a I . . g '3!- -. L4. an. mt: ' «wax .u ‘ ‘“ A ' “a. 4"? ..“.._1.“...L.u. < - c» ‘4 “ha I ““J.) ‘ _-. , 33:2. , “a ,. n .- §”§1. :AJ. ,. ~ - q. ’6“ ‘. m .- u “a." $3335, at“ _ 4L. , ‘R “It?" 11;:‘35. "" ”‘ . ;~;“.“§ s; . w . L 1.. J? . a ‘19}??? -‘" ‘51,. “2‘02“. ' h 4 a“! ~~“ .. «“1: ‘f €1,131 “4* 3! V" ‘ ~ , : ‘ .. 3,. ,. ‘1“? “Wig-a: “figfifzmfiw 335$ ‘- "< ”“4“” -._ fl} ' ‘ E ‘12:”. x 3 “r, Lu. ' any“. ,5 ~€§fiz~ éfiwcaif ( 1X «MA : - u. of ‘L ~‘&»‘-\\J . I; '_ v9.21». “ 1 m 974“” ’54:“? .L :1 . .. :- ,. 9).“,4‘ ~z‘y‘.‘;. «- vw. ’4‘; ‘ what . . Ctyjé 1 > , A m «y- x'. ”9;- m-w . ' . t f . . wan." ,0" . ~w4‘ ' l‘.“" V ' ' “ v'VV" .. “- 1 q M ‘H‘I , , lyir“ awe! . . ,. I. ,A- .u .‘9 i. . v‘l?‘ . . w. ‘12-. ”,2 1}. :"UCR'. I. “’1'h',’ a!“ K ' . 1. a u. , I. a.) I?“ . rig-ii“ ..-, (g, A‘ U45 u'.‘ J ..h “V n c‘ , vr-f'v‘x'i" ,1 _ “A," fut-my, 4r: 4..“ pm ' . ‘h‘1_l,.,plvlvnu'-- g»? .m. -.‘-~‘i'~‘v3“‘"“!';ti ,' . ‘14“ _ . H» . {3)}: Wu. J , . “I. ‘ . ‘55..“ n3..." ‘. £53; ‘ v_ . ”gag-1% PW—fl « ‘fi/r - ’ .511" 5'1". . ”- v. :_. urlll’illjflljlitllfllliilmilll‘lflfiil 01029 2245 This is to certify that the dissertation entitled THE ROLE OF THE B U YER 'S UPPLI ER LINKAGE IN AN INTEGRATED PRODUCT DEVELOPMENT ENVIRONMENT presented by LAURA MARIE BIROU has been accepted towards fulfillment of the requirementsfor DOCTORATE degree in PHILOSOPHY (mafia/“49W o- O, Major profes'sor Date alpine 5"", 199+ MSU is an Affirmative Action/Equal Opportunity Institution 0-12771 LIBRARY Michigan State University PLACE N RETURN BOX to remove thle checkout from your record. TO AVOID FINES return on or More dete due. DATE DUE DATE DUE DATE DUE MSU ie An Affirmative Adm/Equal Opportunity inetitwon WM! THE ROLE OF THE BUYER-SUPPLIER LINKAGE IN AN INTEGRATED PRODUCT DEVELOPMENT ENVIRONMENT By Laura Marie Biron A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Management 1994 ABSTRACT THE ROLE OF THE BUYER/SUPPLIER LINKAGE IN AN INTEGRATED PRODUCT DEVELOPMENT ENVIRONMENT By Laura Marie Birou The focus of this research was to identify the supplier’s role in the new product development process. More specifically, the purpose of this research was to gain an understanding of what constitutes supplier involvement in the new product development process which utilizes 3 Integrated Product Development (IPD) strategy, and determine what impact this involvement had on the success of IPD. The first objective involved defining supplier involvement, and how it can be accurately measured. The ability to accurately characterize and measure supplier involvement facilitated the accomplishment of the second objective, the identification of the relationship between supplier involvement and the results obtained by employing the IPD strategy. The research methodology involved a large scale empirical investigation of firms utilizing the IPD strategy. Data was gathered from 133 respondents, a 51.9 percent response rate, through the use of a self-administered questionnaire. Indepth information was provided regarding the organizational, project, and interorganizational variables which impact the success of new product development efforts. The data collected was used to test several hypotheses concerning the impact of supplier involvement on the success of IPD and the market performance of the firms. The research demonstrated that supplier involvement in the new product development process in an integrated environment had a detrimental impact on product cost, quality, performance, and development time. These findings are contrary to current convention which advocates procurement strategies fostering a high level of supplier involvement such as, partnering, strategic alliances, joint ventures, risk-sharing agreements, and technology sharing arrangements. This research calls into question the strategic advantage of supplier involvement in the new product development process and reveals a need to actively monitor the contributions made through these relationships. Copyright by LAURA MARIE BIROU 1994 AS THE BENEFICIARY OF UNCONDITIONAL LOVE I DEDICATE THIS WORK OF LOVE TO MY HEROES, MY PARENTS. ACKNOWLEDGEMENTS I begin this acknowledgement with trepidation as there are many factors which contribute to the success of any project, as my research has discovered, and I fear that my list will not be all inclusive. In analyzing projects that were considered successes and failures, the underlying question remained-How do we duplicate success? What is the key success factor? Many conversations, brainstorming sessions, and case studies revealed a variable called group cohesion, commitment, leadership, and personal trust. The underlying dimension was the degree to which individuals were willing to extend themselves for the benefit of another or a cause--LOVE. This dissertation is the product of the love demonstrated by many individuals. I will do may best to include them all in this acknowledgement. First of all, I would like to extend my appreciation to the members of my dissertation committee Dr. Stan Fawcett, Dr. Steve Melnyk, and especially my chairperson, Dr. Ram Narasimhan. Their personal dedication to me demonstrated through the countless hours of mentoring, encouraging, developing, pushing, and perfecting this project will forever be remembered. In addition, I would like to thank Dr. John Hoagland for the role he has played in my life. His passion for the field of purchasing has served as a model of dedication. He has served as a mentor, teacher, and most importantly a friend. I can never repay his kindness. I can only try to duplicate VI it with my students. To my friends and colleagues at Michigan State University--Lee Buddress, Barb Cofield, Larry Fredendahl, Mike D’Itri, Soumen Ghosh, Mike Heberling, Vijay Kannan, Joel Litchfield, Steve Lyman, Anne and Scott O’Leary-Kelly, Sue Polhamus, Greg Magnan, David Mendez, and Ernie and Christine Nichols--Thank you, this would not have been possible without you. ”One For All, All For One!" To my students, who have who have been very understanding and supportive during a very demanding part of my life. Your love has helped sustain me during difficult times. Aut Disce Aut Discede--Carpe Diem! To my friends--Barb Cofield, Abby Daniell, Gayle DeBruyn, DeDe Dezelski, Carol Dougherty, Steve Durand, Lisa Ellram, Jeannine Kerwin, Marty and Kerry Mullane, Sue Polhamus, Barb Shannon, Trent Whitehead, and Sue Zarish--who have sacrificed with me in giving me one of the greatest gifts of all in the focused pursuit of this goal, my time. To my family-—Mom, Dad, Grandma, Ronn, Diane, Todd, Lisa, Jeff, Kevin, Kelli, and Randi, thanks for believing in me when my belief in myself was wavering. For two angeles--Vittal Anantatmula and Nancy Manuszak--who have made this process infinitately more bearable. You helped me carry the football into the end zone--the longest yard. Last but not least, I would like to express my gratitude to the National Association of Purchasing Management and The Michigan State Purchasing Development Fund for funding this research effort. I would like to recognize the International Federation of Purchasing and Materials Management, the International Quality & Productivity Center, Productivity Inc. , The Society of Computer-Aided Engineering, and all of the research participants for supporting this research and my personal goal. VII TABLE OF CONTENTS Chapter I INTRODUCTION 1.1 External Pressures for NPD in Manufacturing 1.2 Accelerating NPD Cycles 1.3 Product Cost, Quality, Performance and NPD 1.4 Research Purpose 1.5 Research Contributions Chapter II LITERATURE REVIEW 2.1 Historical Background 2.2 Organizational Level Research 2.3 Project Level Research 2.4 Interorganizational Research Chapter III CONCEPTUAL FRAMEWORK 3.1 Overview of Conceptual Framework 3.2 Supplier Involvement 3.3 Integrative Mechanisms 3.4 Group process (GP) 3.5 Resources 3.6 Integrated Product Development Success (IPDS) 3.7 Firm Performance Chapter IV RESEARCH METHODOLOGY 4.1 Firm Performance 4.2 Supplier Involvement 4.3 Research Design 4.4 Survey Instrument Development 4.5 Sample Population 4.6 Data Collection 4.7 hdeasures 4.8 Model Specification 4.9 Data Analysis 1-14 SOOOQUI 15-62 15 21 32 43 63-87 66 7 1 74 75 77 8 1 83 88-115 88 94 105 108 109 110 113 Chapter V ANALYSIS AND FINDINGS 5.1 Description of Research Participants 5.2 Preliminary Statistics 5.3 Re—Specification of the IPDS Conceptual Model 5.4 Hypothesis Testing 5.5 Controlling for Exogenous Variables 5.6 Impact of Supplier Involvment on an IPD Environment Chapter VI CONTRIBUTIONS AND CONCLUSIONS 6.1 Contributions 6.2 Conclusions 6.3 Limitations 6.4 Implications for Future Research 6.5 Concluding Remarks APPENDIX I Participant’s Letter Survey Instrument APPENDIX II T-Test for Size by Annual Sales T-Test for Level of Innovation T-Tesst for Competitive Intensity APPENDIX III Varimax 5 Factor Analysis Oblim 5 Factor Analysis Varimax 6 Factor Analysis Oblim 6 Factor Analysis BIBLIOGRAPHY LIST OF TABLES LIST OF FIGURES 1 16-203 116 134 161 170 201 202 204-215 204 208 211 213 214 216 218 230 231 232 233 236 239 242 245 XII 5-1a 5-1b LIST OF TABLES Summary of Organizational Level Research Summary of Project Level Literature Summary of Interorganizational Level Research Dimensions and Measures of Supplier Involvement Dimensions and Measures of Integrative Mechanisms Dimensions and Measures of Group Process Dimensions and Measures of Resources Dimensions and Measures of IPD Success Dimensions and Measures of Firm Performance Kolmogorov - Smirnov Goodness of Fit Test-Independent Variable Kolmogorov — Smirnov Goodness of Fit Test-Dependent Variable Dimensions and Measures of Supplier Involvement Dimensions and Measures of Integrative Mechanisms Dimensions and Measures of Group Process Dimensions and Measures of Resources Dimensions and Measures of IPD Success Dimensions and Measures of Firm Performance Varimax 4 Factor Analysis Oblimin 4 Factor Analysis Varimax 7 Factor Analysis Oblimin 7 Factor Analysis Reliability - Supplier Involvement Reliability - Buyer Supplier Relationship Reliability - Integrative Mechanisms Structural/Cultural Reliability - Information Importance Reliability - Information Accessibility Reliability - Group Process (GP) Reliability - Resource Utilization Regression Results for Firm Performance Regression for Market Performance Regression for Relative Performance Summary of Research Findings Summary of Significant Correlations Reduction in Product Cost Reduction in Start-up Costs Reduction in Tooling & Equipment Costs Reduction in Total Manhours Reductions in ECN’s Reduction in Warranty Costs Reduction in Customer Complaints 30 44 59 73 76 78 80 84 86 137 138 140 141 143 144 145 146 148 151 155 158 162 163 164 165 166 167 168 171 173 175 180 181 179 182 183 184 184 1 87 1 88 5-29 5-30 5-31 5-32 5-34 5-35 5-36 5-37 5—38 5-39 5-40 5-41 5-42 Reduction in Rejected Material Reduction in Project Development Time Improvement in Communication Reduction in Manufacturing Cycle Time/Lead Time Improvement in White Collar Productivity Improvement in Product Performance Improvement in Market Share Increase in Perceived Value Increase in Perceived Quality Improvement in Dollar Sales Improvement in Product Profitability Improvement in Product Capabilities Summary of Hypothesis Testing for Supplier Involvement XI 189 191 192 193 193 195 196 197 197 198 199 200 203 5-10 5-11 5-12 5-13 5-14 5-17 LIST OF FIGURES Traditional/Sequential NPD Process Integrated/Simultaneous NPD Process Susman & Dean Causal Model of Variables Supplier Interface in the IPD Strategy Literature Review IPDS Key Success Factors Susman & Dean Causal Model of Variables Supplier Interface in the IPD Strategy Supplier Interface in the IPD Strategy Suppliers Represented Primary Industry Primary Industry - Detailed Size by Number of Employees Size by Annual Sales Product Function Product Development Product Marketing Product Technology Source of Benchmark for the Product Manufacturing Process of the Product Type of Suppliers on Team Primary Reason for Supplier selection Type of Supplier Personnel Involved Integrative Product Development Re-Defined XII 11 13 16 42 65 67 70 118 119 121 122 123 124 125 126 127 129 130 132 133 135 169 CHAPTER I INTRODUCTION The dependence of the United States economy on the manufacturing sector is evidenced as ”the traditional industrial sector has long been the leader in US. growth in productivity, the wellspring of innovation, and the generator of a rising standard of living - Akio Morita” (Norman, 1986: 57). This reliance on manufacturing as the source of wealth for the United States economy is of significant concern as our manufacturing strength continues to deteriorate and the service sector becomes the fastest growing segment of the United States economy. The service sector has not been able to duplicate the wealth-generating capability of the manufacturing sector because of low productivity levels and the limited value-added nature of the product. Revitalizing US. manufacturing prowess, therefore, is a critical element in sustaining the standard of living enjoyed by the American population. New Product Development (NPD) is rapidly becoming the key issue in the quest for sustained growth and profitability for manufacturing firms. NPD ~' involves the range of product development activities from the enhancement of existing products, often referred to as model change, to the development of brand new products which may require the adoption of new technology. A survey conducted in 1981 by Booz, Allen and Hamilton involving 700 U. S. companies revealed that new products would account for one-third of all profits in the 19805, 2 an increase from one-fifth in the 1970s, and the trend is projected to continue (Takeuchi and Nonaka, 1986). In addition, a comparison of firms and the lengths of their new product development cycles revealed that firms with shorter product development cycles demonstrate higher performance (Birnbaum, 1988; Davidson, 1988). The challenge to rapidly develop and introduce new products in the marketplace is the focus of contemporary manufacturing concerns. One strategy being utilized to meet this challenge is known as Integrated Product Development (IPD). The essence of IPD is the integration of the design of the product with the process utilized to manufacture it. The objective of IPD is improving product quality and performance, while reducing product development time and product cost. Traditionally, product and process designs have been done sequentially, effectively ignoring the interaction between the two sources of innovation (see Figure 1-1). The IPD strategy represents a departure from the traditional approach in that product and process designs are developed concurrently (see Figure 1-2). The purpose of the present research was to gain a deeper understanding of the new product development process in an IPD environment. The intention was to determine the impact an IPD strategy has on the NPD process and the performance of the firm, and the supplier’s role and contribution. More specifically, the research sought to determine what constitutes supplier involvement in the development of a new product which utilized the IPD strategy 382m AEZ .mscosaoflficogefik. Z 559... Ewuzou >8JOZZUE. 3w: 3 3 lav—mun 1 $8200 20.30 I 122303. uZCP~ /I 339.. 8:885 L a :28: Sufism 8.63.8.3 c225 SiéeSm .885 / \ E 5:35qu «move... W 30.95qu Ecumxm anion muooz acute: v r 30.9.50... 882a 5 and to determine what impact this involvement had on the success of an IPD effort. 1.1 External Pressures for NPD in Manufacturing ”America’s Third Industrial Revolution” (Helfgott, 1986) and "Post-Industrial Manufacturing” (Jaikumar, 1986) are phrases which have been coined in an attempt to capture the significant trends causing the rapid re-structuring of the US. manufacturing industry. Historically, the shift from an agricultural society to an industrial society took place over the course of 100 years. In the new era of manufacturing, the US economy has gone through a transition from an industrial to an information orientation in a mere 20 years (Warnat, 1983). The unprecedented rate of technological obsolescence- -the rate at: which current technology is replaced by new, improved methods and practices--raises concerns as to whether the United States is losing the innovative capacity necessary to compete in the world market (Van De Ven, 1986). Achieving competitive success in the future, and sustaining it, will depend on our ability to innovate (Howell and Higgins, 1990; Hayes, et al., 1988; Kanter, 1983; Peters and Waterman, 1982; Porter, 1980). Technological obsolescence as a force in the US. marketplace is driven by the emergence of foreign competition and the changes in the buying patterns of .. consumers. Consumers have become increasingly quality conscious. Perceived value and reliability are seen as key components of every product in today’s highly competitive marketplace (Phillips, et al., 1990). As such, consumers have 6 become accustomed to and demand new products and frequent model changes as they seek to satisfy their desire for individualism (Bolwijn and Kumpe, 1986; Gutenberg, 1984; Helfgott, 1986). Success in today’s marketplace depends on a firm’s ability to keep pace with rapid changes in market demands. Product life cycles have been reduced dramatically, placing significant pressure on corporations to introduce new products in quick succession to remain competitive (Howell and Higgins, 1990; Bolwijn and Kumpe, 1986; Harris, 1986). A survey conducted by Gupta and Wilemon (1990) identified several factors leading to the need for accelerated development of new products. The two - primary reasons cited were increased competitive pressure from both domestic and foreign sources and the rapid rate of technological change. Respondents also mentioned the following as contributing factors: consumer demand for new products; business growth objectives; shortened length of the Product Life Cycle (PLC); pressure coming from senior management; and the desire to be the first supplier in the market. Welter (1989) stated that by 1990, the average company would generate 40 percent of its sales from products which were less than five years old. For example, corporate objectives at 3M dictate that each division be evaluated on the percentage of sales generated from new products. The '25 % Rule" states that a quarter of a division’s sales must be derived from products introduced within the last five years (Mitchell, 1989: 61). This heavy reliance on new products points to a major weakness in the manufacturing segment of the United States economy. Manufacturers in the United States take 25 percent more time to develop and deliver a product than in 7 the best of the overseas companies. (Spencer, 1990: 49). While the United States has long held a leadership position in the development of new technology (Clark and Hayes, 1988), industry has failed to capitalize on this position. The problem resides in the inability of firms to effectively ”transfer technology” from basic research to applications which provide value to the consumer. Duffy and Kelly (1989) support the importance of being the first supplier to the market, as it tends to ensure a 50 percent market share for the company. The eventual outcome of this situation is the loss in profits by United States manufacturers to competitors who have the ability to rapidly adopt new technology and convert it into a commercial product, preempting the developer of the technology in the delivery of the product to the market. 