate and able to
work together to a result * D
254
Is able to come to a
good result, due to a
good collaboration 428 Is able to collaborate † F - G - H - L
429 Is able to collaborate with the
principal † I
314 Is able to adjust to the customers
demand * M 314
Is able to adjust to my
needs
Total number of different respondents
in scale 13
* Included in final instrument; ** Not included in the final instrument
† Large overlap with other items
21
4.5 Composition of the questionnaire
After the items had been categorized, the competency components with the highest multiplication score
were included in the questionnaire. This questionnaire is included in Appendix IV, and is divided in four
main parts that will now be briefly discussed.
Background variables
In the questionnaire, 10 background variables about for instance gender and age of the respondent and the
contact frequency with the self-employed worker were assessed, because they may have a confounding
effect on the results. Due to these background variables, significant differences between for instance
occupational groups may be found.
Dependent variable
Questions about the general impression of customers have been partly taken from the BEI, because in the
interview was asked explicitly for factors that determine a positive general impression. Furthermore,
existing literature (e.g. Zhang et al., 2009; Homburg et al., 2001) was examined for scales and items that
determine the satisfaction of customers. Unfortunately, all customer satisfaction questionnaires that were
found included aspects that may have an influence on the general satisfaction of customers (i.e. flexibility,
communication, collaboration, etc.) in the measure itself or questions that are related to the price and
quality of the product. The purpose of this master thesis project is to determine which behavior has the
strongest relation with general satisfaction, beyond price and quality. Therefore, it was impossible to use a
standard customer satisfaction scale from the literature. Due to the confidentiality of the final instrument,
the questions that determine the general satisfaction of customers (e.g. “I would recommend this self-
employed worker to a friend”) are added in Appendix IV. Data of this self-defined scale is measured at
the interval level, using a 5-point Likert-type scale. Respondents have been asked to indicate the extent to
which they agree or disagree with each statement (1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 =
Agree, 5 = Strongly agree).
The scale to determine general customer satisfaction consists of 6 separate items and is the most
important scale of the questionnaire. An additional separate question has been added to the questionnaire
in case the dependent variable scale is not reliable enough (i.e. low Cronbach’s Alpha). This question (i.e.
“In general, I would give the self-employed worker the following grade), is measured on a 10-point scale.
Independent variables
The questionnaire consists of fourteen scales varying from five to ten items per scale with a total number
of 95 items that are placed in a random order. The number of unique respondents who mentioned a
Critical Incident fitting in a particular scale is registered. Every scale was at least mentioned by 9 different
respondents (>40%). This is assumed to have a positive influence on the questionnaire reliability, because
otherwise the scales can be biased by talkative people (Latham and Wexley, 1982). Jansen and Joosten
(1998) give a number of guidelines concerning for instance question type and formulation of the
questions that have been taken into account while formulating the questionnaire.
As described in the previous chapter, the separate items are clustered in competency components. To
validate if the items really measure the given competency component, a factor analysis will be executed.
O’Rourke and Cappeliez (2002) recommend a minimum of three items per scale (i.e. competency
22
component). However, if an item has to be removed from a scale after the factor analysis because the item
does not measure the given competency component, the number of items per scale drops below three. To
prevent this, only scales with four or more items were included in the questionnaire. With this safety
margin, the scale would still be reliable when an item has to be deleted. The next chapter depicts all
included scales with an example question.
Price/quality questions
The purpose of the master thesis project is not to determine if the price/quality ratio of the product or
service has an influence on the general satisfaction of customers. However, it would be useful to establish
to what extent the price/quality ratio influences general satisfaction. If this is a low extent, Keurwerk can
use that information to promote the importance of the general impression. Therefore, one scale consisting
of 5 items was added at the end of the questionnaire that asks respondents to assess the price/quality ratio
(e.g. “I am satisfied with the price/quality ratio of this self-employed worker”). This scale was
deliberately placed at the end of the questionnaire and introduced with a short amount of text to make sure
that the respondents would not take the price/quality ratio into account while filling in the other questions.
4.6 Hypotheses
The BEI’s already gave an initial insight in the behavior of self-employed workers that is valued by
customers. Therefore, the first hypothesis is:
H1: All mentioned scales correlate significantly with general satisfaction of customers.
There is a difference in the frequency in which behavior is mentioned by customers of self-employed
workers. According to Table 7 in section 4.3, the six most mentioned competency components are:
Building Rapport, Projecting Credibility, Targeting Communication, Communicating Proactively, Taking
Responsibility and Working Energetically and Enthusiastically. It is likely to assume that these Critical
Incidents have the highest regression with the dependent variable. Therefore, the second hypothesis is:
H2: The competency components Building Rapport, Projecting Credibility, Targeting
Communication, Communicating Proactively, Taking Responsibility and Working Energetically and
Enthusiastically are significant predictors for general customer satisfaction.
Critical Incidents were collected from multiple respondents who did business with self-employed workers
from different fields. During the BEI’s it was already remarkable that the respondents all came up with
more or less the same Critical Incidents, independent of the self-employed workers’ occupation.
Consequently, it would also be reasonable to assume that there will be no differences in competencies that
predict general satisfaction between respondents who work with self-employed workers from different
fields. This leads to the third hypothesis:
H3: Predictors of general customer satisfaction are independent of the self-employed worker’s field.
23
5 Validation
In this phase, the quantitative questionnaire is executed to measure the degree to which the self-employed
worker exhibited each competency component identified in the previous phase, as well as the “general
impression”. In other words, the most frequently named competencies that have been found in the
identification phase are validated. The questionnaire is distributed to customers of self-employed workers,
in order to measure the competencies that are related to a good general impression to customers. Next, the
outcomes of the questionnaire are analyzed in SPSS. Correlation and regression analysis are executed to
establish which competencies relate significantly to the dependent variable (general impression of the
self-employed worker).
5.1 Data collection
Customers of the self-employed workers were approached to participate in the questionnaire. The focus of
the questionnaire was on customers who recently (i.e. in the last six months) bought something from or
retained the service of the self-employed worker. These customers could form a better picture compared
to customers who had not had contact with the self-employed worker for a longer period of time.
Furthermore, also customers who received an offer in the past, but did not hire the self-employed worker
were approached to fill in the questionnaire. The questionnaires about the self-employed workers were
executed and collected online. The possible respondents were invited by a letter sent by e-mail, in which
the study was shortly explained. Among all respondents, five gift coupons of €25 were raffled. If a
respondent did not fill in the online questionnaire within a week, a reminder was sent to remind the
respondent. Field (2005) recommends a minimum sample size of 50 +8k, where k is the number of
predictors. The previous chapter showed that the number of categories was 16. Hence, with 453
independent responses, the recommendation of Field (2005) has been met. To minimize the design effect,
only a limited number of questionnaires per single self-employed worker were collected.
Because the questionnaires were not distributed within a single company, it was a challenge to collect
enough responses. Furthermore, most questionnaires were not directly sent to customers, but first to self-
employed workers. These self-employed workers had to forward the invitation to their customers, who
should be willing to fill in the questionnaires. All these factors had a negative influence on the response
rate. Therefore, a large network has been used to approach possible respondents for filling in the
questionnaire. First, more than 10,000 e-mail addresses of self-employed workers are collected via the
Dutch Chamber of Commerce. Second, a company that executes payments for self-employed workers has
sent an invitation to their customers. Third, an author of books for self-employed workers has sent an
invitation to more than 4700 of his followers on Twitter. Fourth, LinkedIn in combination with the
personal network of the researcher and the supervisor of Keurwerk were used to find relevant
respondents. All these actions had a contribution to the recruitment of the usable respondents who filled
in the questionnaire.
24
5.2 Examining the data
Before the results of the questionnaire can be analyzed, it is necessary to verify the data, check for
missing data and outliers, check the reliability of the scales, and determine the underlying structure of
scales. Competencies that are used in the questionnaire are explained in the final section of this chapter.
5.2.1 Missing data, outliers and descriptive statistics
In total, 1051 respondents opened the questionnaire and answered at least one question. After filling in
approximately ten questions, more than 50% of the respondents closed the questionnaire; obviously, all
these cases were discarded from the analysis. If for the remaining respondents missing data was evident
on summated scales and at least 70% of the independent variables were filled in, the missing variables
were replaced by item mean using EM approach (Hair et al., 2006). In case of overall missing data over
30%, all variables of the corresponding respondent were discarded. Respondents with missing data for the
dependent variable were all deleted to avoid any artificial increase in relationships with the independent
variables (Hair et al., 2006).
Because outliers can bias and distort statistical tests, it is important to detect them and decide on retention
or deletion. Hair et al. (2006) define outliers as cases with standard scores of 4 or greater. Based on the
requirements of Hair et al. (2006), three multivariate outliers were detected and discarded from the
analysis. Furthermore, a small number of univariate outliers were detected. Based on the source of the
uniqueness and a lack of demonstrable proof indicating that they are truly aberrant and not representative
of any observations in the population, there was no reason to discard these outliers. In total, a sample of
453 respondents met the above mentioned requirements and could be used for the analysis. However,
after a closer look to the standard deviations of the individual respondents, some alarming values were
detected. 28 respondents had a standard deviation greater than one. After observing the values that were
filled in by the 28 respondents, it became clear that they filled in extreme positive as well as extreme
negative scores. Even for questions that were categorized in the same scale, their range was four. This
could be explained by the inclusion of negative formulated questions. If, for instance, a respondent filled
in mainly high scores for every question (i.e. for positive and negative formulated questions), the score of
the negative formulated questions became low after reversing. As a result, there can be concluded that
these respondents filled in a part of the questionnaire at random (i.e. without reading the question
accurately) and for that reason they are discarded from the dataset. It is also possible that respondents
filled in the questionnaire at random, but without extreme scores. In that case, their standard deviation
does not exceed the threshold value of one because only middle scores are filled in. Therefore, 25
respondents with an extremely low standard deviation were also discarded from the analysis, because
their low dispersal on the different scales could seriously disturb the analysis. Consequently, a sample of
400 respondents was used for the multivariate data analysis. Most of the participants were male (75%)
and their age ranged from 20 to 75 (M=46.6; SD=10.3). The self-employed workers were also mostly
male (88%) and were hired by the respondent in 85% of the cases. 60% of the self-employed workers
were working as a specialized worker (e.g. plumber, carpenter, mechanic, etc.), the remaining 40% of the
self-employed workers were working as a professional in the service industry (e.g. website developer,
consultant, graphical designer, etc.). In 51%, the respondents had a long lasting relationship with the self-
employed worker (i.e. more than 6 months), only 12% of the respondents worked less than a week with
the self-employed worker. In most cases (60%) the respondent and the self-employed workers had contact
25
multiple times a week. In only 6%, the contact frequency was less than once in every 6 months and 59%
of the respondents did business with multiple self-employed workers. On average, the respondents graded
the self-employed workers with 7.5 (SD =1.1) on a ten point scale.
5.2.2 Normality and Linearity
To justify the use of multivariate techniques, it is important to check assumptions before deciding which
statistical test is appropriate. The most fundamental assumption in multivariate analysis is normality (Hair
et al., 2006). This assumption was checked by kurtosis (referring to the peakedness), skewness (the
balance of the distribution) and the normal probability plot. According to Field (2005), for large samples
(200 or more) it is more important to look at the shape of the distribution visually than to calculate the
significance of the skewness and kurtosis statistics. Therefore, histograms for all variables were checked
and found to be normally distributed. Next, the data was checked for multicollinearity (i.e. predictors that
correlate too highly with each other) and because none of the predictor variables correlated very highly
(0,80 or more) no multicollinearity appeared (Field, 2005). The next assumption, homoscedasticity, refers
to the assumption that dependent variables exhibit equal levels of variance across the range of predictor
variables (Hair et al., 2006). The homoscedasticity was checked graphically and based on the patterns it
was concluded that the assumption had been met. Furthermore, the data was checked for linearity because
correlations represent only the linear association between variables (Hair et al., 2006). Based on
examination of the scatter plots, no nonlinear patterns in the data were identified.
5.2.3 Factor analysis and reliability of the scales
To define the underlying structure among the independent variables in the analysis, principal component
analysis instead of common factor analysis was applied, because the objective was to summarize the
items in a minimum number of factors for prediction purposes (Hair et al., 2006). Oblique factor rotation
was used, because this is the preferred method when the goal of the factor analysis is to obtain
theoretically meaningful factors or constructs. In contrast, orthogonal rotation extracts factors that do not
correlate, whereas oblique rotation allows factors to correlate (Hair et al., 2006). According to Hair et al.
(2006), factor loadings of ±.30 to ±.40 are minimally acceptable for practical significance at a sample size
>300. Field (2005) starts with looking at inter correlation between variables. As already indicated before,
there were no variables that did not correlate with any other variables. In the analysis, factors were
extracted when the eigenvalues exceeded 1.0 and factor loadings with an absolute value < .30 were
suppressed.
