Study of Buyer-supplier Relationships

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TOWARD SUPPLIER PORTFOLIO MANAGEMENT THEORY:

AN EMPIRICAL STUDY OF BUYER-SUPPLIER RELATIONSHIPS IN

THE U.S. AUTOMOTIVE COMPONENTS INDUSTRY

by

Scott Christopher EllisJanuary 26, 2007

A dissertation submitted to the

Faculty of the Graduate School ofThe State University of New York at Buffalo

In partial fulfillment of the requirementsFor the degree of

Doctor of Philosophy

Department of Operations Management and Strategy


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UMI Number: 3261955

3261955

2007

Copyright 2007 by

Ellis, Scott Christopher

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Copyright

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Copyright by

Scott Christopher Ellis

2007


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To my three girls Amie, Madison, and Caitlinn.

Your love is my greatest treasure.


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iv

ACKNOWLEDGMENTS

Throughout my doctoral program, I have benefitted from the guidance and support of faculty,

friends, and family. I would like to extend my sincere thanks to those who have helped me

develop both academically and personally throughout my doctoral studies.

I would like to acknowledge the thoughtful guidance and mentorship that Dr. Nallan

Suresh has provided me. In preparation for candidacy, Dr. Suresh provided academic

direction and personal insights that facilitated my growth and maturation. As chair of my

dissertation committee, Dr. Suresh provided tremendous support that facilitated the timely

completion of this dissertation. Additionally, I would like to acknowledge my dissertation

committee members Dr. Rajiv Kishore and Dr. Tony Tong for their comments, insights,

and input. Clearly, this dissertation and my personal development have benefitted greatly

from our interaction thank you!

I would like to thank the faculty, staff, and doctoral students of the School of

Management. In particular, I would like to acknowledge Dr. Larry Sanders, Dr. Raj Sharman,

Dr. Natalie Simpson, Dr. John Stephan (Florida Atlantic University), and Dr. Charles Wang

for their supportive role in my scholarly development Judy Bain, Valerie Limpert, and Trish

Wisner for their administrative support and Eugene Colucci for his technical guidance.

Throughout the doctoral program, I enjoyed my interactions and collaborations with several

colleagues, especially Ebe Randeree, Parag Laddha, Jim Hamister, and Mike Braunscheidel. I

am grateful to have completed my doctoral candidacy with such a motivated, knowledgeable,

and collegial group. Additionally, I owe a debt of gratitude to Dr. Joseph Alutto (The Ohio

State University) the financial support that I received through his named fellowship provided

the opportunity for me to engage in doctoral studies.


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This dissertation would not have been possible without the help and support of an

unnamed consultancy, the automotive components manufacturer that serves as the focus of

this study, and several automotive suppliers. Managers and executives from several firms

offered their time and personal insights in support of this research project. The knowledge

gained from purchasing, marketing, and engineering managers in these firms contributed

significantly to the conceptualization and successful completion of this research study. As

such, I am very grateful for the involvement and support of managers and executives within

these firms.

Finally, I would like to express my sincere gratitude to my friends and family for their

unending support and encouragement. In particular, I would like to reiterate my deepest

thanks to my wife, Amie Lynne, and daughters, Madison Leigh and Caitlinn Rose. I will

forever be grateful for your sacrifice, love, and support. I am so very thankful that I share my

life with three wonderful, special girls!


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TABLE OF CONTENTS

ACKNOWLEDGMENTS.................................................................................................... iv

TABLE OF CONTENTS..................................................................................................... vi

LIST OF TABLES............................................................................................................... ix

LIST OF FIGURES ........................................................................................................... xiii

ABSTRACT ...................................................................................................................... xiv

1. INTRODUCTION .......................................................................................................... 1

1.1 Conceptual Research Model ................................................................................... 7

1.2 Major Objectives of This Study .............................................................................. 9

1.3 Organization of the Dissertation ........................................................................... 11

2. LITERATURE REVIEW.............................................................................................. 13

2.1 Buyer-Supplier Relationship Theory..................................................................... 14

2.1.1 Exchange Theory ...................................................................................... 14

2.1.2 Relational Closeness................................................................................. 17

2.1.3 Supplier Portfolio Management Theory .................................................... 27

2.2 Supply Management ............................................................................................. 40

2.2.1 Supplier Selection ..................................................................................... 40

2.2.2 Negotiation............................................................................................... 42

2.2.3 Cost Management ..................................................................................... 46

2.2.4 Supplier Development............................................................................... 51

2.2.5 Inter-firm Communication ........................................................................ 58

2.3 Inter-firm Business Process Integration................................................................. 59

2.3.1 Supplier Suggestion Participation............................................................. 59

2.3.2 Logistics Integration................................................................................. 612.3.3 Supplier New Product Involvement ........................................................... 69