1.2 Accelerating NPD Cycles The importance of Time-Based Competition (Stal, 1988) is beginning to be recognized as a source of competitive advantage. Firms introducing high-tech products six months past the projected release date, but within budget, realized a 33 percent decrease in expected profits over the first five years. On the other hand, firms introducing products on-time, 50 percent over budget, suffered only a 4 percent reduction in profits (Gupta and Wilemon, 1990). Research conducted by Clark, Chew, and Fujimoto (1987) concluded that each day of delay in the introduction of an automobile with a market value of $10,000, leads to a loss of at least $1 million in expected profits. The authors state that this is a conservative estimate since it does not include the impact lost sales have on cost 8 or future market share. The length of development time is, therefore, a crucial ' factor in the success of any new product in the market and the continuing success of a business. The motorcycle industry provides an excellent example of the relationship between the rate and timeliness of new product introductions, and competitive success. In the battle over market share between Honda and Yamaha in the early 19805 (Abegglen and Stalk, 1985), Honda was able to take the leadership position in the industry by introducing 113 model changes in 18 months compared to 37 model changes by Yamaha during the same time period. Consumers responded positively to the rapid product introductions with leading—edge designs incorporating new technology, quality, and value. 1.3 Product Cost, Quality, Performance and NPD It would be inappropriate to conclude that NPD focuses strictly on the timing of new product introductions. Customer satisfaction demands not only new products but also that these products simultaneously deliver high quality and value. Research involving the use of the Profit Impact on Market Strategy (PIMS) database revealed a strong correlation between high quality, high productivity, high market share, high profitability, and high return on investment (Bhote, 1987). The scope of the NPD process therefore encompasses the delivery of a high quality, cost-effective product incorporating the latest technology in the shortest possible time from concept to market. Post-World War 11 manufacturing has carried most of the blame for the 9 decline of the U.S. competitive position in the world market. Poor quality and high product cost were attributed to inefficient and ineffective manufacturing practices. The focus is now shifting from manufacturing to design as the primary cause of poor performance in the marketplace. Forty percent of all quality problems can eventually be traced back to inferior product design. In addition, 60 to 80 percent of a product’s t0tal cost is determined in the design stage of product development (Raia, 1989: 58). The realization that quality and cost must be designed into the product instead of I'built—in" by downstream operations (manufacturing/purchasing) has brought new attention to the process and priority of NPD. Product design is now seen as a formidable weapon in the search for a global competitive position and Integrated Product Development (IPD) is being touted as a solution for the "Transfer of Technology" problem in the area of new product development. 1.4 Research Purpose The purpose of this research was to advance the understanding of what constitutes supplier involvement in the NPD process which utilizes an IPD strategy and what impact this involvement has on the success of IPD. The essence of this strategy involves the integration of the design of the product and the process used to manufacture the product. One objective of the IPD strategy is to design the product for ease of manufacturing and assembly (Stoll, 1988). The goals of this approach are to improve product quality and performance, while simultaneously reducing product cost and development time. 10 With an average of 56 percent of each sales dollar spent on the procurement of production materials, the impact of the supply base on product quality and cost cannot be over-emphasized (Burt, 1989: 127). Research conducted by Clark (1989) involving 29 NPD projects in the automotive industry provided a comparison of performance among firms in Europe, Japan and the United States. The comparisons were based on two variables: the number of engineering man- hours required and the project lead time. Results indicated that one-third of the reduction in man-hours and the four to five months of the lead time advantage enjoyed by the Japanese can be attributed to the impact of their relationship with the supply base and early supplier involvement. It is generally agreed that early supplier involvement in the NPD process should result in beneficial gains for the firm; what remained to be determined was the nature and degree of involvement, and the specific IPD objectives influenced by this involvement. Through this research effort, the term supplier involvement (SI), its meaning and measurement, was developed and interpreted in the context of the IPD strategy. The ability to accurately characterize and measure the level of supplier involvement facilitated the accomplishment of the second objective, which involved identifying the relationship that exists between the level of supplier involvement and the results obtained by employing the IPD strategy. A causal model developed and validated by Susman and Dean (1991), which represents the process associated with the utilization of the IPD strategy (see Figure 1-3), was adapted for the purpose of this research. This model presents a framework for the identification of important variables and their relationship to 11 A 9.3.2 C 35.253362 ._ mmmuuzm .300 hum-tog 0... $2.06.. m3m no .5002 ...5.um4 /._m._ ._w>w._ 43. man: «A .950... .8...» $5890.. 958A.» A... .3 3:83.). I 2 flee—Tom b.3632.— i=8 2...? Essa. $3. . ON 93... 8 .553. PE 8. 5. ebonAe. 83... 3.8 8.8%.. $2. . On .38 . ca 36... .852 e. 58.50 s 8:88.. $80.23 5.... 8855. =o=8.==EEoU $2.895. $3 08.... 23 88:8... 5 8.633. 88.8 .8. u. gnaw. a 88:8... $3.3 2:30 55.53 5 8.8.63. E 83 are“: 38?. a 8:88.. 2 .80 8.62.. s 8:88.. seen $8.3 $9. . on 89—20 ust8e.m>m e. 8.8..qu .83 805.2“ 8% . on $8 25... .858.o>oo c. 332.3. o8. .AEEEA £9an.35 Ax... «£55... .e._..o.....=_u .3 6.53.332 «mo. .wctouc.m=m mataocA=§2 :2 5.2. 6.5.2 xwm. .m:too=.w:m 3:295:52 0.2 :33. ..o....=5w 32 save... .eoEomfias. 3.3. 5.2 e .25. 5.8 883. .383 $2.35 ...8=§..=S.2 e. .33 .0525 <.. ea. 50:932.. .- m e6 .55.; as. .325. ”853m .53.... ..z 2.8 .9... 43 upcost, 65 percent reduction in production leadtime, and better communication. A summary of the project level research is summarized in Table 2-2. 2.4 Interorganizational Research The interorganizational portion of this literature review serves two purposes. The first objective is to understand the dynamics associated with an interorganizational relationship. The second objective is to specifically focus on the interorganizational relationship of interest to this research, that of the buyer/supplier. The review begins by delineating the motives and catalysts for fostering highly integrated buyer/supplier relationships. This is followed by a presentation of the previous research which has identified the nature of the relationship, interorganizational structure, information flow, and resources as some of the key variables which serve to impact the degree of integration between organizations. The section will conclude with the expected benefits of an integrated buyer/supplier relationship in the NPD environment. 2.4-l WM The primary motive for including suppliers in the NPD process is the quest for a sustainable competitive advantage. The source of this competitive advantage is derived during the product design phase of the NPD process which drives 70to 80 percent of the final production cost, 70 percent of the life cycle cost, and 80 percent of the product’s quality performance (Dowlatshahi, 1992: 22). Firms seeking to capitalize on the strategic importance of product design are extending Table 2-2. Summary of Project Level Research AUTHOR COMMENTS STRUCTURE INFORMATION FLOW DixomDuffey (1990) Evans (1988) Fujimoto (1989) 6131:.de (1990) Shrivastava.$ouder(l987) SmDean (1989) SmDean (I989) Fujimoto (1989) Utterback (1974) Vasilsh (1987) Evan (1988) Stauffer (1988) Fujimoto (1939) Martin (1987) Stalk (1988) Smithkeimnsen (1991) Tubman (1988) Utterback (1974) Van De Ven (1974) SW (1988) OM (1974) Developedasixmgemodelforproductdesignwhiehissimilarm traditiomlNPmeeess. Divisimofproductandproeessdesignsandornm’nfiomlm irnpedeIPDprocees. WWbleformofNPDmndpmjeu. Chmineornpetitivernarbtdernndsnpidproductdevdopneu. NPDmasaprofiteemeundrefenedaspmmre. Tndeofibameffeedvmofmremdmin annintionenviromwarithDprocees. Needfiorirmgudouoffunetiouforamfirlinovadoo. MultifunctiomlmforNPDprojeetfruncomepttomtet delivery. Creedonandmmisiouofinformfionasamjormm moftirneinNPDprooess. Proxirnitymummbenisirnpommforthemof prom TuneisaSourceofcornpetitiveedvmge. Ranavingburieummunieefionismaskeyvariablem WW WMMMmMyMuW Table 2-2 Cont'd. 45 AREA AUTHOR COMMENTS LEADERSHIP Farris0982) Efieetivemmgernentsrylesareeuegoriaedeseolhbondon. HomllJiiuim (1990) Product chmpionsdemomate higherrisktakiumimde. greater marmmmmummwm transformationnlleederdripbehavior. Keller.1101hnd(1978) mmmmmmwum Allen,Ooherr0969) breelwdonofprojeetleedeu. Marryothen GROUP Hunphrey0981) Deepperwmlemriunenb-edonimelleemlbefiefindregml COHESION andenrotiomldeeiretoaehieveitwmbringreenlubegw expectations. RESOURCES Gupn,WilernoMl990) Leekofnffieienmhamheuinrthedehyofm productinmduetion. “W096” Depeesoframmem-ouhenidumm Aihenjhge0968) eorrelaterohigherprojectperfomme. M,Cowe1|0979) . W096» Projeeubenefitfrundaekm. M0989) muwawnwmmm M0981) eu-Tqudrirnethods. mow) mammnmmm 50110988) ldeufifiedtheneedtouepnmeMyIisoflPDmimm monument! 211001me Umbeek09‘l4) Aeoeuroruoureeisoneofthebyvuinbleeinareeeufifl m PROJECT 800110988) Whhfiwmdlfl). PERFORMANCE Vasihsh (1987,1989) mmummmmdmo Mnyodrers mummwithm 46 the scope of influence over the process to include the supplier. Inclusion of the supplier in the process is commonly referred to as supplier involvement or "early sourcing” which encompasses a wide spectrum of purchasing strategies including buying in advance of production, and forward buying or hedging. Stone’s (1983) definition of early sourcing states that ”key suppliers will be established during the design phase of new product programs. This early supplier involvement in quality-oriented value engineering activities is aimed toward obtaining quality designs, quality processes, and quality parts." The goals of early supplier involvement include a reduction in manufacturing costs, improved manufacturing competitiveness, fewer part numbers, and technology transfer. ' A nationwide survey of purchasing professionals and design engineers conducted in 1979, 1988 and 1990 by ”Purchasing" and "Design News” consisted of 1,000 respondents from each profession. The respondents overwhelmingly indicated that suppliers are involved earlier in the design cycle in order to capitalize on the vendor’s expertise, capitalize on the latest technology, achieve better quality, achieve better manufacturability, lower costs, gain access to the latest technology, and as a response to shortened design cycles. A comprehensive list of the potential advantages of utilizing an integrated product design process is offered by Dowlatshahi (1992: 22) and includes reduction in product development cycle time, avoidance of costly future redesigns, reduction in duplication of effort, better communication and dialogue, more efficient operations and higher productivity, overall cost savings, avoidance of product recalls, lower maintenance costs, more reliable products, better 2.4.2 47 customer satisfaction, and improved bottom-line earnings. Interorganizational Relationships One framework for understanding interorganizational relationships is based on the scope of the strategic planning environment. Business level strategic planning encompasses the task environment focusing on the immediate competitive environment (industry, customers, competitors). Corporate strategic planning involves domain definition, or the determination of the desired operating environment. Interorganizational strategy is concerned with the mutual interdependence of firms operating in a network. The interorganizational level planning approach moves the focus from the individual organization to a population of organizations. This approach has been referred to as collective strategies which frames the "...concept of strategy in terms of collective mobilization of action toward the achievement of ends shared by the members of the interorganizational network” (Astley and Fombrun, 1983: 577). The rise in the strategic importance of interorganizational relationships has mirrored the movement of the focus of strategic planning from the firm to the network level. An example of this movement is presented by the hierarchial trilogy of the popular strategic planning texts by Michael E. Porter-mm Strategy. Wm and WM (1980, 1985, 1990). The nature of the interorganizational relationship has been portrayed in the literature dichotomously as either independent/dependent or interdependent 48 (Bresser and Harl, 1986; Campbell, 1985), and individualist or communal (Astley and Fombrun, 1983), competitive or collaborative/cooperative (Gerlach, 1987; Astley, 1984). The source of the distinction between the models is often the distribution of power in the relationship (Thorelli, 1986). The collective or network models recognize the shared interdependence and distribution of power. Spekman (1988) refers to this distribution as bilateral, recognizing that the balance of power is essential to successful conflict resolution. Competitive models are based on dependency and a skewed distribution of power. These relationships are marked by a win-lose mentality on the part of participating organizations. Historically, the model adopted by United States firms has been based on the dictates of the capitalist economy which fosters competition. The network model, adopted by Japanese firms, is facilitated by structures which foster complex, long- terrn business alliances based on long-term reciprocity. The impressive competitive position of Japanese firms operating in a variety of industries has elevated the interest in understanding the dynamics of these "strategic alliances”, and their contribution to technological innovation and market development (Gerlach, 1987). Trust has been identified as a key component of effective long-term integrated relationships (Campbell, 1985; Thorelli, 1986; Johnston and Lawrence, 1988). This characteristic is inconsistent with the market-based competitive model which views this as establishing the environment for the greatest exploitation of opportunistic behavior (John, 1984). Mutual commitment, close collaboration, 49 long-term cooperative attitude, repeated contacts, shared information, joint long- term planning, and a non-adversarial approach have also been cited as instrumental in establishing integrated relationships (Sriram and Mummalaneni, 1990). Spekman (1988) refers to this change in buyer-supplier relationship as the "Quiet Revolution” which can only be facilitated by a reduced set of suppliers. Single-sourcing arrangements have been advocated in the supply management literature to improve quality, cost, and innovation (Burt, 1989; Raia, 1989). Some concerns have been raised with regard to a single-sourcing strategy. As the dependency between the buyer and supplier grows there is a corresponding decrease in strategic flexibility (Newman, 1989; Bresser and Bar], 1986). Dual- sourcing has been offered as a strategic alternative and buffering mechanism against the disadvantages of a single-sourcing policy, while capable of delivering many of the same benefits (Newman, 1989). Frazier (1983) has identified goal compatibility between organizations as a requirement for long-term relationships. Congruent goals and expectations are seen as leading to a higher level of role satisfaction and perceived equity in the distribution of rewards stemming from participation in the relationship. The supplier evaluation program developed by General Motors, Targets for Excellence, recognizes this important linkage in the development of integrated supplier relationships. The first section of the audit is dedicated to the identification of the suppliers mission, values, and operating philosophy to assess whether they are compatible with those of General Motors-~Continuous 50 Improvement. An empirical examination (Clark, 1989) of 29 NPD projects representing Japanese, European, and United States automotive manufacturers demonstrated that the Japanese automobile producers enjoy an 18-month development time advantage over their European and United States counterparts. Clark (1989) concluded that one-third of the manhour, and four to five months of the leadtime advantage, was attributable to their relationship with suppliers and early supplier involvement. This finding is consistent with early research conducted by Gee (1978) which identified the use of external sources with a lower average innovation period. A component of successful interorganizational relationships in process or product innovation involves the geographic distance between organizations. The critical role of distance is evidenced by the influx of transplant supply organizations to support the Japanese automobile manufacturers who have located in the United States. Proximity and ”co-location” of suppliers acts as a facilitating variable in the NPD process (Burt, 1989; Bhote, 1987). Large geographic distances have been identified as a barrier to efficient communication and tends to explain why technical cooperation is a product of domestic partners (Hakansson, et.al. , 1987). 