The factor analysis extracted 14 factors (in 68 iterations), which was not equal to the number of scales
that were formulated beforehand. Since all scales were self-defined, it was to be expected that not every
item would load on the corresponding factor. However, the executed factor analyses showed results that
were difficult to interpret. Only the items of the dependent variable and items of the scale about price and
quality loaded exactly on the predicted factors. All other items were distributed fairly at random
throughout the 12 remaining factors. If the original scales would be maintained, the mutual correlation
between the independent variables would be extremely high because items load on multiple factors2. Due
to the high inter correlations of the factors; no meaningful conclusions could be drawn about the relative
2 The correlation matrix of the predefined scales is depicted in Appendix V
26
importance of the factors in predicting general satisfaction. Therefore, the following transformations and
remedies were attempted to transform the factor analysis in order to reduce the mutual correlation.
• Changing the delta factor in the Oblique rotation. Increasing the delta factor allows highly
correlated factors (Field, 2005).
• Square root and logarithmic transformation of the data in order to change the distribution.
• Deleting items that load on multiple factors.
• Merging competency components that belong to the same competency dimension.
None of the remedies resulted in a substantial decrease of the mutual correlation among the predefined
scales. Therefore, a new factor analysis was executed without taking into account the predefined scales of
Bartram (2005). Since the dependent variable scale and the scale about price and quality were considered
as reliable (i.e. Cronbach’s alpha’s of respectively .92 and .88), the corresponding items were excluded
from the new factor analyses. This revised factor analysis extracted 13 factors. Three factors consisted of
only two items, which is not enough for a reliable scale. Therefore, the factor analysis was executed again
with the number of extracted factors fixed to ten. The value of the Kaiser-Meyer-Olkin measure of
sampling adequacy was .97 which indicates that patterns of correlations are relatively compact and so
factor analysis should yield distinct and reliable factors (Field, 2005). The pattern matrix of the factor
analysis is depicted in Appendix VI and shows 21 items that load on multiple factors. These items were
deleted, because they caused a high mutual correlation which negatively affected the analysis. Moreover,
items with a factor loading < .30 and scales with less than three items were also deleted from the analysis.
To prevent the final instrument for becoming too extended, items were deleted from scales with a large
number of questions. Table 9 depicts the revised scales including an example question and the degree of
consistency between the multiple measurements (Cronbach’s alpha).
Table 9: Independent variables including sample question
# Scale # items Example question The self-employed worker:
Cronbach’s α
1 Empathy 4 creates mutual trust .87
2 Customer focus 4 listens to my demands* .78
3 Professional
appearance 4 is dressed properly .76
4 Process
communication 4
communicates transparent how he/she thinks
about the project, even if he/she disagrees with me .82
5 Enthusiasm 4 is dedicated to his/her work .85
6 Availability 3 can visit me within three days if I need help .63
7 Integrity 3 is open for receiving feedback .51
8 Professional
disposition 4
takes own initiative while working on an
assignment .66
9 Not enough items to formulate a reliable scale
10 Proactive
mentality 4
contacts me if an assignment is not finished on
time .85
General satisfac-
tion (dep. var.) 6 came up to my expectations .92
Price/quality
ratio 5
I am satisfied about the price/quality ratio of this
self-employed worker .88
*This question was formulated negatively in the questionnaire
27
According to Hair et al. (2006), Cronbach’s alpha values between .6 and .7 are the lower limit of
acceptability for exploratory research. Since factor 7 has an alpha of .51 it is discarded from further
analyses. Factor nine did not contain enough items to formulate a reliable scale and was also deleted.
All in all, 31 items were retained and will be included in the final instrument. The dependent variable
scale consists of 6 items and the scale about the price/quality ratio consists of 5 items. These 11 items
were also included in the final instrument. Although the items about the dependent variable and the
price/quality ratio were not included in the factor analysis, an example question of both scales is included
in Table 9. The example question about the price/quality ratio does not start with the phrase: “the self-
employed worker”.
5.2.4 Definition of the scales
This section provides insight in the scales that were used to determine general satisfaction. Note that some
competencies overlap each other. Therefore, the descriptions are subjected to the interpretation of the
researcher. The corresponding items that are used in the final questionnaire are depicted in Appendix IX.
Empathy
By showing empathy, the perception of the customer is understood by the self-employed worker. In
addition, the own influence on customers is taken into account. Included behavior in this scale was for
instance inspiring confidence and being agreeable towards a customer in order to create a mutual
connection.
Customer focus
This competency focuses on the customer, especially during communication. It includes for instance
listening to what a customer really wants and going into the customers’ needs. Due to the customer focus,
the mutual relationship between the customer and the self-employed worker is likely to increase, because
the demands and wishes of the customer are central during the assignment.
Professional appearance
This competency does not deal with the content of the assignment, but with the appearance of the self-
employed worker. A professional appearance includes for instance proper clothing.
Process communication
Process communication includes all communication between the customer and the self-employed worker
about the process. The difference between the previous mentioned customer focus is that process
communication emphasizes on the assignment, while customer focus also takes the relationship into
account. Process communication includes for instance sharing information about the assignment in order
to exchange expectations.
Enthusiasm
The competency enthusiasm measures how dedicated a self-employed worker is towards the assignment
and the customer. This includes for instance an active and flexible attitude.
28
Availability
Availability measures if a self-employed worker is available when a customer needs him or her. When
something goes wrong with the product or service that is delivered by the self-employed workers, it
should be repaired within a short amount of time. This time aspect is the main difference between
availability and the previous mentioned competency enthusiasm.
Professional disposition
In this study, the competency professional disposition measures for instance the motivation of the self-
employed worker to finish the work and his or her working speed.
Proactive mentality
Proactive mentality has some overlap with most of the previous mentioned competencies. In this study,
proactive mentality has interfaces with for instance making concrete appointments and acting reliable.
General satisfaction (dependent variable)
The dependent variable is measured by asking customers directly how they would rate the general
satisfaction about self-employed workers. Furthermore, it is for instance asked if the contact with the self-
employed worker fulfilled the expectation of the customer and if they would recommend the self-
employed worker to other people.
Price/quality ratio
As explained before, the price/quality ratio is not a competency but it was included in the questionnaire to
establish to what extent it influences general satisfaction. This scale is for instance measured by asking
customers if they were satisfied about the price/quality ratio, or if they had the feeling they paid too much
for the services of the self-employed worker.
29
5.3 Results
The data of the quantitative questionnaire is analyzed in SPSS and the competencies that significantly
influence the general impression that is left by self-employed workers is determined. First, a correlation
matrix is showed to express the relationships between the variables. With a regression analysis will be
estimated how the value of the dependent variable (i.e. general satisfaction) will change when the value of
the independent variables (i.e. specific competencies) changes. Second, it is investigated if there is a
difference in the predictor equitation between the two sectors in which self-employed workers operate.
5.3.1 Inter correlations among study variables
Dummy variables were created for several background variables to ascertain their possible relationship
with the dependent variable. The means, standard deviations and Pearson product moment correlations of
the study variables were computed, as depicted in Table 10.
A first inspection of the correlation coefficients shows that four background variables (i.e. sector (r = -
.11), contract duration (r = .11), hired by respondent (r = -.10) and contact with multiple self-employed
workers (r = -.10)) are significantly associated at the .05 level with the general satisfaction of self-
employed workers. If a customer personally hires a self-employed worker, their general satisfaction is
higher. Furthermore, if a customer has contact with multiple self-employed workers, their general
satisfaction about a single self-employed worker is also higher. Remarkable is that the contact frequency
is not significantly associated with the general satisfaction.
Inspection of the correlations between the competencies of self-employed workers and general
satisfaction shows exclusively high correlations at the .01 level (.58 < r < .86). Since hypothesis 1 stated
that all mentioned scales correlate significantly with general satisfaction of self-employed workers, it is
empirically supported. The high mutual correlations are not unique in competency research. The
intercorrelations of Bartram’s (2005) Great Eight Competencies, which was based on > 3300 respondents,
were also relatively high (i.e. .26 < r < .61; average r = .45). Furthermore, King, Hunter and Schmidt
(1980) investigated important behavior of police officers at three points in time. This study also showed
high intercorrelations between the investigated dimensions (i.e. .33 < r < .94; average r = .67)
The competencies empathy (r = .86), proactive mentality (r = .82) and enthusiasm (r = .79) were most
strongly associated with general satisfaction. Other strong associations are customer focus, process
communication and price/quality which all had a correlation coefficient of .71. Overall, it must be noted
that the effects of the competencies on general satisfaction represent a large effect according to the
guidelines of Field (2005).
30
Table 10: Pearson correlation coefficients
#
Mean SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
1 General
satisfaction 4.12 .71 (.92)
2 Report mark 7.53 1.07 .76** (-)
3 Gender
(respondent) - - .04 0,09 (-)
4 Age 46.65 10.27 .00 -0,01 -.08 (-)
5 Gender (SEW) - - .02 0,03 .20** -.03 (-)
6 Sector - - -.11* -0,07 -.03 .10* -.30** (-)
7 Contact
duration 3.81 1.45 .11* 0,08 .01 -.01 .06 -.25** (-)
8 SEW hired by
respondent - - -.10* -0,05 .03 -.21** .19** -.19** .03 (-)
9 Contact
frequency 1.82 1.23 .03 0,02 .00 -.01 .07 -.20** .19** .17** (-)
10 Contact with
multiple SEWs - - -.10* -0,03 .05 .01 -.04 .12** -.19** .04 -.02 (-)
11 Empathy 4.09 .60 .86** .72** .06 -.01 .01 -.10* .12** -.07 .03 -.09 (.87)
12 Customer
focus 3.99 .68 .71** .64** .08 -.01 .01 -.03 .09 -.09 -.05 -.08 .66** (.78)
13 Professional
appearance 3.88 .60 .58** .50** .07 .04 .05 -.11* .09 .00 .01 -.02 .62** .52** (.76)
14 Process
communication 3.78 .62 .71** .61** .10* .00 .06 -.10* .06 -.01 .04 .04 .74** .55** .60** (.82)
15 Enthusiasm 4.11 .63 .79** .66** -.01 -.01 .02 -.11* .06 -.07 .06 -.04 .80** .63** .57** .70** (.85)
16 Availability 3.91 .59 .57** .48** .07 .01 .01 -.03 .13** -.08 -.02 -.06 .58** .48** .38** .50** .49** (.63)
17 Professional
disposition 3.89 .58 .62** .53** .09 .01 .01 -.07 .10* -.08 -.03 -.03 .66** .55** .51** .64** .62** .51** (.66)
18 Proactive
mentality 4.04 .66 .82** .67** .06 .01 .03 -.08 .05 -.07 .05 -.01 .79** .61** .56** .73** .74** .52** .60** (.85)
19 Price/Quality
ratio 3.88 .61 .71** .59** .04 .05 -.02 -.05 .14** -.16** .00 -.09 .73** .56** .45** .59** .67** .50** .60** .65** (.88)
* P < .05 (2-tailed); ** p < .01 (2-tailed)
Cronbach’s alpha values are depicted on the diagonal between brackets.
For the dummy variables: male was coded 0 and female was coded 1. Yes was coded 0 and no was coded 1. A professional in the service industry was coded 0 and a
specialized worker was coded 1. This information is necessary to interpret the direction of the effect in the correlation matrix.
31
5.3.2 Predicting general satisfaction
A hierarchical multiple regression analysis was executed to obtain the relative importance of the
competencies in the prediction of general satisfaction. Because the enter-method relies on good
theoretical reasons for including the chosen predictors (Field, 2005), this method is used to enter all
variables in the multiple regression. Step 1 contains only background variables; the other independent
variables are added in step 2.
Variance Inflation Factors (VIF) of the independent variables were checked and they all met the
guidelines formulated by Myers (1990). However, Bowerman and O’Connell (1990) suggest that an
average VIF greater than 1, may be biasing the regression model through multicollinearity. The
competencies had variance inflation factors ranging from 1.6 until 4.9; therefore, the results should be
interpreted with care. The assumption of independent errors in the regression model was assessed by the
Durbin-Watson test. According to the guidelines of Field (2005), the outcome of the test did not show
reasons for concern.
The amount of variance in the outcome explained by the model in step 1 is very low (R² = .04). Step 2
shows a R² of .82 indicating a much higher amount of variance that is explained by the model (∆R² = .78;
p < .01). The regression between background variables as predictors and general satisfaction as outcome
shows that only SEW hired by respondent makes a significant contribution (p < .05) to the prediction
equation. However, when the competencies and the price/quality ratio are included in the regression
equation, this contribution is not significant anymore. Furthermore, it was remarkable that there were no
significant differences between self-employed workers who work as a professional in the service industry
and specialized workers.
Statistically significant predictors were (mainly) found in the competencies of self-employed workers.