2.4 Organizational Competence .................................................................................. 76

2.4.1 Buyer Competence .................................................................................... 76

2.4.2 Supplier Competence ................................................................................ 78

3. MODEL DEVELOPMENT .......................................................................................... 80

3.1 Buyer-Supplier Relationship Closeness Factor Model........................................... 81

3.1.1 Trust ......................................................................................................... 81

3.1.2 Commitment ............................................................................................. 83

3.1.3 Shared Benefit .......................................................................................... 84

3.1.4 Flexibility ................................................................................................. 843.1.5 Information Sharing.................................................................................. 85

3.1.6 Solidarity.................................................................................................. 86

3.1.7 Multi-Dimensional Model of Buyer-Supplier Relationship Closeness ........ 87


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3.2 Buyer-Supplier Relationship Closeness Causal Model .......................................... 89

3.2.1 Integrative Activities................................................................................. 92

3.2.2 Distributive Activities................................................................................ 97

3.2.3 Strategic Importance of Relationship ...................................................... 100

3.3 Characterizing the Supplier Relationship Portfolio.............................................. 104

3.4 Analysis of Supply Management and Operational Benefits Across SupplierRelationship Clusters.......................................................................................... 110

3.4.1 Supply Management Practices ................................................................ 110

3.4.2 Operational Benefits............................................................................... 116

4. RESEARCH METHODOLOGY ................................................................................ 123

4.1 Instrument Development..................................................................................... 123

4.2 Construct Measures ............................................................................................ 124

4.2.1 Relationship Closeness Measures ........................................................... 125

4.2.2 Relationship Closeness Antecedent Measures ......................................... 126

4.2.3 Supply Management Measures................................................................ 127

4.2.4 Operational Benefits Measures ............................................................... 1294.3 Sample Frame..................................................................................................... 131

4.4 Survey Administration........................................................................................ 132

4.5 Statistical Analysis ............................................................................................. 133

4.5.1 Structural Equation Modeling................................................................. 133

4.5.2 Cluster Analysis...................................................................................... 138

5. MEASUREMENT PROCEDURES AND RESULTS ................................................. 141

5.1 Examination of Data........................................................................................... 143

5.1.1 Response Rate......................................................................................... 143

5.1.2 Non-response Bias .................................................................................. 144

5.1.3 Univariate Normality.............................................................................. 147

5.2 Sample Demographics........................................................................................ 149

5.3 Buyer-Supplier Relationship Closeness Construct Validation .......................... 154

5.3.1 Unidimensionality................................................................................... 155

5.3.2 Reliability ............................................................................................... 160

5.3.3 Convergent and Discriminant Validity .................................................... 163

5.3.4 Second-Order Construct ......................................................................... 178

5.3.5 First-Order Construct ............................................................................. 183

5.4 Buyer-Supplier Relationship Goodness Construct Validity .............................. 185


5.4.2 Reliability ............................................................................................... 186

5.4.3 Convergent and Discriminant Validity .................................................... 1875.5 Antecedents to Relationship Closeness Construct Validity............................... 190


5.5.1 Reliability ............................................................................................... 193



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5.6 Supply Management Practices Construct Validity............................................ 208


5.6.2 Reliability ............................................................................................... 210


5.7 Operational Benefits Construct Validity........................................................... 215

5.7.1 Unidimensionality................................................................................... 2155.7.2 Reliability ............................................................................................... 217


6. TESTS OF HYPOTHESES......................................................................................... 223

6.1 Buyer-Supplier Relationship Closeness Factor Model......................................... 223

6.2 Buyer-Supplier Relationship Closeness Causal Model ........................................ 227

6.3 Characterizing the Relationship Portfolio............................................................ 234

6.4 Analysis of Supply Management Practices Across Supplier RelationshipClusters .............................................................................................................. 255

6.5 Analysis of Operational Benefits Across Supplier Relationship Clusters............. 259

7. DISCUSSION OF RESULTS ..................................................................................... 2647.1 Buyer-Supplier Relationship Closeness Second-Order Factor Model .................. 265