2.4.31 err ' ’ r An issue highly related to the nature of the relationship is the form of the relationship. The structural form of the interorganizational relationship has been 51 presented in the literature as a continuum of possibilities ranging from 'Full Integration, Tapered Integration, Quasi Integration, to Contracts (Harrigan, 19). The distinguishing characteristic between these forms is the level of contractual agreement and investment. Contemporary literature incorporates new terminology to describe highly integrated relationships such as Value-Adding Partnerships (Johnston and Lawrence, 1988), Networks (Hakansson 1989; Hakansson, et al., 1987; Thorelli, 1986; Jonsson, 1986), Business Alliances (Gerlach, 1987), and Strategic Alliances (Harrigan, 1987). These structural forms are facilitated by agreements between the organizations which extend beyond purely legal obligations. They are based on the investment in relationships over time which are developed by the individual actors from each organization acting in a boundary-spanning capacity (Hakansson, et al., 1987; Jonsson, 1986). Financial cross-holding arrangements between members of a network are offered as symbolic gestures designed to foster qualitative relationships between firms (Gerlach, 1987). Strategic Alliances are giving rise to many alternative arrangements to facilitate exchange such as research consortia, cross-distribution agreements, cross-production agreements, and cross- licensing agreements (Harrigan, 1987). The goal is structural stability of the entire network for long-term growth and improved information flow. Transaction costs have been identified as an explanatory variable in the choice of interorganizational structures with respect to research and development activities between firms (Brockhoff, 1992). The author suggests that, 1) the degree of formality of cooperative agreements, 2) the scope of technological areas 52 covered by an agreement, 3) the number of partners involved, and 4) the stage in the technological lifecycle influence the perception of high transaction costs and therefore impact the choice of strategic form. Ohmae (1990) utilizes the term ”The Borderless World” to convey the erosion of distinctive boundaries between organization. Overlapping organizations is another descriptive term designed to convey the evolution of integrated structural frameworks which recognize the strategic interdependence of networks and their impact on innovation and competitiveness (Jonsson, 1986). The purpose of interorganizational structures has been cited as enabling control, providing uniformity or flexibility, channeling communication, economies of settle, or accommodating environmental variables (Herbert, 1984). An extension of these goals is to improve the NPD process through effective integration of buying and supplying organizations. 2.4.4 Information Flow These highly integrated interorganizational relationships have been made possible through technological advancements in information processing (Johnston, 1988). Telecommunication and information storage, analysis, retrieval, and transmittal technology have reduced the time necessary to transfer important information among members of a value-added chain improving the coordination and effectiveness of the firms operating as a linked system. Improved information flow allows the individual actors to react to changes in the operating environment of the entire network of firms enhancing the response time of the 53 entire system. Trust has been identified as an important component of an integrated relationship. It also has important connotations to the area of information sharing. The effectiveness of the network is enhanced by the timing, quantity, and quality of the information shared among members. Fujimoto (1989) has identified internal and external information system integrity as a key element in the NPD process. The integrity encompasses the area of quality which conveys the need for accuracy and the willingness to share proprietary information. Improved information flow has also been identified as a benefit of, rather than a prerequisite to, integrated relationships (Gerlach, 1987). It has also been the source of great concern regarding a firm’s competitive advantage, the issue of intellectual property (Newman, 1989), and the potential for the rapid diffusion of innovation through network partners (Hakansson, et al., 1987). There is no universal agreement on the seriousness of this undesirable transfer of technology, or how to resolve this source of conflict. One engineer from Saab-Scania diffused the issue by saying, ”We learn from each other. We are not afraid of industrial espionage. Our factory is custom-made, and those who believe that one can copy a factory make a mistake" (Hakansson, etal., 1987: 39). Establishing channels of communication between organizations is a function of the nature and structure of the relationship, and the technology to facilitate the exchange, but the ultimate responsibility resides with the individual actors representing their firms interest. The individual acts as an information processing agent to link the organization with the environment. This function has been 54 called a ”boundary-role" where the individual is designated as the ”linking-pin" in the communication channel (Jonsson, 1986). 2.4.5 812mm Resource dependency has been the focus for evaluating interorganizational relationships based on resource flow considerations (Pfeffer and Salancik, 1978). These initial premises were utilized to develop an understanding of structure and power distribution in these relationships (Sriram and Venkatapparao, 1990; Herbert, 1984). Cooperation between linked organizations has been identified as an important tool in the mobilization and efficient utilization of resources (Hakansson, et al., 1987). Development of interorganizational relationships requires a commitment of time, labor, and capital and should therefore be regarded as an investment by the firm. The primary incentive for firms to engage in this type of investment is the acquisition and mobilization of valuable resources. “A company’s total resources are in general small compared to the resources which are controlled in common by the other actors in the network. There is, for this reason, always cause for the individual company to attempt to acquire these resources" (Hakansson, et al., 1987: 128). In the area of NPD, these resources take the form of product and process supplier competence. The interaction between the buying and supplying organizations in an IPD environment has a synergistic potential capable of producing a "multi-competence effect” (Hakansson, et al., 1987: 4). Williamson’s model of markets and hierarchies (1975) based on transaction 55 cost analysis has often been utilized as a framework for evaluating the efficiency and effectiveness of interorganizational linkages. Any exchange between the buying and supplying organizations including information, material, labor, or capital, constitutes a transaction cost to the organizations. Highly integrated relationships are hypothesized to lower the cost of transactions between member organizations achieving the benefits of vertical integration without the cost of ownership (Thorelli, 1986; Ettlie and Reza, 1992; Melnyk, et al., 1992, 1993). Transactions between buying and supplying organizations are viewed as a means of developing integrated relationships. The transaction activities can be used to overcome barriers to integration in ”hard dimensions,” physical or geographic distance, and "soft dimensions,” related to differences in attitudes, values, and culture. ”The soft sections of the gap are of special importance in international transactions because differences in cultural concerns are more prominent in these situations. It is also likely to be of unique importance when the transaction activities are characterized by technological exchange” (Hakansson, et al., 1987: 159-160). Transaction analysis has also focused on the area of transaction-specific investments and their contribution to ”source loyalty" in the buyer-supplier relationship. Investments made by the supplying organization can be categorized as retrievable or irretrievable. Irretrievable investments demonstrate the commitment of the supplier and promote a durable relationship (Sriram and Venkatapparao, 1990). Supplier involvement in the NPD process promotes resource concentration 56 (Hakansson, et al., 1987). In this scenario, firms are allowed to specialize and focus their contribution to the value-added chain. Theoretically, the benefits derived from resource concentration include improved utilization of resources, technological expertise, and network effectiveness. The increase in resource dependency in highly integrated buyer-supplier relationships raises the strategic importance of supplier selection. A reduced number of suppliers and the long- term commitment required make supplier selection a central issue in forming strategic partnerships (Burt, 1989; Spekman, 1988; Hakansson, etal., 1987). The problems with these kinds of relationships also cover such issues as choosing and maintaining individual suppliers, the number of suppliers to cooperate with, developing the cooperation patterns and so forth. From a network perspective the dynamics of the interplay between individual relationships and the company’s total relationship structure is a vital concern (Hakansson, et al., 1987: 131). The choice of supplier can often be very strategic. A long-term reason for cooperation with a certain supplier can be, for example, that a specific supplier possesses important competence which the purchasing corporation wishes to take advantage of, not only by way of a developed product but also via the corporation learning form the supplier and at an early stage receiving information of new developments, etc. The purchasing corporation can also have long-term reasons for enhancing certain supplier competence (Hakansson, et al., 1987: 168). Another area of interest is the issue of the specific tools utilized by the buyer and supplier in the development of new products in an IPD environment. Quality Function Deployment (QFD) and Value Analysis/Value Engineering (VA/VE) have been evaluated for their impact on the NPD process and their effectiveness as an interorganizational communications tool (Griffin and Hauser, 1992; Williams, Lacy and Smith, 1992). Raia (1989) and Bhote (1987) advocate the use of Design-of-Experiments (DOE) to improve product quality by creating a 57 robust design. Other tools which have been cited as contributing to cost reduction in the process include reverse engineering, product standardization, part-number reduction, group technology, and early supplier involvement (Bhote, 1987). 2.4.6 Projoot Porformang Case studies have been the primary means of assessing the impact of supplier involvement in the NPD process. Burt (1989: 129) reported a reduction in cost (10 percent), rejected material (93 percent), development time (50 percent), and production leadtimes (65 percent), through supplier partnership programs. Texas Instrument was able to attribute the following results to supplier involvement: 85 percent reduction in assembly time, 75 percent reduction in part numbers, 78 percent reduction in the number of assembly steps, and a 71 percent decrease in the time devoted to metal fabrication. IBM reported the following statistics with the development of the IBM Proprinter: 90 percent reduction in assembly time, and 65 percent fewer part numbers. Ford was able to trim $1.2 billion dollars from manufacturing cost through early supplier involvement. In an empirical study conducted by Ettlie and Reza (1992) supplier integration was evaluated with seven scale items including: 1) We introduced procedures for JIT purchasing or delivery; 2) We introduced new purchasing policies; 3) We buy integrated components from suppliers; 4) We established programs to educate suppliers in areas such as statistical process control; 5) We have established a contingency supply policy; 6) We have reduced our inspection of incoming parts; 58 7) We use supplier award programs. Supplier integration in process innovation resulted in a reduction in scrap and improved cycle time target performance. Unfortunately, while the characterization and measurement of supplier integration demonstrates statistical reliability, a Cronbach’s Alpha of .85 and interitem correlation of .45, the question of whether these items represent valid measures of supplier integration is debateable. Supplier involvement in the NPD process involves the identification and evaluation of the cost of involvement. Development of dependency on partners, high cost of negotiations and transactions, problems of assigning contributions and results to the partners, secrecy problems, problems of technology transfer, loss of own technological competence, and inhibition of own developments were identified as the most important possible disadvantages to interorganizational cooperation in the development of new products (Brockhoff, 1992: 517). A summary of the interorganizational research is presented in Table 2-3. These studies however, have not explicitly characterized supplier involvement in the NPD process. Without such characterization, it will be difficult to suggest ways in which supplier involvement can be gainfully used in ensuring the success of IPD. The need to further investigate the role and contribution of the suppliers and the supply management function in the IPD strategy is frequently mentionedin the literature (Emmanuelides, 1991; Susman and Dean, 1991). Research is needed to understand what constitutes supplier involvement, and how can it be measured and managed during the NPD process. For the purposes of this research the characterization, definition, and 59 Table 2-3. Summary of Interorganizational Level Research. _ AREA AUTHOR COMMENTS BUYER AND Dowlatshahi (1992) CornpetitiveadvamageduringprothetdeaignofNPDprmin SUPPLIER terms of production cost, life cycle coat and quality performance. RELATIONSHIP Dowlatshahi 0992) Comprehensive advances of IPD process. Stone0983) EmblialmeuofkeyauppliendurirrcNPDdeaignphaewith involvuneu to obtain quliry deimproeeaa and parts. RELATIONSHIP Aatley.1‘1mhmn (1983) Strategy comept for collective mum action towards Astley.Fornbrun (1983) BresserJ-Iarl 0986) Campbell (1985) Gerlach 0981) Gerladr 0987) Astley (1984) John (1984) mm (1988) Porter (I980,I985.1990) Spekman (I988) Spekman (1988) SMMW 1990) achievanemofendsaharedbyimerorgarizatiooalmt. lmerorganindomlrelationahipasindividualorcouml. Wreladonflripispormyedaa irrdependeraldependemorirnerdependem. wmmwrmmmmm DWWMWW WW3W,W« kawidrnarletbuedcmetfive-odel. Whthebymofmmw WMWMMEMMM ofatmegyfrmfimtonetworklevel. Wreladodripasbilmalpowermaad halameofpoweriseaserrtialtoaneceaafirleonflictreaohfion. Gauchbuyer-aupplierrelafioaahipaa'Qaietrevoluion'which canbefacilitnedbyredncedaetofamplieu. ummmmmmm. ciedaai-trurneualiaeatabliahia‘irlegmedm Table 2-3 Cont’d. AREA AUTHOR COMMENTS RELATIONSHIP Burt (1989) Proximity and location of suppliers act a a facilitating variable in Bhore (1987) the NPD procees. Burt (1989) Single sourcing improveaquality.cost and innovation Raia(1989) Frazier0983) Goalcombilitybetweenorganinfionsisarequirenentfor loogteunrelarionahipa. Gerlach0987) finncialcroasholdingamngernentsbetweeomernbersofnetwork areofieredasasyrnbolicgeamretofosterqualitativerelationahip betweenfirrns. Hakanssooet.a1.(l987) largegeoaraphicdimareidemifiedasbarrieraoefficieot mm Harrigan0987) Strueorralfirunofimerorganintiomlrelatiooahipisaeenas Harrigan098‘7) Smgicdliamealeadtohcilirateeachangemchasreaeareh were. Herbert0984) Warmeaervethepmpoaeofenabfingcomol, providingan'fornityorfleaibilitymhannelfingcommieanon. eeonomieaofaealeetc. Johmhwrence (1988) Highly imegracd relationshipsare aeenas Value-Adding M. Jonson (1986) WWW-WW“ Newman0989) Imreaaeindeperllencybetweenbtryu-aupplierdecrmmtegic Breaaer.Harl0986) fleaibility. mPORMA‘I'ION Pnjinroto0989) Inernalandeacrnlinfionnadonayauninaegriryisakeyelenerain FLOW NPDproeeaa. Johnaton0988) Mywwwmpodble WWMhWM. 61 Table 2-3 Cont'd. AREA AUTHOR COMMENTS STRUCTURE Gerlach0987) Improved informationflowisidemifiedasabemfitratherthan prerequisitetointegraterelatiomhips. Hakanssonet.al.(1987) Improvedinformationflowasapowmialforrapiddiffusionof innovationthronghnetworkpartners. imam) Individualsrepreaentthefirmareultimtelyreaponaiblefor establishingchannelsofcommmiation. Nemn0989) Improvedinformationflowisaaotnceofgratconcernregarding firm'scompetitiveadvamageandiaaueofintelmnralproperty. RESOURCES Bhote (I981) Identified tools for cost reduction. Brockhoff (1992) Identified important possible disadvantages to imerorganizational cooperationinNPD. Eurt0989) Redncedrarmherofauppliersandlongtermoonninnentmake Spehmn0988) nmplieraeloctionaceraraltateinatrategicrelationahips. Hahnsaonet.al.(1987) Ettlie,Ren0992) Evaluatedamplierimegrationonaevenitems. Ettlie.Rea (1992) Hrghlytmegratedrelanoahtpsachtevebenefits of vernal Thorelli0986) integrationwithontcoetownerahip. GdffimHanaer 0992) QualrtyancnonDeploymem. Value AalyalalValneEngineet-ing William,Lacy.Smith areevaluatedforimpactonNPDproceasandaacmnrn‘ation 0992) tool. Hahmaonet.al.0987) Cooperationnanimpottamtoolinthemobilintionandefficient ntilintionofreoources.1meractionofbuyingandaupplying orgarn'ntionsinIPDhasaaynergetiepowmialofprodueing'nntlti- competenceeffiect'. Hakansaonet.al.0987) SupplierinvolvemetxinNPDproceaspromomsreaource concerlration. Pfefter,8a1ancik(1978) Reaonrcedependencyasafocnsfiorevalnatingimeanrganintioal l' l' Sdienhtappuao Irretrievableinveannemademonatratethrrablerehtioahipofthe (1990) nrpplier. Willi-noon0975) Modelaofntarhetandhmarchieantilinedfiorevalndngemciexy ofimer-organintionallinhges. PROJECT M0991) Themedtofnrtherinveatigateroleandcomihttionofauppliersand PERFORMANCE Snnan.Dean(1991) mpplyntanagernentflmctioninIPDmgy. Sntart0991) Impaetofpnrdtaaeinvolvemeraincollaborativemactivitiea. 62 measurement of the variable supplier involvement will be guided by the research conducted by Stuart (1991) which focused on the impact of purchasing involvement in collaborative research and development activities. The contributions of this research include the recognition of the differences between involvement, and "meaningful involvement". Meaningful involvement was defined as: The timely and useful collaboration of purchasing’s expertise and the scientist’s knowledge in all aspects of the equipment acquisition process. This includes the decision-making process leading to the best buy decision, with the objective of satisfying the immediate needs of the specifier and the long-term needs and strategic objectives of the research unit as a whole (Stuart, 1991: 30). Four factors were deemed necessary to facilitate meaningful involvement: 1) need for proactive involvement, 2) need for physical proximity, 3) need for a high level of relevant technical expertise, and 4) need to define role in terms of client satisfaction, mutual objectives, and team membership (Stuart, 1991: 34). The conclusions drawn by the 1983 study conducted by the National Science Foundation (T ornatzky, et al. , 1983: 28-45) indicated that ”researchers seem only to agree that there are no hard and fast ingredients in successful innovation. " On the contrary, evidence indicates that the conclusions drawn by the research are generally in agreement with one another. Unfortunately, the pool of research related to the process of product innovation is not exhaustive, leaving many areas still unexplored or unsupported. One such area, and an incremental step forward, is the quantifiable evidence to support the relationships identified by the literature. 