Table 11 depicts that empathy is the strongest predictor of general satisfaction (β = .32; p < .01). This
means that if the empathy of the self-employed worker towards the customer increases, the general
satisfaction of the customer about the self-employed worker is also likely to increase. The second
strongest predictor was a proactive mentality (β = .27; p < .01). Other significant predictors were
customer focus, enthusiasm and the price/quality ratio. The regression results suggest that the other
competencies do not make a significant contribution to the prediction equation. Hence, it was remarkable
that the price/quality ratio was not the strongest predictor of general satisfaction. According to the
hierarchical multiple regression analysis, it was more important to possess the crucial competencies. The
competency professional disposition showed a negative β coefficient. The reversed sign could be
explained by a suppression effect, which denotes instances when the “true” relationship between the
dependent and independent variable is hidden in the correlation matrix (Hair et al., 2006). Due to the
addition of competencies in the regression analyses, multicollinearity was induced and some unwanted
shared variance might be explained by the other competencies. The remaining unique variance was
explained by professional disposition which caused the negative sign. However, the negative relationship
with general satisfaction was not significant; therefore it will not be further discussed.
32
Table 11: Hierarchical multiple regression analysis
Variables B SE B β Variables B SE B β
Step 1
Step 2
Gender (respondent) .08 .08 .05
Gender (respondent) -.01 .04 -.01
Age .00 .00 -.01
Age .00 .00 .00
Gender (SEW) -.02 .12 -.01
Gender (SEW) -.01 .05 .00
Sector -.14 .08 -.10
Sector -.03 .03 -.02
Contact duration .04 .03 .08
Contact duration .00 .01 .01
SEW hired by respondent -.25 .10 -.13*
SEW hired by respondent -.05 .05 -.02
Contact frequency .01 .03 .01
Contact frequency .00 .01 .00
Contact with multiple SEWs -.10 .07 -.07
Contact with multiple SEWs -.05 .03 -.04
Empathy .38 .06 .32**
Customer focus .17 .03 .16**
Professional appearance .00 .03 .00
Process communication .03 .04 .02
Enthusiasm .17 .05 .15**
Availability .05 .03 .04
Professional disposition -.03 .04 -.03
Proactive mentality .29 .04 .27**
Price/Quality ratio .09 .04 .08*
R² .04
R² .82
Adjusted R² .02
Adjusted R² .82
∆ R² .78**
Regression F 2.07*
Regression F 104.63**
Degrees of Freedom 8 / 388
Degrees of Freedom 17 / 379
* p < .05; ** p < .01; N = 397
B = regression coefficient; SE B = standard error of regression coefficient; β = standardized regression coefficient
In sum, no background variables made a significant contribution to the prediction equation. The only
competencies that significantly relate to general satisfaction are empathy, customer focus, enthusiasm and
proactive mentality (p < .01). The price/quality ratio shows a small standardized effect size at predicting
general satisfaction (β = .08; p < .05).
Hypothesis 2 stated that the competency components Building Rapport, Projecting Credibility, Targeting
Communication, Communicating Proactively, Taking Responsibility and Working Energetically and
Enthusiastically are the best predictors for general customer satisfaction. Since the items of the
questionnaire are no longer categorized according to the Great Eight, it is impossible to confirm or reject
this hypothesis.
5.3.3 Testing for mediating effects
Since not all competencies contributed significant to the regression equitation, it is investigated if they
may have a mediating relationship with the general satisfaction. Baron and Kenny (1986) subscribed four
steps to test a mediation effect (see Figure 7). The relationships should be tested between: the independent
33
and the dependent variable (c), the independent variable and the mediator (a) and the mediator and the
dependent variable (b). If all these relationships are significant, the relationship between the independent
and the dependent variable should be tested again while controlling for the mediator (i.e. test c while
controlling for b). If the relationship (c) becomes smaller but significant, there is strong statistical
evidence for a mediating effect.
Figure 7: The mediating effect
The steps to establish mediation formulated by Baron and Kenny (1986) were executed with the
competencies professional appearance, process communication, availability and professional disposition
as independent variables and the competencies empathy, customer focus, enthusiasm and proactive
mentality as mediator. The four steps were met for all mentioned relationships which indicates that there
are mediating effects as depicted in Figure 8. In addition, a Sobel test3 is executed to check if the
mediating mechanism is significantly different than zero. The formula that is used for the Sobel test is: Z-
value � ���������������
where a and b are path coefficients and ��= standard error of a and ��= standard
error of b. Since the values were all > 1.96, the mediator carried the influence of the independent
variables to the dependent variables.
Figure 8: Competencies with a direct and indirect influence on general satisfaction
3 An example of the exact calculation of the Sobel test is included in Appendix VII.
34
Although the method of Baron and Kenny (1986) showed that empathy, customer focus, enthusiasm and
proactive mentality mediate the effect from professional appearance, process communication, availability
and professional disposition to general satisfaction, it was also tested the other way around in Table 12.
This test was executed to validate the model by showing if the competencies could also be ordered in a
different way. The left side of the table depicts the mediators and independent variables that are equal to
the model of Figure 8; the right side of the table depicts the independent variables as mediators and the
mediators as independent variables. Per mediator were four tests executed to determine the decrease of
path coefficients in path c. To summarize the effect, the average decrease in path c of the four mentioned
independent variables were calculated and depicted in Table 12. The results of the test clearly showed that
the average decrease in path coefficients in path c is larger on the left side of the table compared to the
right side, which means that a model with empathy, customer focus, enthusiasm and proactive mentality
as mediators has a better fit to the data compared to a model with professional appearance, process
communication, availability and professional disposition as mediators. All Z-values of the Sobel test were
significant at the p < .01 level, indicating a mediating mechanism that is significantly different than zero.
Table 12: Testing the best mediators
Mediator Average decrease
in path c*
Average
Z-value***
Mediator Average decrease
in path c**
Average
Z-value***
Empathy .60 13.6 Professional
appearance .11 4.7
Customer
focus .33 9.1
Process
communication .27 7.7
Enthusiasm .46 11.1 Availability .11 5.3
Proactive
mentality .49 15.6
Professional
disposition .14 5.3
* For the independent variable, the competencies professional appearance, process communication, availability and
professional disposition were used; ** For the independent variable, the competencies empathy, customer focus,
enthusiasm and proactive mentality were used; *** Significant at the p < .01 level.
Table 13 depicts the results of a test with multiple mediators. When professional appearance, process
communication, availability and professional disposition were used as mediators (right side of the table),
there was only a relatively small decrease of path coefficients in path c. On the other hand, when
empathy, customer focus, enthusiasm and proactive mentality were used as mediators (left side of the
table) the decrease of path coefficients was much larger. Moreover, in the right side of Table 13, the
mediators decreased the total effect of the independent variables to a non-significant level which indicates
full mediation. In addition, one of the conditions for testing mediation is a significant coefficient for path
b at the p < .05 level. With professional appearance, process communication, availability and professional
disposition as mediators, not all path coefficients of path b were significant. Again, this confirms the
model that is depicted in Figure 8.
35
Table 13: Testing mediating effect with multiple mediators
Independent
variable Mediators*
Decrease
in path c
Z-
value**
Independen
t variable Mediators*
Decrease
in path c
Z-
value**
Professional
appearance
Em-CF
En-PM . 68�� 14.9 Empathy
PA-PC
Av-PD . 23� 5.4
Process
communication
Em-CF
En-PM . 80�� 17.8
Customer
focus
PA-PC
Av-PD . 37� 10.8
Availability Em-CF
En-PM . 63�� 13.4 Enthusiasm
PA-PC
Av-PD . 35� 9.1
Professional
disposition
Em-CF
En-PM . 76�� 16.1
Professional
mentality
PA-PC
Av-PD . 30� 8.3
* PA = Professional appearance; PC = Process communication; Av = Availability; PD = Professional disposition; Em =
Empathy; CF = Customer focus; En = Enthusiasm; PM = Professional mentality.
** Significant at the p < .01 level; † = partial mediation; †† = full mediation
5.3.4 Explaining the relationships among the variables
The structures of the interrelationships were examined on latent variable level using Structural Equation
Modeling (SEM). Due to the SEM technique, the estimates were computed using all of the information
from all equations that made up the model (Hair et al., 2006). In other words, SEM examines a series of
dependence relationships simultaneously which is particular useful in the model of this study because
some competencies (i.e. mediators) become independent in subsequent dependence relationships. The
scale averages of the variables were used as latent variables in the model. This resulted in approximately
the same regression coefficients as depicted in Table 11.
The measurement model validity can be estimated by goodness-of-fit indices and sufficient evidence of
construct validity. According to Hair et al. (2006), reporting the χ² value and the degrees of freedom, the
CFI and the RMSEA provide sufficient unique information to evaluate a model. The χ² (chi-square) test
provides a statistical test of the difference between the observed and the estimated covariance matrices.
The degrees of freedom represent the amount of mathematical information available to estimate model
parameters. In general, χ²:df ratios on the order of 3:1 or less are associated with better-fitting models
(Hair et al., 2006). The Comparative Fit Index (CFI) is an incremental fit index that is normed so that
values range between 0 and 1, with higher values indicating better fit. CFI values higher than .90 are
usually associated with a model that fits well. The Root Mean Square Error of Approximation (RMSEA)
is an absolute fit measure that tests how well the model reproduces the observed data. Lower RMSEA
values indicate better fit and typically values are below .10 for acceptable models (Hair et al., 2006).
In a model that includes all 9 variables (see Appendix VIII), the path coefficients from the mediators to
general satisfaction are .46 for empathy, .18 for customer focus, .19 for enthusiasm and .30 for proactive
mentality (all significant at the p < .01 level). The χ² value = 330.81; df = 10; CFI = .91 and RMSEA =
.29. Total amount of variance in general satisfaction explained by the model was .79. Although the CFI
value of the model was acceptable, the other fit indices were not. Therefore, it was decided to split the
overall model into four separate models where every mediator was predicted by four competencies. Using
this approach, the main competencies for predicting the mediator could be established. The corresponding
path coefficients and fit indices are depicted in Table 14. Again, the RMSEA values were above .10,
suggesting that the model is not acceptable. However, a quite large amount of variance (i.e. between .43
and .67) in the mediators was explained by the competencies. Furthermore, the model showed that all
36
competencies were approximately equally important in predicting the mediators, because most path
coefficients of the indirect variables to the mediator had a maximum range of .10. Two indirect variables
(i.e. process communication with customer focus as mediator and availability with enthusiasm as
mediator) showed lower values compared to the other predictors, but modification indices were suggested
to improve the fit of these models. First, with customer focus as mediator, it was suggested to add the
path from process communication to general satisfaction. This path had a coefficient of .46 and decreased
the χ² value to 37.58 with 3 degrees of freedom (CFI = .97; RMSEA = .17). Since ∆χ² was 140.75 and
∆df was 1 (p < .01), the model showed significant improvement. Second, with proactive mentality as
mediator, it was suggested to add the path from availability to general satisfaction. This path had a
coefficient of .24 and decreased the χ² value to 44.44 with 3 degrees of freedom (CFI = .97; RMSEA =
.19). Since ∆χ² was 33.47 and ∆df was 1 (p < .01), this revised model also showed significant
improvement.
Table 14: Path coefficients and fit indices
* Values depict path coefficients from mediator to general satisfaction
The values of Table 14 indicate that the proposed models do not fit adequately to the data. However, this
may be declared because the models were tested on “latent level”. If the models would have been tested
by including all observed variables, it is likely to assume that the fit indices demonstrate a better fit of the
models. To amplify this assumption, the observed variables were included to test the full model again.
This resulted in a χ² value of 1238.80 with 603 degrees of freedom (p < .01), a CFI of .99 and a RMSEA
of .05. These fit indices demonstrate a good fit of the full model. Hence, the suggested model that is
depicted in Figure 8 is supported by the data. However, according to Hair et al. (2006), SEM is not used
to obtain a good fit, but to test a theory. Therefore, the above mentioned model is not necessarily the only
approach to predict general satisfaction.
Model I Model II Model III Model IV
Mediators
Empathy Customer
focus Enthusiasm
Proactive
mentality
Indirect variables
Professional appearance .21 .22 .17 .14
Process communication .39 .18 .41 .46
Availability .21 .20 .11 .16
Professional disposition .19 .22 .21 .15
General Satisfaction * .86 .71 .79 .82
Amount of variance explained in mediator
(by independent variables) .67 .43 .57 .59
Amount of variance explained in general
satisfaction (by mediator) .73 .50 .63 .67
χ² 30.86 178.32 96.83 77.91
Degrees of freedom 4 4 4 4
CFI .98 .86 .93 .95
RMSEA .13 .33 .24 .22
37
5.3.5 Comparison between two sectors
Because Keurwerk has the intention to implement the final instrument in large market, it is important to
establish if there is a difference in the crucial competencies between professionals in the service industry
and the specialized workers. For each kind of workers (i.e. 156 professionals in the service industry and
241 specialized workers), a hierarchical multiple regression is executed to discover if there are differences
in the prediction equitation. Assumptions about linearity and normally distributed errors were checked
graphically for both sectors and met the guidelines formulated by Field (2005).