7.2 Causal Model of Buyer-Supplier Relationship Closeness.................................... 268

7.3 Characterizing the Supplier Relationship Portfolio.............................................. 276

8. CONTRIBUTIONS, LIMITATIONS & FUTURE RESEARCH................................. 285

8.1 Contributions...................................................................................................... 285

8.2 Limitations ......................................................................................................... 291

8.3 Future Research.................................................................................................. 294

APPENDIX A .................................................................................................................. 296

APPENDIX B................................................................................................................... 300

APPENDIX C................................................................................................................... 303REFERENCES................................................................................................................. 306


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LIST OF TABLES

Table 2.1 Definitions of close buyer-supplier relationships ...... 19

Table 2.2 Key attributes of close buyer-supplier relationships ......20

Table 2.3 Supplier segmentation criteria ........... 31Table 2.4 Factors affecting purchase importance .. 34

Table 2.5 Factors affecting supply complexity ......34

Table 5.1 Mean comparisons of early versus late responders ..145

Table 5.2 Mean comparisons of non-participants versus participants .....147

Table 5.3 Reported total annual sales ...150

Table 5.4 Reported annual automotive sales ........150

Table 5.5 Reported annual sales to the automotive components manufacturer ...151

Table 5.6 Reported R&D expense as a percent of annual automotive sales ........152

Table 5.7 Reported percent of annual automotive sales to automotive components

manufacturer 152Table 5.8 Reported length of supply relationship ........ 153

Table 5.9 Supplier headquarters locations by region ...154

Table 5.10 Commodity groups ...154

Table 5.11 Standardized path loadings for information sharing ........157

Table 5.12 Standardized path loadings for trust .........158

Table 5.13 Standardized path loadings for solidarity .........158

Table 5.14 Standardized path loadings for commitment ... 159

Table 5.15 Factor loadings for shared benefit 160

Table 5.16 Reliability statistics for information sharing ........161

Table 5.17 Reliability statistics for trust ........ 161

Table 5.18 Reliability statistics for solidarity ........ 162Table 5.19 Reliability statistics for commitment ...162

Table 5.20 Reliability statistics for shared benefit .162

Table 5.21 Modification indices for information sharing and trust ... 166

Table 5.22 Modification indices for information sharing and solidarity ... 167

Table 5.23 Modification indices for information sharing and commitment ..168

Table 5.24 Modification indices for trust and solidarity ........169

Table 5.25 Modification indices for trust and commitment ...170

Table 5.26 Modification indices for solidarity and commitment ...171

Table 5.27 Modification indices for full measurement model .......175

Table 5.28 First-order factor correlations for full measurement model .....176Table 5.29 First-order factor discriminant validity analysis ..176

Table 5.30 First-order factor correlations for revised full measurement model ........ 177

Table 5.31 Descriptive statistics for items within the full measurement model ........ 177

Table 5.32 Relationship closeness second-order factor model path coefficients ...182

Table 5.33 Measures of model fit: alternate factor structures ........182

Table 5.34 Standardized loadings for relationship closeness .........184


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Table 5.35 Reliability statistics for relationship closeness ........ 185

Table 5.36 Standardized loadings for relationship goodness .....186

Table 5.37 Reliability statistics for relationship goodness .........187

Table 5.38 Modification indices for relationship closeness and relationship goodness .189

Table 5.39 Correlation statistics for relationship closeness and relationship goodness .189

Table 5.40 Discriminant validity analysis for relationship closeness and relationshipgoodness ...190

Table 5.41 Standardized loadings for distributive activity ........ 192

Table 5.42 Standardized loadings for integrative activity ..... 193

Table 5.43 Reliability statistics for distributive activity ........194

Table 5.44 Reliability statistics for integrative activity .....194

Table 5.45 Modification indices for distributive and integrative activities ... 197

Table 5.46 Modification indices for distributive activity and relationship closeness 199

Table 5.47 Modification indices for relationship closeness and integrative activity .....201

Table 5.48 Modification indices for full measurement model ...204

Table 5.49 First-order factor correlations for full measurement model .........205Table 5.50 First-order factor discriminant validity analysis ..205

Table 5.51 Descriptive statistics for items within the full measurement model ........ 206

Table 5.52 Factor loadings for comprehensiveness of supplier evaluation ... 209

Table 5.53 Factor loadings for competitive pressure .....209

Table 5.54 Factor loadings for direct involvement ........ 210

Table 5.55 Reliability statistics for comprehensiveness of supplier evaluation .... 211