3.0 CHAPTER III CONCEPTUAL FRAMEWORK The preceding chapters have presented the purpose of this research and the literature from which it draws support and guidance. Previous studies served to identify variables hypothesized to impact the effectiveness of new product development efforts, but there are very few well-defined and empirically validated theoretical frameworks to support the current research effort. One of the intentions of this project is to build on the existing frameworks, offering quantifiable evidence to support the relationships postulated by previous research. To accomplish this, and at the same time address the focus of this research, it has been necessary to adapt existing models to match the interest of this endeavor. This chapter begins by presenting the primary conceptual frameworks adapted for the purposes of this research, followed by the presentation of the conceptual framework utilized in this research. The final section of the chapter is devoted to a detailed description of the development of the analytical framework. The detail is provided to facilitate the goal of theory building. It represents a synthesis of the supporting literature, and information obtained from focus group discussions, brainstorming sessions, and field observations. Included in this section is (1) an operational definition of each construct which promotes measurement and testing of the hypotheses, (2) specific 63 64 dimensions of each construct and the associated measures of those dimensions to facilitate the gathering of data, and (3) a discussion of the expected relationship among the variables represented in the model. The previous research which provided the foundation for the development of the conceptual model for this research was conducted by Susman and Dean (1991) and by Shrivastava and Souder (1987). Susman and Dean’s work, ”Causal Model of Variables Leading to Project Goal Success Via DFM" (Figure 3-1), sought to depict the implementation process associated with utilizing the NPD strategy, Design-for-Manufacturability (DFM). The model was developed and validated based on case studies of twelve companies in the commercial and defense industries. Data collection spanned a one-year period and included two products from each of the participating firms in the sample. The purpose of their research was to gain an understanding of the NPD process and to identify those variables which act as facilitators or barriers to the process employing the Design-for-Manufacturability strategy. Although successful in identifying these variables, the model remains to be empirically tested. To capture the complexity of the new product development process in an integrated environment, formation of the conceptual framework was also guided by the insight obtained from the work of Shrivastava and Souder (1987). In their research, they discuss the need to incorporate project, organizational, and inter- organizational variables to capture the dynamics of an innovative environment. The conceptual framework developed for this research lends itself to analytical 65 .Edd <_> mmmuunm .._ “.0 1.80.2 ._0mh<¢hm en: wt... 2. wuqo>z_ D a _ mwfiaaam 2w.z< 10m: mmmUOma w>....\\-.\ MACHINERY :Q , ; (30.0%) (7.2%) / s \\\\ \ \ \ ‘\\\\\\\’\ ‘\ \ss\\s \\ \ (2.4%) W2\ \\\\\\ (8.4%) / _ WES (8.4%) l TRANS. EQUIP. I ( AUTOMOTIVE SUPPLIER ] FIGURE 5-3 U. ) A % M 8. m s m SIZE BY NUMBER OF EMPLOYEES DO EST v \ SIZE BY ANNUAL SALES DOMESTIC V m \\ \\ 124 PRODUCT FUNCTION DOMESTIC FINISHED PRODUCT (722%) FIGURE 5-6 m Em WES. D O Du P N . E m .. I E mm M mm p In ME— EN 126 PRODUCT MARKETING DOMESTIC NEw MARKET ENTIRELY MARKET SEGMENT 8 NEW MARKET (25.3%) EXISTING CUSTOMER [.75.] FIGURE 5.8 127 PRODUCT TECHNOLOGY DOMESTIC NEW UNRELATED TECHNOLOGY EXISTING TECHNOLOGY NEW RELATED TECHNOLOGY FIGURE 5-9 128 utilization of technology which was related to previously utilized technology as follows: new-related technology 62.7 percent of the time; existing technology, 28.9 percent; entirely new-unrelated technology, 8.4 percent of the projects. The benchmarking process is deemed useful in establishing performance targets for the NPD projects. It was important for this research to quantify the results of the IPD process which was recorded as the percentage change from benchmark projects. Respondents indicated that competitor’s products provided the benchmark for their NPD effort 30.7 percent of the time, a previous model was utilized by 30.7 percent, and a corporate target, 21.3 percent. The remaining respondents (17.3 percent) indicated that the source of the benchmark was derived from one of the following: a combination of the three previously mentioned methods; a function of customer requirements; negotiated by the team; a product of management judgement; the ”whims of the CEO”; or, the team operated without any benchmarks (see Figure 5-10). The majority of the respondents, 65.4 percent, categorized their product- delivery process as mass production. Of the remaining respondents, 25.6 percent indicated that their product-delivery process was Characterized as batch production, followed by job-shop environments, 9.0 percent (see Figure 5-11). The number of different suppliers represented on the NPD teams ranged from one to 99, with a mean of 13, and a mode of one. This distribution reflects the variety of projects involved in the sample in terms of scope and scale. The responses ranged from finished goods automotive manufacturers representing large-scale projects consisting of multiple teams, teams-within-teams, to 129 SOURCE OF BENCHMARK FOR THE PRODUC' DOMESTIC (17.3%) COMPETITOR’S PRODUCT 7%) CORPORATE TARGET m13%) 7%) PREVIOUS MODEL FIGURE 5-10 130 MANUFACTURING PROCESS OF THE PRODUCT DOMESTIC BATCH PRODUCTIcM \ .. (9.0%) JOB sHop s \ (25.6%) \\\\\\§\§ (65.4%) [MASS PRODUCTION ] FIGURE 5.11 131 component and subassembly contributors supplying the perspective from more narrowly-defined projects. Figure 5—12 gives a breakdown of the types of suppliers who were members of a NPD team according to the product or service that they provided. The results are based on the total representation of suppliers on NPD teams as there was often more than one supplier on a given team. Component part and subassembly/assembly suppliers were the most frequently included, with membership on 80.2 percent and 56.8 percent of the projects respectively. They were followed, in rank order, by capital equipment suppliers (34.6 percent), finished goods/OEM suppliers (29.6 percent), raw materials suppliers (25.9 percent), and service providers (14.8 percent). The technology involved in the NPD project was the primary reason for inviting suppliers to be members of the NPD team as indicated by 32.5 percent of the respondents. This was followed by the suppliers’ level of expertise, 19.3 percent, and the type of product or service they provided, 18.1 percent. Of far less importance in the selection criteria were the length of time doing business with the supplier, 9.6 percent, the value of the purchased part or service, 8.4 percent, and the relative proximity of the supplier, 1.2 percent (see Figure 5-13). While the length of the buyer-supplier relationship was not a primary determinant in the supplier selection process, the average life span of the reported relationship was 10 years with a range between 1 to 25. The total number of supplier personnel reported to be involved in the project ranged from 1 to 99, the mean was 35, the median was 15, with the most «Tm NCDOE so to at}? I32 P¢403N00<§0Q<03¢ #23530“ 12.-<0 53.0800 ONIEZE . ,. // 1,47 .// // / /.// / z a.» . /// C/ // , y i 355::- BE R: //// /? 35cm» Ur—Muaq mmm<0 “-0 NOS—.Zmommn 54m... 20 mmm..._n_n:m “.0 mm: 133 PRIMARY REASON FOR SUPPLER SELECTION DOMESTIC (expense J (19.3%) r Fnoxmm ] FYI-IE OF PRODUCT OR SERVICEJ l .. . ea FIGURE 5-13 5.2 5.2.1 134 common responses being two and four. This demonstrates the magnitude of difference in the degree of supplier involvement in the NPD process. Another indicator is the variety of the supplying firms’ personnel who were involved in process. Figure 5-14 depicts the frequency of involvement of the suppliers’ personnel from a variety of departments including sales, engineering, quality, management and manufacturing. All of the suppliers supporting functions were involved in over two-thirds of the cases, with engineering involved in 91.6 percent of the projects. Preliminary Statistics Nermalig A necessary assumption for many statistical procedures including the methods utilized in this research, regression analysis, is a normal distribution of the residuals and independence of the error terms. The first method utilized to confirm the condition of normality was a visual inspection of the distribution of the data for the dependent variables, Firm Performance and IPDS. Casewise plots of the residuals identified outliers which were removed from further analysis. A more formal procedure, the Kolmogorov-Smirnov Goodness of Fit Test, was then employed for additional verification of a normal distribution. While a normal distribution is not a necessary prerequisite for independent variables in regression analysis, the results of this procedure are presented for both the 135 TYPE OF SUPPLIER PERSONNEL INVOLVED PERCENTAGE OF CASES OTHER MANAGEMENT SALES QUALITY MANUFACTURING . :.\ ‘ \\.\\\ \\ ‘.\\.,\\\ \\\\\\ \’.'.-.\\‘ \\\\\:{\ \:\\\\\\\ \ \\\ \ \\ \ " SS \\\ SS \ SSS‘s SS SSS \ .~\ ~‘\\\ ‘\‘\\‘\ \' \‘A \‘\,\:\\ _ \* . \~ a \ \\ x \ \" ‘. \‘ :g‘ \\\‘\‘ \ \S\\\ \x; \\ \\S\\\ ~ \S~.\\\\; ix \\\\\~ \;\§ \_\ \\\\\\ \ . §\ S\ S‘S\\: ~ . \S\\\\ \\\T\\ \\\\\. \\ \\\\\\\\ \\\\\\\ \\\:>:.\\ \\\\\\\ \\\\\\ 1.. j 0 . \\.\\ \\ “:\\ \\\\\\\ \\ .\\\:\: \\\K ‘ \ \\~,\ ., \_ \\\\\‘\ :,\~ , . ‘ .~\ .\\\\\\\\\\\\\\\\‘\\‘\\\\\ j I I T I I Tr 1° 20 30 n 50 ‘0 7O PERCENTAGE OF CASES FIGURE 5—14 136 dependent and independent variables. The construct IPDS plays a unique role in this research, acting as the linking-pin between left and right side of the conceptual model. It therefore acts as both a dependent and independent variable. The Kolmogorov-Smirnov test compares the actual distribution of the data with a normal distribution to determine whether the distributions are statistically different. The desired result is a failure to prove that the distribution of the actual data differs from a normal distribution, a failure to reject the null hypothesis. The results of this analysis are provided in Tables 5-la for the independent variables and 5-1b for the dependent variables. The results demonstrate that there are no serious deviations from normality. Two of the individual measures of IPDS, improved product quality and product performance, deserve further consideration as the results indicate that the distributions do statistically differ from a normal distribution. The multiple regression techniques, while significantly influenced by the presence of outliers, is fairly robust to deviations from the assumption of normality. This confirmation provided the basis for the remaining statistical procedures which were employed to test the research hypotheses. Scatterplots of the residuals demonstrated a descending fan-like distribution for the dependent variable IPDS, indicating nonindependence of the error terms. A logarithmic transformation of the dependent variable IPDS was utilized as a remedial measure prior to further data analysis (Neter, Wasserman, and Kunter: 133-137). 137 Table 5-1 A. Kolmogorov Smirnov Goodness of Fit Test Independent Variable Supplier Involvement Buyer Supplier Relationship 4.98 1.17 0.99 0.28 IM Structure - Culture 4.27 0.79 0.67 0.75 Information Importance 5.51 0.69 0.74 0.64 Information Accessibility 4.94 0.94 0.60 0.85 Group Process 5.53 0.78 0.85 0.46 Resource Utilization 4.45 0.89 0.60 0.86 138 Table 5-1 B Kolmogorov - Smirnov Goodness of Fit Test Dependent Variables Market Performance IPDS Overall Relative Performance Reduce Product Cost Reduce Smrt-Up Costs Reduce Tooling Costs Improve Product Quality Reduce Warranty Costs Reduce Customer Complaint Reduce Rejected Material Reduce Rework Cost Improve Product Performance Improve Market Share Increase Perceived Value Increase Perceived Quality Improve Dollar Sales Improve Product profitability Improve Product Capabilities Reduce Development Time Improve Communication Reduce Total Manhours Reduce Engineering Change Notices Reduce Manufacturing Cycle Time Improve White Collar production MEAN 4.48 4.08 18.31 4.70 8.87 13.16 12.65 16.25 19.00 26.30 14.52 16.89 20.55 11.18 32.97 30.86 21.89 19.05 29.39 18.63 34.59 19.38 24.17 24.51 23.65 STD.DEV 0.89 1.23 12.92 0.92 11.19 13.89 11.10 21.46 15.73 24.30 14.39 18.63 26.42 11.32 28.91 28.81 23.65 16.78 26.23 18.99 33.76 17.21 23.07 19.90 19.13 1.31 1.05 1.70 0.65 0.74 1.88 1.05 1.22 1.15 1.08 1.84 1.06 1.23 1.16 1.04 1.32 1.41 1.75 1.21 1.11 0.79 1.12 0.74 5.2.2 139 RM Due to the exploratory nature of this research, prior to testing the research hypotheses, the reliability of the measures pertaining to the constructs of interest needed to be determined. In order to improve the generalizability of the results the entire sample was utilized to perform this analysis, both the domestic (n=133) and international respondents (n=83) for a total sample population of 216 projects. Coefficient alpha was utilized to test the inter-item reliability of the theoretically-derived constructs with a benchmark value of 0.70, based on standards for exploratory research set by Nunnally (1978: 245). The results of this analysis are provided on the individual dimensions of each construct, as well as the aggregate construct itself, where applicable. One of the objectives of this research was to develop a reliable measure of the construct Supplier Involvement (SI). The construct was measured along five dimensions: quantity, quality, communication, investment, and caliber of the relationship. The reliability of these individual dimensions ranged from .76 for communication, to .94 for relationship, with the overall measure of Supplier Involvement demonstrating a reliability of .94 (see Table 5-2). Integrative Mechanisms (IM), the organizational-level variable, was measured along the dimensions of structure/culture, support systems, information, and status. The individual reliabilities of this dimensions were .63, .84, .85, and .81 respectively, with an overall reliability of .87 (see Table 5-3). The team-level variable labelled Group Process (GP) was composed of a structural dimension (alpha=.74), communication dimension (alpha=.50), 140 Table 5-2 . Dimensions and Measures of Supplier Involvement SUPPLIER INVOLVEMENT (SI) RELIABILTY o 31 . QUANTITY (311) Q 33,35 Q 37 o 38 .7819 (11) Q 42.3 Q 42.4 QUALITY (812) Q 42.2 Q 42.1 Q 50 Q 56 .9306 (22) Q 34 Q 40 Q 45.1-45.6 COMMUNICATION (813) Q 45.1-45.6 Q 48 Q 51 .7586 (10) Q 36 INVESTMENT (814) Q 44.1-8 .8104 (9) Q 42.5 EXPERTISE (SIS) Q 42.6 N.A. Q 39 Q 41 Q 43 RELATIONSHIP (816) Q 49 Q 47,52,54,55 141 Table 5-3. Dimensions and Measures of Integrative Mechanisms STRUCTURE (1M1) Q 9.2-9.5 Q 9.8 Q 9.11 Q 9.1,6,7,9,10 Q 10.1-10.5 .6282 (6) SUPPORT SYSTEM (IMZ) Q 74.1 Q 74.2 Q 74.3 Q 74.4 Q 74.5 Q 74.6 Q 74.7 Q 74.8 .8390 (8) INFORMATION ACCESSIBILITY (1M3) Q 79.1-11 Q 79.12-22 .8513 (22) EQUITY (1M4) Q 73.1 Q 73.2 Q 73.3 Q 73.4 Q 73.5 Q 73.6 .8723 (42) 5.2.3 142 leadership dimension (alpha=.91), and a cohesion dimension (alpha=.87). The overall reliability of the construct Group Process is .90 for the aggregation of the 36 individual items (see Table 5-4). Specific resources identified in the literature as facilitating the NPD process were evaluated based on their utilization (alpha= .87) and adequacy (alpha= .87). The aggregate measure of the Resource (R) construct demonstrated a reliability of .89 (see Table 5-5). The first dependent variable included in the theoretical framework is the outcome measure of the team’s performance, IPDS. Due to the objective nature of the data utilized to measure this construct, reliabilities are unnecessary. They are provided for the benefit of future research. The composite measure for IPDS is a product of the underlying dimensions of cost (alpha=.7786), quality (alpha= .83), product performance (alpha= .8350), and development time (alpha=.7524). The reliability of the composite measure is .91 (see Table 5-6). Firm Performance represents the second dependent variable, and the final construct included in this research. Firm Performance was measured along two dimensions including an assessment of the performance relative to competitors on the key competitive priorities (alpha=.76), and market indicators (alpha=.90). The combination of these two dimensions yielded an overall indicator of firm performance with a reliability of .85 (see Table 5-7). mm The exploratory nature of this research required both the verification of the reliability of the constructs and establishment of the validity of the measures. 143 Table 5-4. Dimensions and Measures of Group Process GROUP PROCESS (GP) STRUCTURE (GPl) Q62 Q63 Q64-65 .7293 (7) l COMMUNICATION (6P2) Q 68 Q 75.1-75.5 .4991 (7) LEADERSHIP (GP3) Q 59.1 Q 59.2 Q 59.3 Q 59.4 Q 59.5 Q 59.6 Q 59.7 Q 59.8 Q 59.9 Q 59.10 .9076 (10) COHESION (GP4) Q 67 Q 69.8 Q 69.1 - 69.7 Q 70 Q 71 Q 72 .8705 (13) 144 Table 5-5. Dimensions and Measures of Resources RESOURCES (R) UTILIZATION (R1) Q 25.6 Q 25.7 Q 25.8 Q 25.9 Q 25.10 Q 25.11 Q 25.12 .8696 (12) ADEQUACY (R2) Q 26,6 Total .8932 (24) 145 Table 5-6. Dimensions and Measures of IPD Success INTEGRATED PRODUCT DEVELOPMENT SUCCESS (IPDS) ; Q 16A . Q 16B l cosr (IPDSI) Q 16C 1 l I Q 16R Q 16S .7786 (5) Q 16D Q 16E QUALITY (IPDS2) Q 16F Q 16G Q 1611 .8305 (5) Q 16P TIME (IPDS3) Q 16Q Q 16T Q 16U .7524 (4) Q 161 Q 161 Q 16K PERFORMANCE (IPDS4) Q 16L Q 16M Q 16N Q 160 Lm======== Total .8350 (7) 146 Table 5-7. Dimensions and Measures of Firm Performance PERFORMANCE (FPl) FIRM PERFORMANCE (FP) Q 8.4 Q 8.5 Q 8.6 Q 8.7 .7649 (7) MARKET PERFORMANCE (FP2) Q 8.8 Q 8.9 Q 8.10 Q 8.11 .8974 (4) Total .8472 (ll) 147 Face validity was established by an intensive review of the literature, through information obtained from interviews and brainstorming sessions with practioners, a pilot test of the survey instrument, and feedback sought from leading academics. Confirmation of the face validity was sought through exploratory factor analytic techniques to determine if the individual measures actually measured the constructs of interest. Orthogonal solutions provide information regarding the ability of the factors to discriminate among the constructs of interest. Oblique solutions enhance the interpretability of the results but do not guarantee an orthogonal solution. Both orthogonal and oblique solutions were sought for this research effort to assess the discrimanability and interpretability of the constructs. The conceptual model identified four independent variables which provided the initial specification for the factor analysis (SI, GP, 1M, and R). A varimax rotation was selected based on the guidelines provided by Kim and Mueller (1978: 36), which suggest that while each of the rotation methods will provide a slightly different result, the differences are not usually meaningful. Therefore, any of the rotation methods should provide an adequate solution for interpretation while the varimax solution will tend to give a clearer separation among the factors. The results of this initial analysis are provided in Table 5-8a. Guidelines regarding the appropriate selection criteria for factor loadings revealed a range of between .30 to .40. For the purposes of this research, an initial value of .35 was utilized. Both the orthogonal and oblique solutions (Table 5-8b) provided clear indications of the existence of four factors based on the initial measures as specified. 148 IIMESJA VARIMAX4 FACTOR ANALYSIS QUESTION FACTOR I FACTOR 2 FACTOR 8 lACl'OR 0 RESOURCES O 28.1 0...0 O 28.2 0.0.00 O 28.8 0.8.. O 28.0 0.82108 O 28.8 0.01 100 O 28.0 0.8.00 O 28.7 0.807. O 28.0 0.8. O 28.0 0.807. O 28.10 0.07288 O 28.1 1 0.00012 O 28.12 0.807. M O 20.1 0.08070 O 20.2 0.088 O 20.8 0.787 O 20.0 0.80.0 O 20.8 0.0. O 20.0 0.02020 O 20.7 0.808. 