Table 15: Hierarchical multiple regression analysis for professionals in the service industry
Variables B SE B β Variables B SE B β
Step 1
Step 2
Gender (respondent) .01 .13 .01
Gender (respondent) .00 .06 .00
Age .01 .01 .09
Age .00 .00 .00
Gender (SEW) -.08 .14 -.05
Gender (SEW) -.02 .06 -.01
Contact duration -.01 .05 -.02
Contact duration -.03 .02 -.05
SEW hired by respondent -.32 .14 -.20*
SEW hired by respondent -.06 .06 -.04
Contact frequency -.05 .05 -.09
Contact frequency .01 .02 .02
Contact with multiple SEWs -.09 .12 -.06
Contact with multiple SEWs -.08 .05 -.05
Empathy .44 .09 .37**
Customer focus .18 .05 .17**
Professional appearance .07 .05 .07
Process communication .04 .07 .03
Enthusiasm .11 .07 .10
Availability .01 .05 .01
Professional disposition -.03 .06 -.02
Proactive mentality .30 .07 .27**
Price/Quality ratio .07 .06 .06
R² .08
R² .85
Adjusted R² .03
Adjusted R² .83
∆R² .77**
Regression F 1.75
Regression F 49.17**
Degrees of Freedom 7 / 148
Degrees of Freedom 16 / 139
* p < .05; ** p < .01; N = 156
B = regression coefficient; SE B = standard error of regression coefficient; β = standardized regression coefficient
The hierarchical multiple regression analysis for professionals in the service industry of Table 15 shows a
large amount of consensus with Table 11. In both prediction equitation’s, no background variables have a
significant relation with the general satisfaction. The order and magnitude of the significant predictor
competencies is also comparable. However, enthusiasm is no longer a significant competency to predict
general satisfaction among professionals in the service industry.
38
Table 16: Hierarchical multiple regression analysis for specialized workers
Variable B SE B β Variable B SE B β
Step 1
Step 2
Gender (respondent) .11 .11 .07
Gender (respondent) .00 .05 .00
Age .00 .00 -.04
Age .00 .00 .00
Gender (SEW) .03 .24 .01
Gender (SEW) .01 .11 .00
Contact duration .06 .03 .13
Contact duration .02 .01 .05
SEW hired by respondent -.13 .16 -.05
SEW hired by respondent -.04 .07 -.02
Contact frequency .05 .04 .08
Contact frequency .01 .02 .01
Contact with multiple SEWs -.09 .10 -.06
Contact with multiple SEWs -.03 .04 -.02
Empathy .34 .08 .29**
Customer focus .18 .05 .17**
Professional appearance -.08 .05 -.07
Process communication .02 .06 .02
Enthusiasm .22 .07 .19**
Availability .09 .05 .07
Professional disposition -.06 .05 -.04
Proactive mentality .29 .06 .28**
Price/Quality ratio .10 .06 .09
R² .04
R² .82
Adjusted R² .01
Adjusted R² .80
∆R² .78**
Regression F 1.35
Regression F 62.35**
Degrees of Freedom 7 / 233
Degrees of Freedom 16 / 224
** p < 0.01; * p < 0.05; N = 241
B = regression coefficient; SE B = standard error of regression coefficient; β = standardized regression coefficient
Table 16 depicts the hierarchal multiple regression analysis for specialized workers. The results show
identical significant predictors for general satisfaction compared to the total sample of self-employed
workers.
Hypothesis 3 states that predictors of general customer satisfaction are independent of the self-employed
worker’s field. This hypothesis is partly rejected, because enthusiasm is not a significant predictor of
general satisfaction among professionals in the service industry. However, the predictor equitation’s show
a large amount of similarity in order and magnitude between the two groups of workers and the self-
employed workers in general. Moreover, the hierarchical multiple regression analysis with both groups of
self-employed workers (depicted in Table 11) did not show significant differences between the two
sectors.
39
5.3.6 Underlying characteristics of competencies
The results of the analyses of the previous sections showed that the competencies empathy, customer
focus, enthusiasm and proactive mentality have a direct influence on general customer satisfaction.
Furthermore, these four competencies also mediate between general satisfaction and the competencies
professional appearance, process communication, availability and professional disposition. This section
determines if there are overlapping characteristics that appear in the mediators4, but not in the
independent variables5 or vice versa.
Competency model of Bartram (2005)
Three out of the four mediators (i.e. empathy, customer focus and proactive mentality) can be categorized
in the same competency dimension (i.e. working with people) of Bartram’s (2005) great eight competency
model. The final mediator (i.e. enthusiasm) can be categorized in the competency component “working
energetically and enthusiastically”. The independent variables are more dispersed throughout the great
eight competency model. The four independent variables all fit into the definition of Kurz and Bartram
(2002) because they measure individual differences in terms of specific work related constructs that are
relevant to successful job performance. However, three independent variables (i.e. professional
appearance, availability and professional disposition) cannot be categorized into only one category of
Bartram’s (2005) great eight competency model, because the items in the independent variables are too
dispersed. Furthermore, the independent variable process communication can be categorized in the
competency dimension “presenting and communicating information”. In sum, the great eight competency
model does not contain one competency domain in which all mediators or independent variables can be
categorized. Therefore, other competency definitions and models from literature were analyzed in order to
find underlying concepts of the mediators and independent variables. The results of this analysis are
depicted in Table 17.
Competency model of Hoekstra and van Sluijs (2003)
Hoekstra and van Sluijs (2003, p. 30) defined a competency as: “The ability to perform effectively in a
specific task situation or in a specific problem situation.” They express this definition in the following
formula:
Effective performance in a situation =
[knowledge + experience + understanding] x [behavior + attention + emotion].
In other words: a competency = expertise x behavior repertoire. With behavior repertoire is meant that an
individual’s availability of behavior, attention and emotion are needed in a variety of situations. Although
expertise and behavior repertoire are both needed to define a competency, the eight self-defined
competencies in this study show more overlap with behavior repertoire. Therefore, the competency
definition of Hoekstra and van Sluijs (2003) can also not be used to find underlying concepts of the
mediators and independent variables.
4 The mediators refer in this section to the competencies empathy, customer focus, enthusiasm and proactive
mentality. 5 The independent variables refer in this section to the competencies professional appearance, process
communication, availability and professional disposition.
40
Competency model of Roe (2002)
Roe (2002, p. 206) defines a competency as: “The ability to execute a task, role or mission adequately”.
This definition has two main characteristics that deviate from other definitions. First, a concrete activity
should be accomplished to reach a result. This activity should contribute to the organizational goals and
generate value for the organization. This is a major difference with the definition of Hoekstra and van
Sluijs (2003) who state that every activity can be a competency, even general characteristics of
individuals. Second, competencies are not a synonym for knowledge or ability. According to Roe (2002),
competencies are always “integrating” with the knowledge that is learned before. This means that an
individual should merge his previously gained knowledge and ability to perform new tasks. Roe (2002)
has composed a model that indicates how competencies are related to other personality characteristics and
is depicted in Figure 9.
Figure 9: The architecture model of competencies (Roe, 2002)
The “building blocks” sub competency and competency that are depicted at the top of Figure 9 are most
relevant for this study. Sub competencies are pieces of the end competency that should be learned first.
According to Roe (2002) these sub competencies differ from competencies in a way that they are needed,
but do not contribute to organizational goals. The sub competency professional disposition is for instance
needed for several other competencies but cannot be seen as an individual competency. In Table 17, all
eight self-defined competencies are categorized into the model of Roe (2002). If the majority of the items
of a self-defined competency were not concrete activities, the self-defined competency was categorized as
a sub competency.
Competency model of Spencer and Spencer (1993)
Spencer and Spencer (1993, p. 9) define a competency as: “an underlying characteristic of an individual
that is causally related to criterion-referenced effective and/or superior performance in a job or
situation.” Most of the previous mentioned authors see knowledge, skills and ability as factors that
muddle the definition of a competency. Therefore, they agree that for superior performance knowledge,
skills and ability are needed in parallel to the competency. Spencer and Spencer (1993) define besides
41
knowledge and skills also motives, traits and self-concept as underlying characteristics for competencies.
Figure 10 depicts how these underlying characteristics relate to each other. According to Spencer and
Spencer (1993), the surface knowledge and skill competencies are easier to develop compared to the core
competencies. The self-defined competencies of Table 17 that are relatively hard to develop and also
related to personality are categorized as hidden competencies. The mediator enthusiasm deals for instance
with someone’s personality which is hard to develop. Therefore, enthusiasm was categorized as hidden
competency. In contrast, the independent variable professional disposition is relatively easier to develop;
therefore it was categorized as visible competency.
Figure 10: Underlying characteristics of competencies (Spencer and Spencer, 1993)
Overview of findings
The previous paragraphs showed that competencies are subjected to interpretation and could be defined in
multiple ways. The competency model of Hoekstra and van Sluijs (2003) did not show any differences in
underlying characteristics between the mediators and independent variables. The competency model of
Roe (2002) showed that three out of four mediators could be categorized as a sub competency. However,
also two of the independent variables could be categorized as sub competency. Therefore, this
competency model did not provide more insight in the underlying characteristics. The final competency
model that was analyzed was the competency model of Spencer and Spencer (1993). It was remarkable
that all independent variables could be categorized as visible competencies. However, also two of the
mediators could be categorized as visible competencies. Therefore, it can be concluded that the three
competency models did not provide unique underlying characteristics that distinguish between
independent variables and mediators.
42
Table 17: Underlying characteristics of competencies
Competencies
Competency models
Hoekstra and
van Sluijs (2003) Roe (2002)
Spencer and
Spencer (1993)
Behavioral Expertise Competency
Sub Visible Hidden
repertoire competency
Mediators
Empathy x
x
x
Customer focus x
x x
Enthusiasm x
x
x
Proactive mentality x
x
x
Independent variables
Professional appearance x
x x
Process communication x
x
x
Availability x
x
x
Professional disposition x
x x
In addition to the statistical proof of the relationship between the independent variables and the mediators,
some examples of the theoretical relationships will now be discussed. The examples start with aspects of
the independent variable. Next, it is discussed how this might be related to the mediator.
Example 1: availability as independent variable.
The independent variable availability contains for instance a response within 24 hours when the customer
needs it. This might increase the mediators empathy and customer focus, because the customer might feel
special due to the fast response to their problems. Moreover, availability might increase the confidence in
a self-employed worker, which also affects empathy. Furthermore, a self-employed worker who is
available might be interpreted as enthusiastic. Finally, the mediator proactive mentality contains items
that deal with making appointments and contacting the customers if an assignment is not finished on time.
It is likely that frequent available self-employed workers have a positive influence on this mediator.
Example 2: process communication as independent variable.
The independent variable process communication contains for instance discussing expectations and
exchanging information about the assignment with the customer. Due to the communication, it is likely
that the empathy increases, because communication might increase the collaboration. In addition,
customer focus might be increased because the self-employed worker listens to what a customer really
wants. A self-employed worker who communicates frequently with the customer and shares information
might be interpreted as a self-employed worker who thinks actively along with the customer. Therefore,
process communication might positively influence the mediator enthusiasm. Finally, the mediator
proactive mentality contains self-employed workers who contact the customer when an assignment is not
finished on time. The independent variable process communication might contribute to this
communication.
43
6 Implementation
The final phase of the master thesis project is the design of the validated instrument. The questions that
had the highest association with the dependent variable are selected to use in this final instrument. The
statistical instrument offers an independent judgment about the self-employed worker according to their
competencies.
6.1 Introduction
Keurwerk has the intention to formulate two different versions of the final instrument. The biggest
difference between the two is the number of respondents that will be realized. The first instrument is
called the “personal version”, and can be bought by paying a registration fee. The “personal version”
includes the questionnaire and advice about the competencies of the self-employed workers. The
respondents of the “personal version” have to be recruited by the self-employed worker. The second one
is called “professional version” and guarantees on top of the advice a certain number of respondents for
the questionnaire. The guaranteed number of respondents will be realized by making phone calls to
customers of the self-employed workers. For the professional version, customers and invoices will be
checked in order to increase the reliability of the study. By law, a self-employed worker is forced to
number all his invoices. To make sure that there is a complete overview of the sample size, all numbers
on the invoices have to be checked. According to the sequence of the numbers, it can be secured that all
relevant customers receive an invitation for the questionnaire. It is not necessary that all customers join
the questionnaire, but by knowing the whole population there is a better insight in the sample. As a result,
a validated advice can be provided and the self-employed workers can refer to this while recruiting new
customers. The “professional version” will be provided to self-employed workers for a higher registration
fee.
