giftjourn@l Indian Institute of Technology Delhi ISSN...
Transcript of giftjourn@l Indian Institute of Technology Delhi ISSN...
Editor-in-ChiefSushilChair, Strategic Management GroupDepartment of Management StudiesIndian Institute of Technology DelhiHauz Khas, New Delhi-110016e-mail : [email protected] : 91-11-26591167Fax : 91-11-26862620
Global Journal ofFlexible Systems Management
ISSN 0972-2696
(Quarterly Journal of Global Institute ofFlexible Systems Management)
Subscription and AdvertisingFor subscription or giving advertisements either write to Production Manager, gi f t j ourn@l S-15, LSC, DDA Commercial Complex, Mayur Vihar,Phase-I, Delhi - 110091 or use e-mail [email protected].
Subscription Rates (yearly for 4 issues including postage). Payments to be made in favour of "Global Institute of Flexible SystemsManagement" payable at New Delhi.
Within India OverseasInstitutions/Corporates Rs 4,500 US$ 200Individuals Rs 900 US$ 50Advertisement RatesFull page Rs 25,000 US$ 1,000
Copyright © 2003, Global Institute of Flexible Systems ManagementThe Journal or any part thereof may not be reproduced in any form without the prior written permission of the publisher.All data, views, opinions etc. being published are the sole responsibility of authors. Neither the publisher nor the editors are in anywayresponsible for them.
Published by Global Institute of Flexible Systems Managementwww.giftsociety.org
giftjourn@l
Printed by New Delhi.Mobile : 9810247997, Ph. : 011-26042537
Editorial BoardRakesh Kumar AgrawalSchool of ManagementUniversity of Western Sydney
Sydney, Australia
Ali DastmalchianDean, Faculty of BusinessUniversity of Victoria
Victoria, Canada
M.C. JacksonDirector of the Business SchoolUniversity of Hull, UK
Editor-in-Chief,Systems Research andBehavioral Science
Jatinder N.D. (Jeet) GuptaEminent Scholar and Chairperson
Department of Accounting &Information SystemsCollege of Administrative Science
The University of Alabama inHuntsville, USAAssociate Editor, Decision Sciences
Anthony MichellVisiting Prof. (Strategy & Global Mgt.)
School of Public Policy andManagement, KDI, Korea
H. PaulProfessor and DeanSchool of Management
Asian Institute of TechnologyPathumthani, Thailand
Daniel RouachProfessorSchool of ManagementESCP-EAP, Paris, France
Kulwant SinghHead, Department ofManagement & Organization
Faculty of Business Admn.National University of SingaporeChief Editor,
Asia Pacific Journal of Management
MembersA.K. AgrawalCEOAutometers Alliance Ltd., Noida
Rajat K. BaisyaHead, Dept. of Management StudiesIIT Delhi
P.K. JainDept. of Management StudiesIIT Delhi
K.M. MitalDepartment of Management StudiesIIT Roorkee
Shyam SethiVice PresidentWhirpool of India Ltd., New Delhi
Sanjay K. SinghManaging Editor-Higher EducationPearson Education IndiaDelhi
Managing Committee
Deputy EditorsK. MomayaDept. of Management StudiesIIT Delhi.
O.P. SharmaDelhi College of Engineering,Delhi
Regional Editor-North America Region
Prabir K. BagchiDir.-Logistics & Operations ManagementSchool of Business & Public ManagementThe George Washington UniversityWashington - DC, USA
Associate EditorsJames H. PerryThe George Washington UniversityWashington - DC, USA
Susan WhiteThe George Washington UniversityWashington - DC, USA
Srinivas PrasadThe George Washington UniversityWashington - DC, USA
Thomas CorsiUniversity of Maryland-College Park, USA
Herbert KotzabCopenhagen Business SchoolDenmark
Tage Skjoett-LarsenCopenhagen Business SchoolDenmark
Helge VirumNorwegian School of Management
Nanua SinghProfessor and Director of IntegratedProduct Development Laboratory,Wayne State University, USA
Kathryn E. SteckeThe University of Texas at DallasSchool of ManagementRichardson, USAEditor-in-ChiefIntl. Journal of Flexible Mfg. Systems
Ushio SumitaProfessorGraduate School ofInternational ManagementInternational University of JapanJapan
Henk W. VolberdaProfessor of Strategic Management &Business PolicyRotterdam School of ManagementErasmus University, The Netherlands
Global Journal ofFlexible Systems Management
giftjourn@l
ISSN 0972-2696 Vol. 4 No. 3, July - September 2003
Contents
Editorial iii
Research Papers
l A Decision Support System for Flexibility in Manufacturing 1
Boppana V. Chowdary and Arun Kanda
l Polarization of Perceptions of IT-enabled PrivacyViolations at Workplace: Impact of Respondent Position,Peer Belief and Peer Pressure 15
Nivedita Debnath and Kanika T. Bhal
l Stakeholder Flexibility in E-Business Environment:A Case of an Automobile Company 21
Rajeev Dwivedi and Kirankumar Momaya
Short Communication
l Innovating Growth through “Six Sigma”:A Strategic Approach for Combining Robustness with Flexibility 33
Amit Chatterjee
Event Diary 39
giftjourn@lGlobal Journal ofFlexible Systems Management2003, Vol. 4, No. 3, pp iii
Editorial
How flexibility andproductivity are
related to each other
A normal proposition isflexibility hampers
productivity by reducedoutput and requirement
of more input
Let us compare theoutput of a mass
manufacturing systemand a flexible
manufacturing system
Less flexibility means moreapparent productivity of
undesired output, whereasmore flexibility willfacilitate more realproductivity of the
desired output
Normal assumption is thata dedicated system
requires less inputs andis more efficient
A flexible system maybetter cope with
uncertainty of demandleading to less inputs per
unit of output
In an uncertain anddynamic environment, thereal productivity of a moreflexible system is expected
to be higher than a lessflexible system
© 2003, Global Institute ofFlexible Systems Management
Flexibility and Productivity
Is there a relationship between the two key performance variables of any enterprise, i.e.flexibility and productivity? If yes, what is its nature? Does it mean that greater flexibilityimplies lesser or higher productivity? These are some of the bubbling questions in the mindof any manager or management researcher.
Normally, it is argued that, as flexibility implies more options, change mechanisms andfreedom of choice, it would be hampering the productivity both by way of reduced outputand more inputs for more options. This proposition can be examined from two viewpoints:one from the output point of view and the other from the input.
By considering the output, as the main variable, do we see that the output of a lessflexible system is higher than a more flexible system. Let us consider two manufacturing systems:(i) a mass manufacturing dedicated assembly line; and (ii) a flexible manufacturing systemable to handle many models/products. In which case, the output is expected to be higher interms of number of products manufactured per day? Obviously, one would argue that in thecase of a dedicated system the output would be higher as there are no changeover times requiredin between. But, in reality, we require many models to be produced as per the customerrequirements and manufacturing more of only one model would not serve the purpose. If morethan one model is to be produced on the dedicated assembly line, it would entail loss ofset-up time as with every change of model a new set-up is to be created. Whereas, in case of aflexible manufacturing system many models can be processed simultaneously thereby havingmore desirable output and thus more productivity in real sense. Thus, with less flexibilityapparently the productivity is high but more of undesired output, whereas more flexibilityfacilitates more real productivity of desired output.
Let us examine the same issue from the viewpoint of input required in a less flexibleand more flexible system respectively. Normally, it is assumed that a dedicated massmanufacturing system with special purpose machines/assembly lines would be more efficientand would require less inputs of manpower and machines per unit product. In a dedicatedsystem, dealing with one product, the production stages are well balanced and the skill levelsof workers are quite high as the job is repetitive in nature. On the other hand, a flexiblemanufacturing system, dealing with multiple products at a time, would require higher inputsof technology and multiskilling on the part of the workers. Thus, on the face it appears thatthe productivity level of a less flexible system would be higher on account of lower inputs.However, in real terms it need not necessarily be so, because a dedicated system might belying idle if the demand of that specific product is low, thereby having higher input costs perunit of output produced. Whereas, since a flexible system is dealing with variety, it may beable to better cope with uncertainty of demand, thereby having higher capacity utilization inreal terms leading to higher productivity by way of less inputs per unit of output.
Thus, from the above discussion it can be concluded that though the apparentproductivity of a less flexible system may be higher than a more flexible system in a stableenvironment, in real terms the situation would be reverse in an uncertain and dynamicenvironment, i.e. the real productivity of a more flexible system is expected to be higher thana less flexible system from both the points of the view of the output and the input.
SushilEditor in Chief
Guidelines for Authors
Global Journal ofFlexible Systems Management
giftjourn@lAimThe journal is intended to share concepts, researches and practicalexperiences to enable the organizations to become more flexible (adaptive,responsive, and agile) at the level of strategy, structure, systems, people, andculture. Flexibility relates to providing more options, quicker changemechanisms, and enhanced freedom of choice so as to respond to thechanging situation with minimum time and efforts.It is aimed to make the contributions in this direction to both the world ofwork and the world of knowledge so as to continuously evolve and enrichthe flexible systems management paradigm at a generic level as well asspecifically testing and innovating the use of SAP-LAP (Situation- Actor -Process-Learning-Action-Performance) framework in varied managerialsituations to cope with the challenges of the new business models andframeworks. It is a General Management Journal with a focus on flexibility.ScopeThe Journal includes the papers relatingto: conceptual frameworks, empiricalstudies, case experiences, insights,strategies, organizational frameworks,applications and systems,methodologies and models, tools andtechniques, innovations, comparativepractices, scenarios, and reviews.The papers may be covering one or manyof the following areas: Dimensions ofenterprise flexibility, Connotations offlexibility, and Emerging managerialissues/approaches generating anddemanding flexibility.CoverageThe journal is organized into varioussections to include following types ofcontributions: Research papers, Shortnotes/correspondence, Applicationsand case studies, Book reviews, Booksummaries, Interviews and round tables,Information about relevant conferencesand seminars, Educational and learning experiments, and any other relevantinformation related with the theme of the Journal.Manuscript SubmissionManuscript should be submitted to the Editor-in-Chief at the address:Prof. Sushil, Department of Management Studies, Indian Institute ofTechnology Delhi, Hauz Khas, New Delhi-110 016, Ph: 91-11-26591167,Fax: 91-11-26862620.It is preferred to have electronic submission through web to avoid delays.Please submit the “word” file attached to email on the following address:[email protected] At the time of final submission, anautobiographical note and a passport size photograph of all the authors willbe required.CopyrightThe submission of paper to giftjourn@l implies that the paper is original andnot submitted elsewhere for publication. Copyright for published paperswill be vested in the publisher i.e. GIFT, and authors should complete astandard publishing agreement, which will be supplied with final proofs. Itis the author’s responsibility to obtain written permission to reproducecopyright material.LanguageAll papers will be published in English and manuscripts must be submittedin that language.Reviewing ProcessEach paper is reviewed by the editor and if it is judged relevant forpublication, it is than sent to referees for double blind peer review. The
Checklist* The paper is original, not submitted anywhere else.* The length of the paper is commensurate with content.* The title and headings are brief and catchy.* The author(s) name and affiliation are given only on cover page.* Abstract and keywords are provided.* Focus on flexibility in management is kept.* The paper incorporates innovative ideas/models in a practical
framework.* Mathematical models, if any, are given in Appendix.* Tables/Figures are properly placed and numbered with brief
titles/captions.* References are in standard style.* Few highlights (8-10) of two-three lines are provided to put in
boxes.* Few key variables (3-5) are identified for flexibility mapping on
a continuum.* Some key questions (2-3) are provided to reflect the applicability
in real life.
papers are reviewed for relevance, focus on flexibility, innovation, practicalconsiderations, quality of evidence, contribution, methodology, readability,and organization. Based on the recommendations of the referees, the editorthen decides whether the paper should be accepted as it is, to be revised orrejected. The reviewing time will normally be 10-12 weeks.Manuscript RequirementsLength: No maximum length for a paper is prescribed, however, authorsshould write concisely.Title: The title should be brief and typed on a separate sheet.Format: The paper should have a cover page giving title, author’s name,complete address, telephone number, fax number, and email of the author.In case of co-authors, these details should also be provided for each co-author. Correspondence will be sent to the first named author unlessotherwise indicated.
The second page should contain the title and an abstract of 100-150words. It should also include upto eightkeywords about the paper. The authorsmay attach the category sheet to definethe relevant categories to which thepaper belongs (available on the website-www.giftsociety.org.). The second pageshould not include the authors name.The paper should begin from the thirdpage.Headings: should be short clearlydefined, and numbered.Footnotes: should be used only whenabsolutely necessary and must beidentified in the text by consecutivenumbers placed as superscript.Text: The main text should be morereadable and mathematical models, ifany, should be provided in Appendix.The ideas proposed should preferablybe supported by real life case examplesfrom business situations.Tables and Figures: All tables and
figures should be kept to a minimum and numbered consecutively usingarabic numerals. Each table should have a brief title written on the top ofthe table, and each figure should have a brief caption written on the bottomof the figure.Photos and Illustrations: must be supplied as good quality black and whiteoriginal with captions. Their position should be shown in the text by typingon a separate line the words “take in Plate n”References: to other publications must be in standard style. That is shownwithin the text as the author’s name followed by a comma and year ofpublication, all in round brackets, e.g. (Volberda, 1997). At the end of thepaper a reference list in alphabetical order must be given as follows:For books: Surname, initials, (year) title, publisher, place of publication.e.g. Mckenzie J. (1996) Paradox: The New Strategic Dimension, McGraw -Hill,Berkshire.For journals: surname, initials, (year) title, journal, volume (number), pages.e.g. Volberda H.W. (1997) Building Flexible Organization for Fast MovingMarkets, Long Range Planning, 30 (2), 169-183.ProofsPage proofs for correction of printer’s errors only will be sent to the authorspecified on the typescript. Proofs should be returned to the printer withinthe specified time period.OffprintsTwenty offprints of each paper will be provided free of charge to theprincipal author. Additional copies may be purchased on an offprint orderform, which will be sent to authors along with proofs.
Complimentary MembershipAll authors, whose papers will be published in giftjourn@l , will be offered one year complementary membership of GIFT.
GIFT Best Paper AwardEvery year one best paper award will be conferred based on evaluation of refrees which will consist of cash award of US$ 500 and
complimentary life membership of GIFT equivalent to US$ 500.
1
© 2003, Global Institute ofFlexible Systems Management
A Decision Support System for Flexibility in ManufacturingBoppana V. Chowdary
Department of Mechanical and Manufacturing EngineeringThe University of the West Indies
St. Augustine, Trinidad and Tobago, West [email protected]
Arun KandaDepartment of Mechanical Engineering
Indian Institute of Technology Delhi
AbstractPerformance modeling and evaluation of manufacturing systems help decision makers at higher levels to conduct an economicfeasibility analysis for expansion/diversification of the system. Manufacturing system design, with flexibility and related issues, isa complex phenomenon, which is concerned with the selection from a wide variety of available system configurations andcontrol strategy alternatives in the light of several criteria (flexibility, quality, productivity, costs etc.), many of which are difficultto quantify. For evaluation and selection of manufacturing systems here an attempt has been made through a decision supportsystem by developing and combining models such as integrated manufacturing performance measurement, multi-criteria evaluationand ranking, and a knowledge based expert system approaches. The usefulness of the proposed decision support system forflexibility in manufacturing is demonstrated through a sample session.
Keywords : flexibility, FMDSS, productivity, quality
giftjourn@lGlobal Journal ofFlexible Systems Management2003, Vol. 4, No. 3, pp 1-13
Introduction
Performance modelling and evaluation of flexiblemanufacturing systems (FMS) helps decision makers athigher levels to conduct an economic feasibility analysis forexpansion/diversification of the system. Also, this could helpin installing a new manufacturing system with a substantialreduction in the number of machines, floor space, inventorylevel, throughput and lead time and also high qualityproducts, with a greater flexibility to respond to the marketneeds (Kakati and Dhar, 1991). Flexible manufacturingsystems design is a complex phenomenon, which isconcerned with the selection from a wide variety ofavailable system configurations and control strategyalternatives in the light of several criteria (flexibility,quality, productivity, costs etc.), many of which are difficultto quantify (Borenstein et al., 1999).
Justification and implementation of advancedmanufacturing technology (AMT) involve decisions that arecrucial for the practitioner regarding the survival of businessin the present day uncertain manufacturing world. Sinceadvanced systems require huge capital investments and offerlarge number of intangible benefits such as flexibility,quality, competitiveness, customer satisfaction etc., whichare ill structured in nature and sometimes very difficult toquantify. Basically, the justification and implementation ofAMT is a very difficult question to answer because:
l Profitability and survival of a manufacturing firm dependsupon accommodating fluctuating product demands, day-to-day technological advancements, and competitionfrom and among different firms. Flexibility plays a vital
role for operation in such a scenario. To meet theobjective, various manufacturing flexibilities need to bemeasured to evaluate and select a desired flexiblemanufacturing system.
l Organizations should act to improve performance incritical areas. To help in such decision-making, anintegrated manufacturing performance measurement interms of both well structured costs like productivity andill-structured costs like quality and flexibility is essential.This would help in, planning of business strategy atthe strategic level, decision-making regardingimplementation of AMT projects, and competitivedisposal of individual products at the global market.
l To evaluate different manufacturing alternatives underunpredictable market environments, changes in productdesign, demand, and mix, a system for differentmanufacturing scenarios under conflicting multi-objectives is required.
l Selection of flexible machining centres using aknowledge based expert system will ease the process ofjustification and implementation of advancedmanufacturing systems.
Thus, it can be argued that such justification andimplementation decisions are unstructured and calls fordecision support systems (DSS) approach that assistsmanagement in translating information in to effective actionsfor the organization. Over the many years of research andapplication around the world, the benefits of DSS, haveclearly manifested through huge tangible returns as profitsor cost savings to the organization.
DecisionSupport System
2
giftjourn@l
Boppana V. Chowdary and Arun Kanda
The organization of the paper is as follows. Section 2gives a brief review of justification approaches. Section 3describes developments of the FMDSS. Section 4 presents asample session. In the last section it gives the discussionand conclusion.
A Review of Literature
Manufacturing system evaluation, design and selectionissues, have developed considerably over the past 3 to 4decades. On the modelling side, emphasis has shifted frommodelling conventional manufacturing systems to modellingof automated systems due to uncertainty in product demandand day to day technological developments. The spirit ofthese attempts is to justify the installation of AMT eitherin phased manner or total.
Son and Park (1987) propose a procedure to quantify andcombine three total performance measures into a singleunified measure, i.e., integrated manufacturing measure(IMP) from productivity, quality and flexibility along witha hypothetical case example, which indicated that theadaption of a FMS improved the integral manufacturingperformance, compared to a conventional system. Hutchinsonand Sinha (1989) enumerated a decision theoretic approachto evaluate a manufacturing system to meet the demand bothfor cost and flexibility with an example. The study of Beachet al. (1998) highlights the importance of manufacturingflexibility, which states that“the desire to exploit newprocess technology and theneed to reduce costs andthroughput times, to acceleratenew product introductions, and to insure against marketuncertainties have contributed to the increased importancemanufacturing enterprises attach to manufacturingflexibility”.
As shown in the studies of Son and Park (1987), theevaluation of manufacturing systems through an integratedmanufacturing performance measure is one of the uniquelyidentified procedures. But the coverage of a number offlexibilities is limited. The number of flexibilitiesconsidered for evaluating a flexible manufacturing systemor an automated factory of future may not be adequate. Therole of performance modelling is to aid this decision-makingin an effective way. During the design and planning stages,performance modelling can help in deciding the number andtype of machines, number of material handling devices,number of buffers, number of fixtures, best possible layout,and part type selection (Stecke, 1985). Progress in themanufacturing sector has been triggered by timelyintroduction of new technologies. Hence the selectionproblem of appropriate manufacturing systems becomes amajor design issue at a strategic level for system designers.