0.00780 O 20.0 0.87128 O 20.0 0.01.7 O 20.10 O 20.1 1 0.020. 0.008 O 20.12 0.81070 SUPPLIER O 20 INVOLVEMENT O 81 O 88.1 om: O 88.2 0.8.18 O 88.8 0.87080 O 88.0 0.80207 O 88.8 0.0102 O 88.0 0.80807 O 88 0.07.0 O 87 0.82” O . 0.8.2 O 02.1 0.02888 O 02.2 O 02.8 0.87010 0-1 O 02.0 0.08881 0.807. O 80 0.08.0 O 80 O 80 O 00 0.01810 O 08.1 0.80.7 O 08.2 0.0.00 O 08.8 0.88. O 08.0 0.0. O 08.8 0.02872 O 08.0 0.00787 O . 0.82.8 O 81 0.8021 1 O a O 00.1 0.08780 O 00.2 0.008. O 00.8 0.87088 O 00.0 0.02808 O 00.8 0.81.0 O 00.0 0.07070 O 00.7 0.01002 O 00.0 0.81288 149 VARIMAX4 FACTOR ANALYSIS eon“. QUESTION FACIOR l FACTOR 2 FACTOR 8 FACTOR 0 O01 O 07 0.800. O 00 0.80720 O 82 0.01080 0-10 O 88 0.82082 0.88700 O 80 0.02100 O 88 0.80020 O 87.1 0.788. O 87.2 0.78021 O 87.8 0.8.78 O 87.0 0.800 O 87.8 0.” O 87 .0 0.01.7 O 87.7 0.701 10 O 87.0 0.01.0 O 87.0 0.700“ O 87.10 0.78“ O 87.1 1 0.001 O 87.12 0.70287 O 87.18 0.70070 O 02.8 O 02.0 0.08280 GROUP PROCESS O 80.1 0.01020 O 80.2 0.070. O ..8 0.807. O 80.0 0.81207 O 00 0.011. O 00.1 0.00.7 O ..2 0.00080 O ..8 0.00718 O 00.0 0.80028 O ..0 0.88080 O 70 0.80007 O 71 O 72 O 78.1 O 78.2 O 78.8 O 78.0 O 78.8 0.80070 INTEGRATIVE O 0.1 0.80708 MECHANISM O 0.2 0.027. 150 VARIMAX 0 FACTOR ANALYSIS C0000. QUESTION FACTOR l FACTOR 2 FACTOR 8 FACTOR 0 O 0.8 O 0.0 O 8.8 O 8.0 O 0.7 O 0.8 O 0.8 0.0.00 O 0.10 0387 O 10.1 O 10.2 0.800. O 10.8 O 10.0 O 10.8 0.001. O 78.1 O 78.8 O 78.0 O 78.8 O 78.0 O 70.1 0.88100 O 70.2 0.07012 O 70.8 0.82800 O 70.0 O 70.8 0.0. O 70.0 0.” O 70.7 0.81 188 O 70 O 70.1 O 78.2 O 70.8 O 70.0 O 78.8 O 78.0 O 78.7 O 70.8 O 70.0 O 70.10 O 78.1 1 O 70.12 O 70.18 O 70.10 O 78.18 O 78.10 O 70.17 O 70.10 O 78.18 O 70.20 O 78.21 O 78.22 0.87.0 RESOURCES SUPPLIER INVOLVEMENT 151 TIMESJB OBLIM 4 FACTOR ANALYSIS QUESTION Hero: 1 norm: 2 moron 3 acme 4 Q 23.1 3.33331 Q 23.2 3.43337 Q 23.3 3.43317 Q 23.4 3.31233 Q 23.3 3.33334 Q 23.3 3.33332 Q 33.7 3.33273 0 23.! 3.33123 Q 23.3 3.3301 Q 23.13 3.33313 Q 23.11 3.43333 Q 23.12 Q 23.1 343333 Q 232 3.3633 3.33343 0 10 3.37333 Q 234 Q I“ 3.41433 Q :33 3.43171 Q 23.7 3.33333 3.43333 0 23.3 3373) Q 23.3 343231 Q 2313 3.33327 Q 2311 3.43332 3.33123 Q 2312 3.43334 Q 23 Q 31 Q 33.1 4.33317 Q 33.2 4.3031 Q 333 Q 33.4 45433 Q 333 “[77 Q 3134 4.37212 0 33 4.43337 Q 37 4.3113 0 1| 4.33331 0 42.1 433333 Q 422 0 42.3 4.3223 Q 42.4 4.4.37 0 50 4.3232 Q 33 Q 34 Q 43 4.33413 Q 43.1 4.33311 Q 43.2 4.43737 Q 6.) 4.32733 Q 43.4 4.47333 Q 43.3 4.423- 0 45.3 4.4352 Q. 4.3333 Q 31 4.33333 Q 33 Q 341 4.43243 Q 44.2 4.43343 0 443 3.33333 Q 44.4 4.37173 Q 443 4.33113 Q 443 443313 Q 417 4.34333 Q 44.3 4.33731 GROUP PROCES Q 99.! INTEGRATIVE MECHANISM 152 OIUMO FACTOR ANALYSIS eon“. QUBTTON FACTOR I FACTOR 2 Q 41 4.33334 Q 43 Q 47 4.37471 Q 43 4.31 173 0 52 4.34333 Q 53 4.31333 Q 34 Q 33 Q 37.1 Q 37.2 Q 51.3 Q 97.4 Q 37.3 Q 37.3 Q 37.7 Q 37.3 Q 97.9 Q 37.13 Q 37.1 1 Q 37.12 Q 37.13 Q 47.9 0 42.6 4.41333 IE Q 99.1 Q 99.3 0.9193! Q 99.4 9.41914 Q 99.5 Q 99.3 Q 9.1 Q 99.9 Q 99.9 Q 99.19 Q 43 Q 31 Q 32 Q 6.1 Q 64 Q 39 Q 33 Q 37 Q 33.1 Q 09.1 0.37196 Q 33.3 3.33313 Q 69.4 Q 39.9 Q 43.3 Q 69.7 0 69.0 9.9761 Q 09.9 06.1.1 0 19 3.33233 Q 71 Q ‘72 Q ‘I 9.92932 Q 73.1 Q 79.: Q 79.1 Q 73.4 Q 19.5 3.73271 Q 3.1 Q 3.2 3.31434 E 15% iiiiii 535% FACTOR .1 40.770. 478702 477000 FACTOR 0 153 OIIJH‘ FACTOR ANALYSIS MM. QUESTION FACTOR T FACTOR 2 FACTOR 3 FACTOR 4 Q 3.3 Q 3.4 Q 3.3 Q 3.3 3.33333 Q 3.7 Q 3.3 Q 3.3 343723 Q 3.13 3.33333 Q 3.11 Q 13.1 333733 Q 13.: Q 13.3 Q 134 3.34333 Q 133 3.411. Q 731 Q 73.: Q 733 Q 73.4 Q 73.3 Q 733 Q 741 3.33337 Q 74.: 3.4333 0 141 3.43333 0 7“ 3.33333 Q 743 3.33333 Q 74.3 3.43333 Q 737 3.33172 Q 73 Q 73.1 Q 73.: Q 73.3 Q 73.4 Q 73.3 Q 73.3 Q 73.7 Q 73.3 Q 73.3 Q 73.13 Q 73.11 Q 73.1: Q 73.13 Q 73.14 Q 73.13 Q 73.13 Q 73.17 Q 73.13 Q 73.13 Q 13.33 Q 73.21 0 13.12 3.33333 154 In an effort to improve on this initial finding, iterations of this process continued until an ”optimal” solution was derived revealing the existence of seven underlying factors (Table 5-9a). This solution provided the highest level of interpretability while also yielding a consistent oblique solution (Table 5-9b). Appendix 11 contains the results of the factor analyses. The factor loadings suggest that data reduction is possible through the elimination of certain questions which did not load sufficiently high enough on any one factor. Additional questions were discarded because they demonstrated sufficiently high loadings on more than one factor. Specifically, the questions regarding resource adequacy tended to load on both the Resource construct, and the Group Process construct so those items were eliminated. In addition, the construct previously identified as Integrative Mechanisms, which was developed to assess the organizational-level impact on the NPD process, was refined into three constructs measuring 1) organizational structure/culture, 2) information importance, and 3) information accessibility. A significant result of this process was the identification of two clearly identifiable and interpretable factors originally intended to measure one construct associated with the level of supplier involvement in the NPD process. This finding led to the disaggregation of the Supplier Involvement construct into two unique factors. The first factor is consistent with the original model and is designed to measure the quantitative level of supplier involvement in the NPD process. The second factor represents one of the dimensions of the original construct, relationship, which was dedicated to the measurement of the caliber of 155 TABLE 9-9 A \‘ARIMAX 7 FACTOR ANALYSIS QUB‘T'ION FACTOR I FACTOR 2 'ACTOII 9 FACTOR 4 [ACTOR 9 FACTOR 4 fACTOR 7 mounts: O 99.1 9.8941 9 99.9 999993 a 33.: 9.97999 Q 13,4 9.91999 0 13,: 9.97.9 9 99.9 9.0999 c 25.1 9.79499 (3 33.3 9.“ o m 9.99391 9 99.19 9.41949 0 99.“ 9.99.9 9 99.19 9.999. 9.41793 9 99.1 9.99999 9 99.9 9 99.9 9 99.4 9 99.9 9 99.9 o 99.7 9.93133 9.93977 9 93.9 9 99.9 a 99.19 9 93.1 1 9.49817 9.99979 9 99.19 9.43997 SUPPUER o 93 INVOLVEMENT o 91 9.99949 9 99.1 9.999. 9 99.9 3.33733 9 99.9 o 99.4 9.49" o 99.9 9.4.31 9 99.3 9.971 19 9 99 9.4899 c 97 9.4909 9 8 9.94199 9 49.1 9.41999 9 49.9 9 49.9 9.9“19 9.97179 0 49.4 9.499“ 9 99 9.91799 9 99 o 94 9 49 9.99949 9 49.1 9.99179 9 499 9.99799 0 49.9 9.99917 9 49.4 9.49149 9 49.9 9.49441 9 49.9 9.47994 9 49 9.99979 9 91 9.97.4 9 99 o 44.1 3.43333 9 44.9 9.9989 9 44.9 9.97999 9 44 4 9.9.41 9 44.9 9.94971 9 44.9 9.49919 9 44 7 9.94447 9 44.9 9.94.9 156 VARIHAX‘I FACTOR ANALYSIS «.39. WW FACTOR l FACTOR 2 FACTOR J FACTOR 4 FACTOR S FACTOR 6 FACTOR 7 9.99933 3.9843 g 4. 3.99949 90799 30997199 9 99 0307” 9.93933 921937701119!” 3 93 3.31334 9.93914 a 35 9‘91 3 97.1 9.7”7 9 97.9 9.79971 0 97.9 9.91799 3 97.4 9.199 O ”.7 0.70107 0 ‘1’ .114. O 31.. 0.7.. O 91.10 0.77“ C 81.12 0.7”? O 81.13 0.7“ O 43.3 0’?“ GMT]? "new 0 “.1 3m 3 h s; 99 -= 3! O T” O ".4 O 73.3 Murmur!" O 9.1 ”MAN!" 0 0.2 N; 157 VARIMAX‘I FACTOR ANALYSIS «.44. QUIST'ION FACTOR I FACTOR 7 FACTOR J FACTOR 4 FACTOR 9 FACTOR 6 FACTOR 7 O 0.) 0.42000 0 0.4 0.“401 O 0.0 0.8141 0 0.0 O 0.7 O 0.0 O 0.0 0.20120 0 0.10 3.13937 0 0.11 O 10.1 0 10.2 0 10.0 0 10.4 0 10.0 0.3410 0 74.1 0.04210 0 74.2 0.“ O 74.0 0.40 O 74.8 0.41021 0 74.0 1'1 14 INFORMATION 0 70.1 0 ‘0’ IRMA”! O 70.2 0.47102 0 70.0 0.4312 0 70.4 0.41010 0 70.0 0.“ 0 70.7 0.~10 O 70.0 0.07101 0 70.10 0.72421 0 70.1 1 INFORHATION O 70.12 0.47410 “MIMI" O 70.10 3.43333 0 70.14 3.43934 0 70.15 0.3“1 O 70.10 0.“! 0 70.17 413779 0 70.10 0.~17 O 70.10 3.37337 0 70.20 0.01042 0 70.21 0.000“ O 70.22 3.34937 158 TABLE 5-9 B OBLIM 7 FACTOR ANALYSIS QUESTION FACTOR l FACTOR 2 FACTOR .3 FACTOR 4 FACTOR S FACTOR 4 FACTOR 7 RESOURCES 0 99.1 4.11313 0 15.1 3.31493 Q 25.: 9.3711 Q 25.4 9.3399 Q 25.: 9.779 Q 1“ 93913 0 99.7 3.79139 Q 13.; 4.31411 Q 95.3 9.34791 0 99.13 9.99997 WPFUER 0 10 INVOLVHENT Q 3| 2 assess S E Q ‘ ““01 Q ‘1 «0.0.110 §§EE§E 555§§S§ Q 407 “1‘ 159 OILIM? FACTOR ANALYSIS 33.44. 005110" FACTOR I FACTOR 2 FACTOR .I FACTOR 4 FACTOR 9 FACTOR 4 FACTOR 7 MIR-SUPPUER Q 32 43.1.4 c0... ”FIONSHIP 0 3.1 m “I! 0 $7.12 0794' GMT/P PROCN Q ”.1 ‘5 §§§§§§E§ Q ”.9 0.71024 0 E! 3 2 3% 552131815 1 13% E E INTEGRATIVE Q 9.! ”KHAN!" O 7.1 INMAFION IUNIT'ANCE INFORHATION amuurr ORLIM7 FACTOR ANALYSIS 44944. 0118511074 01.1 01.4 01.1 01.4 01.1 01.3 01.1 01.14 01.11 014.1 0147 014.1 014.4 014.1 071.1 0711 07.1.1 0714 079.5 07.14 0141 0142 074.1 074.4 074.1 074.4 074.7 074 071.1 071.1 071.1 071.4 070.5 071.4 011.1 011.3 071.1 011.14 011.11 071.19 071.13 07114 071.11 07’.“ 071.11 071.13 07’.” 010.3 071.91 070.73 FACTOR I 0.43“ 0.37374 160 FACTOR J FACTOR S FACTOR 9 FACTOR 7 5.3 161 the buyer-supplier relationship. The clarity of this solution demonstrated a need to redefine the original constructs. Tables 5-10 to 5-16 present the adaptations of the original constructs which now include, Supplier Involvement (SI), Buyer-Supplier Relationship (BSR), Integrative Mechanisms Structural/Cultural (IMSC), Information Importance (11), Information Accessibility (IA), Group Process (GP), and Resource Utilization (RU). The reliability of these new constructs are .92, .96, .71, .84, .85, .93, .87 respectively and are reported for comparison with the original reliability results. The reliability of the measures has improved slightly overall with a corresponding reduction in the item measures, a desirable outcome of a factor analysis. Re-specification of the IPDS Conceptual Model Based on the initial interpretation of the data, it was apparent that the original conceptual model needed to be revised. It is therefore necessary to re-specify the model prior to further analysis of the data. The new model incorporates the seven constructs as re-defined according to the findings of the factor analysis (SI, BSR, IMSC, 11, IA, GP, RU), and the dependent variables Integrated Product Development Success (IPDS) and Firm Performance (FP). The new IPD model suggested by this research is depicted in Figure 5-15. The model suggests that each of the independent variables has a direct influence on the dependent variable IPDS and an indirect influence on FF. 162 Table 5-10 Q 38 Percentage total hours committed by suppliers Q 50 How influential suppliers were Q 40 Percentage total meetings suppliers attended Q 48 Extent supplier updated on product design Q 51 Amount of two-way communication with supplier Q 44.1 How much invested in training Q 44.2 How much invested in research development Q 44.3 How much invested in tooling/equipment Q 44.4 How much invested in technology Q 44.5 How much invested in structural/reorganization Q 44.6 How much invested in material/prototypes Q 44.7 How much invested in labor hours Q 44.8 How much invested in co-location of supplier Q 47 Extent supplier supported design Q 49 Level of risk supplier assumed RELIABILITY COEFFICIENT ALPHA 0.92 163 Table 5-11 l l l QUESTION DESCRIPTION 1 I Q 57 .1 Supplier encouraged open expression of ideas 1 Q 57 .2 Supplier handled criticism well Q 57 .3 Supplier encouraged divergent thinking Q 57.4 Supplier communicated honestly Q 57 .5 Supplier did not force views on others Q 57.6 Supplier believed in cooperation Q 57.7 Supplier demonstrated confidence in others Q 57 .8 Supplier understood other view points ~ Q 57.9 Supplier was trustworthy 1 Q 57.10 Supplier kept commitments \ Q 57.11 Supplier was easy to work with Q 57.12 Supplier equitably shared credit ‘ Q 57 . 13 Supplier did not blame others for project difficulties ! { RELIABILITY COEFFICIENT ALPHA 0.96 ‘ l l 164 Table 5-12 INTEGRATIVE MECHANISMS STRUCTURAL/CULTURAL Q 9.3 Extent agree - highly structured communication channels Q 9.4 Extent agree - insistence on uniform managerial style Q 9.5 Extent agree - emphasis on uniform managerial style Q 9.6 Extent agree - informal style of dealing each other Q 9.11 Results are more important than procedures : Q 10.5 In uncertainty, adopts "wait and see” policy to minimize mistakes Q 60 Structure used for task-fulfillment Q 61 Structure used for task accomplishment Q 62 Structure used for task developments Q 65 Process design tasks were sequential/concurrent RELIABILITY COEFFICIENT ALPHA 0.71 165 Table 5-13 INFORMATION IMPORTANCE Q 79.1 Degree of importance on materials reliability Q 79.2 Degree of importance on materials availability Q 79.3 Degree of importance on material quality (ppm) Q 79.4 Degree of importance on labor cost Q 79.5 Degree of importance on machining tolerances Q 79.6 Degree of importance on parts cost Q 79.7 Degree of importance on parts configuration Q 79.8 Degree of importance on assembly time Q 79.9 Degree of importance on case of fabrication Q 79.10 Degree of importance on ease of assembly Q 79.11 Degree of importance on ease of test RELIABILITY COEFFICIENT ALPHA 0.84 166 Table 5-14 INFORMATION ACCESSIBILITY Q 79.12 How accessible information on material reliability Q 79.13 How accessible information on material availability Q 79.14 How accessible information on material quality Q 79.15 How accessible information on labor cost Q 79.16 , How accessible information on machining tolerances Q 79.17 How accessible information on parts cost Q 79.18 How accessible information on parts configuration Q 79.19 How accessible information on assembly time Q 79.20 How accessible information on ease of fabrication Q 79.21 How accessible information on case of assembly Q 79.22 How accessible information on ease of test RELIABILITY COEFFICIENT ALPHA 0.85 167 Table 5-15 LEADERSHIP Q 59.1 Manager ability to recognize and mediate conflict Q 59.2 Manager influence useful for obtaining resources Q 59.3 Manager had important and useful contacts with R&D Q 59.4 Manager disseminated important relevant information Q 59.5 Manager well informed of professional activities Q 59.6 Manager prepared environment for change Q 59.7 Manager empowered members of the project team Q 59.8 Manager had vision of project goals Q 59.9 Manager able to secure upper management support Q 59.10 Extent team members like each other COHESION Q 69.1 Extent help each other to get the job done Q 69.2 Extent members take interest in each other Q 69.3 Extent members trust each other Q 69.4 Extent members like being with each other Q 69.5 Extent members respect each other Q 69.6 Extent members share information Q 69.7 Extent members agree on project goals Q 69.8 Extent members influence design process Q 69.9 Communication between group members was continuous Q 68 RELIABILITY COEFFICIENT ALPHA 0.93 — 168 Table 5-16 I RESOURCE UTILIZATION : I —— ——— — _— ‘ — 7- '— '—’ fl 7 ’ "" '—" ;; "___ _’ '_ ; .4 ;_ '_._:___; ___ 2;; ’ ' 7 ' ’ "" ' __ *’ —j r ”'—‘___‘W ' ' ' ' __-‘_’T——-—'___—_T i L QUESTION DESCRIPTION ; Q 25.1 Utilization of job-related information 1 Q 25.2 Utilization of tools 'I Q 25.3 Utilization of materials-supplies ‘1 Q 25.4 Utilization of administrative support/services | Q 25.5 Utilization of budgetary support i Q 25.6 Utilization of facilities Q 25.7 Utilization of equipment Q 25.8 Utilization of engineering support Q 25.9 Utilization of total person hours Q 25 . 10 Utilization of development time O 25.11 Utilization of education and training Q 25. 12 Utilization of upper management support RELIABILITY COEFFICIENT ALPHA 0.87 169 DmZEmn—tmm #2930ng Ban—OE th530 003020... 83.0... 98. 8... n2. .3 E. .0523 F 0...... 33020.. 039.0... 88. .8... an. . E. . 8a. . ...q . ...: ... ..w: A... 2:8 3...... 25...... 88. 8.... .... .... .. .8: 8.. 8.3.5.... .88... 92...... 8.. .80 £95. 8:3. 88. a... 5. ... 2‘ 8.. 3.2.2 8.8.3. 8.68. .8. Sod a. 2 E... 4 man. s. can... an... 8:59.50 360.30 8.63— .8. ...... .8. .. 2H . 8.. .2 8n: 5.. .80 5.5.3 8.63. A... ...-.6 .38... 92...... .8. a... .8. .2 .... . 3...: A... .80 ......m\.8.~ ... 8.33. 88. 8... 8.. .. 8.. . 8n . 8%: 8... .80 9-..... ... 8.9.x... .8. 8... .8. . an 2 .8: .... .80 8.63. 8.20.. with .. ... a u <. . . 0 m .2 . . o .. . m . m 55.5.2 .2. 182 independent variables (Cohen and Cohen, 1983: 101; Nie, et.al., 1975: 333) . Supplier Involvement (SI) contributes 11.7 percent of the total variance explained by this regression equation. The Beta coefficient demonstrates that the direction of this relationship is negative. This indicates that higher levels of supplier involvement in the NPD process will result in higher product cost. Table 5-23 Reduction in Start-up Cost Multiple R = .638 R Squared = .407 F-Statistic = 6.180 Adjusted R Squared = .341 Statistical Significance = .0000 Variables Beta Semi-Partial Sig T S] -.060 -.051 .601 BSR -.340 -.286 .005' GP .296 .217 .029“ IMSC .021 .019 .842 II .429 .336 .001 * IA .133 .109 .266 RU -.046 -.043 .579 (constant) .343 "' = statistically significant The explanatory power of the linear regression regarding changes in start- up costs is highly statistically significant (p=.0000) with the ability to predict 40.7 percent of the total explained variance. In this model the independent variables BSR, GP, and II were all statistically significant at the .05 level or better. For this research, the construct BSR is of interest. The direction of the 183 relationship is negative with the individual contribution to the total explained variance amounting to 8.2 percent (p=.005). Hence, the more integrated and cohesive the relationship is between the buyer and the supplier in the NPD process, the higher the relative start-up costs. Table 5-24 Reduction in Tooling and Equipment Cost Multiple R = .518 R Squared = .268 F-Statistic = 3.349 Adjusted R Squared = .188 Statistical Significance = .0042 Variables Beta Semi-Partial Sig T 51 .11 l .098 .364 BSR -.365 -.315 .004"‘ GP .144 .113 .296 IMSC -.114 -.105 .328 II .354 .280 .01 1" IA .039 .032 .764 RU .051 .048 .658 (constant) .756 * = statistically significant Reductions in tooling and equipment costs are inversely related to the strength of the buyer-supplier relationship (Beta= -.365). This relationship is statistically significant (p= .004). 184 Table 5-25 Reduction in Total Manhours Multiple R = .513 R Squared = .264 F-Statistic = 3.376 Adjusted R Squared = .186 Statistical Significance = .0039 Variables Beta Semi-Partial Sig T SI -.055 -.049 .644 BSR -.050 -.044 .680 GP . 184 . 149 .162 IMSC .324 .294 .007“ II .053 .042 .692 IA .098 .080 .454 RU -.241 -.226 .036“ (constant) .435 * = statistically significant While the overall model is statistically significant (p=.0039) as demonstrated by the results of this regression equation, SI and BSR are not statistically significant. Table 5-26 Reduction in Engineering Change Notices Multiple R = .442 R Squared = .196 F-Statistic = 2.330 Adjusted R Squared = .112 Statistical Significance = .0344 Variables Beta Semi-Partial Sig T SI -.l92 -.170 .126 BSR -.149 -.129 .242 GP -.034 -.027 .808 IMSC -.084 -.076 .490 II .320 .252 .025“ IA .229 . 