Table 5.56 Reliability statistics for competitive pressure ..211

Table 5.57 Reliability statistics for direct involvement ..... 212

Table 5.58 Supply management practices rotated component matrix ........ 214

Table 5.59 Supply management practices inter-factor correlations ........214

Table 5.60 Factor loadings for barriers to technology sharing lack of interest ...216

Table 5.61 Factor loadings for barriers to technology sharing fear of informationmisappropriation .. 216

Table 5.62 Factor loadings for cost improvement opportunities ... 216

Table 5.63 Factor loadings for inter-firm quality management ..... 217

Table 5.64 Reliability statistics for barriers to technology sharing lack of interest ....218

Table 5.65 Reliability statistics for barriers to technology sharing fear of informationmisappropriation .. 218

Table 5.66 Reliability statistics for cost improvement opportunities ........ 219

Table 5.67 Reliability statistics for inter-firm quality management ..219

Table 5.68 Operational benefits rotated components matrix .. 221Table 5.69 Operational benefits inter-factor correlations ... 222

Table 6.1 Relationship closeness causal model fit statistics .....231

Table 6.2 Relationship closeness causal model structural path coefficients .....231

Table 6.3 Relationship closeness causal model explained variance ..... 232

Table 6.4 Relationship closeness causal model indicator path coefficients ......232

Table 6.5 Results of hypotheses three through six ...234


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Table 6.6 Correlations (lower triangle) and standard errors (upper triangle) forclassification criteria 235

Table 6.7 Agglomeration coefficients ..239

Table 6.8 Cross-validation of five-cluster solution split sample classification

analysis 242

Table 6.9 Cross-validation of five-cluster solution split sample descriptive analysis .. 243Table 6.10 Means of classification variables for five-cluster solution ...245

Table 6.11 Tests of mean differences of supply management practices for five-clustersolution .........247

Table 6.12 Cross-validation of three-cluster solution split sample classification

analysis .249

Table 6.13 Cross-validation of three-cluster solution split sample descriptive

analysis .250

Table 6.14 Means of classification variables for three-cluster solution .........251

Table 6.15 Tests of mean differences of supply management practices for three-clustersolution .........253

Table 6.16 Demographics for three-cluster solution ..254

Table 6.17 Tests of mean differences of operational benefits for three-cluster solution ...263

Table 7.1 Re-specified relationship closeness causal model model fit statistics ...271

Table 7.2 Re-specified relationship closeness causal model structural path

coefficients .......................................................................................................271

Table 7.3 Re-specified relationship closeness causal model explained variance ..... 272

Table 7.4 Re-specified relationship closeness causal model indicator path

coefficients ...272

Table 8.1 Organization-specific sampling approaches 293

Table A.1 Factor loadings for information sharing ...........................296

Table A.2 Factor loadings for trust ........................... 296Table A.3 Factor loadings for solidarity ...........................296

Table A.4 Factor loadings for commitment ......................297

Table A.5 Factor loadings for shared benefit 297

Table A.6 Factor loadings for relationship closeness ... 297

Table A.7 Factor loadings for relationship goodness ... 298

Table A.8 Factor loadings for distributive activity298

Table A.9 Factor loadings for integrative activity .... 299

Table B.1 Relationship closeness causal model with revised distributive activity constructfit statistics . 300

Table B.2 Relationship closeness causal model with revised distributive activity construct structural path coefficients for revised model ...300

Table B.3 Relationship closeness causal model with revised distributive activity construct explained variance for revised model ... 301

Table B.4 Relationship closeness causal model with revised distributive activity construct indicator path coefficients for revised model ... 301

Table C.1 Respecified relationship closeness causal model with revised distributiveactivity construct model fit statistics 303


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LIST OF FIGURES

Figure 1.1 Conceptual model of relationship management ............9

Figure 2.1 Kraljics purchasing sophistication matrix . 32

Figure 3.1 Multi-dimensional model of buyer-supplier relationship closeness ... 89Figure 3.2 Causal model of buyer-supplier relationship closeness ..92

Figure 5.1 Measurement model for information sharing 157

Figure 5.2 Measurement model for trust ........157

Figure 5.3 Measurement model for solidarity .,.. 158

Figure 5.4 Measurement model for commitment ...159

Figure 5.5 Measurement model for shared benefit .........159

Figure 5.6 Measurement model for information sharing and trust .....165

Figure 5.7 Measurement model for information sharing and solidarity .....166

Figure 5.8 Measurement model for information sharing and commitment ........167

Figure 5.9 Measurement model for trust and solidarity ......... 168Figure 5.10 Measurement model for trust and commitment ........ 169