The selection of a manufacturing system to suit aparticular production environment from among the largernumber of available configurations has become a difficult
task. Various considerations such as product design, choiceof equipment, flexibility, and economics need to beconsidered before a suitable manufacturing systemconfiguration or machining centre can be selected. In thisaspect, the literature review exercise has been divided intotwo sub groups. (i) selection of user desired manufacturingsystem configuration and (ii) selection of advancedmachining centre or facility and is presented below.
Selection under Multi-Criteria Decision MakingEnvironment
A characteristic of most of the formal techniques that havebeen used for decision-making is the selection of the bestalternative with respect to a certain figure of merit.Tabucanon (1988) proposed a conceptual model of decision-making in industrial systems suitable for social, technical,and economic objectives. He also listed severaltechnological, economic, ethical, political, legal, and socialfactors that affect an organization. Multi-criteria decision-making (MCDM) refers to making decisions in the presenceof multiple, usually conflicting criteria in complex andunstructured situations. MCDM can be defined as theprocess of decision-making in the selection of an act orcourses of action from among alternative acts or courses ofactions such that it will produce optimal results under somecriteria of optimization. In precise terms criteria are
considered to be 'strictly'conflicting if the increase insatisfaction of one results in adecrease in satisfaction of theother. A conflict may arise due
to intrapersonal and interpersonal reasons. The processrequires the decision makers to develop a hierarchicalstructure of the problem, identifying the relative importanceof each of the criteria, specifying a preference for eachdecision alternative with respect to each criterion in the formof a prioritized ranking so as to arrive at overall preferencefor each of the decision alternatives.
Stam and Kuula (1991) developed a visual interactivedecision support framework, to aid the decision maker inselecting the most appropriate technology and design whenplanning an FMS. Their work was divided into two phases.The first phase, namely, prescreening phase, used thequalitative and quantitative criteria and are used to narrowthe set of alternative system configurations underconsideration down to a small number of most attractivecandidates. In the second phase, multi-objectiveprogramming was formulated for each of the remainingconfigurations to explore and evaluate the costs and benefitsof various different scenarios for each configuration. Stamand Kuula (1985) developed equations to various multi-criteria like production, cost and flexibility with in thesystem-dependent machine time constraints under FMSdesign environment. Significant contributors in this MCDMfield include Steuer (1985), Gupta, Evans and Gupta (1991);Stewart (1992); Mollaghasemi and Evans (1994); Kim, Chan
Advanced systems require huge capitalinvestments - gives intangible benefits which aredifficult to quantify.
3
© 2003, Global Institute ofFlexible Systems Management
A Decision Support System for Flexibility in Manufacturing
DSS provides tangible benefits as profits orcost savings.
and Yoon (1997); Parkan and Wu (1998); Parkan and Wu(1999) and Chang and Yeh (2001). Inclusion of multi criteriain the framework of DSS can be seen in the studies ofKorhonen, Moskowitz, and Wallenius (1992); and Rao andDeshmukh (1997).
Selection of Advanced Machining Centre throughArtificial Intelligence Techniques
In developing countries, the right machine could be verydifferent from the one suited for the developed countries.So decision-making in the area of advanced machining centreselection is affected by the ongoing development of newtechnology, practices and machines having enhancedcapabilities and complex characteristics. Further it isunderstood that the specific problem of advanced machiningcentre selection is a knowledge-intensive and complicatedtask due to the presence of many feasible non-determinedalternatives, and the need to satisfy multiple and possiblyconflicting objectives. Machine selection influences itsoperational capabilities in terms of various part designfeatures, various performance measures set by the customerand then cost. The elicited hierarchy (Wick, 1979, Vermaand Kumar 1989) in selection of a machining centre is asuitable working length, working diameter, achievabletolerance, number of axes, number of tool stations, price,level of available power, speed, and automatic swarfdisposal. Hence, machining centre selection procedure is acomplex and unstructured, hence,special attention is required tomeet the varying customerrequirements in the market.
The selection of machining centre is a typical designproblem. It is frequently unstructured, characterized byextensive domain dependent knowledge, and requiressubstantial expertise, making it an ideal candidate for theapplication of expert systems. Apart from multi-attributedecision-making models discussed earlier, expert system isalso a valid tool for dealing with the problem of selectionof machining centres. A brief review of literature in this areais now presented.
Knowledge Based Expert Systems
Artificial intelligence (AI) gained popularity in the late1960s. Since then it has experienced considerablemomentum. Expert Systems, one application of AI, haveachieved considerable success in recent years. Specialists inindustrial and production engineering are beginning to takeinterest in expert systems as a means of solving problems intheir domain. Several prototype systems are being built inthe areas of manufacturing, facilities layout, maintenanceand fault diagnosis. Malmborg (1989) described amicrocomputer based, expert system for selection ofindustrial trucks. Rambabu and Murthy (1989) has workedon the problem of optimum design of the machine layoutfor an FMS using knowledge based expert systems (KBES)approach, whereas, Shivathaya and Fang (1993) developed
an expert scheduling system for tool room operations (whichcan be used on-or-off-line) through if-then rules. The KBESconcept had been applied to various areas such as materialsselection (Ram et al., 1989), scheduling of FMS (Rambabuand Murthy, 1989) acceptance sampling (Reddy and Murthy,1989), process planning (Ajmal, 1989) design of FMS(Borenstein, 1998, Borenstein et al 1999), design of materialhandling equipment selection system (Chan, 2002), and alsofor other areas related to AMS (Jain and Chandwani, 1989,Rambabu 1997, Rambold 1989). The use of expert systemsfor the selection of a flexible machining centre thus seemsa promising area for research.
It is apparent from the literature that evaluation andselection of manufacturing systems is a problem specific,unstructured and involves large number of multipleattributes. Developing and combining modules such asintegrated manufacturing performance evaluation, multi-criteria evaluation and ranking; and knowledge basedmachining centre selection approaches can deal with it. Inthis context, a decision support system for flexibility inmanufacturing (FMDSS) for evaluation and selection ofmanufacturing system is developed and demonstrated here.A brief description of the heuristics used in the model basesuch as the models for evaluation of integratedmanufacturing performance, multi-criteria evaluation ofmanufacturing configurations, and knowledge based expert
system for the selection of aflexible machining centre isgiven in Table 1. The proposedFMDSS and its capabilities
through a sample session are provided in the followingsections.
Development of the Decision Support System forFlexibility in Manufacturing (FMDSS)
Decision support system is an aid that assists managementin translating information in to effective actions for theorganization. It may be said that the deployment of a DSSrepresents the engineering of managerial decision-makingprocess to meet the challenges posed by demandingconstraints and objectives in a complex environment. Overthe many years of research and application around the world,the benefits of DSS, have clearly manifested through hugetangible returns as profits or cost savings to the organization.
A decision support system for handling of flexibility andrelated issues in manufacturing should possess thecharacteristics like simple to use, with an ability to evaluatethe system in terms of both quantitative and qualitative keyperformance measures, such as flexibility, productivity, andquality. It should also have the ability to integrate variousperformance and operational aspects in a modular fashionso that evaluation and selection of manufacturing systemsbecomes easy. Also, the DSS should have the ability toaccount for individual preferences, and permit the use ofsystem by any user. Some of the developments in the areaof DSS are now explained.
4
giftjourn@l
Son (1991) developed an integrated decision supportframework for economic justification of factory automationproject and demonstrated it through a real application. Raoand Deshmukh (1997) developed a decision support system(DSS) for selection and justification of advancedmanufacturing technologies. Also, this study says thatselection and justification of AMT are unstructured andshould consider other issues such as economic, analyticaland risk factors in a decision support environment. Asummary of literature in the area of DSS applied tomanufacturing is presented in Table 2. The listed literature(in Table 2) shows that decision support systems have beenapplied for different applications such as productionplanning, production control, production management,project analysis and for justification of advancedtechnologies. These studies lead to develop a new DSS
Table 1: Description of Heuristics used inModel Base of FMDSS
Heuristic Used Description
1. For Evaluation of System Performance
i) Total productivity (TP) Total productivity measure ismeasure computed primarily from various
partial measures of productivitysuch as labour, capital, equipment,material, and overhead
ii) Total quality (TQ) Computed from product failure,measure process failure, and appraisal costs
of quality
iii) Total flexibility (TF) Computed based on various partialmeasure flexibilities such as product, process,
demand, and equipment.
iv) Integrated manufacturing Integrated measure of TP, TQ, andperformance measures TF for existing and proposed(IMP, RIMP) approaches
2. Multi-criteria Evaluation and Ranking
i) Simple additive weighting To compute weighted alternativesmethod (SAW) for ranking of manufacturing
system configurations using simpleadditive weighting method
ii) Hierarchical weighting To compute composite vector ofmethod (HAW) manufacturing system configura-
tions for ranking using hierarchicaladditive weighting method
iii) Elimination et Choice Pair-wise comparison of alterna-Translating Reality tives based on the degree to whichMethod (ELECTRE) evaluation of alternatives and
preference weights confirm orcontradict the pair-wise dominancerelationships among the alternatives
iv) Technique For Order Ranking of manufacturing systemPreference By Similarity alternatives based on the concept ofTo Ideal Solution Method shortest distance from the ideal(TOPSIS) solution and the farthest from the
negative ideal solution
3. Knowledge based for selection of a machining centreexpert system (KBFMS) Intelligent selection of a
machining centre based on userspecified features like shape, size,investment, and control system.Through data base, knowledgebase, and inference engine (adaptedfrom Chowdary, 1997).
Legend:IMP - Integrated manufacturing performanceRIMP - Revised integrated manufacturing performance
Author(s), Year DSS Application
Janos and Temesi (1988) Production control undermultiple criteriadecision-making
Wu and Tabucanon (1988) Production management
Qingwen and Yingchu (1988) Multi-objective projectanalysis
Chidambaram and Rambabu (1989) Production planning
Ravichandran and Design of FMSChakravarty (1989)
Son (1991) Factory automation
Stam and Kuula (1991) Design of FMS
Ashfaq (1991) Selection of processparameters in milling
Aly and Subramaniam (1993) Design of FMS
Rao and Deshmukh (1997) Selection andjustification ofautomation technologies
Ozdamar, Bozyel, and Birbil (1998) Production planning
Table 2 : Literature on DSS Applicationto Manufacturing Problems
Justification and implementation advanced manufacturingtechnologies involve decisions that are crucial forthe practitioner regarding the survival of business inthe present market environment. Since advancedsystems require huge capital investments and offer largenumber of intangible benefits such as flexibility, quality,productivity, customer satisfaction etc., which areill structured in nature and hence complex to quantify.But traditional justification approaches are insufficientto justify advanced technologies (Rao and Deshmukh,1997).
framework for evaluation and selection of manufacturingsystems in this paper.
From the literature it is clear that design and selectionof manufacturing systems is a complex process involving alarge number of key system performance measures becauseof which the evaluation of a manufacturing system problemis tend to unstructured. By combining economic andsubjective attributes, a decision maker will have greateropportunity to evaluate and rank the flexible manufacturingsystem under a multi-criteria environment. In addition to thisa knowledge based expert system will further strengthen thedecision process in selection of a flexible machining centrefor design of flexible manufacturing systems. Byincorporating all these features a decision support systemfor flexibility in manufacturing (FMDSS) is proposed in thispaper.
Boppana V. Chowdary and Arun Kanda
5
© 2003, Global Institute ofFlexible Systems Management
Architecture of the Proposed System
The development of the FMDSS has been taken up in amodular manner. The major components of the proposedsystem are: data base, knowledge base, and model base.The architecture of the proposed FMDSS is presented inFigure 1 and each module dealt in detailed in the followingsections.
IFpremise(s)
THENconclusion(s)
For example a rule for selection of a machining centrebased on job shape is:
IF(The Job Shape is Plate Type) AND(The Operations to be Performed are ofBoring Operations)
THEN(Select Vertical Type Machining Centre)
Model Base
The model base contains the models, namely, heuristics formeasurement of partial and total measures of productivity,quality, flexibility, and integrated performance measure. Italso comprises of various multi-criteria evaluation modelsfor selection of manufacturing configurations apart from aknowledge based expert system for selection of a flexiblemachining centre.
The flexibility measure of each type is computed toarrive at the resultant total flexibility measure. Eachflexibility type under each level is connected with the
performance measures namely totalproductivity and total quality tocontribute towards the total systemperformance measure. The total
productivity (TP), total quality (TQ), and total flexibility(TF) measures are used to derive the RIMP measure. Thepartial flexibility measures are computed in terms of costfactors. The procedure for arriving at RIMP is presented inAppendix A.
Based on the structure of the problem and theinformation available, we consider four well known andcommonly used multi-attribute value theory-based MADMmethods (Hwang and Yoon, 1981) suitable for obtaining anoverall cardinal ranking of manufacturing configurations.These methods are (a) the simple additive weighting (SAW)method, (b) the hierarchical weighting (HAW) method, (c)the elimination et choice translating reality (ELECTRE)method and (d) the technique for order preference bysimilarity to ideal solution (TOPSIS) method. The basic logicof SAW is to obtain a weighted sum of the performanceratings of each alternative over all attributes. In HAW,composite vector for ranking of manufacturingconfigurations is computed based on hierarchical additiveweighting method. ELECTRE logic uses the degree towhich evaluation of alternatives and preference weightsconfirm or contradict the pair-wise dominance relationships.TOPSIS is based on the concept that the most preferredalternative should not only have the shortest distance fromthe positive ideal solution, but also have the longestdistance from the negative ideal solution. For more details
Role of performance modeling is tomake decision-making effective.
Figure 1 : Proposed Decision Support System for Flexibilityin Manufacturing (FMDSS)
Data Base
The data base will contain the data items such as flexibility,quality, productivity, decision matrix for selected attributes,weights vector (to reflect the customer's preferences), andknowledge base. Data regarding a machining centre featuresneeds to be referenced in the operation of the expert system.This sub module is created usinglinked list structure with the detailsof machining centre type, job size,weight, and price. A user interfaceprobes the data base files whenever required during theconsultation session.
Knowledge Base
The technical knowledge about the manufacturing systemand the logic used by successful practitioners in selectingthe appropriate machining centre must be captured into thesystem. This becomes a knowledge base. The knowledge,which a system designer uses in selecting a flexiblemachining centre, is vast and complex. Knowledge aboutthe selection of a flexible machining centre can be obtainedfrom literature (Wick, 1979, Verma and Kumar 1989), byinterviewing experts in that specific domain, and byobserving the experts at work.
In the present study, the knowledge representation hasbeen carried out through a combination of declarativeknowledge, which includes the machine tool facts andprocedural knowledge, which consists of the rules formachining centre selection. The rules are expressed in thestandard if -then format and are used to represent relationshipbetween facts and the kind of inference used in forwardchaining. The rule based expert system is selected in thepresent machining centre selection system because of itsmerits like built in hierarchy, dynamic representation andease of implementation. A generic rule may, therefore, bestated as
A Decision Support System for Flexibility in Manufacturing
6
giftjourn@l
DSS assists management in translatinginformation into effective actions.
on these methods, the reader has been referred Hwang andYoon (1981).
Inference Engine : The dialogue base facilitates the userinterface to traverse through the decision-makingenvironment. The capability to apply the machine toolknowledge and planning logic contained in the knowledgebase is the problem solving procedure known as inferenceengine (IE). The IE manages the sequence of reasoning,interpreting the machining centre facts and selection rulesand determining the sequence of rules activation. In thepresent expert system model, the inference process is carriedthrough a forward chaining rule. The format of forwardchaining rule used in the process is
IF Premise(s) THEN
Conclusion
The KBFMS contains threeprincipal inference modules (i)classification of machiningcentres, (ii) an exact/close machining centre selectionmodule, and (iii) advising module. Based on the dependentrules created in the knowledge base, the first module willclassify the machining centres by extracting the centre nodeinformation from the data base i.e. it will group all themachining centres which fall or satisfy all the dependentrules. This forms the basis for selecting a close machiningcentre through the next module. The exact/close machiningcentre selection module will try to match the centresinformation that is grouped in the above module with theinformation taken from the user. If there is exact matchingit will suggest the corresponding best centre. If exactmatching fails then this module will suggest a closemachining centre as per the requirements of the user withinpermissible limits, which can be specified for each nodewhile building the data base. An advising module providesthe message by interacting with the user and the system. Themessage is in the form of suggested exact/close machiningcentre along with machine features if there is matching ofuser information with the classified centres either exactly orclosely. Otherwise it will direct the user to try again foranother centre.
The knowledge based expert system has an interface withthe user where the expert system seeks certain informationabout the problem. Based on the information the expertsystem tries to match the information available in theknowledge base and fact base. The analysis will be carriedout depending on the closeness of the match.
This module in FMDSS gathers all the user specifiedinformation both in qualitative and quantitative form. Thisinformation is provided as new facts to the system and helpsthe inference engine in computing system performance,multi-criteria evaluation and ranking of manufacturing
configurations, and selecting a close machining centre. Thesalient features of data base and model base of the proposedFMDSS are depicted in Table 3. FMDSS requires thefollowing information at the data base level:
l details of productivity cost elements (CL, CR, COH, CC )
l details of quality cost elements (OT, CP, CF, CA )
l details of flexibility elements (CL, CiR, COH, CC, CP, CF,CA, CIC, COB, CCF, CTP, CW, CS, CR, CID, CMH, CCF, CIPC,CPR, CIN)
l details of alternative system configurations and attributes(decision matrix and weights vector)
l preferences/weightage vector to reflect the attitude of theuser
l facts and rules relating with flexible machining centre(data base, knowledge base)
The underlying logic of the modular FMDSS and thefunctional details of variousmodels are presented inFigure 2. All the models (referTable 1) used in developing the
FMDSS are integrated using interactive menus. The mainmenu of FMDSS is as given in Appendix B1.
Figure 2 : Decision Support System for Flexibilityin Manufacturing (FMDSS)
The sub-levels (such as total productivity, total quality,total flexibility, and integrated performance evaluation) ofmodule 1 are as shown in Appendix B2. All these levelstake inputs from the existing manufacturing system such asoutput of the system, cost elements relating with various
Boppana V. Chowdary and Arun Kanda
7
© 2003, Global Institute ofFlexible Systems Management
system performance measures like productivity, quality andflexibility. This module computes various total performancemeasures such as total productivity (TP), total quality (TQ)and total flexibility (TF) and revised integratedmanufacturing performance measure (RIMP).
Module 2 evaluates the identified alternative configura-tions under multi-criteria environment. This module hasfour sub modules (SAW, HAW, ELECTRE and TOPSIS) asshown in Appendix B3. Each sub-module will evaluate andrank the alternative configurations as per the user'spreference.
The selection process of a machining centre is a complexproblem as it is influenced by many parameters such as jobshape, design features, accuracy required, tool requirements,cost etc. In this study, the machining centre selectionproblem is based on the criteria such as (i) flexibility, (ii)quality, (iii) productivity, and (iv) cost. The rationale inselecting these criteria is based on the opinions ofresearchers, and informationfrom machine tool brochures, andtechnical reports. Theconstituent elements of theknowledge base and the selected criteria for selection of aflexible machining centre are presented in Table 3.
Flexibility Criterion: Under the flexibility criterion,machine, control and program flexibilities are considered asoptions, which are created in the knowledge base. Eachflexibility option follows with rules/facts, which influencethe selection process. For example, machine flexibilitydepends upon the capability of handling of various jobshapes and number or nature of operations it can perform.An example rule in this regard is
IF (Job Shape is Multi Sided) AND(Operations to be performed are of ALL type) AND(Type of Control System required is CNC)
THEN (Select Centre = Horizontal Type)
The remaining flexibility options and the associated rulesidentified are presented in Table 3.