186 .094 RU .086 .080 .471 (constant) .426 "' = statistically significant 185 Supplier Involvement (SI) and BSR are not significant variables contributing to the 19.6 percent explanatory power of the regression equation (p=.0344) predicting reductions in Engineering Change Notices (ECN). The majority of the explanatory power stems from the utilization of Important Information (II) accounting for 6.4 of the 19.6 percent of the variance explained by this regression model (p=.025). Individual analysis of the five measures of product cost reveal that the direction of the relationship between SI and BSR, and the cost element of IPDS is negative as indicated by the negative Beta coefficients. The only exception to this generalization is the relationship between SI and reductions in tooling and equipment costs which was positive, but not statistically significant. In addition, the influence of the supplier was significant in three of the five regression analyses with SI the primary determinant of reductions in product cost, and BSR a significant determinant of reductions in start-up and tooling and equipment costs. The results demonstrate that the influence of the supplier in the NPD process in an integrated product development environment is negative with respect to the performance measures associated with product cost. The evidence suggests that the null hypothesis should be rejected, and that supplier involvement in the process actually increases overall product cost. 5.4.4.2 186 Quality Supplier involvement in the IPD process was expected to be associated with higher levels of product quality. Overall quality was measured by the percent improvement in quality, and reduction in warranty costs, customer complaints, rejected material, and rework costs. Hypothesis 5: H . 0. Quality is unrelated to the level of supplier involvement in IPD. H1: Quality is related to the level of supplier involvement in IPD. Linear Model: IPDS2 = f(SI,BSR,GP,RU,IMSC,II,IA) = Bo + 31(31) + 320358) + 53(01’) + BJRU) + BsUMSC) + 3.01) + MIA) + 6 Two of the independent measures of quality, overall improvements in product quality and reductions in rework costs, did not prove to be statistically significant. The analysis will focus on the remaining three measures which were all statistically significant at the .01 level (Table 5-20). The impact of the supplier (BSR) proved to be significant with regard to reductions in warranty costs and customer complaints. Reductions in rejected material were not significantly influenced by the involvement of the supplier in the process (Tables 5-27, 5-28, 5-29). 187 Table 5-27 ReduCtion in Warranty Costs Multiple R = .484 R Squared = .234 F-Statistic = 2.842 Adjusted R Squared = .112 Statistical Significance = .0120 Variables Beta Semi-Partial Sig T SI .114 .100 .361 BSR -.328 -.281 .011“ GP .327 .263 .018* IMSC -.091 -.083 .448 II .279 .223 .044“ IA -.105 -.085 .435 RU -.119 -.112 .306 (constant) .756 "‘ = smfistically significant The seven independent variables incorporated in this linear regression determine 23.4 percent of the explained variation associated with the quality measure, reductions in warranty costs, with a statistical significance of p= .0120. The relationship between the buyer and the supplier as captured by the construct BSR, demonstrates a negative (Beta= -.328), statistically significant (p=.001) contribution of 7.9 percent of the explained variance. This inverse relationship means that warranty costs actually rise as the caliber of the relationship between the buyer and the supplier becomes more cohesive and integrated. 188 Table 5-28 Reduction in Customer Complaints Multiple R = .488 R Squared = .238 Adjusted R Squared = .156 F-Statistic = 2.902 Statistical Significance = .0106 Variables Beta Semi-Partial Sig T SI -.035 -.030 .784 BSR -.336 -.294 .009“ GP .295 .238 .032“ IMSC -.060 -.055 .615 II .168 .134 .222 IA .107 .085 .434 RU -.275 -.256 .021“ (constant) .022 * = statistically significant The regression results for reductions in customer complaints display a similar pattern to the findings regarding reductions in warranty costs. The BSR construct is statistically significant (p=.009) in the regression model contributing 8.6 percent of the explained variation. The R2 value is .238 and the regression equation is statistically significant at the .01 level. The relationship between this independent variable and the dependent variable, reductions in customer complaints, is negative indicated by the Beta coefficient (-.336) for BSR. This finding indicates that reductions in customer complaints are achieved through less tightly integrated buyer-supplier relationships in the NPD process. 189 Table 5-29 Reduction in Rejected Material Multiple R = .489 R Squared = .239 F-Statistic = 2.921 Adjusted R Squared = .157 Statistical Significance = .0101 Variables Beta Semi-Partial Sig T SI -.040 -.036 .744 BSR -.101 -.089 .412 GP -.235 -. 188 .086 IMSC .410 .381 .001* II .250 .201 .067 IA .109 .091 .405 RU .193 .184 .094 (constant) .365 "' = statistically significant Reduction in the amount of rejected material is highly related to the integrative structure and culture of the firm (IMSC, p= .001) accounting for 14.5 percent, of the total explained variation of 23.9 percent, in the dependent variable. While the regression equation demonstrated a statistical significance of .0101, SI and BSR did not prove to be statistically significant (p=.744 and .412 respectively). The results of the three independent analyses determined that the relationship with the supplier (BSR) is a significant influence IPDS measures of quality, reductions in warranty costs and customer complaints, and is negatively related to the attainment of these goals. The quantitative measure of supplier involvement in the IPD process, SI, was not statistically significantly related to the attainment of these goals. In evaluating the null hypothesis, which postulates that the IPDS quality I90 dimension is not influenced by the level of supplier involvement in the process, the results are mixed. The quantitative component of supplier involvement (SI) does not demonstrate a significant influence with regard to any of the individual measures of quality. The qualitative measure of supplier involvement in the IPD process (BS R) does demonstrate a statistically significant, albeit negative influence on the attainment of these goals. These findings support the rejection of the null hypothesis, recognizing the important influence of the relationship between the buyer and the supplier in the pursuit of quality. 5.4.4.3 Wm; Supplier involvement in the process was expected to reduce the product development time. Project development time, communication, manufacturing cycle time/lead time, and white collar productivity were utilized to evaluate the aggregate dimension of time. Hypothesis 6: Ho: Time is unrelated to the level of supplier involvement in IPD. H,: Time is related to the level of supplier involvement in IPD. Linear Model: IPDS3 = f(SI,BSR,GP,RU,IMSC,II.IA) =30 + 31(51) + 320381?) + BAG?) + 64(RU) + BJIMSC) + 36(11) + MIA) + e The results for the individual regression equations regarding the measures of development time are provided in Tables 5-30 through 5-34. All of the regression equations proved to be statistically significant, reductions in product development time (p=.047), improvements in communication (p=.0053), reductions in manufacturing cycle time/lead time (p=.0091), and improvements in white collar productivity (p=.0144). Supplier Involvement (SI) in the IPD process demonstrated significant influence (p=.051) only with regard to the reductions in the manufacturing cycle time/lead time (Table 5-32). 191 Table 5-30 Reduction in Project Development Time Multiple R = .368 R Squared = .136 Adjusted R Squared = .088 F-Statistic = 2.828 Statistical Significance = .0470 Variables Beta Semi-Partial Sig T BSR -.162 -.151 .237 GP .257 .238 .065 IMSC .238 .235 .068 (constant) .000 " = statistically significant Reductions in the amount of time required to develop the product was regressed on three of the independent variables, BSR, GP, and IMSC. The regression equation is significant at the .05 level accounting for 13.6 percent of the variation in reductions in project development time. None of the independent variables are statistically significant at the .05 level. However, GP and IMSC are close to the conventional significance level. 192 Table 5-31 Improvement in Communication Multiple R = .508 R Squared = .258 F-Statistic = 3.232 Adjusted R Squared = .178 Statistical Significance = .0053 Variables Beta Semi-Partial Sig T SI -.219 -.193 .075 BSR .110 .096 .371 GP .336 .269 .014* IMSC . 103 .095 .378 II .114 .090 .403 IA .070 .057 .597 RU .097 .089 .409 (constant) .401 "' = statistically significant The full linear model explains 25.8 percent (p=.0053) of the variance associated with improvement in communication. Group Process (GP) is the only statistically significant independent variable (p=.041) accounting for 7.2 percent of the variance explained. Neither quantitative (SI), or qualitative (BSR), measures of supplier involvement in the IPD process proved to be statistically significant in this regression equation. 193 Table 5-32 Reduction in Manufacturing Cycle Time/Lead Time Multiple R = .492 R Squared = .242 F-StatiStic = 2.972 Adjusted R Squared = .161 Statistical Significance = .0091 Variables Beta Semi-Partial Sig T SI -.241 -.215 .051* BSR .060 .052 .633 GP .095 .077 .478 IMSC .120 .108 .319 II .341 .268 .016“ IA .050 .039 .720 RU -.149 -. 142 .194 (constant) .262 * = statistically significant Supplier Involvement (SI) in the regression model utilized to predict reductions in manufacturing cycle time is statistically significant at the .05 level. The SI construct demonstrates a negative relationship to the dependent variable (Beta = -.241), while accounting for 4.6 percent of the explained variation in the reductions in manufacturing cycle time. Table 5-34 Improvement in White Collar Productivity Multiple R = .375 R Squared = .141 F-Statistic = 3.771 Adjusted R Squared = .104 Statistical Significance = .0144 Variables Beta Semi-Partial Sig T GP .206 . 174 . 124 IMSC .175 .172 .129 II . 182 . 152 .177 (constant) . 144 "‘ = statistically significant 194 The results of the regression equation indicate that none of the independent variables are statistically significant in predicting white collar productivity. The aggregate results of the individual measures of the time dimension of IPDS indicate that overall, supplier involvement in the process plays an insignificant role in the attainment of improvements in project development time, communication, and white collar productivity. Supplier Involvement is significant in the efforts to reduce manufacturing cycle time/lead time. This requires the rejection of the null hypothesis which postulated that time is unrelated to the level of supplier involvement in the IPD process. 5-4-4-4 W Supplier involvement in the NPD process was expected to have a positive impact on quality and cost, two of the components of IPD Success. This relationship was expected to transfer into the subjective evaluations of the customer’s perceptions of quality and value and the capabilities of the product. .Overall product performance was measured based on the improvement in tangible product performance, market share, perceived value, perceived quality, sales, profitability, and product capabilities. Hypothesis 7: Ho: Product performance is unrelated to the level of supplier involvement in IPD. H,: Product performance is related to the level of supplier involvement in IPD. 195 Linear Model: IPDS. = f(SI,BSR,GP,RU,IMSC,II,IA) = 60 + {31(31) + BJBSR) + BAG?) + B.(RU) + 35(IMSC) + 6601) + MIA) + e The seven individual regression analyses related to the IPDS product performance dimension are presented in Tables 5-35 through 541. All of the regression models proved to be statistically significant, improvements in product performance (p=.0074), improvements in market share (p=.0004), increases in perceived value (p=.0101), improvements in dollar sales (p=.0015), improvements in product profitability (p= .0119), and improvements in product capabilities (p=.0383). Each of the dependent variables, and the influence of supplier involvement, will be discussed following the presentation of their individual regression results. Table 5-35 Improvement in Product Performance Multiple R = .434 R Squared = .188 F-Statistic = 4.410 Adjusted R Squared = .146 Statistical Significance = .0074 Variables Beta Semi-Partial Sig T SI -.368 -.329 .008" IA .231 .225 .064 RU .342 .309 .012“ (consmnt) .068 "' = statistically significant Improvements in the tangible performance characteristics of the product 196 (speed, strength, weight, etc) can be predicted (R2=.188) by the level of Supplier Involvement (SI), Information Accessibility (IA), and Resource Utilization (RU) (p=.0074), Table 5-35. The supplier’s influence in the achievement of tangible product performance improvements is negative (Beta= -.368). SI is a significant determinant of the changes in product performance demonstrating the highest individual explained variation (10.8 percent) and statistical significance (p = .008). Table 5-36 Improvement in Market Share Multiple R = .570 R Squared = .325 F-Statistic = 4.538 Adjusted R Squared = .253 Statistical Significance = .0004 Variables Beta Semi-Partial Sig T SI -.518 -.448 .000“ BSR .010 .084 .411 GP -.261 -.210 .042" IMSC .247 .225 .029“ II .260 .207 .045* 1A .048 .041 .688 RU .227 .205 .047" (constant) .400 "' = statistically significant The seven independent variables which were included in the linear model for explaining improvements in market share account for 32.5 percent of the observed variation in this dependent variable (Table 5-36). This model is statistically significant (p=.0004) with five of the independent variables 81 (p=.000), GP (p=.042), IMSC (p=.029), II (p=.045), and RU (p=.047) having significant T-statistics. Supplier Involvement (SI) in the IPD process 197 demonstrates a strong inverse relationship to the IPDS goal of improvements in market share indicated by the high negative Beta coefficient of -.518. The individual contribution of the independent variable S] to the explained variation is 20.1 percent. Table 5—37 Increase in Perceived Value Multiple R = .489 R Squared = .239 F-Statistic = 2.921 Adjusted R Squared = .157 Statistical Significance = .0101 Variables Beta Semi-Partial Sig T SI -.192 -.174 .110 GP .205 . 195 .075 RU . 331 . 312 .005“ (constant) .374 "' = statistically significant Three of the independent variables (SI, GP, RU) were selected for inclusion in the predictive model relating to increasing the perceived value of the product (Table 5-37). The role of SI in increasing the perceived value of the product is not statistically significant (p=.110). Table 5-38 Increase in Perceived Quality Multiple R = .233 R Squared = .055 F-Statistic = 4.151 Adjusted R Squared = .041 Statistical Significance = .0453 Variables Beta Semi-Partial Sig T IA .233 .233 .045"‘ (constant) .000 * = statistically significant 198 A simple linear regression proved to yield the highest explanatory power for the dependent variable increasing the perceived quality of the product (Table 5-38). The accessibility of information (IA) explained 5.5 percent of the variance in this product performance measure with a statistical significance at the .05 level. Neither SI or BSR were included in this regression equation which means they have no influence on increasing the perception of quality. Table 5-39 Improvement in Dollar Sales Multiple R = .528 R Squared = .278 F-Statistic = 3.800 Adjusted R Squared = .205 Statistical Significance = .0015 Variables Beta Semi-Partial Sig T SI -.226 -. 198 .057 BSR .345 .281 .008“ GP .006 .005 .963 IMSC .335 .304 .004“ II -. 175 -. 140 .175 IA -.090 -.074 .473 RU .307 .285 .007 " (constant) .876 " = statistically significant Another indicator of product performance is the increase in sales associated with the development of a new product (T able 5-39). The overall regression model served to explain 27.8 percent of the variation in sales, measured in dollars, with a statistical significance of .0015. The relationship between the buyer and the supplier in the IPD process (BSR) is positively correlated with improvements in dollar sales (Beta= .345) offering 7.9 percent of 199 the explanatory power of the regression equation. This relationship demonstrated a statistical significance of .008. The influence of SI in the process, reporting borderline significance of .057, is negative with the direction and magnitude of the relationship indicated by the Beta coefficient of -.226. Table 5-40 Improvement in Product Profitability Multiple R = .484 R Squared = .235 F-Statistic = 2.845 Adjusted R Squared = .152 Statistical Significance = .0119 Variables Beta Semi-Partial Sig T SI -.260 -.229 .039“ BSR .212 .186 .092 GP -.013 -.010 .926 IMSC .280 .255 .022" II -.113 -.090 .410 IA .225 .181 .101 RU .032 .030 .782 (constant) .284 "' = statistically significant A related measure to sales, and an indicator of product performance, is the relative improvement in the profitability of the product (Table 5-40). Two of the independent variables demonstrated significant T-statistics, SI and IMSC, at the .05 level or better (p=.039 and p=.022, respectively). In conjunction with the remaining five independent variables, the model accounts for 23.5 percent of the variance in the improvements in product profitability (p=.0119). The level of SI is inversely related to the improvement in product profitability, Beta equal to -.260, with an absolute contribution to the variance explained of 5.2 percent. 200 Table 5-41 Improvement in Product Capabilities Multiple R = .439 R Squared = .192 F-Statistic = 2.279 Adjusted R Squared = .108 Statistical Significance = .0383 Variables Beta Semi-Partial Sig T $1 -.154 -.134 .225 BSR .306 .240 .032" GP -.419 -.325 .004“ IMSC .179 .163 .143 II .011 .009 .935 1A .018 .014 .897 RU .253 .234 .037 * (constant) .029 * = statistically significant Improvements in product capabilities measured the percent change in the functionality of the product for its intended use (Table 5-41). The seven independent variables reported a predictive capability of 19.2 percent with a significance level of .0383. The BSR construct is positively and significantly correlated (p=.032) with improvements in a products capabilities (Beta=.306), providing 5.8 percent of the explained variation. The SI construct demonstrated a negative relationship with the dependent variable but did not demonstrate a statistically significant individual T-statistic (p=.225). The results clearly support the rejection of the null hypothesis which postulates that product performance is unrelated to the level of supplier involvement in the IPD process. The construct SI consistently displays a negative relationship with the individual measures of product performance. This relationship was statistically significant in the determination of improvements in 5.5 201 product performance (Table 5-35), improvements in market share (Table 5-36), improvements in product profitability (Table 5-40), and marginally significant with regard to improvements in dollar sales (Table 5-39). These findings are polar to the results attributed to BSR in the determination of the independent variables measuring the IPDS goal of product performance. The relationship between the buyer and the supplier in an IPD environment is consistently positively correlated with the seven independent measures of product performance. This relationship is statistically significant in the regression results associated with improvement in dollar sales (T able 5-39) and product capabilities (Table 5-41). The discrepancies in the results of the two constructs, depicting the suppliers involvement in the IPD process (SI and BSR), make the determination as to whether this involvement is a positive or negative influence on the performance aspect of the IPDS variable difficult to determine. The results are best interpreted on the disaggregated individual measures of product performance than an aggregated score for the purpose of parsimony. Controlling for Exogenous Variables In the development of the research design, three exogenous variables were identified as potentially having an important influencing role in the regression results. The size of the firm (S), measured by annual sales, the degree of product innovation (PI), routine/incremental versus radical/quantum, and the competitive intensity (CI), measured by the rate of change and growth in the competitive 202 marketplace. In order to assess the impact of these exogenous variables the sample was stratified into large, medium, and small for the exogenous variable firm size, and high medium, and low for product innovation and competitive intensity/environmental uncertainty. T-tests for a difference between means were run for the independent and dependent variables. A summary of the results of this analysis is located in Appendix III. The findings indicated that very few of the 24 dependent variables incorporated in this research demonstrated a statistically significant difference in the means between the groups. This result held true for the seven independent variables as well. Based on these results, it was concluded that the influence of the exogenous variables was negligible, and that further analysis would not provide significant additional information pertinent to the regression results. 