6.2 Final instrument
The final instrument is included in Appendix IX and is a condensed version of the questionnaire that was
sent to the customers of self-employed workers. All questions are classified per scale in the appendix,
whereas they will be asked at random to customers, to prevent respondent bias. The implementation of the
questionnaire will be realized by Keurwerk and they become the owner of the instrument.
Table 18 depicts the means and standard deviations per variable. These values can serve as guidelines for
the feedback that would be provided to self-employed workers. Statistically, 68% of the self-employed
workers should be rated ± one standard deviation from the mean. In practice, the values obtained could be
interpreted as follows: if self-employed workers “score” above the mean, there is no need to worry about
the corresponding scale. If they are on average rated more than one standard deviation below the mean of
a particular competency, there is need for concern because they belong to the lower 16% of the
corresponding competency. The unmarked competencies of Table 18 do not predict general satisfaction
directly. The competency enthusiasm is not a significant predictor for general satisfaction in the service
industry. The sum of the number of professionals in the service industry and specialized workers is 397
instead of 400, because three respondents did not mention in which sector the self-employed worker was
working.
44
Table 18: Means and Standard Deviations per sector
Variables All self-employed
workers *
Professionals in the
service industry **
Specialized
workers ***
Mean SD Mean SD Mean SD
Report mark 7.53 1.07 7.62 1.09 7.47 1.05
General satisfaction 4.12 .71 4.22 .70 4.07 .71
Empathy † 4.09 .60 4.17 .59 4.04 .59
Customer focus † 3.99 .68 4.01 .67 3.97 .68
Professional appearance 3.88 .60 3.96 .65 3.83 .57
Process communication 3.78 .62 3.86 .59 3.74 .63
Enthusiasm †† 4.11 .63 4.20 .63 4.06 .62
Availability 3.91 .59 3.93 .61 3.90 .57
Professional disposition 3.89 .58 3.95 .59 3.86 .57
Proactive mentality † 4.04 .66 4.11 .64 3.99 .68
Price/quality ratio 3.88 .61 3.92 .61 3.86 .60
* N = 400; ** N = 156; *** N = 241; † Significant predictor of general satisfaction; †† Significant predictor,
except for specialized workers.
6.3 Recommendations for self-employed workers
Although the final advice for self-employed workers will be given by Keurwerk, this section provides
recommendations for self-employed workers according to the analyses.
The correlation matrix of Table 10 indicates that all competencies correlate significant with general
satisfaction. According to Murphy, Jako and Anhalt (1993), the inflated correlations among rating
dimensions may be due to the influence of a general evaluation on specific judgments. When a self-
employed worker is rated on multiple performance dimensions, the customer’s overall satisfaction or
evaluation is thought to strongly influence ratings of specific attributes; this phenomenon is referred to as
halo effect or halo error (Murphy et al., 1993). Nisbett and DeCamp Wilson (1977, p. 250) define the halo
effect as: “the influence of a global evaluation on evaluations of individual attributes of a person” Thus,
if a customer likes a self-employed worker, they often assume that those attributes of the self-employed
worker about which they know little are also favorable. The analyses in this study show that there are four
competencies that significantly predict general satisfaction. However, the other competencies may
contribute indirectly to the general satisfaction due to the possibility of halo error. Once customers have a
positive impression of a self-employed worker, they may not distinguish between the competencies
anymore. Therefore, it may be advantageous to perform extremely well on one or two competencies to
cause a positive impression. Since empathy and a proactive mentality are the best predictors of general
satisfaction, these competencies would have priority in this respect. However, it is recommended to focus
on all competencies, including the competencies that do not influence the general satisfaction directly.
After the online questionnaire was filled in by customers, they had the opportunity to write down
comments about the questionnaire or the self-employed worker they had in mind. One of the comments
that confirm the above recommendation was: “The self-employed worker I have in mind is not always
45
strictly in deadlines, but is very creative, open and agreeable. Therefore, I accept her disorganized
behavior and keep it in mind for my own planning”. Because this self-employed worker performs very
well on several competencies, it compensates her lack in planning. Another comment from a respondent
was: “This self-employed worker shows arrogance in his communication. However, his work is always
finished in time and fulfills my demands”. Hence, the questionnaire was mainly filled in positive and the
respondent gave the self-employed worker an 8. Again, this example emphasizes that only one negative
competency does not always cause dissatisfied customers, provided that this competency can be
compensated. One of the respondents gave the self-employed worker on average a 6 and wrote down:
“Because this self-employed worker had to run the business on his own, he was answering phone calls
from other customers all the time which was very annoying”. Unfortunately, this respondent did not
mention anything about the performance of the self-employed worker. Although the 6 is still sufficient, it
was below average. It is likely to assume that answering phone calls affected multiple competencies (e.g.
customer focus, enthusiasm and availability). Taking into account the earlier mentioned recommendation,
the grade might be higher if the self-employed worker compensated his annoying behavior with other
competencies. However, the best solution might probably be switching off the phone to prevent the
annoying behavior!
The small bars at the top of Figure 11 depict the means and standard deviations per competency based on
the questionnaires of 400 respondents. This figure can form the basis for feedback that is going to be
provided to self-employed workers. The red, orange and green colored bars are an example of how a
particular self-employed worker may score on the different competencies. If the average score is above
average, the bar is colored green and there is no need to worry about the corresponding competency. If the
average score is between the mean and one standard deviation, the bar is colored orange indicating that
this competency might be improved. Finally, a red colored bar means that the score on the corresponding
competency is more than one standard deviation below the mean; these competencies are reason for
concern and definitely need to be improved.
Figure 11: Example of a feedback graph
* Competency influences general satisfaction directly
46
The right side of Figure 11 depicts the general satisfaction score with a more specific method of providing
feedback called “Stanine”. Stanine scores are normalized standard scores that range between one and nine
with a mean of five and a standard deviation of two. (Freed, Hess and Ryan, 2002). The relationship
between the Stanine scores and the normal distribution is depicted in Table 19. A limitation to Stanine is
that the data should be normally distributed. The data of this study is not perfect normally distributed,
because more than 4% of the respondents gave the maximum score of five to self-employed workers.
Therefore, the categories stanine 8 and stanine 9 are the same in this study. Although the implementation
of the instrument is executed by Keurwerk, it is recommended to use the Stanine scores since they
provide a simple way to describe customers’ achievement.
Table 19: Relationship between stanine scores and normal distribution
Stanine Percentiles included Questionnaire scores Description
9 96 - 99 4.84 – 5.00 very high
8 89 - 95 4.84 – 5.00 high
7 77 - 88 4.51 – 4.83 quite high
6 60 - 76 4.18 – 4.50 above average
5 40 - 59 3.84 – 4.17 average
4 23 - 39 3.68 – 3.83 below average
3 11 - 22 3.18 – 3.67 quite low
2 4 - 10 2.18 – 3.17 low
1 1 - 3 1.17 – 2.17 very low
The example of Figure 11 depicts that a particular self-employed worker has the lowest average score on
the competency empathy. According to Hoekstra and van Sluijs (2003), empathy includes showing in
contact with others that feelings, attitude and motivation of the other are understood. Furthermore, by
showing empathy the own influence on other people is taken into account. Table 20 provides suggestions
for self-employed workers in order to increase their empathy towards customers. Note that the
recommendations are based on the BEI’s and give just an indication how to improve the corresponding
competency. Due to the possible halo effect in the results, the suggestions that are mentioned may also be
applied to increase other competencies. The first column of Table 20 depicts suggestions that are based on
questions that are included in the final instrument. The second column depicts behavior (in random order
of importance) that was mentioned in the BEI’s but was not included in the quantitative questionnaire.
Table 20: Suggestions to improve Empathy
Behavior of self-employed worker Suggestions for improvement
Being honest towards the customer
Stick to your appointments; Inform the customer if a target of
deadline is postponed; Execute what has been promised; Inform
the customer beforehand about possible uncertainties in the
assignment.
Inspire confidence to the customer
Start as soon as possible with the assignment; Show
perseverance; Be loyal towards the customer even during a short
collaboration. Be faithful to a customer.
Coming to a result by collaborating
with a customer
Be involved in a customer; Think along to develop new insights;
Be flexible to get on with; Take initiative without
communicating with the customer about every detail; Adjust to
the customer’s need.
47
Being agreeable towards a customer
in order to create a mutual
connection
Be polite towards the customer; Show flexibility to adjust to the
profile of the initiator; Show certain amount of humor; Try to
discover how the customer thinks about issues; Act relaxed in
order to communicate in an attractive way; Show social
capabilities.
It is difficult to provide a minimal sample size that has to be collected in order to obtain accurate results,
because the calculation depends on unknown numbers and factors. One of the unknown numbers is the
size of the entire population. In this case, it is assumed that the entire population is equal to the number of
customers that a self-employed worker could theoretically have. Because this number can vary between a
very small number of potential customers until more than 1000, the range of the required sample size
varies accordingly. Furthermore, also other factors like for instance the confidence interval (i.e. margin of
error) and the confidence level should be defined. According to Bartlett, Kotrik and Higgins (2001), there
are different options to calculate a sample size. The following formula is defined by Cochran (1977) and
is used as a guideline to estimate an appropriate sample size for the final instrument:
�� � ������������� where t = value for selected alpha level; s = estimate of standard deviation in the
population; d = acceptable margin of error for mean being estimated. If the sample size exceeds 5% of the
population, Cochran’s (1977) correction formula should be used to calculate the final sample size. The
formula for the correction calculation is: � � ���� �� !"#$%&!��
Cochran’s (1977) formula is used for an assumed entire population of 100 with:
t = 1.96 (based on an alpha level in each tail of .025)
s = .63 (based on the average standard deviation of the quantitative questionnaire)
d = .15 (based on the guidelines of Bartlett et al., 2001)6
As a result, the minimum returned sample size should be 40. So, if 40 customers provide information
about a self-employed workers competencies, and this self-employed worker has 100 customers in total,
his or her true score will be within the obtained score ± .15 with a probability of 95 percent. Furthermore,
the response rate should also be taken into account. If the response rate is for instance predicted to be
50%, at least 80 customers (i.e. number of customers divided by response rate) should be asked to fill in
the questionnaire to obtain the 40 respondents. Note that this is just a guideline for the required sample
size, because the calculation depends on several unknown factors that vary per self-employed worker. As
explained earlier, one of these factors is the number of customers a self-employed worker has. If a self-
employed worker has only a small number of customers (e.g. < 10) who are all willing to participate in
the study, the instrument is still unable to generalize the results to the behavior of a self-employed worker.
In other words, a sample size of 10 is too small to give a reliable advice to self-employed workers about
their competencies. According to Somekh and Lewin (2005), correlation studies were the relationships
between particular characteristics are investigated should at least contain 30 participants.
6 The value of d is calculated by multiplying the number of points on primary scale (5) by the acceptable margin of
error (.03). The value of the acceptable margin of error is based on a general rule in social research (Krejcie &
Morgan, 1970).
48
7 Discussion
This chapter starts with providing an overview of the results and the relationships that were found
between the variables. Formulating an instrument to measure competencies was the main goal of this
master thesis project. Therefore, only recommendations related to implementing the instrument into the
market are provided in section 7.2. Finally, section 7.3 discusses the limitations of the study, followed by
suggestions for further research.
7.1 Overview of the results
The purpose of the study was to investigate which competencies of self-employed workers influence the
general satisfaction of customers. Contrary to what was expected, there was no single competency that
mainly predicted general satisfaction. In addition, there were also no investigated competencies that could
be neglected because they did not have an influence on general satisfaction. The objective of this study
was to answer the research question: “which competencies of self-employed workers significantly
influence the general impression of customers and are quantitatively measurable?” The results of the
research show a significant influence of the competencies empathy, customer focus, proactive mentality
and enthusiasm.
The correlation analysis supported the first hypothesis in showing that all mentioned scales correlated
significantly with general satisfaction of customers. It must be noted, however, that the possibility of halo
error may had an influence on the results. Because respondents may have on forehand certain (positive or
negative) thoughts about the self-employed worker, they may not distinguish between the competencies
anymore. Hence, positive thoughts may have resulted in positive overall assessments independent of the
competency and vice versa.
Hypothesis 2 mentioned six competency components as best predictors for general customer satisfaction
i.e. Building Rapport, Projecting Credibility, Targeting Communication, Communicating Proactively,
Taking Responsibility and Working Energetically and Enthusiastically. Based on the factor analysis -
which revealed other scales- it was decided not to use the predefined scales of Bartram (2005), but to
compose self-made scales. As a result, hypothesis 2 could not be confirmed or rejected. The Critical
Incidents were categorized by three independent raters, while the outcome of the factor analyses was
based on 400 respondents. The assumption that 400 independent respondents are more reliable in finding
underlying competencies compared to three raters was the main reason for the formulation of the self-
made scales. The hierarchical multiple regression analysis identified four competencies as main predictors
of general satisfaction i.e. empathy, customer focus, enthusiasm and proactive mentality. The other four
competencies -although they did not predict general satisfaction significantly- had an indirect influence
on general satisfaction, because the main predictors also served as mediators.