Quality Criterion: The quality level of a product has beendivided into three categories: very high, high, and average.Classification of the quality as 'very high' depends upon thecharacteristics such as minimum accuracy that can beachieved from the machine, and flexibility to modify thecontrol functions (if it is a CNC Machine). These two rules,which are important in the selection of advanced machiningcentre based on the quality criterion, can be explainedfurther with respect to their dependent rules (alternatives)presented in Table 4. For example,
011 OT, CL, CR, COH, CC P1, P2, P3, P4; TP
0121 OT, CP, CF QP, QF; TQ
0122 OT, CP, CF, CA QP, QF, QA; TQ
0131 OT, CI, CSU, CW, CI FE, FP, FS, FD; TF
0132 OT, CIC, COB, CI, CCU, FD, FM, FV, FC, FP, FEX,
CSU, CA, CW, CS, CR, FS, FM, FR, FE, FMU,
CID, CMH, CCF, CIPC, FPR, FID, FC, FPD; TFCPR, CIN
0141 OT, CL, CR, COH, CC, TP, TQ, TF, RIMP
CP, CF, CI, CSU, CW,CINV
0142 OT, CL, CR, COH, CC, TP, TQ, TF, RIMPCP, CF, CA, CIC, COB,
CCF, CTP
021 * Decision Matrix * Comparable Numerical(for Matrixselected * Weights Vector * Weighted Alternativesattributes)
022 * Decision Matrix * Consistency Matrix(for * Weights Vector * Composite Vectorselectedattributes)
03 Machining Centres Inference EngineInformation* Data Base* Knowledge Base
Table 3 : Data Base and Model BaseDetails of FMDSS
Data Base Model Base
LegendOT = System Output
CL = Labour Cost
CR = Raw Material Cost
CP = Prevention Cost
CA = Appraisal Cost
COB = Cost of Obsolete Products
CCU = Cost of Additional Tooling for Capacity Utilization
CA = Additional Cost of Infrastructure for Expansion
CW = Parts Waiting Cost
CS = Cost of Additional Setup
CIE = Idle Cost of Equipment
CPR = Cost Incurred Due to Frequent Changes in Production Programs
CTPC = Total Production Cost
CIN = Investment Cost for Information Processing
CR = Additional Cost Incurred due to Rerouting
CNH = Additional Material Handling Cost
CCF = Cost of Controlling
CC = The Service Cost ofusing Invested Capital
COH = Overhead Cost
CF = Failure Cost
CSU = Cost of Setup
CIC = Investory Costs of Finished Products and Raw Material
CI = Infrastructure Cost Incurred to Produce Break-even Volume
TP = Total Productivity
TQ = Total Quality
TF = Total Flexibility
RIMP = Revised Integrated Manufacturing Performance
DSS should be simple to use, able to evaluate thesystem both qualitatively and quantitatively.
A Decision Support System for Flexibility in Manufacturing
8
giftjourn@l
IF (Control System Type = Advanced) AND(Tool Monitoring System required is ofExpert System) AND(Positional Accuracy = 0.0015)
THEN (Select Centre = CNC Type Centre)
Productivity Criterion: Each machining centre possesses itssignificance depending on the functional features. Amachining centre could havedifferent benefits such as reductionin set-up for job and tool, andreduction in material handlingefforts. This criterion should be able to discriminate betweenalternative machining centres based on the presence of suchfeatures. This criterion incorporates these rules and likewiseone can develop several dependent rules. For example, arule under this criterion is
IF (Setting Effort = Automatic Pallet Changer) AND(Tool Changing Time = 6 seconds) AND(Number of Tools = 48)
THEN (Select Centre = Centre having two Pallets)
The sub-menus of this module are depicted in AppendixB4. The structure used for creation of the knowledge baseis very flexible so that the user can add more criteria to it.The robustness of the proposed knowledge base structure istested through a 'cost' based criterion and is demonstratedin the sample session.
Salient Features of the FMDSS
The user is provided with wide scope to evaluate themanufacturing system performance, multi-criteria ranking of
Table 4 : Summary of Selected Criteria and their Details
Criterion Options Rules DependentRules
Action Value Match TypeParameter* Node*
Flexibility Machine Shape Plate Type Vertical Machiningor or centre typeMulti-sided Horizontal Machining
Centre
Operation Tool effort ATC Possible Fexpan Toolmaz
Program Control System CNC Advanced Control ControlSystem Type System Type
Quality Very High(0.0008-0.001) Control System CNC Advanced Control Control
System Type System Type
High(0.00030- 0.00079) Control System CNC Advanced Control Control
System Type System Type
Average(0.0001-0.00029) Control System CNC Advanced Control Control
System Type System Type
Productivity High(151-200%) Tool Effort ATC Possible Future expansion Tool Magazine
Medium(101-150%) Tool Effort ATC Possible Future expansion Tool Magazine
Average Tool Effort ATC Possible Future expansion Tool Magazine(90-100%)
Note: The numerals with in the parenthesis represent the option value fixed in the sample session* Notation followed while developing the FMDSS
manufacturing configurations and selection of a flexiblemachining centre. The salient features of the proposedFMDSS include:
l The developed FMDSS is easy to understand since mostof the input is in the form of monetary values.
l Greater emphasis on manufacturing flexibility
l Evaluation of system in terms ofboth well structured and ill-structured costs such as flexibility,productivity and quality
l Evaluation and ranking ofmanufacturing configurations under multi-criteriaenvironment
l Intelligent selection of flexible machining centre throughuser defined criteria such as flexibility, productivity andquality.
A Sample Session with FMDSS
Usefulness of the present FMDSS is demonstrated througha case situation. The case situation is taken from Chowdary(2001) as illustrated in Table 5. Input cost elements are theimportant data items (as explained in module 1) incomputing the integrated manufacturing performance.Identification of alternative configurations and formation ofdecision matrix (D) is an important task in evaluating andranking of manufacturing systems under multi-criteriaenvironment. Finally, building of data base (facts) relatingwith the latest machining centres and creation of productionrules in consultation with the experts are the twoindependent and crucial inputs under flexible machining
DSS should have ability to accountindividual preferences.
Boppana V. Chowdary and Arun Kanda
9
© 2003, Global Institute ofFlexible Systems Management
centre selection module. The procedure explained inChowdary (1997) is followed for preparation of data baseand knowledge base. A sample test run for the proposedFMDSS under selected case situation is presented inAppendix C.
Usefulness of the FMDSS
Decision support system for flexibility in manufacturing(FMDSS) may serve the needs of modern industry in termsof providing guidelines for evaluation and selectionof manufacturing systems. Therobustness of the individual modulesis tested through different casestudies and results are available withthe corresponding author. The results show that theperformance evaluation module can be used as a decisiontool to assess the performance of variety of manufacturingsituations. First, the impact of addition of a new facility ona manufacturing system was investigated. Secondly, currentand past performance of a manufacturing system wascompared. Finally, evaluation of system performance hadcarried out when there are fluctuations in the product design.
The second module aims at evaluation of amanufacturing system under multi-criteria environment,which supports the user in selection of a desiredmanufacturing alternative in terms of various costs andbenefits. This module also has been tested for quantificationof costs of quality, productivity and flexibility throughdifferent real manufacturing situations, where conventionalfacilities are in use and the managements are looking forwardfor conversion of existing systems into flexible systems.Some of the highlights of the results that are obtained fromthe module-2 of FMDSS are:
l Various production costs and operational benefits dueto relocation of an existing facility
l Multi-criteria ranking of manufacturing alternatives withoptions for routing and machine flexibilities
The third and final module deals the selection of amachining centre through a knowledge based expert system.Building of data base (facts) relating with the machiningcentres and creation of production rules in consultationwith the experts are the two independent and crucialinputs under the flexible machining centre selection module.
The utility of this module is demonstrated by assistingthe practitioner for introduction of flexible advancedmachines. This has been tested through a set of keyperformance criteria such as productivity, quality, flexibility,and cost.
Discussion and Conclusions
Decision support systems assist management in translatinginformation in to effective actions for the organization. Inany manufacturing system design and selection process,quantitative as well as qualitative factors should be takeninto account since it is a complex process and whichinvolves a number of system performance measures such asflexibility, productivity, quality, system utilization,implementation risk, and WIP inventory. For evaluation andselection of manufacturing systems here an attempt has beenmade through a decision support system by developing andcombining models such as integrated manufacturingperformance, multi-criteria evaluation and ranking, and aknowledge based expert system approaches.
The major components of the decision support systemfor flexibility in manufacturing (FMDSS) are data, model,
and dialogue bases. The data basecontains items such as flexibility,productivity, quality, decision matrixfor selected attributes, and weights
vector. The model base contains models such as integratedmanufacturing performance measurement, multi-criteriaevaluation and ranking heuristics, and an inference enginerelating to selection of flexible machining centres. Thedialogue base facilitates the user when traversing throughthe decision-making environment. The usefulness of theproposed FMDSS is demonstrated through a sample session.The developed FMDSS is expected
l to judge whether the system is capable to accommodateany changes in product design or not (Module-1 i.e.Compute System Performance).
l to evaluate a manufacturing system under a multi-criteriadecision-making environment for ranking of variousmanufacturing configurations (Module-2 i.e. Multi-criteria Evaluation and Ranking).
l to assist the practitioner for introduction of automationin a phased manner, by replacing the conventionalsystem with advanced machining centres and to help indesign a full-fledged flexible manufacturing system withgrowing adoption of AMT in developing countries(Module-3 i.e. Machining Centre Selection).
The type of exercise carried through the FMDSS here issought before investing huge amounts on automationprojects. The present study is also useful to organizationsworking with conventional systems and consideringconversion to FMC, FMS, or CIM. Some of the additionalfeatures of the developed FMDSS include:
i) It is user-friendly software and can embed theknowledge obtained from the experts.
Traditional approaches are insufficientto justify advanced technologies.
A Decision Support System for Flexibility in Manufacturing
Company Precision machine tool manufacturing
Products CNC lathe and machining centres
Distribution network Global as well as local markets
Existing machinery type Combination of NC, CNC andconventional
System's capability Cable of producing 6 and 3 modelsof first and second product typesrespectively
Company goals Maintain competitive edge byintroducing new products
Table 5 : Case Situation (Chowdary, 2001)
10
giftjourn@l
ii) It can handle qualitative as well as quantitative data.
iii) It has minimal user interaction.
Limitations
Some of the limitations presented here, if rectified by futureresearchers, will further provide guidelines for introductionof flexible manufacturing systems for improvement inproduction operations, where still conventionalmanufacturing practices are in existence. Some of thelimitations associated with the proposed FMDSS are:
i. The case studies selected for testing the robustness ofthe FMDSS are combination of traditional and semi-automated, because of which only a selective numberof flexibilities are computed.
ii. While creating the data base under the machining centreselection module the following assumptions are madedue to the non-availability of the data:
l Accuracy parameter of a machining centre is taken asthe deciding factor for selection of a machining centreunder quality criterion
l Number of pallets available within a machining centreis chosen as the selection criteria of a machining centreunder productivity criterion.
ReferencesAjmal A. (1989) Knowledge Based Expert Systems for ProcessPlanning: A Review and Its Impact on CAD/ CAM, Proceedings ofthe 4th Fourth International Conference on CAD, CAM, Robotics andFactories of the Future, Indian Institute of Technology, New Delhi,December 19-22, III, 527-536, Tata McGraw Hill, New Delhi.
R. B.R., Muhlemann A.P., Price D.H.R., Paterson A. and Sharp J.A,(1998) Information Systems as a Key Facilitator of ManufacturingFlexibility: A Documented Application, Production Planning andControl, 9 (1), 96-105.
Borenstein D. (1998) ExpertFlex: A Knowledge-based System forFlexible Manufacturing System Design, Production Planning andControl, 9 (6), 598610.
Borenstein D., Becker J. L. and Santos E.R. (1999) A Systematic andIntegrated Approach to Flexible Manufacturing Systems Design,Integrated Manufacturing Systems Design, 10 (1), 6-14.
Chang Y. and Yeh C. (2001) Evaluating Airline Competitiveness UsingMultiattribut Decision-making, Omega, 29, 405 - 415.
Chan F.T.S. (2002) Design of Material Handling Equipment SelectionSystem: An Integration of Expert System with Analytic HierarchyProcess Approach, Integrated Manufacturing Systems, 13 (1), 58-68.
Chowdary B.V. (2001) Flexibility and Related Issues in Evaluationand Selection of Technological Systems, Global Journal of FlexibleSystems Management, 2 (2), April-June, 11 - 20.
Chowdary B.V. (1997) Flexibility and Related Issues in Evaluationof Manufacturing Systems, Unpublished PhD Thesis, MechanicalEngineering Department, IIT Delhi, India.
Gupta Y.P., Evans E.W. and Gupta M.C. (1991) A Review of Multi-Criterion Approaches to FMS Scheduling Problems, InternationalJournal of Production Economics, 22,13-31.
Hutchinson G.K. and Sinha D. (1989) A Quantification of the Valueof Flexibility, Journal of Manufacturing Systems, 6 (1),47-56.
Hwang C. and Yoon K. (1981) Multiple Attribute Decision MakingMethods and Applications -A State of the Art Survey, Springer-Verlag.
Jain and Chandwani (1989) A Conceptual Model of FactoryAutomation System through Knowledge Based Systems, Proceedings
of the 4th International Conference on CAD, CAM, Robotics andFactories of the Future, Indian Institute of Technology, New Delhi,December 19-22, III, 545-552, Tata McGraw Hill, New Delhi.
Kakati M. and Dhar U.R. (1991) Investment Justification in FlexibleManufacturing Systems, Engineering Costs and Production Systems,21, 203-209.
Kim G., Park C.S. and Yoon P. (1997) Identifying InvestmentOpportunities for Advanced Manufacturing Systems with Comparative-integrated Performance Measurement, International Journal ofProduction Economics, 50, 23-33.
Korhonen P., Moskowitz H. and Wallenius J. (1992) Multiple CriteriaDecision Support-A Review, European Journal of OperationalResearch, 63, 361-375.
Malmborg C.J. (1989) EXIT: A PC-Based Expert System for IndustrialTruck Selection, International Journal of Production Research,27 (6), 927-941.
Ozdamar L., Bozyel M.A. and Birbil S.I. (1998) A HierarchicalDecision Support System for Production, European Journal ofOperational Research, 104, 403-422.
Parkan C. and Wu M. (1998) Process Selection with MultipleObjective and Subjective Attributes, Production Planning and Control,9 (2), 189-200.
Parkan C. and Wu M. (1999) Decision-Making and PerformanceMeasurement Models with Applications to Robot Selection, Computersand Industrial Engineering, 36, 503-523.
Ram J., Prasad L.V. and Rao U.R.K. (1989) Selection of Materialsfor Components, Proceedings of the 4th International Conference onCAD, CAM, Robotics and Factories of the Future, Indian Institute ofTechnology, New Delhi, December 19-22, II, 453-462, Tata McGrawHill, New Delhi
Rambabu K. and Murthy S.S.N. (1989) A Knowledge-Based Systemfor Scheduling FMS, Proceedings of the 4th International Conferenceon CAD, CAM, Robotics and Factories of the Future, Indian Instituteof Technology, New Delhi, December 19-22, II, 472-482, TataMcGraw Hill, New Delhi.
Rambabu K. (1997) Knowledge-based System for Selection of CuttingTool to be Used in Real-Time Control (On-Line Scheduling) of FMS,Industrial Engineering Journal, XXVI (7), 4-16.
Rambold U. (1989) Role of Artificial Intelligence in the Factory ofFuture, Proceedings of the 4th International Conference on CAD,CAM, Robotics and Factories of the Future, Indian Institute ofTechnology, New Delhi, December 19-22, III, 562-582, Tata McGrawHill, New Delhi.
Rao K.V.S. and Deshmukh S.G.(1995) A Decision Support Systemfor Selection and Justification of Advanced ManufacturingTechnologies, Production Planning and Control Journal, 4 (2),1-15.
Rao K.V.S., Rambabu K. and Deshmukh S.G. (1993) An IndustrialEngineering Perspective for Adoption of Advanced ManufacturingTechnologies in India, Industrial Engineering Journal, 12(10), 13-17.
Reddy C.D. and Murthy S.S.N. (1989) Expert Systems Approachfor Selection of Inspection Levels in Acceptance Sampling,Proceedings of the 4th Fourth International Conference on CAD,CAM, Robotics and Factories of the Future, Indian Institute ofTechnology, New Delhi, December 19-22, II, 519-527, Tata McGrawHill, New Delhi.
Shivathaya S.S. and Fang X.D. (1993) Expert Scheduling System forTool Room Operations, International Journal of Computer IntegratedManufacturing, 8 (4), 247-254.
Son Y.K. and Park C.S. (1987) Economic Measure of Productivity,Quality and Flexibility in Advanced Manufacturing Systems, Journalof Manufacturing Systems, 6 (3), 193-207.
Stam A. and Kuula M. (1991) Selecting a Flexible ManufacturingSystem Using Multiple Criteria Analysis, International Journal ofProduction Research, 29 (4), 803-820.
Stecke K.E. (1985) Design, Planning, Scheduling and ControlProblems of Flexible Manufacturing Systems, Annals of OperationsResearch, 3, 3-12.
Boppana V. Chowdary and Arun Kanda
11
© 2003, Global Institute ofFlexible Systems Management
Tabucanon M.T. (1988) Multiple-criteria Decision Making in Industry,Studies in Production and Engineering Economics-8, Elsevier.
Verma A. and Kumar S. (1989) Knowledgeable Expert System forFlexile Manufacturing, Proceedings of the 4th International Conferenceon CAD, CAM, Robotics and Factories of the Future, Indian Instituteof Technology, New Delhi, December 19-22, III, 603-618, TataMcGraw Hill, New Delhi.
Wick C. (1979) Machining Center Update, Manufacturing Engineering,September, 76-94.
Wu D.S. and Tabucanon M.T. (1988) Multiple Criteria DecisionSupport Systems for Production Management, Multiple CriteriaDecision Making: Applications in Industry and Society Proceedingsof the International Conference held on December 6-8, Asian Instituteof Technology, Bangkok, Thailand, 357-374.
The various partial measures of flexibilities can be given bya) Demand flexibility (F
D) = O
T / C
IC
b) Market flexibility (FM) = O
T / C
OB
c) Volume flexibility (FV) = O
T / C
I
d) Capacity flexibility (FC) = O
T / C
CU
e) Product flexibility (FP) = O
T / C
SU
f) Expansion flexibility (FEX
) = OT / C
Ag) Process flexibility (F
S) = O
T / C
W
h) Machine flexibility (FM) = O
T / C
S
i) Routing flexibility (FR) = O
T / C
R
j) Equipment flexibility (FE) = O
T / C
IE
k) Material handling flexibility (F
MH) = O
T / C
MH
l) Program flexibility (FPR
) = OT / C
PR
m) Information and Data handlingflexibility (F
ID) = O
T / C
IN
n) Control flexibility (FC) = O
T / C
CCF
o) Production flexibility (FPD
) = OT / C
TPC
The TF during a given period is given byTF = O
T / (C
IC + C
OB +...+C
TPC) … (3)
4. Revised integrated manufacturing performance measure
The revised integrated manufacturing performance (RIMP)measure in terms of TP, TQ and TF is given by
1 1 1 1
RIMP TP TQ TFor
RIMP = (TP*TQ*TF) / (TP*TQ) + (TQ*TF) + (TF*TP) …(5)
Appendix B1
Main Menu of FMDSS
1. Compute System Performance
2. Multi-Criteria Evaluation and Ranking
3. Machinning Centre Selection
4. Exit
Enter Your Selection:
Appendix B2
Sub Menu for System Performance of FMDSS
1. Compute Total Productivity (TP)
2. Compute Total Quality (TQ)
3. Compute Total flexibility (TF)
4. Perform 1, 2 and 3
5. Integrated Performance Measure
Enter Your Choice :
31. Existing
32. Proposed
51. Existing
52. Proposed
Appendix B3
Sub Menu for Multi-Criteria Evaluation and Ranking
1. SAW 2. HAW
3. ELECTRE 4. TOPSIS
Enter Your Choice :
Appendix B4
Sub-Menu for Machining Centre Selection of FMDSS
1. Data Base 2. Knowledge Base
3. User Interface 4. Quit
Enter Your Choice :
A Decision Support System for Flexibility in Manufacturing
Appendix A
Development of the Revised IntegratedManufacturing Performance Measure
1. Total productivity (TP) measure
Total productivity (Son and Park, 1987) for a given period is theintegrated measure of partial measures like labour productivity,capital productivity, material productivity and overhead productivity.