Figure 5.11 Measurement model for solidarity and commitment ........170

Figure 5.12 Full measurement model for first-order factors ........ 174

Figure 5.13 Relationship closeness second-order factor model ...181

Figure 5.14 Measurement model for relationship closeness ........ 184

Figure 5.15 Measurement model for relationship goodness ........ 186

Figure 5.16 Measurement model for relationship closeness and relationship goodness ..188

Figure 5.17 Measurement model for distributive activity 192

Figure 5.18 Measurement model for integrative activity . 192

Figure 5.19 Measurement model for distributive and integrative activities .196

Figure 5.20 Measurement model for distributive activity and relationship closeness . 198

Figure 5.21 Measurement model for relationship closeness and integrative activity ...200

Figure 5.22 Full measurement model for all latent constructs . 203

Figure 6.1 Relationship closeness path diagram ........ 233

Figure 6.2 Step-wise approach to cluster analysis ......237

Figure 6.3 Plot of change in agglomeration coefficient versus number of clusters ... 239

Figure 7.1 Re-specified causal model of relationship closeness ....273

Figure B.1 Relationship closeness path diagram with revised distributive activity

construct 302

Figure C.1 Respecified relationship closeness path diagram with revised distributive

activity construct ...305


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ABSTRACT

This dissertation reports the results of an empirical research study that seeks to develop new

insights into supplier portfolio management. Positioned as a logical extension of transaction

cost economic and relational contracting theory, supplier portfolio management theory

advocates the differential management of groups or segments of supply relationships based on

the importance of each supply segment. In accordance with supplier portfolio management

theory, more important supply relationships may warrant closer, partner-style supply

relationships, which may be likened to hybrid forms of governance espoused by relational

contracting theory. Conversely, traditional, arms-length relationships, as described within

transaction cost economics literature, may be well-suited for suppliers of lesser importance.

Central to the notion of supplier portfolio management theory is that buying firms should

allocate limited internal resources to those sets of supplier relationships that generate greatest

value for the buying firm.

This research adds to the developing body of supplier portfolio management literature

in several ways. First, this research aims to theoretically ground supplier portfolio

management theory within the logical frameworks of transaction cost economic and relational

contracting theories. Previous research in the area of supplier portfolio management is

primarily practitioner driven and largely maintains a phenomenological rather than theoretical

orientation. Second, this study provides an initial large-scale empirical test of the assertions

of supplier portfolio management theory by examining the buyer-supplier relationships that

exist between a first-tier global automotive components manufacturer and its global direct

materials supply base. In particular, this research seeks to empirically validate buyer-supplier

closeness as a second-order latent construct, examine the extent to which measures of


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relationship closeness may be used to identify clusters or sets of supplier relationships within

the focal buyers supply base, assess the differences in relationship closeness across sets of

supplier relationships, investigate the factors that influence supplier relationship closeness,

and explore the benefits that are derived from close supplier relationships.

Using survey response data from 425 buyer-supplier relationships between a focal

automotive components manufacturer and its global direct materials supply base, this study

contributes to the growing body of supplier portfolio management literature by testing three

models and sixteen hypotheses that center on the investigation of the following research

questions:

1. To what extent do buying firms manage clusters or sets of supply

relationships within their direct materials supply base?

2. How do suppliers perceptions of relationship closeness vary across a

single buyers supply base?

3. How do integrative and distributive supply management practices

differentially affect suppliers perceptions of relationship closeness?

4. How do suppliers perceptions of relationship closeness influence the

operational benefits derived from a buyer-supplier relationship?

In the first set of empirical analyses, a progression of confirmatory factor analyses was

used to test a second-order factor model of buyer-supplier relationship closeness. In

particular, this research advanced a second-order factor model of buyer-supplier relationship

closeness that consists of six first-order factors: trust, commitment, information sharing,

solidarity, flexibility, and shared benefit. Using a comprehensive validation process,


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empirical results indicate that relationship closeness is well-represented by a second-order

factor model that consists of four first-order factors: trust, information sharing, solidarity, and

shared benefit.