Since all interviewed customers of self-employed workers emphasized in the BEI’s more or less the same
behavior that may influence general satisfaction, it was hypothesized that predictors of general customer
satisfaction would always be the same, independent of the self-employed worker’s field. This hypothesis
was partly rejected because the competency enthusiasm turned out to be a significant predictor among
49
service workers, but not for professionals in the service industry. However, the other three competencies
were significant predictors in both sectors.
While not hypothesized, there was only one background variable with a significant contribution to the
prediction equation. If a self-employed worker was hired by the respondent, the general satisfaction of the
respondent increased. A possible reason may be that the respondent felt responsible or connected to the
self-employed worker which may influence the satisfaction. However, when all competencies were
included in the prediction equation, this background variable was not significant anymore. Furthermore, it
was remarkable that the price/quality ratio of the self-employed worker was not a significant predictor for
general satisfaction. Even customers of specialized workers valued for instance empathy and a proactive
mentality above a beneficial price/quality ratio.
To the author’s knowledge, there was no previous research about determinants of general satisfaction
before. Related research about satisfaction was always in a specific field (e.g. organization, health care,
etc.) and investigated how satisfied employees were. In the past, it was also investigated how satisfied
employees were with aspects of a job, or how for instance motivation or salary influenced their
satisfaction. However, the determinants of general satisfaction were never investigated before. Therefore,
this study contributes to the existing literature.
7.2 Recommendations
The aim of Keurwerk is to implement the final instrument into the market. In order to do so, they have to
approach self-employed workers and ask them whether they are interested in registration for the
questionnaire. Based on experiences while recruiting self-employed workers for the BEI’s, the best way
to approach people is by using a combination of e-mail and telephone. Only sending a commercial e-mail
will hardly cause any reaction, because people in general do not take the time to initiate action. On the
other hand, the risk of only calling people is that they refuse to take the time to listen and react in an
unresponsive way. Therefore, it is recommended to start with sending an e-mail to inform the
respondents. Next, a phone call has to be made to convince people and answer their questions. This
combination of e-mail and phone calls is likely to have the highest probability to increase the response
rate of the final instrument.
Guidelines were provided in Table 15 to advise self-employed workers according to the results of the
final instrument that is filled in by customers. In case a self-employed worker performs below average on
more than two competencies of a single questionnaire, it is recommended to contact the corresponding
customer. The negative judgment may be caused by particular behavior (e.g. making phone calls with
other customers while working) of the self-employed worker that irritates the customer. These negative
competencies can cause an overall negative impression about the self-employed worker. To discover
whether this is the case and which behavior causes the negative impression, contacting the customer
might be a solution.
The current version of the final instrument contains a number of background variables. However, the
analyses in SPSS showed that they do not have a significant influence on the dependent variable.
Therefore, it may be decided to omit certain background variables (e.g. age, gender, contact frequency,
50
etc.) in order to reduce the time that is needed to fill in the questionnaire. On the other hand, if only a
limited number of questionnaires per self-employed worker can be collected, the emphasis can be on
customers with a high contact frequency. Also the anonymity of the final instrument should be
considered. For the self-employed worker it is beneficial to know which customer filled in the
questionnaire and what his or her opinion was. On the other hand, the reliability of the outcome could be
influenced because customers know that their opinion is known by the self-employed worker.
Furthermore, it may also decrease the response rate of the final instrument, because not all customers may
be willing to fill in a questionnaire if they know that the self-employed workers are able to see their
responses. Taking into account that the main goal of the instrument is improving the self-employed
workers’ competencies, a traceable instrument is considered as the best option. This may be implemented
by Keurwerk on their website by offering a personal log in code to customers that is only know by the
customer and Keurwerk. As a result, the customers can fill in the questionnaire anonymously (because the
self-employed worker does not know who filled the questionnaires) which may increase the response rate
and the reliability. Subsequently, Keurwerk can register which customers filled in the questionnaire and
contact the customers that did not. The open question at the end of the questionnaire gives customers the
opportunity to express their opinion about the functioning of the self-employed worker, so Keurwerk can
give specific feedback accordingly.
After Keurwerk has given advice to the self-employed workers according to the questionnaires, it is
reasonable to assume that the behavior of the self-employed worker towards his or her customers
improves. However, Aderson et al. (1994) showed that economic returns from improving customer
satisfaction are not immediately realized. Therefore, Keurwerk can use another questionnaire after for
instance six months to verify if the opinion of the customer has also been significantly changed due to the
new insights and the advice which has been provided to the self-employed worker. With this repeated
measurement, Keurwerk can show the self-employed worker if the questionnaires have worked out
positively or not.
Contrary to what was expected, the price/quality ratio of self-employed worker was not the strongest
significant predictor of general satisfaction. This finding could be used by Keurwerk to attract possible
customers to use the instrument. It is likely to assume that many self-employed workers emphasize a
favorable price/quality ratio while underestimating the importance of their competencies. Therefore, the
outcome of the hierarchical multiple regression analysis can serve as an advertisement strategy to make
self-employed workers aware of the importance of possessing crucial competencies.
51
7.3 Limitations and suggestions for future research
According to Cooper and Schindler (2003), an instrument should meet three major requirements, which
are (1) reliability, (2) validity and (3) practicality. This section will first evaluate the final instrument
according to these three criteria. Second, other limitations and suggestions for future research are
provided.
7.3.1 Evaluation of the final instrument
According to Hair et al. (2006) the reliability of an instrument refers to the extent to which scales are
consistent in what is intended to be measured. The reliability can be assessed by determining the internal
consistency, the factor structure and the stability of the scale over time (Hair et al., 2006). In this study,
the internal consistency of the scales was measured by calculating Cronbach’s Alpa for every scale. The
Cronbach’s alpha values of the included scales were all greater than .66, which met the guidelines of Hair
et al. (2006). Next, the factor structure of the instrument was assessed by a factor analysis. Initially, not
all items loaded on the predicted factors. Therefore, the scales of the final instrument were reformatted
according to the outcome of the factor analysis, resulting in a stable factor structure. A limitation of the
final instrument is the stability of the scales over time, because this was not assessed in the study. To
determine the stability of the scales over time, the same questionnaire could be distributed among the
respondents again. If the two questionnaires highly correlate with each other, it can be concluded that the
final instrument is stable over time. In addition to the reliability, the objectivity of the study was secured
as much as possible. Due to the BEI’s, the respondents were not able to give socially desirable answers,
because they were asked to describe situations. As a result, their answers were objective and not
influenced by the interviewer. Furthermore, the quantitative questionnaire was distributed among a
different population. Since the respondents did not have prior knowledge about the study, it is likely to
assume that this contributed to the objectivity of the study.
According to Hair et al. (2006, p. 137), the validity of an instrument is “the extent to which a scale or set
of measures accurately represents the concept of interest.” The validity of the instrument was assessed
using Structural Equation Modeling and this analysis showed a valid model. However, the extent to which
the separate scales really measure the corresponding competencies was not explicitly determined.
Therefore, this could be considered as a limitation of this study. As explained before, there was no
previous research that examined competencies that have an influence on the general satisfaction of self-
employed workers. Therefore, the results of this study could not be compared with other similar scales.
To obtain the final instrument, only one group of people (i.e. customers of self-employed workers) was
approached to fill in the questionnaire. Implementing multiple measures to demonstrate that the results
are valid may be a suggestion for future research. However, this would be difficult for self-employed
workers, because they do not have subordinates, peers, supervisors or even subcontractors. Therefore, for
instance 360 degree feedback would not be a possible option. Since the main objective of the study was to
determine which competencies influence the general satisfaction of customers, other groups of people
may bias the results. A self-employed worker can also assess his or her own behavior. Future research
may determine if the results of this reflection are comparable with the opinion of customers. Furthermore,
this study might be subject to mono-method bias. According to Bartram (2007), the use of “ipsative”
instruments (i.e. using item formats that require respondents to make choices between items from
different scales) increases validity by 50% compared to “normative instruments” (i.e. making choices
52
between levels of the same scale). In addition, ipsative instruments also reduce the influence of halo error.
Since this study used a normative instrument, it could be further investigated if an ipsative instrument
reduces response bias. Furthermore, the results of the ipsative instrument could be compared with the
current study to assess its validity. A drawback of the ipsative measurement is that it is inherently less
reliable item-for-item compared to normative measurement (Bartram, 2007). Therefore, more items
should be included which increases the assessment time.
According to Cooper and Schindler (2003), the practicality of the instrument can be evaluated by
considering economy, convenience and interpretability. Since the final instrument is not yet implemented
by Keurwerk, not all aspects of the practicality are known. Therefore, the evaluation of the practicality is
based on the questionnaire that was used in this study. The economy refers to the length and the financial
aspects of the instrument. Based on a test panel of ten respondents, the quantitative questionnaire could be
completed in approximately 18 minutes. Since the final instrument contained only half the number of
questions of the quantitative questionnaire, it is likely that the final instrument can be completed in less
than ten minutes. The answers of the instrument will be collected online. Therefore, no major costs are
involved with the collection of the data. The online collection of the data also contributes to the
convenience of the instrument, because there is no pre-set time to fill in the questions. Hence, a clear
instruction for the instrument is provided. Finally, the interpretability is related to the extent to which
outsiders can understand the results. Since Keurwerk did not yet make the questionnaire ready for use, the
interpretability of the instrument is unknown. However, when Keurwerk uses the feedback graph of
Figure 11, the results of the instrument are easy to interpret by self-employed workers.
In conclusion, based on the previous mentioned criteria for reliability, the internal consistency and the
factor structure of the final instrument were sufficient. The stability of the scales over time was not
assessed in this study. Moreover, the validity of the scales was not determined. Therefore, Keurwerk
should provide feedback to self-employed workers with care. Finally, based on the economy, convenience
and interpretability it is believed that the practicality of the instrument is sufficient.
7.3.2 Limitations
Keurwerk wanted to have a measurement instrument to establish the most important competencies of a
self-employed worker without looking to the content of the job, in order to generalize the results to a
larger population. Initially, it was an interesting research area because at that time it was unknown which
competencies determine general customer satisfaction. However, the results of the questionnaire showed
that a lot of competencies correlated with each other. In other words, the focus of the study might be too
much on competencies, which resulted in closely related outcomes. All in all, the biggest limitation of the
study was probably the strong focus on competencies. Although it was not demanded by Keurwerk, also
other factors (e.g. content related aspects of the job) could have been taken into account. In addition, the
absence of the price/quality ratio in the prediction equation might also be declared because all
respondents were already customers of a self-employed worker. Therefore, they all accepted the price that
was demanded by the self-employed workers and customers might not take this into account while filling
in the questionnaire about general satisfaction. It is likely that the price/quality ratio was a criterion in an
earlier phase (i.e. while selecting a self-employed worker). Future research could determine how
important for instance the price/quality ratio and content related factors are in relation to competencies.
53
The next limitation is in line with the previous mentioned strong focus on competencies. After the Critical
Incidents were collected, they were categorized by three independent assessors. This categorization
process was difficult because there was no huge dispersal between the Critical Incidents. Although the
calculated kappa value showed substantial agreement between the three assessors, the Critical Incidents
were not all placed into the same category. This was a first sign that the focus of the study might be too
much on competencies. The second sign of a too strong focus on competencies were the results of the
factor analysis. Even though the sample size was large enough, the factor analysis did not show the
predicted results. For future equivalent research, it is recommended to broaden the scope to prevent
correlated results.
7.3.3 Suggestions for future research
The correlation matrix of section 5.3 indicated that all competencies correlated significantly (p < .01) with
general satisfaction. However, this may also be caused by a halo effect. Although it is expected that halo
error has affected the results of the study, its impact is unknown. The magnitude of the influence can be
further investigated and may also be compared to the influence of halo error in other studies. According to
Baltes and Parker (2000), it is difficult to eliminate this judgment bias, because research consistently
indicates that people are unaware of halo effects. A number of strategies are suggested by Murphy et al.
(1993) for removing the halo effect. These strategies include for instance increased observation,
manipulation of rating scales and scale formats and rater training. However, none of these has proved to
be fully effective in controlling the halo effect (Murphy et al., 1993). The regression analysis should be
interpreted with care due to the high mutual correlations between the competencies. In addition, the
possibility of halo error makes it more difficult to distinguish a self-employed worker’s strengths from his
or her weaknesses (Murphy, 1993). Moreover, the competencies that do not contribute significant to the
predictor equitation should not be disregarded, because they have a high correlation with general
satisfaction. Due to the possibility of halo error and the indirect effect these competencies have on general
satisfaction, they are indirectly important to increase the general satisfaction among customers.