LetO
T = System output (usually expressed in physical volume, such
as pieces, tons and other measurable units).C
L = Labour cost
CC = The service cost of using invested capital
CR = Raw material cost
COH
= Overhead cost
Now TP is given byTP = O
T / (C
L + C
C + C
R + C
OH) … (1)
2. Total quality (TQ) measure
Total quality measure (Son and Park, 1987) for a given period isthe integrated measure of partial measures like prevention andfailure costs. But based on the literature and the opinion of theexperts in the field it is decided to include the appraisal quality inthe definition of the total quality measure (TQ).LetC
P = Prevention cost
CF = Failure cost
CA = Appraisal cost
Now TQ is given byTQ = O
T / (C
P + C
F + C
A) … (2)
3. Total flexibility (TF) measure
In addition to the partial flexibilities such as demand, volume,equipment, and process defined earlier (Son and Park, 1987), somemore partial measures of flexibilities in terms of monetary valuesare considered in this research. These measures are presented asbelow:
LetC
IC = Inventory costs of finished products and raw materials
COB
= Cost of obsolete productsC
I = Infra-structural cost incurred to produce break-even volume
CCU
= Cost of additional tooling for capacity utilisationC
SU = Cost of setup
CA = Additional cost of infrastructure for expansion
CW
= Parts waiting costC
S = Cost of additional setup
CR = Additional cost incurred due to rerouting
CIE
= Idle cost of equipmentC
MH = Additional material handling cost
CPR
= Cost incurred due to frequent changes in production programsC
IN = Investment cost for information processing
CCF
= Cost of controllingC
TPC = Total production cost
12
giftjourn@l
Appendix C
Sample Test Run for Demonstration ofFMDSS Decision Support System for
Flexibility in Manufacturing
Main Menu of FMDSS1. Compute System Performance2. Multi-Criteria Evaluation and Ranking3. Machining Centre Selection4. Exit
Enter Your Choice: 1
Sub-menu for system performance1. Compute Total Productivity2. Compute Total Quality3. Compute Total Flexibility4. Perform 1, 2, and 35. Integrated Performance Measure
Enter Your Choice: 5
1. Use Existing (IMP) Measure2. Use Proposed (RIMP) Measure
Enter Your Choice: 2
Input from the User
System output(millions of Rs.) =? 570.74Labour cost(millions of Rs.) =? 323.36Overhead Cost(millions of Rs.)=? 50.82Capital Cost(millions of Rs.) =? 57.07Equipment Cost(millions of Rs.) =? --Raw Material Cost((millions of Rs.) =? 49.22Cost of Prevention(millions of Rs.) =? 47.52Cost of Failure(millions of Rs.) =? --Cost of Appraisal(millions of Rs.) =? --Idle Cost of Equipment(millions of Rs.) =? 80.72Setup Cost(millions of Rs.) =? 33.26Part Waiting Cost(millions of Rs.) =? 27.72Work-in-process inventory(millions of Rs.) =? 370.98
FMDSS OutputTotal Productivity(TP)= 1.18Total Quality(TQ)= 12.01Total Flexibility(TF)= 1.11Revised Integrated Manufacturing Performance (RIMP)Measure = 0.548Are You Satisfied with the Output (Yes/No): noYou want to design a new manufacturing system (Yes/No): yes
Main Menu of FMDSS1. Compute System Performance2. Multi-Criteria Evaluation and Ranking3. Machining Centre Selection4. Exit
Enter Your Choice: 2
Sub-menu for system performance1. HAW2. SAW3. ELECTRE4. TOPSIS
Enter Your Choice: 2
Input from User
How many Criteria ? 9Number of Manufacturing Alternatives to Evaluate? 3Preference/Weights Vector: (give in row wise,also ensure that sum = 1.0)0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.05 0.05Type of Criteria ?1. Benefit type2. Cost typeEnter Your Choice: 1Criteria #1: Elemental values in Criteria #1: 8.93 7.80 7.78Type of Criteria ?1. Benefit type2. Cost type
Enter Your Choice: 2Criteria #2: Elements in Criteria #2: 0.0330 0.0296 0.0299Type of Criteria ?1. Benefit type2. Cost type
Enter Your Choice: 2Criteria #3: Elements in Criteria #3: 0.737 0.719 0.587Type of Criteria ?1. Benefit type2. Cost type
Enter Your Choice: 2Criteria #4: Elements in Criteria #4: 0.707 0.698 0.563Type of Criteria ?1. Benefit type2. Cost type
Enter Your Choice: 2Criteria #5: Elements in Criteria #5: 1253.00 1222.97 0997.90Type of Criteria?1. Benefit type2. Cost type
Enter Your Choice: 1Criteria #6: Elements in Criteria #6: 1.23 1.27 1.38
Type of Criteria?1. Benefit type2. Cost type
Enter Your Choice: 1Criteria #7: Elements in Criteria #7: 1.72 3.99 3.99Type of Criteria?1. Benefit type2. Cost type
Enter Your Choice: 2Criteria #8: Elements in Criteria #8: 1 7 7Type of Criteria?1. Benefit type2. Cost type
Enter Your Choice: 2Criteria #9: Elements in Criteria #9: 1 7 7
FMDSS OutputManufacturing Alternatives Ranking
Alternative# RankI 2II 3III 1
Are You Satisfied with the Output (Yes/No): yesYou want to select flexible/advanced machining centre(Yes/No): yes
Main Menu of FMDSS1. Compute System Performance2. Multi-Criteria Evaluation and Ranking3. Machining Centre Selection4. Exit
Enter Your Choice: 3
Sub-menu for Machining Centre Selection1. Data Base2. Knowledge Base3. User Interface4. Quit
Enter Your Choice:
Q: Which criteria would you like to base upon?1. Flexibility2. Quality3. Productivity4. Cost
Enter Your Choice: 4
Type of Investment1. Large Scale Investment: (0.45 -0.500)2. Medium Scale Investment: (0.30 -0.449)3. Small Scale Investment: (0.01 -0.229)
Enter Your Choice: 3
Boppana V. Chowdary and Arun Kanda
13
© 2003, Global Institute ofFlexible Systems Management
Input from User
Criteria: CostEnter '-' If you do not know the precise valueCentre type (ct) value: --Job shape (shape) value: plateOperational capability (opc) value: boring group of
operationsFuture expansion for MH (expansion) value: --Accuracy required (acc) value: 0.0011Control system required (cs) value: Numerical ControlType of control system value: --Number of pallets required value: --You want automatic tool changer value: --Tool magazine
no. of tools value: --future expansion value: not required
Tool capacitymaximum diameter of tool value: --maximum length of tool value: --maximum tool weight value: --tool change time value: 9
Work sizelength value: 15width value: 20height value: 15weight value: --
Travel rangex-direction value: --
y-direction value: --z-direction value: --
Spindlespeed range (rpm) value: 2000drive motor (hp) value: --
FMDSS OutputDetails of the Centre Selection are:Machining centre close to Requirements: Centre (V2)Complete Features of the selected Centre:Centre type (ct) : VerticalSuitable to : Plate Type JobsCapable to perform : Boring operationsFuture expansion for MH (expansion) : not possibleMinimum budget required :0.0594 million US dollarsAccuracy possible : 0.001 inchControl System attached : Numerical Control TypeType of Control system : Non advancedNumber of pallets attached : nilAutomatic tool changer setup : Not availableTool magazine
number of tools attached : 40future expansion for tools : Not possible
Tool Capacitymaximum diameter of tool : 4.0maximum length of tool : 12maximum tool weight : 12tool change time : 10 seconds
Work sizelength : 12width : 24height : 18weight : 300
Travel rangex-direction : 24y-direction : 12z-direction : 5
Spindlepossible speed range : (60-2000) rpmmotor power : 2 hp
A Decision Support System for Flexibility in Manufacturing
Flexibility Mapping : Practitioner's Perspective
1. What types of flexibilities you see in "DSS for flexibility in manufacturing" on the following points:
l Flexibility in terms of “options”
l Flexibility in terms of “change mechanisms”
l Flexibility in terms of “freedom of choice” to participating actors.2. Identify and describe the DSS for flexibilities in manufacturing that are relevant for your own organizational
context?
3. Try to map your own organization on following continua(Please tick mark in the appropriate box(es))
DSS
User Friendly Non-User Friendly
Performance Measure Flexibility
Evaluation Quantitatively Evaluation QualitativelyOutside
Performance Measure ProductivityEvaluation Quantitatively Evaluation Qualitatively
4. Develop a SAP-LAP (Situation Actor Process-Learning Action Performance) model of "DSS for flexibility inmanufacturing" relevant to your organization.
Reflecting Applicability in Real Life
1. Is your organization using any decision support system for flexibility in manufacturing? How would yourorganization will benefit using the proposed system?
14
giftjourn@l
In the uncertain and turbulent business environment, assessment and management of risk is key for the better businessperformance and effectiveness of any enterprise. Many researchers over time have stressed the importance of incorporatingflexibility in the formulation of business strategy as it may help to achieve better business success. Therefore, 'flexibility'assumes significance for enterprises dealing with uncertainty. In fact, both flexibility and risk are inter-linked with eachother. In general, flexibility in the systems helps in managing the risk; for example, financial flexibility of options canbe used as a hedging mechanism. However, it should be recognized that flexibility can also enhance the risk. For instance,flexibility in manufacturing and supply chain to cope with changing customer requirements may add unused capacityand thereby affect profitability and operating risk.
The purpose of this special issue is to group together high-quality research papers that lie at intersection of theissues of flexibility and risk management. Both the terms flexibility and risk are adapted in most generic sense andincludes both the service and manufacturing enterprises. The flexibility in the context of an enterprise means moreoptions, change mechanisms and freedom of choice. Some examples of the subject matter of the papers suitable for thespecial issue, inter-alia, are:
l Measurement/Implications of Business Risk, Financial Risk and Flexibility.
l Financial flexibility and Risk Management.
l Sensitivity Analysis and Risk Management.
l Financial Derivatives as Tool of Risk Management.
l Risk Management in Flexible Enterprises.
l Flexibility in Production System and its Impact On Operating Risk.
l Risk Assessment in Flexible Supply Chain System.
All manuscripts should follow the standard guidelines and will be reviewed as per the standard practice of the“International Journal of Risk Assessment & Management”.
Please submit a soft copy by e-mail to any of the two Guest Editors on the following addresses, latest byJune 30, 2004.
Guest Editors
Prof. P. K. JainDepartment of Management StudiesIndian Institute of Technology DelhiHauz Khas, New Delhi 110 016Phone: 91-11-26591199Fax: 91-11-26862620E-mail: [email protected]
Prof. SushilDepartment of Management StudiesIndian Institute of Technology DelhiHauz Khas, New Delhi 110 016Phone: 91-11-26591167Fax: 91-11-26862620E-mail: [email protected]
Call for Papers Special Issue of “International Journal of Risk Assessment & Management”
on “Flexibility and Risk Management”
15
© 2003, Global Institute ofFlexible Systems Management
Polarization of Perceptions of IT-enabled Privacy Violationsat Workplace: Impact of Respondent Position,
Peer Belief and Peer PressureNivedita Debnath
Research Scholar
Kanika T. BhalAssociate Professor
Department of Management Studies,Indian Institute of Technology Delhi
AbstractWhereas Information Technology (IT) has given us freedom to do things in more easy and flexible ways on one hand, on theother, it also given us some ethical issues to look into. One such issue is that of privacy. People’s perceptions on the issues ofprivacy and IT vary and it is important to assess how they vary. Perceived ethicality is not a normative fact, the perceptionvaries from situation to situation and individual to individual. It is a function of how the individual constructs the socialsituation. There are many factors that influence how the individual constructs and perceives a situation. This paper empiricallyassesses the role of three such factors, respondent position (as a target or an actor), peer beliefs / perception of the situation,and the tendency of an individual to give in to peer pressure. Responses of 125, undergraduate and postgraduate students, ona structured questionnaire are analyzed. Results show a significant difference in the perception of respondents when they aretarget and when they are actors. Peer perception, is related to perceived ethicality and peer pressure moderates the relationshipbetween peer perception and perceived ethicality though only for situation where the respondent is the actor.
Keywords : ethics, IT enabled, privacy, peer pressure
giftjourn@lGlobal Journal ofFlexible Systems Management2003, Vol. 4, No. 3, pp 15-20
Introduction
Information Technology (IT) has given freedom to do thingsin easier, faster and flexible ways. The use of IT has givenrise to many capabilities both immediate and derived. Tobegin with the data and information is now accessible to amuch larger number of potential users than previouslypossible. It has made the capturing of until now intractabledata possible at a much faster speed, with facilities forstorage. Indeed these capabilities have helped tremendouslyin managing operations at a much larger scale in a muchshorter time. As in any other managerial function, the studyof Management Information systems raises questionconcerning “appropriate or responsible” managerial behavior.No doubt, IT has provided the capacity to do many thingsand make many decisions, but the ethical issue would be,does this capacity to do something justify the act itself? Forexample, if a manager can monitor employees behavior atall times of the working day, should he or she do so? Theindividual privacy in the workplace is becoming animportant ethical issue in the present day context. Thenotion of privacy in recent times is undergoing changeowing to the recent developments in the use of informationtechnology. People’s perceptions of what is ethical and whatis not are under flux and get governed by many factors.Before we address the issues of privacy in this context, letus look at how the concept of privacy has been treatedtraditionally.
Privacy is a fundamental human right recognized in the UNDeclaration of Human Rights, the International convict oncivil and political rights and in many other international andregional treaties. Privacy underpins human dignity and otherkey values such as freedom of speech. It has become one ofthe most important human rights issues of the modern age.Of all the human rights in the international catalogue,privacy is perhaps the most difficult to define (Michael,1994). Privacy has roots deep in history. The Bible hasnumerous references to privacy (Hixon, 1987). There wasalso a protection of privacy in early Hebrew culture, classicalGreece and ancient China (STOA). These protections mostlyfocused on the right to solitude. Definitions of privacy varywidely according to the context and environment. In manycountries the concept has been fused with data protection,which interpret privacy in term of management of personalinformation (Davies, 1996).
The law of privacy can be traced as far back as 1316,when the justice of the Peace Act in England provided forthe arrest of peeping toms and eavesdroppers. In 1888,Cooley planted the seed of privacy for the legal profession’sinterest in the soil of the United States of America accordingto him the right to respect for private life is the right to beleft lone. A couple of years later in (1890), Warren andBrandies (1890) cultivated the notion with the initialanalysis of the concept of privacy. Interest in the right ofprivacy increased in the 1960s and 1970 with advent of IT.
EmpiricalStudy
16
giftjourn@l
The surveillance potential of powerful computer systemsprompted demands for specific rules governing thecollection and handling of personal information.
Different authors have defined privacy in different ways.Alan Westin (1967) defined privacy, “as the desire of peopleto choose freely that under what circumstance and to whatextent individuals will expose themselves”. According toHenderson and Snyder (1999), privacy is a right ofindividual to control the collection and use of personalinformation about themselves.
As mentioned earlier, over the past decade IT has becomean important tool for communication and research. Thetechnology is growing at an exponential rate with millionsof new users. IT is also used increasingly as a tool forcommercial transactions. The capacity, capability, speed andreliability of IT are constantly improving, resulting inconstant development of new uses for the medium. IT haschanged the public’s perception of privacy. Organizationsare faced with completely new policy decisions in term ofwhich actions can be deemed damaging to individual’sprivacy and which are merely inconvenient (Agranoff, 1991).Information gathered via computer monitoring is likely tobe increasingly used to coach employees. Currently manyorganizations use the information so gathered as a basis forcriticism (De Tienne, 1993). The increasing sophisticationof information technology with its capacity to collect,analyze and disseminate information has introduced a senseof urgency to the demand for legislation (Davies, 1996). Twoforces threaten our privacy. One is the growth of informationtechnology, with its enhancedcapacity for surveillance,communication, computation,storage and retrieval. A secondand more insidious threat is theincreased value of information in decision-making.Information is increasingly valuable to policy makers; theyconvert it even if acquiring it invades another’s privacy(Mason, 1986). For some privacy is a psychological state, acondition of being apart from others closely related toalienation (Weinstein, 1971).
As mentioned earlier concept of privacy has beenflexible, largely determined and decided by the individual.However, the current presence of information technology hasmade it even more unclear and ambiguous. In the wake ofnewer situations and newer issues relating to privacy, thereis a need to assess how individuals perceive these newersituations. The perceived ethicality or otherwise of differentissues related to privacy will involve a study of individualdecision-making process and the factors that affect thisprocess. Ethical issues by definition, involve a socialconstruction by the individual, this process becomes morecomplex and important where is situational norms are alsoin a flux. Thus, the perceived ethicality of issues related toprivacy depends upon the factors that affect this individualdecision-making process. One important factor beingconsidered in this work is the respondent position as an actor
or target of violation of privacy. Using the ego defense bias,the rationalization processes are at work when the individualis the actor of situation involving violation of privacy, usingthe mechanism of neutralization (McDonald and Pak, 1996)and denial of an unethical act. It is also possible that theindividual uses rationalization process to justify his or heract. Given the human tendency to diminish the negative actsof the self, it is likely that the individual will not perceivea violation of privacy as unethical. On the other hand, ifthe individual is the target of an unethical act of violationof privacy, it is likely that perceived unethicality isexaggerated.
Thus, our first objective is to study the perceivedethicality of a situation as a function of respondent position.On first hypothesis, hence is given below
H1: Situations where individuals are targets are likely to beperceived as more unethical as compared to the situationwhere individual are actors
There are many other factors that affect the perceptionof individual while making any ethical/unethical decisionregarding privacy issues, peer belief is one such variable weare studying, the impact of this variable on perceivedethicality.
Peer Beliefs /Perception
Sutherland and Cressey’s (1970) theory of differentialassociation assumes that ethical/unethical behavior is learnedin the process of interacting with persons who are part of
intimate personal groups or roleset. Research by Ferrell andGresham (1985) research, showthat differential associations withpeers are better predictors ofethical/unethical behavior as
compared to one’s own ethical belief system. The findingssupport a model, which assumes that individual couldbecome engaged in unethical behavior with a supportingbelief system. This research further determines that thereferent other group predicting ethical/unethical behavior ofthese employees is peers rather than top management.
Ferrell and Ferrell (1982), in another study onadvertisement agency executives found that peers, thereferents group closest to the focal person, is the strongestpredictor of their ethical/unethical behavior. Watson and Pitt(1993) in their study investigated the personal computeruser’s attitudes towards ethical issues in personal computing.The findings of this study indicate that behavior of personalcomputer users when faced with an ethical/unethical issuesis determined by their impression of how their peers behavein that situation. Thus, our second objective is to study theimpact of peer beliefs about ethicality of privacy on theperceived ethicality.
However, we further believe that this relationship mightvary for situations where the respondent is either the actoror the target. Our second hypothesis is as follows:
The individual privacy in the workplace isbecoming an important ethical issue in thepresent day context.
Nivedita Debnath and Kanika T. Bhal
17
© 2003, Global Institute ofFlexible Systems Management
H2: Peer beliefs about ethicality of privacy will influencethe perceived ethicality for situations where the respondentis the actor and not when the respondent is the target.