In a second set of analyses, the causal relationships amongst strategic importance of

the relationship, integrative supply management activity, distributive supply management

activity, and relationship closeness were tested. Results from path analysis support the

hypothesized positive relationships between strategic importance of the relationship and

integrative activity and between integrative activity and relationship closeness. However, the

anticipated negative relationships between strategic importance of the relationship and

distributive activity and between distributive activity and relationship closeness were not

empirically supported. Results from the structural model indicate that there is no relationship

between buying firms use of distributive activity and relationship closeness. Further,

contrary to expectations, the path coefficient between strategic importance of the relationship

and distributive activity was positive and significant.

Drawing support from relational contracting theory, the causal model of relationship

closeness was re-specified to include a causal path from integrative activity to distributive

activity. Results from model estimation support the notion that buyers use of integrative and

distributive supply management activities are positively related. Further, results from the re-

specified model indicate that integrative activity fully mediates the positive relationship

initially found between strategic importance of the relationship and distributive activity.

In the final set of analyses, the nature and distribution of supplier relationships within

the focal automotive components manufacturers supplier relationship portfolio were

explored. Using a split sample approach to cluster analysis and the six dimensions of the


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CHAPTER 1

INTRODUCTION

The field of supply management has been the focus of considerable interest in recent years,

due to several major developments. First, purchasing practices are gaining increased attention

as firms continue to rationalize their business portfolio and focus on core businesses, products

and processes, and outsource others. Second, direct materials costs have amounted to as high

as 60-80% of an end-products final cost. Third, intense competition and globalization are

affecting outsourcing practices, as buying firms increasingly rely on their global supply base

to deliver appealing, high-quality products in a timely, cost effective manner (Kraljic, 1983

Krause and Ellram, 1997a Stalk and Hout, 1990). Fourth, firms are employing just-in-time

(JIT) purchasing strategies in order to reduce inventory costs, shorten lead-times, and improve

productivity (Dong et al., 2001). Under the JIT approach, on-time delivery and supplier

quality are critical success factors as traditional buffer inventories are eliminated (De Toni

and Nassimbeni, 2000). As such, buying firms pursuing a JIT approach have much to gain by

creating and maintaining a network of competent suppliers who can provide a synchronized

flow of high quality goods and customized services (De Toni and Nassimbeni, 2000 Wasti

and Liker, 1997).

In addition to the above, firms are actively reducing the size of their supply base and

are increasingly willing to take direct action to help the remaining suppliers (Trent and

Monczka, 1998). As buying firms continue to consolidate purchasing volumes, there is

increased incentive for purchasers to develop a closer relationship with their remaining

suppliers, upon whom the buying firm has an increased reliance (Choi and Hartley, 1996).

Supply management activities and buyer-supplier business process integration represent


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mechanisms through which buyer-supplier partnerships may be strengthened (Bensaou and

Anderson, 1999 Stump, Athaide, and Joshi, 2002 Trent and Monczka, 1998 Wasti and

Liker, 1997).

Transaction cost economics forms one of the earliest theories advanced in this context.

The primary thrust of transaction cost economics is that markets and hierarchies serve as

alternate governance mechanisms for facilitating efficient exchange (Coase, 1937). Central to

transaction cost analysis is the premise that exchange efficiency is optimized when

governance mechanisms are properly aligned with exchange characteristics (Williamson,

1991a, 1991b). While arms-length market-based relationships facilitate the efficient

exchange of commodity-like goods, this mode of governance may not suffice when

transactions require high degrees of buyer-supplier coordination or when repeated

transactions are executed within an uncertain environment (Williamson, 1991a). Traditional

transaction cost economic theory suggests that higher levels of coordination and mutual

adaptation may be more efficiently accomplished within a hierarchical mode of governance

in this approach, transactions are internalized within a single administrative bureaucracy and

managerial fiat, rather than contractual stipulations, serve to coordinate exchange.

A contemporary view of transaction cost analysis recognizes the hybrid form of

organization as a special mode of governance that incorporates mechanisms of both markets

and hierarchies (Dyer, 1996a Liker, Kamath, Wasti, and Nagamachi, 1996 Powell, 1987

Wasti and Liker, 1997 Williamson, 1991a). In accordance with relational contracting theory,

high levels of coordination and adaptation may be efficiently achieved when market-based

transactions are executed within buyer-supplier relationships characterized by high levels of

bilateral relationship-specific investments (Dyer, 1996c Williamson, 1991a). Thus, hybrid


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governance mechanisms integrate the high-powered incentives of markets and the enhanced

adaptation, coordination, and safeguarding capabilities associated with hierarchies while

simultaneously avoiding the high transaction costs associated with bureaucratic control

(Williamson, 1991a).