5 .6 Impact of Supplier Involvement on an IPD Environment Table 5-42 presents a summary of the research findings based on the data provided in Table 5-21, and the results of the individual hypothesis testing. The focus of the hypothesis is located in the left column and corresponds to the discussions of product cost (Hypothesis 4), product quality (Hypothesis 5), development time (Hypothesis 6), and product performance (Hypothesis 7). The columns devoted to SI and BSR indicate the direction to the relationship between the independent variable, positive (+) or negative (-), and whether the relationship was statistically significant (*). 203 Table 542 Summary of Hypothesis TeSting for Supplier Involvement Hypothesis SI BSR Decision Costs _ * _ * Reject H, Quality _ * Reject H, Time _ * Reject H, Product Performance _ * + * Reject H, * = statistically significant The results demonstrate that the impact of the supplier in the NPD process utilizing an IPD strategy is significant. The direction of the relationship between the independent and dependent variables (negative), with the exception of BSR and Product Performance, is counter to the expectations of the research. The implications of this finding will be addressed in Chapter VI. This chapter has been devoted to a detailed description of the sample population, presentation of the statistical analysis, development of a new IPDS conceptual model, and the results of the hypotheses testing. Chapter VI addresses the conclusions that can be drawn from this research, the contributions stemming from this research, and the implications for future research. CHAPTER VI CONTRIBUTIONS and CONCLUSIONS 6.0 Previous chapters have addressed the relevance of this research problem, focus of this research project, supporting literature, the conceptual model, the research design and methodology, and the data analysis and research findings. This chapter presents the contributions and conclusions which can be drawn from this research, the limitations of the study, and the implications for future research. 6.1 Contributions This study represents the first large-scale empirical study of the Integrated Product Development (IPD) strategy being utilized in the New Product Development (NPD) process investigating the role of the supplier in this process. In addition to the size of the sample, the research was strengthened by the purposive diversity of the population which was incorporated in the research design to increase the generalizability of the research findings. The scope of the investigation, incorporating organizational, project, and interorganizational variables in the analysis, was designed to build on previous research by taking the conclusions drawn from other fragmented research, and synthesizing them into one cohesive study. The purpose of this effort was to try 204 205 and develop an understanding of the inter-play between the variables postulated by previous research, and capture the dynamics associated with the N PD process. The focus of the research was to isolate and measure the impact of supplier utilization in the IPD strategy in the NPD process. The nature of supplier involvement was evaluated along two dimensions. The first dimension representing the quantitative evaluation of the volume of supplier involvement (SI) on the project level. The second dimension involved the evaluation of the interorganizational dynamics, and character, of the buyer-supplier relationship (BSR). By incorporating the project and organizational level environments in the same study, the influence and contribution of supplier involvement was assessed in a holistic context, rather than in a piecemeal fashion. Incorporated in the research design was the utilization of the Susman and Dean framework (1991), Figure 1-3, as the foundation for testing the relationships postulated by the literature. This facilitated the objective of building on previous research in the development of a theory regarding an integrated approach to the NPD process. Based on the findings of this research, the initial framework has been refined and a new conceptual model proposed which attempts to capture the dynamic nature of an IPD process, Figure 5-17. The model includes the incorporation of seven independent variables, Supplier Involvement (SI), Buyer-Supplier Relationship (BSR), Integrative Mechanisms Structure/Culture (IMSC), Information Importance (11), Information Accessibility (IA), Group Process (GP), and Resource Utilization (RU), and two dependent variables, Integrated Product Development Success (IPDS), and Firm 206 Performance (FP). The research served to identify the direction and magnitude of the relationships between the variables proposed by this new model. Another contribution of this research has been the development of reliable, validated scales to foster the measurement of those constructs which were identified in the literature, and utilized in this research. The results of this analysis are provided in Tables 5-10 through 5-16 for the seven independent variables, SI, BSR, 1M, 11, IA, GP and RU. Secondary measures which were developed in this process, and are of significant interest to researchers and practioners, are two dimensions of the GP construct, Leadership and Group Cohesion. The two dependent variables incorporated in this research, PP and IPDS, were scrutinized, validated, and tested in the same fashion (see Tables 5-6 and 5- 7). Establishment of reliable measures of firm performance based on market performance and competitive position will serve to facilitate research of a strategic nature. This research also incorporated an innovative method at collecting objective information of a sensitive nature in the measurement of the IPDS. Each dimension of IPDS was measured as a percent change from a benchmark. This facilitated the aggregation of objective data across industries and projects. These research findings lay the foundation for future research in the specific area of integrated approaches to new product development, and at the more global level of product development and innovation in general. They also facilitate any future research efforts targeting the assessment of supplier 207 involvement in an interorganizational context across a wide variety of applications. The research served to identify the importance of two dimensions of supplier involvement, the quantitative component which focused on the measurement of the quantity of involvement across a wide variety of criteria (SI) and the quality or caliber of the buyer-supplier relationship (BSR), which focused on the assessment of the nature of the interaction between the two parties. An important contribution of this research is the verification of a positive, significant relationship between the utilization and success of an IPD process to developing new products and firm performance. This insight supports the utilization of teams in this problem context, and rationalizes the initial costs which may be incurred to establish this structure in an organization. Identification of the market-based (Market Performance-M P) and competitor-based (Relative Performance-RP) criteria which are influenced by the individual measures of Integrated Product Development Success (IPDS) in the assessment of Firm Performance (FP) provides project managers key performance criteria to evaluate the success of their development efforts. This information provides the linking-pin between the achievement of corporate strategic objectives and the success of individual NPD projects. Managers will be able to focus on the criteria relevant to specific corporate goals whether they be market penetration, growth, profitability, etc. Establishing these criteria, and the significance of the relationship, can help facilitate the deployment and utilization of critical resources in the development of new products. 6.2 208 Conclusions Based on this study,.supplier involvement, as determined by the joint assessment of the constructs SI and BSR, in the NPD process appears to have a significant impact on the cost, quality, development time, and product performance dimensions of IPDS (see Tables 5-21 and 5-41). The importance of supplier involvement in the process as a determinant of project success is equal to, or greater than, the impact of the other independent variables incorporated in this research [GP, IMSC, 11, IA, RU (Table 5-21)]. A priori expectations were that supplier involvement would be significant, and a positive influence on the attainment of the strategic initiatives incorporated in the IPDS construct. The results support the initial conclusion that supplier involvement is, in fact, significant. Unfortunately, the results also indicate that the nature of the influence is predominately negative, with nine out of the eleven statistically significant correlations reporting a negative Beta coefficient (T able 5- 21). The magnitude of this result is acute when a comparison is drawn with the remaining relationships, between the independent and dependent variables which were found to be statistically significant, 26 in all (Table 5—21). Of these, only four demonstrate a negative correlation, with the relationship between RU and a reduction in total manhours (Beta = -.241) being negative as expected. This result defies conventional wisdom and the current paradigm concerning the inclusion of the supplier in the NPD process. Interpreting this result serves to raise more questions than it provides answers. Evidence which has led to the development of the current paradigm has been the product of case 209 studies of individual projects, hearesy, and common sense. Empirical testing of this relationship across a variety of projects (in scope and scale), industries, firms, cultures, competitive environments, technologies, levels of innovation, etc., indicates that this previous paradigm does not hold true. One possible explanation is the potential for the presence of sample bias in other studies, which may have led to the erroneous conclusion that supplier involvement is a positive influence in the NPD process. Other research in this area has been restricted in scope to primarily two industries, automotive and electronic. In addition, the sample population for these research efforts has predominately focused on executives in the purchasing and materials management function. Respondents have often been requested to provide information regarding the key success variables, as well as gauging the degree of success of the NPD project. Due to the difficulty in collecting objective data, these studies have primarily relied on the utilization of perceptual measures to capture information for both the independent and dependent variables. The results are therefore speculative due to the threat of mono-operational bias. In this research, a wide variety of industries were represented. The respondents were also from a wide spectrum of functional backgrounds including, engineering, marketing, production, materials management, purchasing, and sales. The threat of mono-operational bias was minimized in the research design by utilizing objective and perceptual measures for both the dependent and independent variables. 210 Another possible explanation for the discrepancy between the current research findings, and the conclusions drawn from the literature, lies with the potential to bias the data by disclosing the focus of the research to the research participants. To protect against this form of data contamination, participants were told that the research was an investigation of the NPD process utilizing a team approach. Respondents were not given any further insight as to the focus of the research, supplier involvement in the process. In fact, the questions on the survey regarding supplier involvement in the process were addressed in the last section of the ten page survey to minimize the potential for biasing the results. A final explanation is the influence of the learning curve associated with the team approach to the development of new products. The unit of analysis for this research effort was the individual NPD project. As such, the results are based on the aggregation of individual events representing a given point in time. The data collected did not differentiate the projects based on the level of experience the firm, team, and/or supplier demonstrated with an IPD strategy. There is reason to believe that experience with an IPD approach would yield more effective utilization of both internal and external resources. This assumption is based on the organizational and interorganizational initial cultural inertia demonstrated by firms utilizing the IPD strategy. Adoption of this approach requires the development of a new system to facilitate the process including the appropriate culture, structure, information channels, rewards, etc. While the current research did not directly measure the learning/experience curve of the respondents, information was sought regarding 211 the degree of innovation as a control variable to provide some additional insight. The T-test for a difference between means indicated that there was no substantial difference in the levels of supplier involvement (SI, BSR), or project performance (IPDS) based on the degree of innovation (Appendix III) with one exception, reductions in warranty costs. 6.3 Limitations The research is limited by the purposive, convenience sampling technique employed to insure that respondents were utilizing an IPD approach in the NPD process. The data were provided almost exclusively by manufacturing firms reporting on the experience in developing a tangible product for delivery to the market. Consequently, the majority of the suppliers involved were also the providers of tangible products. The results are therefore only representative of the manufacturing sectors of the economy and can not be generalized to the service sectors. The primary limitation of this study is a function of the research design, and was done intentionally to improve the general izability of the results across industries. The sample population selected for this research consisted of a variety of industries, nine including the "other” categorization (Figure 5-2), for a sample size of 83 projects. While the sample size is more than adequate to provide meaningful results across industries, it is inadequate for comparative purposes between industries. 212 A question which therefore remains to be answered is if these findings are consistent within each industry. The number of independent variables incorporated in this research does not facilitate an in-depth analysis by industry, given the sample size for each industry represented. The large automotive industry representation did allow for this investigation, and the results were consistent with the overall research findings. Additional information regarding the experience of the firm and individual team with the IPD approach to NPD and specifically, the incorporation of the supplier in this process, would have provided some valuable insight. Another improvement would have involved the inclusion of perceptual measures of project success to use in conjunction with the objective measures incorporated in the research. This information would have facilitated the bi-polar examination of the impact of supplier involvement in projects that were considered to be a success, versus those that were considered to be a failure, as a measure to normalize the data across industries. In addition, the findings of this research are based on the information provided by the buying organization. The research would have been strengthened by a research design which incorporated the supplying organizations input. Valuable information could have been obtained with case comparisons between the buying and supplying organizations based on the level of supplier involvement and the degree of project success. 213 6.4 Implications for Future Research The results of this research are a well-spring of opportunities for many future research endeavors through an incremental step in the advancement of a theory regarding an integrated approach to the innovation process involving new product development. The development of a conceptual framework and reliable, valid constructs provides researchers with a foundation and some additional tools to facilitate future research. In addition, the findings serve to provoke the development of more questions and plausible explanations for the conclusions drawn from this research which need further investigation. A logical extension of this research is the development of a path model which specifies the order and interactions among the variables. In addition, specific research to identify the influence of intervening variables such as international differences, organizational culture, leadership, industry, and group dynamics needs to be conducted. The present research calls for parallel studies utilizing a different sample to determine if these results are an anomaly or demonstrate the need for a paradigm shift regarding the buyer-supplier relationship in the realm of NPD. Specifically, in.depth comparison studies by industry would be beneficial. This would require the commitment of enough participants by industry to facilitate comparative statistics. Given the growth and importance of the service sector in the overall economy, and the significant differences between manufacturing and services in the product development and delivery process, a thorough 214 investigation regarding the utilization and effectiveness of an IPD strategy in the services industries is needed. Another approach involves the use of a stratified sample based on the point of supplier involvement in the NPD process. This methodology would offer insight as to what point in the process the supplier’s involvement is the most beneficial and facilitate the optimal integration of the supplier in the IPD environment. Two additional methodological contributions include a follow-up longitudinal study to determine the impact of the experience/learning curve, and a paired case study approach including input from the supplier and buyer in the analysis. The longitudinal study would serve to identify if the role of the supplier changes over time as the organizational barriers to the IPD approach are minimized or eliminated, and if the overall process also becomes more effective. The paired approach would validate the contributions of the supplier and eliminate the threat of mono-operational bias in the analysis. 