Though peer belief is an important predictor, it is likelythat individuals vary on the extent to which they getinfluenced by peer perception. One factor that affects thisrelationship is the tendency of an individual to give in topeer pressure. Hence peer perception is the next issue thatwe explore.
Peer Pressure
Peer pressure occurs when the individual experiencesimplicit or explicit persuasions to adopt similar values,beliefs and goals or to participate in the same activities asthose in the peer group. Ideally, the individual should makea decision based on a combination of value internalizedfrom the family (as socialization process), values derivedfrom thinking independently and values derived from friendsand peers. Individuals vary in the extent to which they usethese factors in decision-making. Thus, peer pressure is highfor those who get influenced by the values of the relevantpeer group. Though, peer perception is an importantdeterminant but individuals vary in terms of the extent towhich they get influenced by the peers. Peer pressure is theperceived pressure on the person from the peers. Thus peerpressure is likely to affect the above mentioned relationshipbetween peer perception and perceived ethicality. Thus, ourthird hypothesis is as follows:
H3: Peer pressure will moderate the relationship betweenpeer belief and perceived ethicality such that the perceivedethicality would be more like that of the peers for thoserespondents who show high peer pressure.
MethodologyRespondents
The present study collecteddata using questionnaire from125 respondents. There were56 undergraduates’ studentsand 69 MBA student of IITDelhi, India. The average ageof undergraduate respondents was around 20 years, and theaverage age of MBA students was around 30 years. Of these91 were male and 34 were female respondents.
Procedure and Questionnaire
Data was collected through a structured questionnaire, whichwas divided into two sections. The details of thequestionnaire are given below:
Section 1
This section contains two situations regarding privacy. Firstsituation is where an individual is a target and the secondsituation is where the individual is the actor. Both thesituations are followed by a question of perceived ethicality
and peers perception of ethicality. (Please see Appendix forthe situations)
Section 2
This section of the questionnaire assessed the peer pressure,i.e., the extent to which an individual gets influence bypeer’s beliefs. The four-item scale is taken from Taylor andPeter (1995) and modified for the present study to assesspeer pressure only.
Results
Our first objective was to assess whether there is asignificant difference in the perceived ethicality of situationswhere the respondent is either the target or the actor. Totest this t- test was conducted between the perceivedethicality means for the two situations. Results are reportedin Table 1.
It can be seen from Table 1 that the perceived ethicalityof the first situation where the individual is the actor issignificantly higher than that of the second situation wherethe individual is the target. Thus our first hypothesis findsfull support.
To assess the relationshipof peer belief, and peerpressure with perceivedethicality, correlations werecomputed. The results (seeTable 2) showed that for boththe situations, the correlationswere highly significant, there
by indicating that peer belief strongly affects perceivedethicality of the individuals both as targets as well asactors. Thus our second hypothesis receives only partialsupport as, we expected the relationship to be significantonly for the first situation where the individual is theactor.
To assess the moderating role of peer pressure, ahierarchical regression analysis was conducted for perceivedethicality as dependent valuable (DV), and Peer Belief, PeerPressure and the interaction between the two (in that order)as independent variables. For each interaction term thevariables were first converted into Z- scores to give thescores equivalence. The interaction term was taken as theproduct of the Z – scores. The regression method used
Two forces threaten our privacy, one is theenhanced capacity for surveillance,communication, computation, storage and retrievalwith the growth of information technology andsecond is the increased value of information indecision-making.
Situation 1(Actor)
Table 1 : t–Test for Perceived Ethicality forTwo Situations: Actor and Target
Situation 2(Target)
T
Mean 3.5200 3.1680
SD 1.13 1.10 3.927**
N 125 125
Note. ** = p<. 01
Polarization of Perceptions of IT-enabled Privacy Violations at Workplace
18
giftjourn@l
Situation 1(Actor)
Table 2 : Inter Correlations amongst PerceivedEthicality, Peer Belief and Peer Pressure
Situation 2(Target)
PE(PerceivedEthicality
PB(Peer Belief)
PB(Peer Belief)
PP (PeerPressure)
PE(PerceivedEthicality
PB(Peer Belief)
PP (PeerPressure)
PE(PerceivedEthicality) 1 0.430** -0.127 1 0.474** 0.033
PB(PeerBelief) 0.4300** 1 -0.001 0.474** 1 0.019
PP(PeerPressure) -0.1227 -0.001 1 0.033 0.019 1
** Correlation is Significant at 0.01 level.
requires the researcher to specifythe order of independentvariables. In this research, theindependent effects of the twovariables are included first andthe interaction term was included last. Thus, by taking theinteraction at the third step the compounding effects of thefirst two were removed. For the interaction hypothesis to besignificant, the beta weights of the product term had to besignificant.
Table 3 shows the results of perceived ethicality inprivacy situation one, where individual is the actor. Theresults show that both peers belief and peer pressure has amajor influence on individual perceived ethicality regardingprivacy issue. Results also show that peer pressure interactswith peer belief to predict perceived ethicality. Before wetest the direction of this moderator let us look at results forthe second situation (target).
Table 3 : Perceived Ethicality in Situation 1(where individual is the actor) of Privacy
Beta t Sig
Peer Belief (PB) 1.723 3.073 0.003**
Peer Pressure (PP) 1.755 2.569 0.011*
Interaction (PBEPP) -2.264 -2.58 0.011*
Table 4 shows the results of perceived ethicality inprivacy situation two, where individual is a target in thesituation. The result shows that the interaction of peer beliefand peers pressure has no impact on perceived ethicality ofindividual decision regarding privacy.
The interaction effect is significant for situation one, i.e.,where the respondent is the actor. To see the direction ofthe results means are identified. Significant interaction isfurther analyzed graphically scores with ± one standarddeviation from the means were plotted (Hunt and Osbrun,
1975). It needs to be mentioned here that the graphicalrepresentation shows the direction of the interaction effect,which is not shown by the beta weights. For the graphicalpurpose data are grouped into qualitative categories (lowand High) Table 5 lists the mean scores on perceivedethicality for different combinations low and high of peerpressure and peer beliefs. The same data is shown
graphically in Figure 1. Theresults clearly indicate that forhigh peer pressure perceivedethicality is lowest when peerbelief is low and it is highest
when peer belief is high. Thus our third hypothesis too findsfull support.
Beta t Sig
Peer Belief (PB) 0.085 0.144 0.886
Peer Pressure (PP) -0.066 -0.09 0.928
Interaction (PBEPP) 0.128 0.138 0.891
Table 4 : Perceived Ethicality in Situation 2(where individual is a target) of Privacy
Ethical/unethical behavior is learned in theprocess of interacting with persons who arepart of intimate personal groups or role set.
3.44
SD = 1.05
N = 64
3.14
SD = 1.41
N = 14
2.33
SD = 1.12
N = 9
4.08
SD = .81
N = 38
L
PeerPressure
(PP)
H
Figure 1: Perceived Ethicality as a Function of Interactionbetween Peer Belief and Peer Pressure for Situation 1 (Actor)
Discussion
In the present study we have taken ethical issues ofprivacy and tried to assess the impact of peers belief andpeers perception on unethical/ethical decision-makingregarding these issues, at the same time we are alsotrying to assess the difference in the opinions of individualin a situation where they are acting as an actor and in a
Nivedita Debnath and Kanika T. Bhal
Peer Belief (PB)
Table 5 : Mean Scores on Perceived Ethicality forLow and High Belief and Peer Pressure
19
© 2003, Global Institute ofFlexible Systems Management
situation where they are a target themselves. At the firstlevel, there is a significant difference in the perceivedethicality of the situation where the respondent is eitheran actor or the target. For the identical situation if oneis the actor the situation is perceived as more ethicalas compared to a situation where the actor is a target.Ego defensiveness biases are operating while makingdecisions of ethicality. Hence it is important to build thisreason and logic into any assessment of individual’sperceptions.
Our first result shows that a situation is perceived to beunethical if self is the target as compared to the situationwhen the self is the actor. It seems that at least in thesesituations self-interest is the guiding principle in decidingthe ethicality of an issue and not a set of independentstandards or values. This could be explained on the basisof changing situation and no clear social norms of right orwrong in the context of IT. Thematerial worlds (IT) changes fastand the non-material world(values and beliefs) take a whileto fall in place. In this time offlux, self-interest might govern ethical decision-making. Atthe individual level it looks like the psychological defensemechanism of neutralization is at work. Individuals, to lessenthe impact of norm-violating behaviors upon their self-concept often use the neutralization framework as atechnique. This is a rationalization process. The mostcommon perceptual components of neutralization are (1)Denial of responsibility: where individuals might argue thatthey are not personally accountable for their actions becauseof circumstances beyond their control. (2) Denial of Injury:where the individuals contend that their action is notimportant and is an acceptable violation of normativebehavior as probably no one suffers. (3) Denial of victim:where individuals condone their action by arguing that theviolated party deserved whatever happened, i.e, a form ofretributive justices is provoked. (4) Condensing thecondemner: where individual points out that that they arenot alone in the unethical action and that other are involvedin similar disapproved behavior. Thus it seem in the caseof a situation where ones own self acts as a violator ofethical norms the impact is significantly diminished. On theother hand, when one is the target the tendency is toenhance the negative impact. Thus, when the organizationsdesign systems for control privacy issues this tendency toeither inflate or deflate the impact needs to be accountedfor.
The results of present study clearly show that individualdecision-making gets influenced by what their peers thinkis right or wrong. Social belief of the referent group playsan important role in the perceptions of ethicality. Thus, itmeans that the collective norm or value operating in anorganization will be a strong predictor of the pervasivenessof an unethical act. From the point of view of the
organization, hence developing cultural belief throughformal and informal mechanism are likely to yield positiveresults for controlling breach of privacy.
However, when the focus of attention is the individual,one important factor that predicts the perception is thetendency of an individual to get influenced by peerbeliefs. However, it needs to be mentioned here that peerbeliefs and peer perception are important predictors in ourstudy because the sample of our study is the students whoare more likely to get influenced by their peer groups. It islikely that the results (specially for hypothesis 2 and 3) arenot all that strong for another sample of matureprofessionals.
Our study thus indicates that the individuals use ethicalperception flexibly even for the same situation, as a functionof their position. Thus the cognitive rationalization moves
on a continuum of high ethicalityto low ethicality depending upontheir position. Also this perceptionis used flexibly as a function ofpeer belief and peer pressure. Thus,the design of system must respond
to the issues flexibly (Bhal, 2000), keeping in mind theindividual variations. The design of HR system, for privacymust keep in mind the position of the employees, as theperceptions of higher level employees (likely to be actors)will be different from that of the lower level employees(likely to be targets). The system must respond to thedynamic flexibility of level wise perceptions. The perceptioncould be seen as moving on a continuum of ethical tounethical but it needs to integrated based on the situationand the actor involved, (Sushil, 2000 a, b). The flexibilityhas to be made operational at the level of diagnosis andanalysis of the systems, keeping in mind the varyingperceptions. At the next level the design of systems haveto be flexible depending upon the situation and the positionof the people.
Thus, the perceived ethicality of the same individualvaries and there is a flexibility in the perception of ethicalityspecially by virtue of the position the respondent is in. Afact that must be addressed in the diagnosis and design ofappropriate systems.
ReferencesAgranaff H.M. (1991) Controlling the Threat to Personal PrivacyCorporate Policies must be Created, Journal of Information SystemsManagement, 8, 48–52.
Alan F.W. (1967) Privacy and Freedom, Athenaeum, New York.
Bhal K.T. (2000) Organization Theory Revisited: Toward a Paradigmof Flexibility, In Sushil (Ed.) Cornerstones of Enterprise Flexibility,New Delhi, Vikas Publishing House.
Davies S. (1996) Big Brother: Britain Web of Surveillance and theNew Technological Order, London, Pan
De Tienne K.B. (1993) Big Brother or Friendly Coach, Futurist, 27,33 – 37.
Peers, the referents group closest to thefocal person, is the strongest predictor oftheir ethical/unethical behavior.
Polarization of Perceptions of IT-enabled Privacy Violations at Workplace
20
giftjourn@l
Ferrel O.C. and Greesham L.G. (1985) A Contingency Frameworkfor Understanding Ethical Decision Making in Marketing, Journal ofMarketing, 49, 87 – 96.
Ferrell Z.M. and Ferrell O.C. (1982) Role Set Configuration andOpportunity as Predictors of Unethical Behavior in Organization,Human Relations, 35 (7), 587 – 604.
Henderson S.C. and Snyder A.C. (1999) Personal Information Privacy:Implication for MIS Managers, Information and Management, 36,213–220.
Hixon R. (1987) Privacy in Public Society, Human Rights inConflict, 3.
Hunt J.G., Osborn R.M. and Larson L.L. (1975) Upper Level TechnicalOrientation of First Level Leadership Within a Non-contingency andContingency Framework, Academy of Management Journal, 18,475-488.
Mason (1986) Four Ethical Issues of Information Age, MIS Quarterly,10 (1), 4–12.
McDonald G. and Pak P.C. (1996) Its all Fair in Love and Business:Cognitive Philosophies in Ethical Decision-making, Journal of BusinessEthics, 15, 973-996.
Michael A.W. (1971) The Uses pf Privacy in the Good Life, PrivacyNomos XIII.
Michael J. (1994) Privacy and Human Rights, UNESCO.
Shirle T. and Peter A.T. (1995) Understanding Information TechnologyUsage: A Test of Competing Models, Information Systems Research,6 (23), 144-176.
Sushil (2000a) Cornerstones of Enterprise Flexibility, New Delhi, VikasPublishing House.
Sushil (2000b) Flexibility in Management, New Delhi, Vikas PublishingHouse.
Sutherland E. and Cressey S. (1970) Differential Association Theory,Principles of Criminology, Lippincatt, Chicago.
Warren and Brandies (1890) The Rights to Privacy, Harvard LawReview, 4.
Watson R.T. and Pitt L.E. (1993) Determinants of Behavior towardsEthical Issues in Personal Computing, Omega, 21 (4), 457–470.
Appendix IInstructionFollowing are two likely situations in the work place. Please readthe situations respond to the questions that follow each situation.Situation 1You are HR manager, and you want to see that the employeesare using phone and e – mail only for business purposes. Youuse a computer and other devices to randomly monitorcompliance with this policy.Q1. How correct is this activity in your view.
Very wrong….Wrong….Not sure….Correct….. Very correct….Q2. What would your peers think about your action. Would they
consider it.Very wrong….Wrong….Not sure….Correct….. Very correct….
Situation 2Suppose you are working for a company with a policy that phonesconversation and e – mail use should be related only to businessonly. The company uses a computer to randomly monitorcompliance with this policy.Q1 How correct is this activity in your view.
Very wrong….Wrong….Not sure….Correct…..Very correct….Q 2 What would your peers think about your action. Would they
consider it Very wrong….Wrong….Not sure ….Correct…..Very correct….
Section 2Following four items assess the pressure of your peers regardingthe use of computer. Please mention on the scale given, how truethey are for your peers and friends.1. I get influenced by what my friends think that I should do.
Very true…. True….Not sure ….Not true….. Not at all true….2. Generally speaking, I want to do what my friends think I
should do.Always…. Usually….Sometimes ….Rarely…..Never….
3. I would get influenced by what my classmates think that Ishould do.Always…. Usually….Sometimes ….Rarely…..Never….
4. Generally speaking, I want to do what my classmates think Ishould do.
Always…. Usually….Sometimes ….Rarely…..Never….
Nivedita Debnath and Kanika T. Bhal
Flexibility Mapping : Practitioner's Perspective1. What types of flexibilities you see in the IT enabled environment regarding "Privacy at Workplace" on the
following points:l Flexibility in terms of “options”l Flexibility in terms of “change mechanisms”l Flexibility in terms of “freedom of choice” to participating actors.
2. Identify and describe the types of flexibilities in “Privacy at Workplace” that are relevant for your own organizationalcontext? On which dimensions, flexibility should be enhanced?
3. Try to map your own organization on following continua (Please tick mark in the appropriate box(es))Manager's Perspective (Actor)
High Important Low ImportantSubordinates Perspective (Target)
High Important Low ImportantOutsideIndividual Personality (Peer Pressure)
High Important Low ImportantOPeer Group Belief
High Important Low Important
Reflecting Applicability in Real Life
1. Is your organization going through IT enabled privacy violations at workplace? How will you use the findingsof this study to manage them?
21
© 2003, Global Institute ofFlexible Systems Management
Stakeholder Flexibility in E-Business Environment:A Case of an Automobile Company
Rajeev DwivediResearch Scholar
Department of Management StudiesIndian Institute of Technology Delhi
Kirankumar MomayaAssistant Professor
Department of Management StudiesIndian Institute of Technology Delhi
AbstractEarlier, researchers talked about Stakeholder Theory, Stakeholder Responsibility, Stakeholder Partnerships, StakeholderManagement, Stakeholder Engagement, Stakeholder Relationships, Stakeholder Reporting, Stakeholder Mapping, StakeholderPerformance, Stakeholder Strategy, Stakeholder Dialogue, Stakeholder Networks etc. and various dimensions of stakeholder.E-Business is the concept to bring flexibility in the business. Researchers emphasized e-flexibility of online business in manyways such as CRM flexibility, SCM flexibility, marketing flexibility etc. This paper introduces a new concept of stakeholders andflexibility, i.e. stakeholder flexibility due to e-business environment. In the new economy, data, information, knowledge, interaction,technology, trust, and the relationship are the keys to success but flexibility is for sustaining in the dynamic and unpredictedpresent business environment. Flexibility is defined by three terms: more options, freedom of choice, and change mechanism.This paper is based on the strategic and flexibility aspects of E-Business transformation. This flexibility helps to produce a new,integrated approach of flexibility, which is dual in nature and sometimes it shows the multidimensional nature of flexibility. Thepaper examines the flexibility for stakeholders from business and from business to stakeholders in E-Business environment. Thereare mainly two groups of stakeholders: one is direct stakeholders and the other is an indirect stakeholder. This paper explainsthe direct stakeholder flexibility. The paper also addresses certain fundamental questions such as: Why flexibility? Why stakeholderflexibility? What is the nature of flexibility?
Keywords : e-business environment, flexibility, stakeholders, stakeholder flexibility
giftjourn@lGlobal Journal ofFlexible Systems Management2003, Vol. 4, No. 3, pp 21-32
Introduction
E-Business is the new, evolving paradigm. Management hasfaced several transformations from the age of agriculture tillinformation technology. Recent decades are the witness torapid changes, which may be due to MIS or ERP. The focusof time-based paradigm has shifted from traditional brick andmortar centered setting to click and brick systems. In fact,competitive priorities in many firms have shifted fromsimply business speed to e-speed (Norris et al., 2001). Thee-business revolution is impossible to ignore. It istransforming businesses in virtually every industry andreshaping the global economy. The traditionalorganizational structure and operational processes aresuddenly changed due to information technologyrevolution. The e-business transformation is an evolvingtransformation since last five years and need lot of researchin context of strategic management.
Gartner Research (1999) developed an e-businessstrategy framework that can help business leaders to getbetter results from strategic plans. This strategic frameworkconsists five phases: e-vision, e-management, e-competition,e-plans and e-review. These are the basic components ofstrategic management. Those e-business strategies maximizeopportunities and minimize the risks.
E-Business is not one-man effort; it needs variousstakeholders such as technology providers, application
service providers, supplier, distributor, retailer, shareholder,customer, and financial service providers. The keystakeholder involved gain lower cost of the product, betterservices, and ultimately more profits.