The difference between satisfaction of customers of self-employed workers and fixed salary workers for a
company can be further investigated. The main difference between them is that self-employed workers
have to do everything on their own. In a company this is all cut into smaller pieces because everyone has
his or her own specialty. For instance, managers delegate work to professionals in a specific field and the
administration department plans the appointments. This may cause other competencies (i.e. mutual
communication between employees) that influence the satisfaction of customers. Further research can
investigate this.
To validate whether the final results can be generalized among the entire group of self-employed workers,
another group of self-employed workers that does not fit into the investigated target group may be asked
to fill in the questionnaire. The present study distinguished between two sectors (i.e. specialized workers
and professionals in de service industry), but also other differentiations can be made (e.g. B2B and B2C).
It is likely that also other groups of self-employed workers are comparable in terms of competencies. All
self-employed workers should be for instance reliable, follow their arrangements, adjust to the customers
need, etc. However, future research should determine if this can be generalized among the whole sample
of self-employed workers.
54
Finally, future research can determine the best way to implement the results of the research. This study
showed for instance that empathy is related to the satisfaction of customers. Suggestions to improve
empathy are provided based on the outcome of the BEI’s. It is likely to assume that these suggestions
have an influence on empathy, but the significance should be verified in order to give Keurwerk the
opportunity to provide a quality mark in addition to an advice to self-employed workers. Besides the
verification, the most effective way to improve the competencies can also be further investigated.
55
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59
Appendix I: The Great Eight competencies
The great eight, 20 competency dimension and 112 competency component titles (Bartram, 2005).
1 Leading and Deciding
1.1 Deciding & Initiating Action
1.1.1 Making Decisions
1.1.2 Taking Responsibility
1.1.3 Acting with Confidence
1.1.4 Acting on Own Initiative
1.1.5 Taking Action
1.1.6 Taking Calculated Risks
1.2 Leading and Supervising
1.2.1 Providing Direction and Coordinating
Action
1.2.2 Supervising and Monitoring Behavior
1.2.3 Coaching
1.2.4 Delegating
1.2.5 Empowering Staff
1.2.6 Motivating Others
1.2.7 Developing Staff
1.2.8 Identifying and Recruiting Talent
2 Supporting and Cooperating
2.1 Working with People
2.1.1 Understanding Others
2.1.2 Adapting to the Team
2.1.3 Building Team Spirit
2.1.4 Recognizing and Rewarding Contributions
2.1.5 Listening
2.1.6 Consulting Others
2.1.7 Communicating Proactively
2.1.8 Showing Tolerance and Consideration
2.1.9 Showing Empathy
2.1.10 Supporting Others
2.1.11 Caring for Others
2.1.12 Developing and Communicating Self-
knowledge and Insight
2.2 Adhering to Principles and Values
2.2.1 Upholding Ethics and Values
2.2.2 Acting with Integrity
2.2.3 Utilizing Diversity
2.2.4 Showing Social and Environmental
Responsibility
3 Interacting and Presenting
3.1 Relating & Networking
3.1.1 Building Rapport
3.1.2 Networking
3.1.3 Relating Across Levels
3.1.4 Managing Conflict
3.1.5 Using Humor
3.2 Persuading and Influencing
3.2.1 Making an Impact
3.2.2 Shaping Conversations
3.2.3 Appealing to Emotions
3.2.4 Promoting Ideas
3.2.5 Negotiating
3.2.6 Gaining Agreement
3.2.7 Dealing with Political Issues
3.3 Presenting and Communicating Information
3.3.1 Speaking Fluently
3.3.2 Explaining Concepts and Opinions
3.3.3 Articulating Key Points of an Argument
3.3.4 Presenting and Public Speaking
3.3.5 Projecting Credibility
3.3.6 Responding to an Audience
4 Analyzing and Interpreting
4.1 Writing and Reporting
4.1.1 Writing Correctly
4.1.2 Writing Clearly and Fluently
4.1.3 Writing in an Expressive and Engaging
Style
4.1.4 Targeting Communication
4.2 Applying Expertise and Technology
4.2.1 Applying Technical Expertise
4.2.2 Building Technical Expertise
4.2.3 Sharing Expertise
4.2.4 Using Technology Resources
4.2.5 Demonstrating Physical and Manual Skills
4.2.6 Demonstrating Cross Functional
Awareness
4.2.7 Demonstrating Spatial Awareness
60
4.3 Analyzing
4.3.1 Analyzing and Evaluating Information
4.3.2 Testing Assumptions and Investigating
4.3.3 Producing Solutions
4.3.4 Making Judgments
4.3.5 Demonstrating Systems Thinking
5 Creating and Conceptualizing
5.1 Learning and Researching
5.1.1 Learning Quickly
5.1.2 Gathering Information
5.1.3 Thinking Quickly
5.1.4 Encouraging and Supporting
Organizational Learning
5.1.5 Managing Knowledge
5.2 Creating and Innovating
5.2.1 Innovating
5.2.2 Seeking and Introducing Change
5.3 Formulating Strategies and Concepts
5.3.1 Thinking Broadly
5.3.2 Approaching Work Strategically
5.3.3 Setting and Developing Strategy
5.3.4 Visioning
6 Organizing and Executing
6.1 Planning and Organizing
6.1.1 Setting Objectives
6.1.2 Planning
6.1.3 Managing Time
6.1.4 Managing Resources
6.1.5 Monitoring Progress
6.2 Delivering Results and Meeting Customer
Expectations
6.2.1 Focusing on Customer Needs and
Satisfaction
6.2.2 Setting High Standards for Quality
6.2.3 Monitoring and Maintaining Quality
6.2.4 Working Systematically
6.2.5 Maintaining Quality Processes
6.2.6 Maintaining Productivity Levels
6.2.7 Driving Projects to Results
6.3 Following Instructions and Procedures
6.3.1 Following Directions
6.3.2 Following Procedures
6.3.3 Time Keeping and Attending
6.3.4 Demonstrating Commitment
6.3.5 Showing Awareness of Safety Issues
6.3.6 Complying with Legal Obligations
7 Adapting and Coping
7.1 Adapting and Responding to Change
7.1.1 Adapting
7.1.2 Accepting New Ideas
7.1.3 Adapting Interpersonal Style
7.1.4 Showing Cross-cultural Awareness
7.1.5 Dealing with Ambiguity
7.2 Coping with Pressure and Setbacks
7.2.1 Coping with Pressure
7.2.2 Showing Emotional Self-control
7.2.3 Balancing Work and Personal Life
7.2.4 Maintaining a Positive Outlook
7.2.5 Handling Criticism
8 Enterprising and Performing
8.1 Achieving Personal Work Goals and
Objectives
8.1.1 Achieving Objectives
8.1.2 Working Energetically and
Enthusiastically
8.1.3 Pursuing Self-development
8.1.4 Demonstrating Ambition
8.2 Entrepreneurial and Commercial Thinking
8.2.1 Monitoring Markets and Competitors
8.2.2 Identifying Business Opportunities
8.2.3 Demonstrating Financial Awareness
8.2.4 Controlling Costs
8.2.5 Keeping Aware of Organizational Issues
Note that each component is further defined
within the framework in terms of negative and
positive behavioral indicators.
61
Appendix II: BEI (in Dutch)
Step 1: Introduction and Explanation
Het doel van deze stap was om het vertrouwen van de geïnterviewde te winnen en om “goodwill” te
creëren. Tevens werd er om toestemming gevraagd om het gesprek op te nemen.
1. Introductie van de interviewer.
a. “Mijn naam is Tom Bongers, en ik ben aan het afstuderen aan de Technische Universiteit
Eindhoven, in de richting Human Performance Management.”
2. Uitleg over the doel en de opzet van het interview.
a. Voor het afstudeeronderzoek wil ik analyseren welke competenties het verschil maken in
de indruk die ZZP-ers (Zelfstandige Zonder Personeel) achterlaten. Dit kan een goede
indruk zijn, hiermee bedoel ik het type gedrag waarvan je hoopt dat alle ZZP-ers
waarmee je zaken doet het hebben (bv. gemotiveerd zijn). Maar dit kan ook een minder
goede indruk zijn (bv. ongemotiveerd overkomen).
b. Ik ben aan uw telefoonnummer gekomen omdat u onlangs zaken hebt gedaan met de
ZZP-er [naam]. Over uw contact met deze ZZP-er zou ik graag wat vragen stellen.
c. Het interview zal anoniem worden afgenomen, dus de ZZP-er zal niet te weten komen
wat u over hem gezegd hebt.
Step 2: Job Responsibilities
Specifieke vragen werden in deze stap gesteld over het beroep van de geïnterviewden en de betreffende
ZZP-er.
Om te beginnen wil ik u een aantal algemene vragen stellen:
3. Wat is uw huidige baan en functie?
a. Hoe groot is de organisatie waar u voor werkt?
b. Heeft u de ZZP-er zelf ingehuurd? Of was het iemand anders binnen uw bedrijf?
4. Wat is het beroep van de ZZP-er(s) over wie we het dadelijk gaan hebben?
a. Heeft u het afgelopen jaar met nog meer ZZP-ers zaken gedaan?
b. Heeft u ook contact gehad met ZZP-ers die uiteindelijk de opdracht niet hebben
gekregen? ZZP-ers die dus niet voorbij het offerte stadium zijn gekomen. Deze ZZP-ers
zijn ook waardevol voor mijn onderzoek, door de reden van de afwijzing.
5. Algemene vragen
a. Wanneer had u voor het eerst contact met de ZZP-er? Hoelang heeft de ZZP-er in totaal
in opdracht van u gewerkt?
b. Kende u de ZZP-er al voordat u hem aannam voor de opdracht?
Step 3: Behavioral Events
Deze stap beschrijft tot in detail zo veel mogelijk complete verhalen van “Critical Incidents”. In dit geval
is een “Critical Incident” een specifieke tijd of situatie waarin iets redelijk goed ging, moeilijk was, of
een situatie waarin de geïnterviewde voelt dat hij goed, of juist niet goed is behandeld.
62
6. “Ik zou nu graag van u een voorbeeld willen horen van een specifieke ervaring die u het
afgelopen jaar heeft gehad met de ZZP-er. Kunt u een situatie beschrijven waarin een handeling
van de ZZP-er erg goed uitpakte, of juist niet. Laten we beginnen met een handeling waarover u
tevreden was.”
o Herhalingsvraag: “Kunt u een situatie beschrijven waarin u erg tevreden, of ontevreden
was door een handeling van de ZZP-er.”
o Nee?!:
� Wanneer vond u dat u goed behandeld werd door de ZZP-er?
� Wat was bijvoorbeeld de eerste indruk die u had van de ZZP-er?
� Wanneer heeft u voor het laatst contact gehad met de ZZP-er, wat is er toen
gezegd? Hoe kwam dat op u over? Waar werd deze indruk door veroorzaakt?
o Kunt u ook een voorbeeld noemen van een situatie waarin u niet zo tevreden was met de
ZZP-er?
� Herhalingsvraag: “Wanneer vond u dat u slecht bent behandeld door de ZZP-er?”
� Wat vond u teleurstellend gedrag van de ZZP-er?
Om het verhaal zo compleet mogelijk te maken werden de volgende vragen gesteld:
7. Wat was de situatie? Wat waren de omstandigheden? Waardoor werd het veroorzaakt?
8. Wat deed de ZZP-er precies dat een zodanig goede, of slechte (positieve of negatieve) indruk
achterliet?
9. Hoe is het voorbeeld dat u zojuist beschreef een voorbeeld van goed, of minder goed gedrag? Met
andere woorden, hoe beïnvloedde dit het werk dat de ZZP-er aan het uitvoeren was?
10. Wat dacht u, voelde u, of deed u in die situatie?
a. Wat dacht u op dat moment over de ZZP-er?
b. Wat vond u van de hele situatie? Wat was uw gevoel bij de situatie?
c. Hoe reageerde u op de situatie? Wat motiveerde u tot deze actie?
11. Wat gebeurde er uiteindelijk, hoe liep de situatie af?
Step 4: Characteristics which are needed to do the job
12. Wat denkt u dat ervoor nodig is om een effectieve ZZP-er te zijn?
13. Welke karaktereigenschappen, kennis, of vaardigheden denkt u dat er nodig zijn om een
succesvolle ZZP-er te zijn?
14. Als u opnieuw een ZZP-er moet inhuren, waar zou u dan op letten?
15. Welke eigenschappen van een ZZP-er bepaald hoe tevreden een klant over hem is?
16. Zijn er nog andere opmerkingen die u kwijt wilt die betrekking hebben op het handelen van de
ZZP-er?