6.5 Concluding Remarks Based on this research, inclusion of the supplier in the NPD process as a member of an integrated product development team is seen as detrimental to the success of the project. The only exception to this finding is that the quality of the interaction between the buyer and the supplier positively impacts the improvement in the sales (dollar) and capabilities of the product. These results serve as an indication that current purchasing practices advocating a high level of supplier 215 involvement in the NPD process be revisited. In addition, the results call into question current purchasing strategic practices such as strategic alliances, partnering, joint ventures, long-term contracts, sole sourcing, etc., which are based on the premises of collaboration. A far-reaching conclusion is that the research supports a reinstitution of competitive market conditions in the buyer- supplier relationship to achieve a competitive advantage in the introduction of new products to the market place. APPENDI X I 216 MICHIGAN STATE UNIVERSITY GRADUATE SCHOOI. or BUSINESS ADMINISTRATION EAST LANSING - MICHIGAN - «121.113 DEPARTMENT Of MANAGEMENT - (SIT) ”Mus CHAIRPEISON - (31‘) 155-1171 IA! (517) 316-1111 DearReeearchParticipant: Firstofall, Iwouldlikemthankyouforyotneomminnmtmdsupponofthismeamhproject investigatingnewproductdevelopmt. Yoruparticipationiscritiealtothesueeeesofthis project. Your contribution will serve to facilitate the development of a knowledge~base regardingmemnicaupmasodamdwimnewpmduadevdopmmtuwenunnowingu toeornpletemydoctoraldegroeatMichiganStateUniversity. Thereforeyouanviewyour MmtuamfibuMmmeadvamtofmmdahumaninfimgm. The pmposeofmismerkmprwideymwithmedenflregudingmemandseopeofm marchprojedfihebarefitywwfldaivefiomparfidpafinginthisfldnmdmhdc mmmwmmwmmdmm devdopmentandmechallargemnpidlydevdopandhmodueenewprodueninme mrketplaee,aconceptknownas‘l'ime-Based€ompetition. Tnditimllymroduetandproeees dedgmhawbemdmeaquenfiany,efiecfivdyignofingmehtaacdmbaweenmetwom ofinnovation. Adeparnnefromdrenaditionalapproachinvolvestheuseofteamsinthenew productdeveloprnentefiort. 'I'hisreearchaeekstonnderstand,meesureandexplaindteinrpact ofindividmlmrgamndomhandhcr-mpnindomlmwhichefieamemofnew productdevelopmentefforts. Therendtsofthisreearehwillservetoidentifywhichvariabler impactdteprocessandmeirrelativeorderofmagnimde. Thiswillprovidefirmswiththe tangibledataneeessarytoefl’eetivelyalloatereeotnoer. Themamhfindingswmheaproduaofalugesakempinalfiwufigafiminvdvingmy firmsfrornaerossa widedisnibutionofindusnieshothdomesticandahmad. Datawillbe whaeddumghtheuseofamwyandwppmbdbyincdepthasemdiesoffimsfiomaeh oftherepreeentativeindustrier. Thereeultswillbesharedwithparticipantsontheauregate leveICrnvolvingallthefir-mslproject).hyindusny, andainternationalversusdomertieanalysis. eroufirmufilifingmhruarchuamninifiafiwmvidmgmmlem). aeonfidendalstafisticllanalysisofdtefirm’srendtswillalsobeprovided. Participatinginthis mmmmmmmwmmmmym Indusu'y, acrossindustries,and internationally. Whawwwm ' -_-__,p___ 217 The survey is designed to gather information regarding a specific new product development project which has made it through the design phases, and is actually into production. The survey should be completed by an individual who was actively involved with the project since conception, a core team member, project leader, or manager. The survey was pilot tested and took about two hours to complete. The survey provided to you is number .This number can be found on the lower right-hand portion of the last page. You ean utilize this number for your own internal tracking and control purposes. lsuggestthatyoumakeacopyofthecompletedqtresticnnaireforyomownusepriorto returning the original. Please return all the questionnaires, both completed and uncompleted, ulneedmishrformafimfordnsudsfiealanalysisanddiereporfingofresults. Ifyouhave questions,orrequireadditional questionnairesmleasefcelfrcetomll. AnahardamdisstneameupinamvdmkickmccldfiomNavismmmfimnl. Rickaskedmeiflwouldhelphimfacilitatethefonnafionofa'romrdtable'discussiongroup devotedtonewproductdeveloprnent. 'I'hepurposeofthegroupwouldbethe'transferof echnology'orsharingot‘int‘ormationandexperiencesinvolving product developmentinan integratedenvironrnent. 'Ilieideaistoprovidealow-keyJow-costenvironmentforlarning fromeachother. Noformalpresentafions,butndieranachangeofinfomfionandideasfiom allparticipants. Ifyouareinterested, pleaseealIchkMaleckr (219-461-1438),ormyse1f(517- 339-4651),andhe1pustodeterrninetheappropriatetimeandlocaticn. lanly,lwonldliketothankdtelnternafionalQulity&ProducdvityCenu, Productivitylnc., The Society of Computer-ended Pagineering, The National Association of - MmgunentmdlheLfichiganSmeUnivusitmechan'ngDevdopmentFmdfu-meir supportofthisresearchefiort. Asweallknow, meprodnctisonlyasgoodastheteam! 218 Survey of New Product Development Strategies And Processes MIEHIBAN This research is being funded by the National Association of Purchasing Management and the Michigan State University Purchasing Development Fund. 219 Information The information prenatal about your company will be held strictly confidential. Please fill in the following or attach a business card. (Optional) Name. Position/ Title: Company: Address: Telephone/ Extensioru Please return the completed survey to: [aura M. Biron Michigan State University Management Department 232 Eppley Center East Lansing, MI 488244121 517-339-4651 (Direct) 517-353-5415 (Main Office) 517-336-1111 (Fax) The success of this research is highly dependent on your participation. Therefore, I would like to thank you for your time, energy, and droughtfulneas. Your assistance is greatly appreciated. General Instructions 1. Thisqresfiomaheshouklbefilbdwtflmspcamamwpoductdevdopnmtprojca whichhasnndeitthroughthedesignphaseandisinproduction. 2. Thehflividuflcmrmlefingdfisnnveydmuldhawahighhvdoffmufluuywimmprojca identifiedforthisrcsearch. 3. quwsfiomadtyoumcheckabonchckanmrba,mpmvidespedficdam1haeuem ‘fighf'm‘finmgfimmDifiaentpmjecumexpecmdmhawdifiamtrespmseeThe pmposeofdiismchistourtdastanddiediffm 4. Pleasemswuanquesfionsasincomphtequesfimnahesmsuimprouamindam analysis 5. Memdnquesdonsasmnmlyasyoucmhemofdnmrdydepmdsm mfianknessandcareinamweringquestions. 6. Pleasercnnnallquestionnairesindieencloscdenvelopewithinhm PS” 220 I. General Information The primary industry in which your products compete. (Check one) [:1 Automotive [:1 Machinery, except Electric C] Defense D Electronic/ Electric C] Transportation Equipment 13 Other (Please Specify) Indicate the size of your firm/business by the number of employees. employees Indicate the size of your firm/business unit by the annual sales. dollars Indicate the relative importance of the alternatives below to your firrn's ability to compete. Not Important Extremely Important Product Cost 1 2 3 4 5 6 7 Product Quality 1 2 3 4 5 6 7 Dependability] Delivery] Due Date Performance "...... l 2 3 4 5 6 7 Flexibility] Responsiveness l 2 3 4 5 6 7 Rapid New Product Introduction] Innovation «mama... 1 2 3 4 S 6 7 Indicate the relative importance of each characteristic to your firm's business strategy. Not Important Extremely Important New Product Development 1 2 3 4 5 6 7 Brand Identification l 2 3 4 5 6 7 Innovation in Marketing Techniques 1 2 3 4 5 6 7 Advertising 1 2 3 4 S 6 7 Operating Efficiency 1 2 3 4 5 6 7 Competitive Pricing l 2 3 4 5 6 7 Procurement of Raw Materials 1 2 3 4 S 6 7 Innovation in Manufacturing Processes l 2 3 4 S 6 7 Compared to3yearsago, whathssbeenthetrend inyourindustry? Significantly Sinifleantly Decreased Increased Market growth (domestic) l 2 3 4 5 6 7 Market growth (intermtionslly) l 2 3 4 S 6 7 Rate of technologial changes in pond-m l 2 3 4 5 6 7 Rate of technological changes in processes......._..................-.... 1 2 3 4 S 6 7 Competition 1 2 3 4 5 6 7 Describe your firm's competitive environment. Strongly Agree Strongly Disagree Our firm rarely changes its marketing practices.................... 1 2 3 4 5 6 7 The rate of product W is slow- 1 2 3 4 5 6 7 Actions of competitors are easy to predict 1 2 3 4 S 6 7 Demand and consumer tastes are easy to ioroeast............. 1 2 3 4 5 6 7 The rate of process obsolescence is slow. I 2 3 4 5 6 7 Whyatrhdmgmnrpctfim,mdiateymnfirm'spodtbnmdufdlmvingdw. Significantly Significantly lower Higher Responsiveness/Minty 1 2 3 4 5 6 7 Customer Service 1 2 3 4 5 6 7 Innovation/rate of new product introduction 1 2 3 4 5 6 7 Product met 1 2 3 4 S 6 7 Product paformanca l 2 3 4 5 6 7 Product quality/um puception l 2 3 4 5 6 7 Process innovation 1 2 3 4 5 6 7 Market share growth I 2 3 4 5 6 7 Sales growth 1 2 3 4 5 6 7 Eurdngs growth 1 2 3 4 5 6 7 Return on asses l 2 3 4 5 6 7 221 9. Indicate the extent to which you agree with the following statements regarding your firm's internal environment. 58"” Disagree Innovation and change are encouraged l 2 3 4 5 6 7 Authority and responsibility are decentralized ..__..._..... I 2 3 4 5 6 7 Highly structured channels of communication ...... l 2 3 4 5 6 7 A strong insistence on uniform managerial flyie..............-....... ‘l 2 3 4 S 6 7 A strong emphasis on formal procedures 1 2 3 4 5 6 7 Informal style of dealing with each other 1 2 3 4 5 6 7 Mistakes are tolerated l 2 3 4 S 6 7 Important decisions are made by individuals I 2 3 4 5 6 7 Cooperation and trust exists between departments .. I 2 3 4 5 6 7 ‘I'heorganizationandpeopleareclosedandsacretivem l 2 3 4 5 6 7 Results are more important than proceduru 1 2 3 4 5 6 7 IO. Indicate what you believe most accurately describes your firm's innovative environment. My my Agree Disagree ‘I'herateofnewproductintroductionbythefirmhas deer-sed compared to leading competitors. _____ I 2 3 4 S 6 7 ‘l'heruteofchange in yourmethods of production has declined compared to leading competitors ..... ...... 1 2 3 4 5 6 7 Risktakingbylteyexecutivesofthe firm inseizing and exploring a “risky' growth oppatunky has decreased. ‘I 2 3 4 5 6 7 Seeking unusual, novel solutions by senior executives to problems via the use of ”idea men} brainstorming dc. has declined. ‘ I 2 3 4 S 6 7 When confronted with decision-making situations involving uncertainty, my firm typically adopts a cautious, “waitandsae' poatrueinordertominimiu the probability of making a mistake. I 2 3 4 S 6 7 II. Project Specific Information Please answer the following questions with respect to a specific new product development effort you were personally involved in. n. Whatisthenameofthisproject/ptoduct? (Tobaheldstflctlycoefldeaflal). 12. WasthisproducciChsckOIe) D Aminorimprmementof U Amaioranluncementof CI Anentirelynew anodstingproduct anedstlngproduct product 13.1‘hisproiectiequlredtheutllintionofzimaekne) C] Mtghclmoiogy Cl New-relatedtechnoiogy Cl New-unreIaMtchnoIogy 14. ‘l'hispo'pctwasddgusdtomtflythenssdsofziosckoael D Existingcustomers CI Anewmarbtsegmmt/uiche U Anewmarkat 222 15. This product represents: (Check one) D A finished product [3 A subassembly C] A component part 16 For the following project goals, indicate the targeted change in pa-formance improvement and the actual change in nce improvement on this project as a percentage (it, 0%, 35%, IM. etc.) . Then provide the unit of measure utilized to monitor this goal achievement atom-s, dollars, people, etc.). Example: In thedeveloprnent ofthenew ADC widget. thenew product development team targeted a 10% cost reduction. They wereabletoachievea12%costreductioruandtheunitolmeasurewasdollars. Unit of Project Goal Target Actual Measure Example: Reduce fioduct Cost “5 12% Dollars MuceProductht loductioainStart-UpCost Iaduce'foolingCosts/Emlipmeotoost ImproveProducthality Hues WarrantyCou RaducaCustomsrComplsints Roducelejactad Material RducelleworkCod Iaipronnodunmkqsspadwdght) ImproveMarltetShare IncreasePeroeivad VaIuerCustomer Irraaassl’erceivsd QulityDyCustcmsr ImproveDolIarSal. ImproveProductProfltabIIty ImprovsProductCapabiIIiss Reduce Pio'pct Development'l'ims ImprovedCommrmicatlsn Reduce Total Manhours Raductioain'l’otalfinglnauirgdungefloticas RaductiminManufachulndee'l'lme/Indflm lmprovadWhlta-Collarl’roductiviry 223 I7. The answer to the previous project performance goals is based on the establishment of a project benchmark or target. Please indiate the source of this benchmark (Check only one). A competitor’s product A corporate target A previous model Qher, plmsespecify 18. The manufacturing process to produce this product is: D Mass production [:1 Batch production Cl lob sh0p On this project: Low Risk High Risk 19. Degree of product technical risk? I 2 3 4 S 6 7 20. Degree of process technical risk? I 2 3 4 5 6 7 Strongly Agree Strongly Disagree 2]. The new product development process on this project: was characterized by the simultaneous consideration of pro- duct and process design opportunities and constraints... I 2 3 4 S 6 7 led to the development ofa product in the shortest amormt of development time -.....m---...... I 2 3 4 5 6 7 provided superior value to the customer I 2 3 4 S 6 7 provided the lowest possible cost of ownership am.-...a-..... I 2 3 4 5 6 7 provided superior quality I 2 3 4 S 6 7 provided a competitive advantage for the firm ..........._..-. I 2 3 4 S 6 7 provided the firm adeqmte returns and growth I 2 3 4 5 6 7 22. How many core team members were involved, from the beginning to the completion, on this new product development team? employees 23. I-iowmanytotalpaoplewereinvolvadJromthebegrnnmg’ ’ tothecoutpletion.’ onthisnewproductdevelopmentteam? employees 24. Indicate which departments were represented on this new product development team! (Check all that apply) U Manufacturing [3 Suppliers C] Product Development Cl Quality C] Customers D Other (Identify Below) C] Purchasing U Marketing D C] Customer Service [:1 Accounting [:1 C] Finance U Process Development [3 25. ComparedwprwbruprodmtdwdopmauprojmbddeummagmndeaMsmpe,mdiamtlubvddm utilizationonthisprojact. Significantly my Less Same Greater lob-related information I 2 3 4 S 6 7 Tools I 2 3 4 S 6 7 Mate-ials and suppli- I 2 3 4 5 6 7 Administrative styport/sanicss I 2 3 4 5 6 7 Manny support 1 2 3 4 s 6 7 Fldlitiefl I 2 3 4 S 6 7 Equipment 1 2 3 4 s 6 7 Engineering suppa't (person hours) I 2 3 4 S 6 7 Total person hours I 2 3 4 S 6 7 Development tim- I 2 3 4 5 6 7 liduation and training I 2 3 4 5 6 7 Upper managamant support I 2 3 4 5 6 7 224 26. Indicate the adequacy of the following internal resources during the project. Significantly Sufficiently More Than Inadequate Adequate Adequate loborelated information I 2 3 4 5 6 7 Tools I 2 3 4 5 6 7 Materials and supplies I 2 3 4 S 6 7 Administrative support/ services I 2 3 4 S 6 7 Budgetary support I 2 3 4 5 6 7 Facilities I 2 3 4 5 6 7 Equipment 1 2 3 4 5 6 7 Engineering support (person hours) 1 2 3 4 5 6 7 Total person hours I 2 3 4 5 6 7 Development time I 2 3 4 5 6 7 Education and training I 2 3 4 5 6 7 Uppa management support I 2 3 4 5 6 7 27. Were suppliers‘ representatives members of the new product development team? Yes or N o If NOgotoQuostion number”. 28. Howmanydr'fierenf supplies waserepresented onthenewproductdevelopment team? Suppliers 29. Muttypeofsupplierts)wereonthetaam:(0sscltallthatapply) Cl Raw Materials D Capital Equipment U Component/Part E] Service, Type D Subassembly/Assembly [3 Finished Goods/GEM El). Whatwastheprlnraryrusonthesuppws)wasselected?(5electoae) El Technology Cl Proudmity D Other Cl Dollarvalueofpurchasedpart Cl lengthofexistingrelationship U Typeofproduct/serviceprovided C] Expertise 31. Howmanytotalsupplierpersonndwsreinwivedintheproject? 32. mmmwdmpphmmmmnuemimmmwpm C] Sales [:1 Management U Engineering CI Manufacturing [3 Quality [J one, 33. Indicate the supplier’s involvement at mch stage. Supplies Involvement Not Involved Highly Involved Product Conception I 2 3 4 S 6 7 Product Ddgn I 2 3 4 S 6 7 Prototype 1 2 3 4 S 6 7 Tooling and Facilitim I 2 3 4 5 6 7 Ramp-up 1 2 3 4 5 6 7 Pull«Scale Production 1 2 3 4 5 6 7 225 Flying Driving Walking Distance Distance Distance . On average, the distance between your site and the supplier’s location. I 2 3 4 5 6 7 0% 50% 1007. . How complete was the project when the supplier(s) began to make comments on the product design?..-................... 1 2 3 4 5 6 7 . How complete was the project when the supplier(s) started making commitments to purchase tools and equipment? I 2 3 4 S 6 7 . Length of time the supplierts) were involved as a percentage of the total time (concept-to-market). ...—......m... I 2 3 4 S 6 7 Number of hours committed by the supplier(s) as a percentage of total development hours on the project. _ ........ I 2 3 4 S 6 7 . Degree of commitment made by your firm to the suppliens) for future business. 1 2 3 4 5 6 7 . Attendance rate by the supplier(s) as a percentage of the total meetings involved? I 2 3 4 S 6 7 . The percentage of business your account represents of the supplier’s total businas 1 2 3 4 5 6 7 . Indicate the level of supplier's: Low High creativity I 2 3 4 S 6 7 autonomous contributions 1 2 3 4 5 6 7 ideas generated by the supplier I 2 3 4 5 6 7 ideas generated which were implemented .....m.............................. I 2 3 4 5 6 7 expertise in process technology I 2 3 4 5 6 7 expertise in product technology 1 2 3 4 5 6 7 . Average length of time you have been doing business with the supplier“). years . How much of each of the following types of support did the suppliefls) provide in order to improve the way that the supplier and manufacturer work together? No Average High Investment Investment Investment Investment in: Training I 2 3 4 5 6 7 Research and Development 1 2 3 4 S 6 7 Tooling/Equipment I 2 3 4 5 6 7 Technology (EDI. CAD, CMI, IIT, etc.) I 2 3 4 5 6 7 Structural] Reorganization I 2 3 4 5 6 7 Material/Prototype I 2 3 4 S 6 7 Labor Horus 1 2 3 4 5 6 7 Co-Ioation of supplier I 2 3 4 S 6 7 . I-Iowfrequentlydid thesupplierinitiatethefollowing methodsofcommunicationwiththemufactmer? V Never Sometimes Neatly Written Letter/Memos 1 2 3 4 5 6 7 Electronic Transfer 1 2 3 4 5 6 7 Telephone 1 2 3 4 5 6 7 Teleconferencing/Videoconferencing 1 2 3 4 5 6 7 Face-to-face/ Direct meetings 1 2 3 4 S 6 7 On-site supplie- wave/Coleman I 2 3 4 5 6 7 226 46. When evaluating supplier(s)' performance, how much weight is placed on the following areas? 51. . 1hetypeofsupportgivenbythesupplia