The recent advances in IT and telecom are changingbusiness processes and structures, they are reshapingrelationships with business partners and competitors, and insome cases they even cause the transformation of an entireindustry. The Internet has brought about a dramatic changein the way business is done in today's world. And buildingan E-Business strategy is perhaps the single most importantissue faced by corporate strategists. E-Business, of course,is not about technology itself – it's about how to use thetechnology to transform business processes. It's about newmodels of commerce, marketing and distribution. In fact, oneof the key parameters companies are being evaluated ontoday is how well, and how fast, they can adapt themselvesto the Internet.
Within next two years nearly two-third businesstransactions will be conducted through e-business in India.Business-to-business (B2B) e-commerce will continue itsrapid pace of growth, generating $7.29 trillion in salestransactions worldwide in 2004. The revenue generation inthe year 2001 was $953 billion, $2.18 trillion in 2002, and$3.95 trillion in 2003. The report estimates that such activitywill make up 37 percent of the B2B e-commerce market,
CaseStudy
22
giftjourn@l
worth $2.71 trillion by the year 2004. Business-to-business(B2B) e-commerce will continue its rapid pace of growth,generating $7.29 trillion in sales transactions worldwide in2004, according to a report published by the research firmGartnerGroup (2002). The Internet business in India is worthabout INR 120,00 billion per annum.
This paper presents an approach which providestractability from strategy to process through the critical linkof the business stakeholders: all those who have a 'stake' orinterest in the success of the company whether they arecustomers, suppliers, owners, staff, or community-based.Stakeholder flexibility is very important to successfully runa business in competition. The stakeholder flexibility is morestrategic approach in e-business environment. The area ofe-business strategy is emerging and needs a lot of attentionin order to understand the stakeholder flexibility. Theflexibility is the key to sustain in the dynamic and uncertainworld. The e-business strategy is fundamental to transforma business from brick and mortar to brick and click.Therefore, it becomes important to study e-businesstransformation, which brings stakeholder flexibility tosustain in competitive world.
E-Business (New Economy) Change Mechanism
The changes in technology and economy are creating a newset of business rules and practices what is being called “TheNew Economy” or “E-Economy”. Some of major businessbeliefs in the old economy and how these beliefs are shiftingin the new economy (e-business environment) are shown in
Tables 1 and 2.
The change comes often when the previous phase facesthe saturation of S shape growth curve. Previous change wasMIS. The failure of e-commerce brought e-business to createnew opportunities for business, especially for B2B.E-Business, is to exploit the opportunities created by theInternet and information technology for business to createvirtual marketplace. E-Business is concerned specially aboutB2B segment because the failure the B2C segment(e-commerce). The transaction of money is much more inB2B as compared to B2C e-business.
For Whom E-Business is?
E-Business is for thestakeholders of the business:customers, employees, andshareholders, every one. Itgives flexibili ty and JITservices at one place. From business point of view, it's forbig MNCs to exploit the resources and opportunitiesavailable globally. They can afford the cost infrastructureof e-business with the help of world-class technologypartners. The e-business can be for small and medium sizedenterprises to adopt and transform e-business step by stepas the Sawhny & Zabin (2001) described the ladder frominform to transform.
According to Tettech and Burn (2001), Web basedbusiness can be an extremely attractive option for most
SMEs to extend their customerbase into a global marketwithout vast expenses, butthere are many hurdles andhidden costs. SMEs canachieve the globalcompetitiveness without
necessity increasing their actual size, but rather by buildingon their virtual or soft assets in order to expand. Thesevirtual assets include information skills, digital resources,and competencies for managing inter firm relation andcollaborative engagements with other firms.
Economic development is a goal of most governments.Globally it is recognized that approximately 80 per cent ofeconomic growth comes from the SME sector. It is, therefore,
Old Economy New Economy
Advertisement based brand Performance based brandbuilding buildingCost Value
Customer Acquisition Customer RetentionLook primarily at financial Look also at marketingscorecard scorecard
Marketing does the marketing Everyone does the marketingOrganize by product units Organize by customer segments
Over promise under deliver Under promise, over deliver
Product Technology Process TechnologyShareholder Stakeholder
Table 2 : Business Focus from Old Economy toNew Economy
Change Areas Old Economy New Economy
Assets Tangibles IntangiblesBusiness Change TransformationCommunication Physical Meetings TelecommunicationCompetition Known UnknownControl Centralized DecentralizedDemand/Supply Market Driven Customer DrivenFuture Prediction UncertainIntegration Vertical Integration Virtual IntegrationKnowledge Utilization Creation & RenewalManagement Compliance Self ControlOrganization Structure, Hierarchy Edge of Chaos,
NetworkedReach Local GlobalSharing Information Sharing Knowledge SharingSkills Individual CollectiveStrategy Prediction Anticipation of surpriseTechnology Convergence DivergenceTechnology In-House Development, Tech Outsourcing,Resource Innovation DiffusionTrade Rules Government Driven WTO DrivenWork Office Work, Flexi Work,
Flexi Time Fixed Time
Table 1: Changes from Old Economy toNew Economy
E-Business is not one-man effort; it needs variousstakeholders such as technology providers,application service providers, supplier, distributor,retailer, shareholder, customer, and financialservice providers.
Rajeev Dwivedi and Kirankumar Momaya
23
© 2003, Global Institute ofFlexible Systems Management
likely that government strategies aimed at facilitating SMEsadopting the Internet enabled business processes andpractices to help increasing national GDP (Dawan, Bodorikand Dhaliwal, 2002).
Who Are Stakeholders?
The Webster Business Dictionary defines stakeholders as“Stakeholders include all individuals and groups who areaffected by, or can affect the organization”. The dictionarymeaning of stakeholder is "one who holds a stake". Theword stake is defined as "apersonal interest orinvolvement" or " a monetaryor commercial investment insomething, as in hope ofgain."
Corporate Stakeholders and e-Business
A company involved in e-business has a responsibility toprotect its corporate stakeholders, because in any e-businessmodel, corporate stakeholders may be harmed in number ofways. This may turn in financial loss, reputation loss, andloss of trust. Stakeholder groups (Fig.1) always includecustomers, vendors/suppliers, service providers, shareholders/investors, corporate executives, board of directors and thegeneral public.
for this route must focus on areas that have challenged theirindustry, for example, e-channel fulfillment or establishingprivate marketplaces. The key advantage is the opportunityto get a jump-start with a proven e- business model. A maindisadvantage is the lack of control of customer demand ina Web channel.
The Pressure for Flexibility
There are causes of pressure for flexibility demanded bystakeholders, shown in Table 3. All stakeholders want profit
and money by long-termassociation with the business.On the other hand, businessputs pressure on stakeholder forflexibility, shown in Table 4. E-Business environment has thepotential to tolerate both
pressures at the same time by conducting the businesselectronically and results in stakeholder flexibility.
Why are Stakeholders Important forE-Business Transformation?
A company can transform itself including value network (allthe stakeholders). To do this, companies must divest non-core businesses to partners to cut cost and gain flexibility.In doing so, they'll create a value network of partners thatwill fulfill the same demand, but with a smaller asset andresource base. If businesses choose this route, a critical massof capable business service providers emerges. This wouldresult that the company benefits from its partner's growthand capabilities. Successful value networks excel largelythrough their technology and information sharing practices.To create an e-business transformation, companies shouldpartner with or acquire a company with a proven e-businessmodel and channel. For competitive advantage, firms going
Stakeholders are those who have rights orinterests in a system. For an organization,stakeholders are any group or individual, whocan affect, or is affected by the achievement ofthe organization's purpose.
Figure 1 : Key Stakeholders of E-Business
Stakeholder Cause
Customer Want ever lower prices and moreimmediate delivery
Competitors Want to strive to satisfy these samecustomers
Shareholders They want higher profit on theirinvestment
Government agencies They are squeezing budgets anddemanding better value for moneyin service delivery
Employee Want high salary, services and flexiwork
Suppliers Want accurate order process systemand more demand
Distributors Want higher commission and fastorder fulfi l lment and productdelivery
Retailers More commission and to satisfycustomer demand
Technology Providers Want long time association
Call Centers Want profit by renewing tenureand assignment for more time
Consultants Want to give the more solutions ofproblems for earning
IT Partners/comp Want to upgrade new technologiesand log term engagement
Financial Service providers/ Want to provide financial servicesbanks/Insurance to increase revenue
Media Partners Want to promote productcampaign to earn money
Table 3 : Pressure for Flexibility by Stakeholders
Dual Nature of Stakeholder Flexibility
Stakeholders are those who have rights or interests in asystem. For an organization, stakeholders are any group orindividual who can affect, or is affected by the achievementof the organization's purpose. Those, who has a 'stake', claimor vested interest, those who provide something ofimportance to the organization, and expect something in
Stakeholder Flexibility in E-Business Environment : A Case of an Automobile Company
24
giftjourn@l
return. Stakeholders can be individuals, communities, socialgroups, or organizations that has the ability to influencedecision-making in an organization. Stakeholders are viewedas playing an important role in determining organizationaldirection by influencing the goals and strategies thatorganizations adopt.
E-Business can create new value propositions for everystakeholder. A value proposition describes the perceivedvalue that each member of the value chain (buyer,seller, distributes, alliancepartners, etc.) receives fromparticipating in a businessmodel. This creates flexibilityfor stakeholder as a wordchange in order to getinformation, transaction, and transformation of work culture.
Flexibility of a business process is how easily a businessprocess can be adjusted according to different stakeholder'sneeds. Moreover, flexibility means more options and morechoices in change mechanism (Sushil, 2000). There are twotypes of flexibility: first to stakeholders and second tobusiness from the stakeholders. We are taking both the waysof flexibility in the account. The dual nature of stakeholderflexibility is shown in Appendix I in detail.
Customers
Customers are the focus points of any business. E-Businesscreated many options and choices for customers to save timeand money and get better quality with better services. Now,the second phase of the coin, how e-business creates
Stakeholder Cause
Customer Buying product and long termretention
Competitors Information of competition andmarket demand
Shareholders Investment
Government agencies Facilities and flexible rules
Employee High Productivity
Suppliers Cheap materials and immediatedelivery
Distributors Fulfill the customer demand andbetter services to customers
Retailers Fulfill the customer demand andbetter services to customers
Technology Providers Innovative and new technology togain competitive advantage
Call Centers Customer care and providinginformation to stakeholders
Consultants Accurate planning and bettersolution of the problem
IT Partners/comp Better hardware, software andservices with time to time updating
Financial Service providers/ Easy financial processes with lowbanks/ Insurance interest rate
Media Partners Better campaigning for brandbuilding
Table 4 : Business Demand from Stakeholders flexibility for business? This is helpful to establish one-to-one customer relationship. This also brings end-to-endbusiness solutions to ensure long-term success in managingcustomer relationships based on ongoing learning with thehelp of information. The most important thing brought bye-business, is information gathering about market with in thetime, helpful in learning about customers and marketinganalysis. This will help to determine its place in theelectronic marketplace of future. This will help to formbetter customer relationship.
Employees
Employees may be benefited in terms of flexible hours,flexible work, and flexible place to work. This could bebeneficial in terms of less stress, more time with family andfriends and easy to work at home. Employees may getknowledge not only of their own field but also other fields,which are essential and influences their work. On the otherhand, business or company will get the benefit in terms ofconnectivity with employees. So the management can getinformation about their performance and may establishedbetter relationship with their employees. The business canalso save their expenses from the facilities reduction. Jobshare and location independent among employees mayenhance the flexibility and knowledge managementperspectives. So they can share their knowledge with thehelp of e-business, and facilitate job rotation to enhanceknowledge, not only their own job but also other jobs, ifneeded.
Shareholders
The flexibility to shareholders from e-business is to getupdate information about the stock exchange and theirposition (Trading Update) time-to-time by newsletter or dailynews. They can also share their view and ideas with the
company by providing thesuggestions through onlinemeeting and communities. Newinitiative about the businesswill be provided to all theshareholders to get their
feedback. The second phase how business is gettingflexibility from e-business in terms of shareholders. Businesswill get more investment from shareholders as well as newshareholders associated with the business. Now, shareholderswill also care about the IT, because the failure of New YorkStock Exchange. Business can give the information aboutnew policies, initiative, and can also get feedback just intime so decision-making would be made easily for abusiness. Online traders, such as e-trade, and evenexchanges, such as New York exchange, have experiencedsystems failure that has made them the unhappy centers ofworld attention. In June 1999, the Internet auction site e-buy was down for 22 hours. In the next two trading days,the e-buy's share price dropped by 25%. So definitely yourshareholders will care about the IT.
A company involved in E-Business has aresponsibility to protect its corporate stakeholders,because in any e-business model, corporatestakeholders may be harmed in a number of ways.
Rajeev Dwivedi and Kirankumar Momaya
25
© 2003, Global Institute ofFlexible Systems Management
Supply Chain Partners (Suppliers, Dealers, Retailers)
The information about all the products, reviewing products,review product specifications, check availability of rawmaterial and production schedules, commit order, track orderstatus, schedule delivery, will be easily availableelectronically due to e-business. The transaction givesfreedom of space and time, and also avoid burden of hardfiles and manuals. There is difficulty of security and secrecyof information and money transaction. The seamlessintegration of all supply chain activities reduces cost ofprocurement, delivery cost of product, inventor informationcost and production cost. The manufacturer benefits fromincrease in sales. The retailer gets benefits from having anadequate stock of the product and being able to offer it tothe end consumer at a lower cost, thereby increasing salesvolume. This will be helpful to increase profit margin forbusiness and all supply chain partners (IBM e-biz resource).
Information Technology Companies
E-Business forms alliances with leading e-business software,hardware, networking, and service provider companies todevelop and deliver the back-end integration capabilitiesthey required to provide theircustomers and business withcomplete e-business portal andmarketplace solutions. Company products help partnerscreate an open, scalable framework that supports complexinteractions among customers, buyers, suppliers, partners,and employees. Technology company alliances includeIBM, Oracle, Microsoft, and so on.
Call Centers
Call centers are helpful to communicate with dealers andconsumers. When dealers communicate with theirmanufacturer online, and when consumers find the answersto the questions online, the cost comes down dramatically:through the dealer e-channel, manufacturers and dealers cankeep their costs down. Consumer questions are answeredonline, and they can research the products and otherinformation they seek online as well. For dealers, they canconduct business with consumers. They save the enormouscost-of-business expenses. Call centers will be benefited bylong term engagement with the business for profit making.
Media Partner
The media partner provides promotion of business throughdifferent channels such as radio, TV, Web publishing,posters, hoardings, newspapers, magazines and so on. But,the booking and transaction of promotion could beelectronic and payment could be made by electronictransaction between business and media partners. Mediapartners also provide consulting, business assurance services,ad delivery and privacy attestation and consultation,assistance to mergers and acquisitions, tax planning andcompliance, capital structuring and employee benefits and
executive compensation packages. Media partners will havelong-term association in providing so.
Financial Services Providers
This includes bankers and insurance companies to providefinancial services online into interest of business, and tomake money from the business.
Consultants
E-consultancy is the way to get benefit of electronicmedium for facilitating business customers and businessonline, results in reducing time, and cost from both ways.Internet also helps to provide information to consultantsregarding business and search.
All Alliance Partners
The non-core process will be shifted to all alliance partners,so they may become a part of e-business. If the business getsprofit then they will also be benefitted; if they grow thebusiness also grows. E-Business includes all the alliancepartners, IT partners and different channel partners. Thee-business brings flexibility for alliance partners in terms of
development of new thoughts,research and development, newlearning opportunities, creatingnew forums and virtual
meetings, information sharing and access, and finallyrecognition.
Case Study : Maruti Udyog Limited (MUL) isThriving Stakeholder Flexibility inE-Business Environment
Maruti Udyog limited (MUL) is the largest car manufacturerof India. In the year 1982, the government signed a jointventure with Suzuki Motors Corporation of Japan and setup the first joint venture of Government of India in carmanufacturing. Maruti has 2.8 million customers round theglobe, an average of 30,000 to 40,000 cars coming outof assembly lines each month, and a network of 10regional offices across the country. Maruti exports to 70countries. Some of the key processes and their results arepointed in Table 5.
IT at MUL
Maruti, an INR 9,6720 million company is doing well toretain its market leadership, and seems to coming out ontop. One of the biggest weapons in Maruti's is informationtechnology. Currently, almost 75% percent of Maruti'syearly business transactions is conducted online; thecompany is poised to take it to 80 percent by 2003. On anaverage, Maruti invests between INR 150-200 million everyyear on IT.
B2B at MUL
As part of its Web initiative Maruti is also a part of aconsortium of eight majors, which intends to set up anautomotive e-marketplace for India. This kind of a market,
Stakeholder flexibility in any business is veryimportant to successfully run business incompetition.
Stakeholder Flexibility in E-Business Environment : A Case of an Automobile Company
26
giftjourn@l
which gives an opportunity for the company for supplychain optimization as well as helps in eliminating flab fromoperations at various tiers of the value chain. On the B2Bfront it includes putting its entire dealer and vendor networkfully online by developing extranet-based systems, whichintegrate dealers and suppliers to Maruti's business systems.The first step was the linking of its 260 dealers in India intoits Wide Area Network (WAN).
Being a transaction-heavy organization, Maruti's primearea of focus in installing its numerous systems andapplications has been to cater to its various functions, thushelping it achieve the highest efficiency levels. Maruti hasestablished collaborative systems with its business partners,e.g. dealers and suppliers besides enhancing/re-engineeringits in-house systems and processes. With almost 99 percentof dealers using the extranet facility today, currently Marutihas implanted similar facilities for its vendors. Maruti boastsof a full-featured B2B marketplace for business partners,which is the Maruti extranet based on a Virtual PrivateNetwork (VPN). Maruti has implemented various modulesand systems including production planning, scheduling andmaterial scheduling in order to enhance its supply chainefficiencies. The company has implemented a Just in Time(JIT) materials procurement system. Vendors under thissystem are given specificdelivery instructions formaterials supply, which specifyall details to the last degree theexact date and time of delivery,even the specific workstation inside Maruti and the exactquantity to be supplied to any of these. This allows thevendor adequate time to schedule his own productionsystem and ensures smoothening at his end.
B2C at MUL
On B2C front Maruti is currently in the process of fine-tuning its purely informative product-specific website to a
customer relationship oriented corporate website that willboast of a virtual showroom, using Microsoft's yet to bereleased portal development software Microsoft Share Point.The company is connecting the new site to about 260 dealersites, all of which have been developed by Maruti itself andare hosted on VSNL. This will allow the customersprivileged access to information catering to their specificneeds and tastes and also allow customers to book carsonline.
IT Infrastructure
IT at Maruti is a competitive weapon. IT infrastructure atMaurti is shown in Table 6 given below. Maruti developssome of the IT software and services in house and some areoutsourced.
Processes
l End to end streamline procurement system, which integratesover 500 suppliers and around 300 dealers network.
l Use of Extranet and Intranet
l Offers JIT procurement
l Teleconferencing from Suzuki Motors Japan
l Oasis portal and Knowledge Bank
l Marutiudyog.com provides wide range of information for all
Results
l Reduce 50% cost of procurement processes.
l Cost reduction of inventory and other overhead costs
l 75% cost saving of paper and other stationary
l 72 Laks Rs by online reverse auction
l Helpful in maintaining Maruti's core competency to providecheapest car
l Customer Information Management, customer support
l Online transaction of 75% of total revenue
Table 5 : E-Business at Maruti
IT Department l Separate IT department at Maruti, heads byMr. Rajesh Uppal, General Manager IT
IT Staff l Around 70 people IT staff at Maruti
IT Systems l 12 Compaq Alpha servers,
l 20 PC servers,
l Around 850 PCs,
l 300 VT100 terminals.
Enterprise Storage Architecture (ESA12K),
l Tape Library,
l Enterprise backup facility of 17.9 TB,
l A remote backup and disaster recovery siteNetwork environment
l 20 km of optical fibre cabling within plantlocation at Gurgaon (1,000-node LAN).