Step 5: A final note
De geïnterviewde wordt bedankt voor zijn/haar tijd en medewerking. Verder is er gevraagd of de
geïnterviewde nog meer klanten van ZZP-ers kent die ook bereid zijn om geïnterviewd te worden.
63
Appendix III: Calculation of Fleiss Kappa
The chance-corrected measure of overall agreement proposed by Fleiss (1971) is:
'() � ∑ +,-� ∑ k,/01/-� – kn41 6 �n 7 1�∑ p/01/-� 9
kn�n 7 1�:1 7 ∑ p/01/-� ;
The subscript mc is for multiple categories
k = number of Critical Incidents
n = number of raters
c = number of categories
<== ��> ∑ ?@=>@-� = proportion of all assignments to the A�B category. In this formula, ?@= is the number
of raters who assign the C�B subject to the A�B category (i = 1, 2, …k; j = 1, 2, … c)
For computational ease, Shoukri (2004) re-wrote the above mentioned formula as:
'() � <D 7 <E 1 7 <E
where
<D � ∑ ∑ ?@=0 7 �?)=-�>@-�?��� 7 1�
and
<E �FG=0)
=-�
where
<= � 1�?F?@=
>
@-�
The number of competency components is 112, therefore, c = 112. The number of independent raters (n)
is 3 and the number of relevant Critical Incidents (k) = 314. As a result of formula (3), (4) and (5):
<D � 0.57
(1)
(5)
(4)
(3)
(2)
64
If a random selected item will be categorized by a random selected individual, the probability that a
second random selected individual will categorize this item in the same category will be 0.57 (Fleiss,
1971).
<E � 0.03
Therefore,
'() � <D 7 <E 1 7 <E �
0.57 7 0.031 7 0.03 � 0.56
65
Appendix IV: Final questionnaire (in Dutch)
The final questionnaire consisted of 12 pages, so the respondents did not have to scroll down to read a
question. A print screen of the sixth page is depicted in figure 12. The remaining part of the questionnaire
is not depicted in this appendix, because the questions are confidential. For more information please
contact the initiator of Keurwerk on [email protected].
Figure 12: Random page of the final questionnaire
66
Appendix V: Correlation matrix of the original scales
Table 21: Pearson correlation coefficients
Mean SD N 1 2 3 4 5 6 7 8 9 10 11 12
1 General satisfaction 4.12 .71 400 (.92)
2 Report mark 7.53 1.07 400 .76** (-)
3 Gender (respondent) - - 400 .04 .09 (-)
4 Age 46.65 10.27 398 .00 -.01 -.08 (-)
5 Gender (SEW) - - 400 .02 .03 .20** -.03 (-)
6 Sector - - 397 -.11* -.08 -.02 .08 -.29** (-)
7 Contact duration 3.81 1.45 400 .11* .08 .01 -.01 .06 -.26** (-)
8 SEW hired by
respondent - - 400 -.11* -.06 .03 -.22** .19** -.20** .03 (-)
9 Contact frequency 1.81 1.24 400 .03 .02 .00 -.01 .07 -.21** .19** .17** (-)
10 Contact with multiple
SEWs - - 400 -.10* -.03 .06 .01 -.04 .11* -.18** .06 -.01 (-)
11 Reachableness 3.86 .71 400 .67** .56** .06 .03 .04 -.13** .12* -.06 -.01 -.05 (.68)
12 Follow appointment 4.15 .62 400 .80** .64** .05 .05 .09 -.12** .13** -.07 .05 -.05 .67** (.86)
13 Acting with confidence 4.01 .66 400 .86** .72** .06 .04 .06 -.08 .11* -.10* -.01 -.07 .72** .86**
14 Acting on own initiative 3.81 .61 400 .75** .65** .08 .00 .03 -.10* .07 -.06 .03 -.02 .62** .64**
15 Adapting to the team 3.83 .55 400 .79** .69** .09 .00 -.01 -.12* .08 -.07 .06 -.07 .66** .72**
16 General commu-
nication skills 3.87 .59 400 .71** .62** .11* -.02 .05 -.15** .08 .02 .08 -.02 .57** .66**
17 Project related
communication 3.84 .60 400 .81** .69** .07 .01 .00 -.06 .07 -.08 -.02 .00 .70** .78**
18 Self knowledge 3.82 .58 400 .80** .69** .07 .03 .04 -.08 .08 -.06 .06 -.03 .61** .74**
19 Building rapport 3.98 .61 400 .85** .73** .05 .01 .02 -.12* .15** -.09 .03 -.07 .70** .75**
20 Acting representative 3.90 .56 400 .65** .56** .07 .03 .03 -.10 .09 -.02 .04 -.02 .55** .59**
21 Acting professional 3.86 .53 400 .71** .61** .09 .06 .03 -.06 .09 -.04 -.01 -.02 .60** .72**
22 Targeting
communication 3.88 .62 400 .81** .70** .12* .00 .04 -.09 .09 -.10* .02 -.02 .68** .78**
23 Adapting 3.92 .55 400 .78** .70** .04 -.04 -.01 -.06 .07 -.05 .04 -.02 .67** .72**
24 Working energetically 4.00 .63 400 .77** .65** .03 -.01 .05 -.12* .10* -.07 .04 -.07 .66** .71**
25 Price/Quality ratio 3.88 .54 400 .71** .59** .04 .05 -.02 -.07 .14** -.17** .00 -.10* .57** .65**
67
Mean SD N 13 14 15 16 17 18 19 20 21 22 23 24 25
13 Acting with confidence 4.01 .66 400 (.90)
14 Acting on own initiative 3.81 .61 400 .74** (.87)
15 Adapting to the team 3.83 .55 400 .78** .75** (.80)
16 General commu-
nication skills 3.87 .59 400 .72** .72** .73** (.73)
17 Project related
communication 3.84 .60 400 .86** .81** .83** .78** (.89)
18 Self knowledge 3.82 .58 400 .82** .73** .76** .71** .81** (.81)
19 Building rapport 3.98 .61 400 .83** .78** .81** .76** .83** .78** (.85)
20 Acting representative 3.90 .56 400 .66** .65** .70** .70** .69** .65** .71** (.72)
21 Acting professional 3.86 .53 400 .75** .71** .76** .72** .78** .74** .77** .73** (.77)
22 Targeting
communication 3.88 .62 400 .84** .81** .83** .81** .89** .82** .85** .75** .79** (.88)
23 Adapting 3.92 .55 400 .80** .77** .80** .74** .80** .76** .81** .66** .73** .84** (.80)
24 Working energetically 4.00 .63 400 .78** .81** .74** .69** .77** .73** .78** .62** .67** .78** .76** (.83)
25 Price/Quality ratio 3.88 .54 400 .70** .67** .65** .58** .67** .69** .69** .52** .58** .68** .68** .67** (.88)
* P < .05 (2-tailed); ** p < .01 (2-tailed)
Cronbach’s alpha values are depicted on the diagonal between brackets.
For the dummy variables: male was coded 0 and female was coded 1. Yes was coded 0 and no was coded 1. A professional in the service industry was coded 0 and a
specialized worker was coded 1. This information is necessary to interpret the direction of the effect in the correlation matrix.
68
Appendix VI: Factor Analysis
There was one item in scale six that loaded also on factor five. Due to theoretical arguments it was
decided to retain this item in scale six.
HIJJKLM NIJLOP Q
1 2 3 4 5 6 7 8 9 10
Empathy 1* .51
.36
Empathy 2** .48
Empathy 3* .45
.35
Empathy 4** .44
Empathy 5** .43
Empathy 6 .40
Empathy 7* .39
.37
Empathy 8 .38
Empathy 9* .35
.32
Empathy 10 .34
Empathy 11** .34
Empathy 12 .33
Empathy 13** .31
Empathy 14** .31
Customer focus 1**
.63
Customer focus 2
.56
Customer focus 3
.52
Customer focus 4**
.52
Customer focus 5
.49
Customer focus 6
.43
Customer focus 7* .30 .39
Customer focus 8*
.38
.37
Customer focus 9**
.37
Customer focus 10*
.34
.34
Professional appearance 1
.77
Professional appearance 2
.77
Professional appearance 3
.48
Professional appearance 4*
.47 .33
Professional appearance 5
.41
Professional appearance 6**
.39
Professional appearance 7*
.37
.32
Professional appearance 8**
.36
Professional appearance 9 ***
Professional appearance 10**
.71
69
1 2 3 4 5 6 7 8 9 10
Process communication 1
.58
Process communication 2**
.56
Process communication 3**
.46
Process communication 4
.45
Process communication 5 **
.42
Process communication 6*
.42
.40
Process communication 7**
.40
Process communication 8**
.39
Process communication 9
.37
Process communication 10**
.36
Process communication 11**
.35
Process communication 12**
.33
Process communication 13
.33
Process communication 14 * .31
.31
Process communication 15**
.30
Enthusiasm 1*
.56
-.32
Enthusiasm 2
.52
Enthusiasm 3
.50
Enthusiasm 4
.45
Enthusiasm 5*
.43
.39
Enthusiasm 6
.42
Enthusiasm 7*
.32
-.39
Enthusiasm 8**
.39
Enthusiasm 9*
.38
.35
Enthusiasm 10**
.33
Availability 1***
Availability 2
.57
Availability 3**
.52
Availability 4
.36 .45
Availability 5
.34
Integrity 1**
.71
Integrity 2**
.32
Integrity 3**
.32
Integrity 4***
Professional disposition 1
.74
Professional disposition 2
.41
Professional disposition 3*
.37 -.32
Professional disposition 4*
.35
.31
Professional disposition 5**
.31
70
1 2 3 4 5 6 7 8 9 10
Taking initiative 1
-.73
Taking initiative 2*
-.30
-.45
Proactive mentality
.62
Proactive mentality 1**
.59
Proactive mentality 2**
.58
Proactive mentality 3
.57
Proactive mentality 4
.51
Proactive mentality 5**
.48
Proactive mentality 6*
.31
.45
Proactive mentality 7* .33
.43
Proactive mentality 8**
.41
Proactive mentality 9
.40
Proactive mentality 10**
.39
Proactive mentality 11**
.37
Proactive mentality 12**
.32
Proactive mentality 13***
Extraction Method: Principal Component Analysis.
Rotation Method: Oblimin with Kaiser Normalization.
a. Rotation converged in 68 iterations.
* Deleted items since they load on multiple factors
** Deleted items on theoretical grounds to reduce the number of items per scale
*** Deleted items due to a factor loading < .3
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Appendix VII: Sobel test for mediating mechanisms
For the final instrument, the mediating effects and Sobel tests are calculated for every competency. This
Appendix provides an example of the calculation method.
The test starts by determining if there is a mediating effect between professional appearance (independent
variable), empathy (mediator) and general satisfaction (dependent variable) according to the method that
is defined by Baron and Kenny (1986). Figure 13 illustrates this mediating effect graphically.
Figure 13: The mediating effect
The relationship (c) between the independent variable (professional appearance) and the dependent
variable (general satisfaction) is tested and significant.
Table 22: Regression analysis for relationship c
Variable B Std. Error β
Professional appearance .68** .05 .58
Dependent Variable: General Satisfaction; ** p < .01
The relationship (a) between the independent variable (professional appearance) and the mediator
(empathy) is tested and significant.
Table 23: Regression analysis for relationship a
Variable B Std. Error β
Professional appearance .61** .04 .62
Dependent Variable: Empathy; ** p < .01
The relationship (b) between the mediator (empathy) and the dependent variable (general satisfaction) is
tested and significant.
Table 24: Regression analysis for relationship b
Variable B Std. Error β
Empathy 1.02** .03 .86
Dependent Variable: General Satisfaction; ** p < .01
72
Finally, the relationship between the independent variable and the dependent variable is tested while
controlling for the mediator (i.e. test c while controlling for b). The B coefficient of relationship c was .68
and has been reduced to .09. Hence, the relationship has become smaller but is still significant. As a
result, there is statistical evidence for partial mediation.
Table 25: Regression analysis for relationship c while controlling for b
Variables B Std. Error β
Empathy .96** .04 .81
Profession appearance .09* .04 .08
Dependent Variable: General Satisfaction; ** p < .01; * p < .05
The formula that is used to for the Sobel test is: Z-value � ���������������
where a and b are path
coefficients and ��= standard error of a and ��= standard error of b. The values of the variables for this
example are obtained with SPSS and depicted below:
a = .61
b = 1.02
�� = .04
�� = .04
The Z-value for this example is:
R � S�S0 � ��0 6 R0 � ��0
� . 61 � 1.02√1.020 �. 040 6.610 �. 040 � 13.09
Since the above calculated value is > 1.96, the mediator carried the influence of the independent variable
to the dependent variable.
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Appendix VIII: Structural Equation Model on latent level
.18
.19
.38
.25.18
.23
74
Appendix IX: Final instrument (in Dutch)
The final instrument is confidential. For more information, please contact the initiator of Keurwerk on