Several studies have examined investment in relationship-specific assets within the

context of relational contracting theory. In a study contrasting the strategic sourcing practices

of U.S., Japanese and Korean automakers, Dyer et al. (1998) noted that Japanese partner-style

relationships included significantly higher levels of physical asset specificity and human

resource specificity as compared to Japanese arms-length relationships. Comparatively, U.S.

and Korean automakers achieved little differentiation, suggesting that these OEMs manage

partner-style relationships in a similar manner as traditional arms-length relationships. In a

cross-industry study of supplier development adoption, Krause (1999) found that the adoption

of transaction-specific supplier development activities is directly related to inter-firm

communication efforts and buyers perception of supplier commitment, and indirectly related

to the buying firms perspective toward suppliers. In a landmark study of U.S. and Japanese

automakers, Clark (1989) concluded that a significant portion of Japanese automakers

advantage in new product development cost and lead-time is attributable to the extent to

which Japanese automakers involve suppliers in the development of customized automotive

components. Further, Clark (1989) suggests that these advantages are largely attributable to

the unique relational attributes that characterize Japanese buyer-supplier relationships.

Consistent with relational contracting theory, these aforementioned studies highlight

the importance of interdependence and mutual commitment in the coordination of

collaborative market-based transactions. A common theme amongst these studies is that


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This research advances the study of the theoretical linkages between supply

management practices, buyer-supplier relationship closeness, and the operational benefits

derived from the management of close buyer-supplier relationships using an empirical

approach suggested by supplier portfolio management theory. This study builds on prior

research on buyer-supplier relationships (Anderson and Weitz, 1992 Cannon and Perreault,

1999 Goffin et al., 2006 Mohr and Spekman, 1994), supply management (Kannan and Tan,

2002 Krause, 1999 Perdue and Summers, 1991 Smeltzer, Manship, and Rossetti, 2003

Vonderembse and Tracey, 1999 Wen-li, Humphreys, Chan, and Kumaraswamy, 2003

Zsidisin and Ellram, 2001 Zsidisin, Ellram, and Ogden, 2003), and inter-firm business

process integration (Dong et al., 2001 Li, Rao, Ragu-Nathan, and Ragu-Nathan, 2005

Petersen et al., 2005) by conducting a comprehensive investigation of the antecedents and

consequences of buyer-supplier relationship closeness across a single buying firms supply

base. In particular, this study investigates the relationships between: (1) several supply

management practices, including supplier selection, supplier evaluation, and supplier

development, (2) buyer-supplier relationship closeness, measured in terms of trust,

commitment, flexibility, shared benefit, solidarity, and information exchange, and (3)

operational benefits, such as cost reduction opportunities, ease of technology sharing,

effectiveness inter-firm quality management efforts, supplier involvement in new product

development, and suppliers use of collaborative relationship management practices within

their supply base.

This study of buyer-supplier relationships uses survey data obtained from suppliers to

divisions of a global automotive components manufacturer to test and extend the theoretical

assertions of supplier portfolio management theory. Using supplier response data to


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2006 Griffith, Harvey, and Lusch, 2006 Heide and John, 1992 Maloni and Benton, 2000

Prahinski and Benton, 2004), this study models buyer-supplier relationship closeness as a

multi-dimensional construct. While past research identifies several potential dimensions of

buyer-supplier closeness, this study proposes that relationship closeness may be defined in

terms of trust, commitment, flexibility, solidarity, information sharing, and shared benefit.

Third, in accordance with supplier portfolio management theory, closer buyer-supplier

relationships are hypothesized to yield greater value in the form of operational benefits to

both the buying and supplying firms. As shown in the conceptual model, this research posits

that closer buyer-supplier relationships lead to several operational benefits, including greater

opportunities for cost savings, reduced barriers to product technology sharing, more effective

inter-firm quality management, earlier supplier involvement in buyers new product

development process, and improved supply management across the suppliers supply bases.

By examining a broad set of intermediate operational benefits, this study may provide new

insights into the value derived from the management of close supply relationships.