Network l Plant to corporate office connectivityEnvironment 2 Mbps.
l 10 regional offices connected throughVSATs.
l 64 Kbps leased line ISDN link to Suzuki,Japan
Softwares l In House Development, MS Office,Windows, Oracle 9i
Website l Self development with self maintenance
Table 6 : IT Infrastructure at Maruti
MUL Stakeholders
Maruti's stakeholders are listed down in Table 7 but Marutialso has those indirect stakeholders, who are getting
flexibility from e-business suchas Haryana Vidyut Board,Haryana Transport Corporation,society, hospitals (Batra,Escorts) etc. We are consideringonly direct stakeholders of
Maruti's e-business. We are avoiding indirect stakeholderssuch government and society.
Customers
Customers are the focus point of Maruti as in any business.Maruti provides detailed information to the customersthrough their website (marutiudyog.com), that contains allpossible information of customers' interest, such as dealers
Business environment has the potential totolerate both pressures at the same time byconducting the business electronically andresults in stakeholder flexibility.
Rajeev Dwivedi and Kirankumar Momaya
27
© 2003, Global Institute ofFlexible Systems Management
Stakeholders Description of Stakeholders
Customers l All Customers of all segment (around 5million vehicles are sold till 2002 and3,50,000 are sold every year)
Employee l Around 2000 employee are IT savvy outof around 5700 employee
Suppliers/vendors l Around 500 suppl ie r and a l l a reconnected through Extranet
Dealers/Retailers/ l Around 260 dealers (show room) all areworkshops/ connected through WAN.
l Around 277 dealers workshops
l Around 1329 Maruti authorized servicestation
Technology l Suzuki Motors Japan with strong Provider communication system
Call center l GE Gurgaon for customer Informationcenter
l i2i enterprise across all 25 cities of India
Financial Service l ABN AMROProviders (Bankers) l American Express Bank Ltd
l Bank Of Tokyo-Mitsubishi Ltd.l Banque Nationale De Parisl Citibank N A.l Citicorp Maruti finance ltdl Corporation Bankl Credit Lyonnaisl HDFC Bankl ICICIl Kotak Mahindral Maruti Countrywide Financel Punjab National Bankl Sanwa Bank Ltd.l SBI Maruti car loansl Standard Chartered Grindlays Bank Ltd.
[Merged]l State Bank of Indorel State bank of Mysorel State Bank Of Travancorel Sundaram Financel Union Bank Of India
Insurance l Maruti Insurance Distribution Services(MIDS), MIDS was set up to sellinsurance as a corporate agent of BajajAllianz General Insurance
l Maruti Insurance Brokers (MIBL). MIBLwas constituted to sell insurance productsof the state-owned National Insurance.
IT partners l Compaql HPl Oraclel Microsoft
Consultants l PWC (Auditor of the Maruti)l AT Kearney for E-Business solutionl MB Athreya for HR (employees
performance system)
Shareholders l Suzuki Japanl Government of Indial Recently Issued Public Shares
Media Partners l Yahoo Indial FM Radiol Indiatimes.coml Business magazines, Newspapersl TV
Table 7 : Key Stakeholders of Maruti information, workshop information, maintainace planner,broucher, online calculator for calculating financial schemeand insurance policy, price of the car, financial schemes,insurance, true value, N2N fleet management, quarry answer,It provides special information and order booking to thespecial buyers such as Handicapped (see Table 8). Thespecial information for holidays around Maruti dealers inIndia also available on the website. Maruti is getting thebenefit in order to retain old customer, acquiring newcustomer, gaining customer trust, and building customerloyalty.
Table 8: Dual Nature of CustomerFlexibility at Maruti
Flexibility to Customers Flexibility to Maruti
l Online information aboutfinance or loan schemes
l Online information aboutinsurance
l Maruti Gateway guide forTravel in India
l True value dealer information
l Product/price/ availabilityinformation
l Information about servicestations/workshops/Maruti roadservice.
l Online brouchers
l Customer want to sell the callfor that online help
l E-mail account on Maruti forservices
l E-newsletter
l Online owner manual
l Online feed back and quarry
l Toll free customer informationfrom GE gurgaon
l Online answer and help
l Trust
l Transparency about availabilitywith online status of booking
l Customer Loyalty
l Long term associations andfeedback from customers
l Online True valueinformation attracts newcustomer segment
l Online information aboutdealers service stationsprovide better reach ability tocustomer and trust
l Global customer interaction
l Rich database of customers
l Rich database of customerdemand
l Database of customer quarry
l Market Informat ion andanalysis
l Regional Demand analysis
Employees
Computerization benefitted Maruti for improving the qualityof life for every employee, by simplifying procedures,reducing paper work and giving instant access to accurateinformation. Moreover the availability of all sorts of datalike production of vehicles to medical claim of employeesonline has resulted in punctuality and accuracy of work.Intranet supports Maruti's organizational work electronicallyin order to reduce work of the employees and reduce paper-stationary cost by managing file transfer and storageelectronically. All intra and extra organizational works areconducted either through intranet, extranet or Internet.Maruti has OASIS portal with in the organization to supportits HR policies. Oasis provides individual ID and passwordto all employees for getting information related toemployee's interest such as monthly incentives, his
Stakeholder Flexibility in E-Business Environment : A Case of an Automobile Company
28
giftjourn@l
Flexibility to Dealers
Table 9 : Dual Nature of EmployeeFlexibility at Maruti
Flexibility to Employees Flexibility to Maruti
l Oasis portal to provide HRinformation with in theorganization to all employee
l Less Work load using userfriendly software's
l Paperless work usingcentralized server with inorganization
l Maruti started knowledge Bankdatabase for storage andretr ieval of knowledge oforganization
l All Policies and Informationthrough intranet on personalaccount
l E-mail account @mul.co.in
l Fast and flexiblecommunication system
l Teleconferencing betweenSuzuki and Maruti people fromJapan to India and vise-versa
l Oasis helps in HR strategy ofthe Maruti
l Annual 50,000 Suggestionsfrom employees electronically
l Saving paper and stationarycost
l Just in time informationamong employees
l Just in time information andinteraction among employeesfor better decision-making
l Information and interactionwith regional offices of Maruti
l Cut paper and mailing cost ofdocuments with fastprocessing, saving time
l Full detail of staff
of the car, true value information, Maruti Insurance, andcustomers query (see Table 12). The dealership applicationand rules are also available online. E-Business is helpful inMaruti's supply chain management and dealer satisfaction.
Suppliers
Around 500 Maruti's suppliers are connected through theextranet to conduct JIT procurement. The e-procurementsaves the cost of procurement and inventory and processesfast. E-procurement helps Maruti's suppliers in order toprovide information such as inventory information, bidding,auction information, online supplier order rejectionand current position of supplier, online tendering,financial transactions, online order process and approval(see Table 11). This helps Maruti to reduce inventory costfrom 2 days to 2 hours and helps to achieve significantreduction in procurement processes.
Flexibility to Shareholders Flexibility to Maruti
l E-newsletter
l Share market informationonline to Maruti shareholders
l Maruti share information onMaruti website
l Online suggest ions andinteraction about companiespolicies
Table 10 : Dual nature of ShareholderFlexibility at Maruti
l Recently started but Marutiis looking for investment
l Shareholder satisfaction
l Shareholder will care aboutbusiness
performance score, guest entry, claim status of loan, pass ofbill and payment, special policies and related informationto individual, e-learning etc (Table 9). Maruti is having theonline knowledge bank to manage knowledge in theorganization. Through electronic system, Maruti got 50,000feedbacks from their employees last year.
Shareholders
The public issue to Maruti shares was launched recentlyhence much information is not available to get shareholdersfeedback. But, Maruti's two shareholders, Suzuki andGovernment of India get online newsletter and allinformation electronically. This helps to Maruti formore investment and shareholder trust for investment(see Table 10).
Dealers
Maruti has the presence of dealer network at each and everypart of India and connecting through strong electronicnetworking. Maruti's dealers are using e-business (EDI) forbooking online orders, order status, availability of choice
Flexibility to Shareholders Flexibility to Maruti
Flexibility to Maruti
l E-newsletter
l Inventory information ofMaruti
l Online Bidding for Order
l Online payment with Maruti
l Online Order Processing
l Online Order Tracking
l Online vendor ranking
l Online quality informationand rejection rate
l Online contract informationfor vendors
l Auctions/reverse auctioninformation
Table 11 : Dual Nature of SupplierFlexibility at Maruti
l Seamless Procurementusing extranet with around500 dealers
l Online vendor rating helpto reach almost zero defectin Maruti
l Quality inspection rating
l Cut procurement cost
l Manage inventory fromminimum 2 hours tomaximum 2 days, savinginventory cost
l Auctions/reverse auctioninformation
Flexibility to Suppliers Flexibility to Maruti
Flexibility to Maruti
l Online status of the order toprovide accurate information tocustomer about availability of thecar at place
l Less time to book orderl EDPl Online interaction with direct
suppliers for parts delivery andpayment
l Online interaction with financialservice providers and forinsurance parties regarding loansand insurance schemes
l Fast and easy follow-up processesto customers due database
l Electronic bi l l ing and al ldatabases of customer enquiry
l Order tracking systeml Online information about Maruti
and newsletter and all otherinformation electronically
l Information about dealers locationwise given on the Maruti website
Table 12 : Dual Nature of DealerFlexibility at Maruti
l Wide Dealers networkacross country at smallplace
l EDP with dealersl Satisfying dealers demand
by supplying as soon asgetting information
l 70 countries globallyexport dealers for Maruti
l Global reachl Global interaction with
dealers via Internet andknowing their demandelectronically
l Better dealerscommunication system
l Easy sharing and gettingdealers view for Maruti'spolicies
Rajeev Dwivedi and Kirankumar Momaya
29
© 2003, Global Institute ofFlexible Systems Management
IT Partners
To run such a successful integrated e-business system,Maruti needed an infrastructure. This infrastructure consistedof hardware, software, and networking provided by ITpartners. These IT partners gaining advantage to beassociated for long life because Maruti requires continuoustechnology updating and maintenance (see Table 13). Theyalso get advantage to provide same solution for Maruti'ssuppliers. This is helpful to Maruti in order to gain latesttechnology and better streamlined e-business system forbetter and faster processes.
Flexibility to Maruti
l Time to time updatingsoftware's cause longtimeengagement
l Always updating Marutiwebsite
l Always engagement tomaintain such big IT system
l Hardware maintenance andnew hardware supply
Flexibility to IT Partners Flexibility to Maruti
l Centralized Serves for datastorage and services
l FIBER optics line inorganization for better andfast data transfer
l Save CPU cost by using linkbox
l Self ID division to fulfillmost of IT requirementsapart from hardware
Table 13 : Dual Nature of IT PartnerFlexibility at Maruti
Call Centers
GE Gurgaon call center is the call center for Maruti. It istoll free on BSNL and MTNL from all metros and fromGurgaon. Its called Maruti's Customer Information System.E-business is helping GE callcenter for providinginformation to customerselectronically, to solve queryof customer electronically, tosend information and to getback information fromMaruti electronically. The i2i enterprise, who cares Maruti'scustomer in 25 cities in India. This is helpful to Maruti forgaining customer database, information, requirement, andfeedbacks (see Table 14). It helps to improve customer careof Maruti.
Successful value networks excel largely throughtheir technology and information sharing practices.To create an e-business transformation, companiesshould partner with or acquire a company with aproven e-business model and channel.
Flexibility to Maruti
l Communication with Marutithrough Internet tocommunicate customerinformation
l Can get the information aboutcustomer quarry from Maruti'speople online
l Long term association
Flexibility to Call Centers Flexibility to Maruti
l Properly managed customersinformation system
l No bother ness about carsinformation
Table 14 : Dual Nature of Call CenterFlexibility at Maruti
from Gurgaon to Japan, online training to Maruti employeesabout technology and about e-learning from Japan(see Table 15). All information and document transactionsare through the Internet from Suzuki to Maruti and fromMaruti to Suzuki.
Flexibility to Maruti
l Suzuki Motor Japan hasteleconferencing system toconduct meetings
l All information anddocuments transaction throughInternet
Flexibility to SuzukiMotors Japan
Flexibility to Maruti
l E-learning for employeesabout new technologies
l Teleconferencing to discussissues with directors
Table 15 : Dual Nature of Technology ProviderFlexibility at Maruti
Media Partners
Media partners take order for publicity and campaign fromMaruti electronically. The new channels help for bettercampaigning of Maruti. Indiatimes promote Martui's productonline. FM radio in Delhi broadcasts daily a Maruti programcalled” Delhi Traffic” electronically. E-Business supportsMaruti's marketing strategy globally. This helps forcampaigning worldwide with easy and cheaper and frommore channels (see Table 16).
Financial Services Providers
Information about financial services and information aboutfinancial service providers are available of Maruti's website.
Customers can calculate thefinancial scheme throughonline calculator and canchoose accordingly. Again,Maruti is getting customersatisfaction in order toprovide better information to
the customers (see Table 17).
Flexibility to Maruti
l Time to time ad campaign
l Time to time marketingassignment
l New channels for promotion
Flexibility to Media Flexibility to Maruti
l New and cheaper ways forpromotion for Maruti
l Save marketing cost
Flexibility to MarutiFlexibility to Financial ServiceProviders
Flexibility to Maruti
Table 17 : Dual Nature of Financial ServiceProvider Flexibility at Maruti
l Easy loan and financialservices to Maruti's customers
l 70 % of Maruti revenuecomes online
l All financial servicesinformation available onMaruti website
l All policies and Onlinecalculator for getting details onMaruti website
l Online documents transactionand financial processes
Stakeholder Flexibility in E-Business Environment : A Case of an Automobile Company
Technology Providers
Suzuki Motors Corporation is the technology provider tothe Maruti. E-Business helps MUL to have teleconferencing
Table 16 : Dual Nature of MediaFlexibility at Maruti
30
giftjourn@l
Consultants
E-consultancy is the way to find a better solution to aproblem. Maruti takes help of MB Athreya, and AT Kerneyfor performance and e-business respectively. PriceWaterhouse Cooper takes the responsibility of auditing ofthe Maruti. This is helpful both ways, to reduce cost andtime (see Table 18).
Norris M., West S. and Gaughan K. (2001) e-Business Essential:Technology and Network for the Electronic Marketplace, John Wileyand Sons Ltd., New York.
Sawhney M. and Zabin J. (2001) The Seven Steps to Nirvana, TataMcGraw Hill Publishing Company Limited India, Delhi.
Sushil (2000) Flexibility in Management, Vikas Publishing House Pvt.Ltd., New Delhi.
Tettech E. and Burn J. (2001) Global Strategies for SME-Business:Applying the Small Framework, Logistics Information Management,14, 171-180.
Wheeler D. and Sillanpaa M. (1997) The Stakeholder Corporation: ABlueprint for Maximizing Stakeholder Value, Pitman Publishing,London.
www.flexibility.co.ukwww.gartnerresearch.comwww.gartnertechwatch.com (A Broad Guide of E-Business)www.ibm.comwww.marutiudyog.comwww.stakeholderpensionsdirect.co.uk/ stakeholder_for_companies.html
Conclusion, Implications and Limitations of the Study
Conclusion
Successful competitive strategy and corporate results arelikely to focus on performance attributes including speed,flexibility, quality and scale. E-Business can bring suchthings for their stakeholders. Stakeholder flexibility providessystematic understanding of value chain partners and actorsinvolved in e-business system. This understanding is 360degree via considered options, freedom and choice andchange mechanism of stakeholders of any business. The casestudy proves that the flexibility to stakeholders and fromthe stakeholders is the key to success of Maruti UdyogLimited in an e-business environment.
Implications
The managerial implication of the stakeholder flexibility isto enhance understanding of both side of business (businessto partners, customers and vise-versa) in an electronicenvironment of business. The understanding reflects newstakeholder acquisition, old stakeholders retention, andultimate long term association of stakeholders forcompetitiveness of the business via transparency, speed,cost saving, knowledge management, information,communication, better processes and operation, fastertransaction, participation of stakeholders and so on.
Limitations
The paper considered only key stakeholders of thee-business (see Figure 1). Some other stakeholders may beaffected due to e-business environment such as thegovernment, society, and community. We have restricted ourpaper only up to key stakeholders. But, for further study,all the stakeholders may be considered.
ReferencesDawan J., Bodorik P. and Dhaliwal J. (2002) Supporting thee-Business Readiness of Small and Medium Sized Enterprises:Approaches and Metrics, Internet Research: Electronic NetworkingApplications and Policy, 12, 139-164.
l M B Athreya has developeda new performancemeasurement and develop-ment method system andusing electronically
l E-consultancy option ispossible to save money
l E-consultancy can be given toMaruti as Maruti is IT savvy
l Still A T Kerney group isengaged with Marutiregarding problems inE-Business system
Table 18 : Consultant FlexibilityFlexibility to Consultants Flexibility to Maruti
Appendix I : Dual Nature of Stakeholder Flexibility
Stakeholder Flexibility to Stakeholderfrom Business
Flexibility to Businessfrom Stakeholder
Customers l Online Catalogl Online Shoppingl Online after sales
servicesl Online Enquiry/quarryl Order Trackingl Online Paymentl Online Invoicel Online shopping globallyl More options for same
productl Online Feedback and
Suggestionsl Additional servicesl Time Saving, Money
Savingl 24*7*365 days servicesl Flexi time
Employee l E-mail accountsl Online workl Paperless office & workl Fast information
highwayl Online file transferl Online HR policiesl Online performance
statusl Central Knowledge
Bankl Online Communicationl Online Training and
E-Learningl Flexi Timel Flexi Workl Online Business
Informationl Online Company
Informationl Online market
Informationl Analysis softwares
l Customer Acquisitionand Retention
l Database of customersl Customers feedback
and inputsl Market Informationl Market Analysisl Low cost of setting
distribution centersl Online transactionl Lower cost of
marketingl Time and money
savingl Global customer reachl Telemarketingl Showroom Problems
solvel Operation flexibility
l Better Productivityl Proper Document
Managementl Fast information and
document deliveryl Fast intra organization
workl Less cost of paper and
other materialsl Less manpowerl Teleconferencesl Easy system for
performance appraisall Reduced workloadl Fast decision-makingl Knowledge
managementl Fast information
sharingl Remote online
communication
Rajeev Dwivedi and Kirankumar Momaya
31
© 2003, Global Institute ofFlexible Systems Management
Cont... Appendix I
Stakeholder Flexibility to Stakeholderfrom Business
Flexibility to Businessfrom Stakeholder
Suppliers/ l Online biddingVendors l Online order
l Online process fulfillmentl Online order trackingl Online inventory
informationl Online auctionl Online communicationl Online status of orderl Reduced paper workl Reduced process workl Time savingl Online paymentl Global manufacturer
reachl Information of marketl Information of dealers
Distributor l Online Booking of orderRetailers l Online status of orderDealers l Online availability of
productl Electronicl Online insurancel Online financel Online customer quarry
and responsel Online after sales servicel Online paymentl Electronic data
interchangel Market Information,
share information, priceinformation etc.
l Order tracking
Financial l Online Financial policiesServices l Online enquiry/responseproviders l Online feedback/inputs
l Online financel Online billing & invoicesl Online transactionl Online paymentl Online insurance
schemesl Online insurancel All financial information
Technology l Technology consultancyPartners/ l Technology projectIT Partners l Technology updating
l Long term associationl Brand building
Call Centers l Long term associationl More projectl More product assignmentl Knowledge gaining
l Minimum inventorymanagement
l Online status ofsuppliers
l Lower process costl JIT procurementl Order trackingl Reduced paper workl Electronic
communicationl No follow-upl Global suppliers reachl Distributors suppliers
information
l Electronic DataInterchange
l Online order statusl Online demand
informationl Online supply
informationl Online market
informationl Online market researchl Order trackingl Reverse auctionsl Customer demands
l Financial flexibility tocustomers
l Insurance flexibility tocustomers
l Financial transactionl Financial policy and
schemes sharingl Customer satisfactionl Electronic
communication
l Less bother ness abouttechnology
l Latest and updatedtechnology
l Competitive move bybetter technology
l Better processes
l Customer carel Customer quarryl Information to all
information seekersl Services 24*7*365
Cont... Appendix I
Stakeholder Flexibility to Stakeholderfrom Business
Flexibility to Businessfrom Stakeholder
Shareholders l Share informationl Share market informationl Company position and
informationl Company policiesl News lettersl Feed back/inputsl Participation in online
meetings
Media l More channels formarketing
l Long time associationl Lower cost of marketingl Online marketingl Web marketingl Different channels for
promotion
Consultants l Time to timeconsultancy
l Long term associationl Online consultancy
l Shareholder valuel More investmentl Shareholder
perception
l Different channels forbrand building
l Global Promotionl Information reach to
all stakeholders
l Less bother nessl Better solutionl Online consultancy
Stakeholder Value Propositions ofStakeholders
Value Propositions toMaruti
Customers l More interactiveinformation channels
l Increased informationdetail
l Anywhere, any timeservice
l Transparency in services
Employee l Reduced overall load onstaff
l Improved flexibility ofanalysis
l Better matched withemployee needs
Suppliers l Lower cost oftransaction
l Reduced transaction timel Faster access
Dealers l Increased transparencyin order booking andtracking
l Fast EDP
Technology l IncreasedProviders teleconferencing
l Faster informationavailable
l Increased Retainingold customers andacquiring newcustomers
l Increased globalcustomer reach
l Cheaper channel fordissemination ofinformation
l Increased anywhereaccessibility
l Faster process
l Easy supplier selectionl Electronic linkage
with suppliers
l Better probability tosatisfying dealers
l Availability of marketinformation
l Increased technologylearning
Appendix II : Value Proposition for Stakeholders ofMaruti in E-Business
Value proposition is described as perceived value by theinterest group of business in participating in business model.Table shown below in the context of Maruti's e-businessmodel, explains the value propositions from both ends.
Stakeholder Flexibility in E-Business Environment : A Case of an Automobile Company
32
giftjourn@l
Stakeholder Value Propositions ofStakeholders
Value Propositions toMaruti
Call Centers l Increased long timeassociation
Financial l Better security ofservice transactionproviders l Increased financial
information andtransactions online
IT l Increased long timeCompanies association
Media l New ways of marketingPartners
Consultants l Increased E-consultancy
Shareholder l Increased online tradingl Update information of
share
l Enhanced customercare
l Increased onlinetransactions
l Reduced transactiontime and cost
l Better maintenanceand better IT
l Reduced cost ofmarketing
l Easy Global reach
l Reduce cost ofconsultancy
l More investment
Cont... Appendix II Acknowledgement
The authors are thankful to Mr. H. Srivastava of MarutiUdyog Limited for providing valuable information and theirexperiences for the case study.
Flexibility Mapping : Practitioner's Perspective
1. What types of flexibilities you see in the practical situation of "e-Business Environment" on the following points:
l Flexibility in terms of “options”
l Flexibility in terms of “change mechanisms”
l Flexibility in terms of “freedom of choice” to participating actors.
2. Identify and describe the types of flexibilities in “e-Business Environment” that are relevant for your ownorganizational context? On which dimensions, flexibility should be enhanced?
3. Try to map your own organization on following continua(Please tick mark in the appropriate box(es))
E-Business Transformation
Technology only Strategy only
Business Concept
Module Concept System Conceptutside
Business Integration
Vertical Integration Virtual Integration
Business Focus
Shareholder Stakeholder
Nature of Stakeholder Flexibility
One Way Flexibility Dual or Multiway Flexibility
Reflecting Applicability in Real Life
1. How important is the stakeholder flexibility for the success of your organization particularly in e-businessenvironment?
2. How would you enhance the stakeholder flexibility in your organization?
Rajeev Dwivedi and Kirankumar Momaya
33
© 2003, Global Institute ofFlexible Systems Management
giftjourn@lGlobal Journal ofFlexible Systems Management2003, Vol. 4, No. 3, pp 33-37
Introduction
Six sigma framework has been traditionally used for enhancing operational performance byfocusing on reduction of process variations and bringing it within predetermined limitsbased on specified requirements. The essence is to have an analytical approach with anoutside-in view, keeping the end users or customer in focus. So far concepts of six sigmahad been applied to areas related to operations, design or manufacturing either forimprovement of existing processes or design of new products and processes. The core idea ofStrategic Six Sigma is to analyze the likely risks/variations in any given system of initiativescomprising the strategy, identify the cause and effects, and apply “Define, Measure, Analyze,Innovate and Control (DMAIC)” philosophy based qualitative and quantitative tools for processimprovement.
Recently, the six sigma concepts have been innovatively adapted to strategy process andapplied uniquely in the Indian industry for making the strategy deployment process morerobust, yet maintaining the flexibility of options. The liberalization and globalization processhas strengthened the competitive environment which has thrown up unique set of challengesfor Indian industry to be met through innovation. This calls for a unique combination in ourapproach to strategy - “robustness to minimize risks with flexibility to adapt to change” andenhancing organizational effectiveness towards strategy deployment.
The Potential to Unlock Value for the Organization
The defining characteristics of six sigma is disciplined through an analytical approach. Sixsigma in conventional terms is a performance target which reflects how effective and efficientwe are in doing what we are supposed to do. Six sigma is a breakthrough strategy and is amethodology to achieve the six sigma target. If we are not doing things right at the first time,then such situation leads to some kind of waste and every such waste has cost or risks associatedwith it. Be it wastage of engineering man-hours, material, time or even cost of identifying awrong opportunity in strategic sense.
Sigma is a measure of how consistent and hence predictable our actions are. At a highsigma level (say five sigma) our actions will lead to more consistent and predictable resultsthan if we are at a low sigma (say one sigma).
Six sigma is about asking questions and finding answers. General logic and commonsense can lead to general results. To achieve special and different results we need to thinkand act differently. For that, we must ask questions differently. Six sigma orients us to askquestions differently and provides a toolbox of various tools, which help find answers tothose questions.
What cannot be measured cannot also be controlled and managed. We also measure whatwe value and sigma level is a measurement of performance for any process that produces anytype of tangible value based output.
Innovating Growth through “Six Sigma”:A Strategic Approach for Combining Robustness
with FlexibilityAmit Chatterjee
Head-Corporate Strategy & Business Initiatives, TATA Honeywell [email protected]
Six sigma so far applied tooperations, design or
manufacturing andprocesses
Recently six sigma havebeen adapted tostrategy process
Unique combination inapproach to strategy
robustness with flexibility todeal with unique
challenges
Six sigma is a performancetarget which reflects howeffectively and efficiently
we are working
Six sigma is askingquestions differently and
finding answers tothese questions
ShortCommunication
34
giftjourn@l
Motorola pioneered andsuccessfully applied six
sigma in early 80’s
It is performancedeployment, benchmarking
and continuousimprovement tool
Six sigma projectprogresses through
five phases
A Brief History and its Recognition as a World Class Benchmark
The concept of six sigma was pioneered and successfully applied at Motorola in early eightiesand transmitted through Larry Bossidy at Allied Signal/Honeywell which was one of the firstorganizations to adopt six sigma to GE in mid nineties. This phase saw GE’s dramaticturnaround strategy under the legendary Jack Welch. Every aspect and process in GE went thesix sigma way and Jack Welch attributed this approach in bringing in the discipline that laidthe foundation for the organizational success.
Since then it has been recognized as the common language of disciplined approach tobusiness across all organizations around the world that have reaped success. It is nowacknowledged as the performance deployment, benchmarking & continuous improvement toolto be used in conjunction with any business excellence framework the organization may wishto adopt such as TBEM, Malcolm Baldridge or Deming.
A six sigma project progresses through five phases (Figure 1) : Define, Measure, Analyze,Innovate and Control. In Define phase the initiatives definition is completed and scope isfinalized. In Measure phase “as is” situation is assessed. In Analyze phase what is going wrongor risks entailed is studied. In Innovate phase the recommendations are deployed and changeis tested. In Control phase an operational plan is put in place along with necessary measurementsfor monitoring sustained gains. This model is known as DMAIC model. Various six sigma toolsused in these different phases.
Amit Chatterjee
Figure 1 : Five Phases of Six Sigma Project
The approach links up all elements, starting from strategy to the final process that deliversthe desired product or service. Figures 2 and 3 integrative approach that ties up all elementsof the business value chain.
The process flow is as depicted in Figure 4 with extensive usage of tools in each stage ofthe process.
The inherent checks and balances using the stage gate mechanism shown in Figure 5 ofthe six sigma process ensures that investments are focused on the right opportunities andthe risk are minimized. The profile above indicates how investments increase as ideaspropagate through stage gate clearances after satisfying requirements of the process in eachphase.
The Framework and Tools
35
© 2003, Global Institute ofFlexible Systems Management
Figure 2 : Approach 1, Linking Various Elements
Figure 3 : Approach 2, Linking Various Elements
Innovating Growth through “Six Sigma”: A Strategic Approach for Combining Robustness with Flexibility
36
giftjourn@l
Figure 4 : Strategy Implementation-The Six Sigma Way
Robustness with Flexibility by Stage Gate based Checks and Balances
Figure 5 : Stage Gate Balancing for Optimal Investment Profile
Todays competitiveenvironments leaves
no room for error
Six sigma act as long rangeradar that provide balanced
insight and flexibility
Amit Chatterjee
Conclusion
Globalization, disruptive technologies and instant access to information, products and serviceshave changed the way our customers conduct business – old business models no longerwork. Today’s competitive environment leaves no room for error. The dynamics of change isshifting the context of business over night, hence leaderships approach in setting the strategicdirection has to be guided by a sensitive radar. Six sigma strategy tools and framework actsas such a long range radar that guides and develops a balanced insight and at the same time
37
© 2003, Global Institute ofFlexible Systems Management
provides for the flexibility of options needed for strategic corrections in journey to growthand excellence.
Glossary of Terms and Definitions
DFSS – (Design for Six Sigma) is a systematic methodology utilizing tools, training andmeasurements to enable us to design products and processes that meet customer expectationsand can be produced at Six Sigma quality levels.
DMAIC – (Define, Measure, Analyze, Innovate and Control) is a process for continuedimprovement. It is systematic, scientific and fact based. This closed-loop process eliminatesunproductive steps, often focuses on new measurements, and applies technology forimprovement.
Six Sigma – A vision of quality which equates with only 3.4 defects per million opportunitiesfor each product or service transaction. Strives for perfection.
Quality Tools
Associates are exposed to various tools and terms related to quality. Given below are just afew of them.
Control Chart – Monitors variance in a process over time and alerts the business tounexpected variance which may cause defects.
Defect Measurement – Accounting for the number or frequency of defects that cause lapsesin product or service quality.
Pareto Diagram – Focuses on efforts or the problems that have the greatest potential forimprovement by showing relative frequency and/or size in a descending bar graph. Based onthe proven Pareto principle: 20% of the sources cause 80% of any problems.
Process Mapping – Illustrated description of how things get done, which enables participantsto visualize an entire process and identify areas of strength and weaknesses. It helps reducecycle time and defects while recognizing the value of individual contributions.
Root Cause Analysis – Study of original reason for nonconformance with a process. Whenthe root cause is removed or corrected, the nonconformance will be eliminated.
Statistical Process Control – The application of statistical methods to analyze data, studyand monitor process capability and performance.
Tree Diagram – Graphically shows any broad goal broken into different levels of detailedactions. It encourages team members to expand their thinking when creating solutions.
Black Belt – Leaders of team responsible for measuring, analyzing, improving and controllingkey processes that influence customer satisfaction and/or productivity growth. Black Beltsare full-time positions.
Control – The state of stability, normal variation and predictability. Process of regulatingand guiding operations and processes using quantitative data.
CTQ : Critical to Quality (Critical “Y”) – Element of a process or practice which has a directimpact on its perceived quality.
Customer Needs, Expectations – Needs, as defined by customers, which meet their basicrequirements and standards.
Defects – Sources of customer irritation. Defects are costly to both customers and tomanufacturers or service providers. Eliminating defects provides cost benefits.
Green Belt – Similar to Black Belt but not a full-time position.
Master Black Belt – First and foremost teachers. They also review and mentor Black Belts.Selection criteria for Master Black Belts are quantitative skills and the ability to teach andmentor. Master Black Belts are full-time positions.
Variance – A change in a process or business practice that may alter its expected outcome.
Innovating Growth through “Six Sigma”: A Strategic Approach for Combining Robustness with Flexibility
38
giftjourn@l
Introduction
Third GLOGIFT International Conference with the themeon “Technology Transfer, Innovation and Flexibility forReshaping the world” is an effort to bring togetherleading representatives of academic, business andgovernment sectors worldwide to present and discusscurrent and future issues of critical importance related totechnology management. It will provide a platform totechnology researchers, practitioners, developers and usersto explore cutting edge ideas and to exchange techniques,tools and experiences.
Conference Coverage
GLOGIFT International Conference invites researchers andpractitioners to submit papers in areas such as technologyflexibility, technology transfer, innovation systems andhuman aspects of innovation management. The ProgramCommittee encourages practical papers on experienceor on the validation of implementation. The broad areasthat will be of interest for the conference are as follows:
l Technology Flexibility
l Technology Acquisition and Transfer
l Innovation Management
l Culture of Innovation and Flexibility
l Technology Practices in Developing Countries
Who Should Attend
Following the GLOGIFT tradition, this conference will setthe stage and define the directions of technologymanagement for decades to come. Leading experts fromacademic institutions, industrial corporations andgovernment agencies will participate in the discussions.
Important Dates for Papers
The papers are invited from professionals, executives,practitioners and researchers from the world of businessand academics on the topics related to the theme of theconference. A spectrum of relevant areas has beenexhibited under the coverage.
Submission of abstracts (250 words) December 10, 2003
Acceptance of abstracts December 20, 2003
Submission of full papers January 30, 2004
Acceptance of full papers February 15, 2004
All submissions through e-mail at:[email protected]
Registration Details
Registration Fee within India Overseas
Delegates (Academic /R & D) Rs.3000/- US$ 150
Delegate (others) Rs.5000/- US$ 200
Students Rs.2000/- US$ 100
Note - Delegates/Authors will be offered one-yearcomplimentary membership of GIFT - 10% discount toAnnual Members of GIFT, and 15% discount to LifeMembers & Corporate Members of GIFT. Registration feeincludes a copy of the conference proceedings, registrationkit, tea, lunch and attendance in session services. Theregistration fee does not include the cost of boarding/lodging etc.
About Jamia Millia Islamia
Jamia Millia Islamia was founded in 1920 during the noncooperation movement. It was elevated to the status of aCentral University vide Jamia Millia Islamia Act 1988Today, Jamia Millia Islamia is one of the most prominentand promising Central University of India
Conference Proceedings
All the accepted papers will be published in the form ofproceedings and shall be available at the time ofconference. Selected papers presented at the conference willalso be considered for publication in “Global Journal ofFlexible Systems Management” after due review process.
Sponsorship
Organizations are invited to sponsor the conference. Thecontribution made will be prominently acknowledged inall promotional and other conference material. Thepayment is to be made in favour of “Jamia Millia Islamia”payable at New Delhi.
Address for Communication
Organizing SecretaryProf. Abid HaleemFaculty of Engineering and Technology,Jamia Millia Islamia, New Delhi 110025, INDIATel: 91-11-26981268, 91-11-26981717 Ext 2551Email: [email protected]
Third Global Conference on Flexible Systems Management‘GLOGIFT’
From March 13 to 15 2004Theme : TECHNOLOGY TRANSFER INNOVATION & FLEXIBILITY
FOR RESHAPING THE WORLDat
Jamia Millia Islamia, Jamia Nagar, New Delhi -25, INDIA
39
© 2003, Global Institute ofFlexible Systems Management
Event DiaryThis section will contain events related to flexibility. Only highlights and important dates are provided. For moredetails, please visit the web page or contact the organizers. If you are planning any major flexibility related event(global conference/workshop/seminar), please submit the details (Event title, Dates, Place, Theme, Deadlines, ContactInformation, Email, Web Page, etc.) to Mr Ashish Jain, at email [email protected].
Event : The 12th International Forum on Technology Management
Dates : November 18 - 20, 2003
Place : Shanghai, China
Theme : Technology Leadership in the 21st Century: Global Challenge for East and West
Contact : From China, Mrs Vicky YU at [email protected] all other countries: Prof. J.J. Chanaron [email protected] [email protected] details on the program available on the website: www.iftm.net
Event : Bridging the Gap: Sustainable EnvironmentThe First UN Global Compact Academic Conference. Organized by The Wharton School-SabanciUniversity with the Support of UNEP
Theme : Part 1- Innovation and Diffusion of Environmentally Sound Technologies
Dates : May 31 - June 1, 2004.
Place : Istanbul, Turkey
Theme : Part 2- Globalization, Development and Environmental Management
Dates : September 17-18, 2004
Place : Philadelphia, U.S.A.
Contact : Dr. Oktem , [email protected]
See details in the following Internet address: http://opim.wharton.upenn.edu/gc/
Event : IAMOT 2004
The 13th International Conference on Management of Technology
Theme : New Directions in Technology Management: Changing Collaboration Between Government, Industryand University
Dates : April 3-7, 2004
Place : Washington D.C.
Contact : Program Information: Dr. Yasser Hosni, University of Central Florida: [email protected] or for moreinformation visit www.iamot.org
giftjourn@lGlobal Journal ofFlexible Systems Management2003, Vol. 4, No. 3, pp 39
ShortCommunication
40
giftjourn@l
Correspondence :All correspondence and membership applications may be
addressed to the Manager of the instituteat the following address:
Ashish JainGlobal Institute of Flexible Systems Management (GIFT)
S-15, LSC, DDA Commercial ComplexMayur Vihar, Phase-I,
Delhi - 110 091
l All individual members will get onecomplimentary copy of the gif t journ@l .
l All corporate/institutional members willget three complimentary copies of theg i f t j ou rn@l , one for library and two fornominees.
About GIFTGIFT (Global Institute of Flexible Systems Management) is a professional society to enhance “flexibility” in business andmanagement.
MissionTo evolve and enrich the flexible systems management paradigm for the new millennium.
VisionEvolving as a global forum for interaction of all interested professionals and organisations in a truly flexible mode so asto help them create more options, faster change mechanisms and greater freedom of choice in their own settings.
SchoolsThe Institute comprises of various schools, which are autonomous bodies, dealing with contemporary areas at the cuttingedge contributing to the flexible systems management paradigm. At any point of time, each member can opt for anassociation with any two of the following schools in the respective thrust areas:* GIFT School of Global Management* GIFT School of Technology and Innovation Management* GIFT School of Information Technology & Knowledge Management* GIFT School of E-Governance* GIFT School of Learning Organisation and Strategic Transformation* GIFT School of Quality, Productivity and Wastivity Management* GIFT School of Environment Management and Sustainable Development* GIFT School of Human Values and Management Ethos
Publications– Book Series on Flexible Systems Management– Quarterly Journal - “Global Journal of Flexible Systems Management” gi f t j ourn@l– Newsletter - “Flexibility”
MembershipThe membership fees for different types of members, unless changed/revised by the Governing Council from time to time,will be as given under:
With in India Overseas
Student (Annual) Rs. 500.00 US$ 25.00
Annual Rs. 1,000.00 US$ 50.00
Life Rs. 10,000.00 US$ 500.00
Corporate/ (a) for corporate bodies having turnover has less than Rs 20 Crore and for non-Institutional business/non-profit making organisations/institutions:
Rs. 50,000.00 US$ 5,000.00
(b) for corporate bodies having turnover more than Rs 20 Crore:
Rs. 1,00,000.00 U$ 5,000.00