Fourth, the conceptual model suggests that supply management efforts have a direct

impact, in addition to an indirect effect, on the operational benefits derived from a buyer-

supplier relationship. Past studies of buyer communication strategy (Prahinski and Benton,

2004) and supplier development (Krause et al., 2000) suggest that supply management efforts

directly influence performance gains. Thus, collaborative activities, such as direct supplier

development may yield operational benefits, even within the context of a traditional, arms-

length buyer-supplier relationship.


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Second, this study examines the extent to which a single buyer manages a portfolio of

supplier relationships across its supply base. Using cluster analysis, sets of supply

relationships, which vary in terms of relationship closeness, are identified within the buyers

supply base. To complement past research, this study assesses the number of supplier clusters

within the supply base, the extent of differences in buyer-supplier relationship closeness

across clusters, and the spatial distribution of buyer-supplier relationship closeness across

clusters (Webster, 1992).

Third, this study investigates the extent to which a buying firm pursues particular

supply management practices in order to achieve desired levels of supplier relationship

closeness. This study advances the notion that buying firms may adopt integrative supply

management practices, distributive supply management practices, or a complementary mix of

integrative and distributive management practices in order to achieve desired levels of buyer-

supplier relationship closeness. Using past literature as a guide, this study identifies

integrative supply management activities, which are collaborative in nature and represent a

win-win approach to supply management, and distributive supply management activities that

are market-based, characterizing a zero-sum (win-lose) perspective (Krause, Scannell, and

Calantone, 2000 Perdue and Summers, 1991). Specifically, this study examines the extent to

which the use of integrative and distributive supply management practices differ across sets of

supply relationships and their differential effect on buyer-supplier relationship closeness.

Fourth, this study assesses a set of intermediary operational benefits that may be

derived from close inter-firm relationships. Several studies have highlighted the beneficial

outcomes of closer buyer-supplier relationships, including improved supplier performance

(Cusumano and Takeishi, 1991 Humphreys, Li, and Chan, 2004 Krause, 1997 Krause and


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Ellram, 1997b Monczka, Trent, and Callahan, 1993 Watts and Hahn, 1993), and improved

buying firm performance (Curkovic, Vickery, and Droge, 2000 De Toni and Nassimbeni,

2000 Humphreys et al., 2004 Krause, 1997 Krause et al., 2000). This study aims to provide

complementary evidence of the value of close supply relationships by examining a unique and

comprehensive set of intermediary operational benefits, including improved cost management

opportunities, enhanced technology sharing between firms, earlier supplier involvement in the

buyers new product development process, improved effectiveness of buyers quality

management efforts, and improved management of indirect (third-tier) suppliers. In

particular, this study examines how these operational benefits differ across supplier clusters

that compose a single buying firms portfolio of supply relationships.

The aforementioned objectives motivate the primary research questions listed below:

1. To what extent do buying firms manage clusters or sets of supply

relationships within their direct materials supply base?

2. How do suppliers perceptions of relationship closeness vary across a

single buyers supply base?

3. How do integrative and distributive supply management practices

differentially affect suppliers perceptions of relationship closeness?

4. How do suppliers perceptions of relationship closeness influence the

operational benefits derived from a buyer-supplier relationship?

1.3 Organization of the Dissertation

This dissertation presents the development and empirical assessment of sixteen hypotheses

that seek to advance supplier portfolio management theory. The presentation of this empirical

research study is segmented into eight chapters. Chapter 2 provides a comprehensive


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literature review within this chapter, supplier portfolio management theory is positioned as a

logical extension of relational exchange theory. Additionally, an array of supply management

practices and inter-firm business processes are discussed. The third chapter presents the

development of theoretical models and hypotheses that serve as the basis for empirical

investigation. In particular, the sixteen hypotheses developed within this study are based

upon three complementary models: (1) a second-order factor model of buyer-supplier

relationship closeness, (2) a causal model of buyer-supplier relationship closeness, and (3) a

supplier relationship portfolio model. Chapter 4 discusses methodological issues related to

this study. As such, the survey instrument, construct measures, sample frame, survey

administration, and statistical approaches are explained in chapter four. Chapter 5 reports the

results of the assessments of the measures used within this study. In particular, this chapter

presents the procedures used to establish construct validity and the results of validity tests. In

chapter six, the results of the formal tests of hypotheses are presented. Chapter 7 examines

the results of hypothesis tests and offers explanations for contradictory findings. In the final

chapter, the major contributions are summarized, limitations are presented, and ideas for

future research are discussed.


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CHAPTER 2

LITERATURE REVIEW

This chapter provides a comprehensive review of conceptual and empirical research that

serves as a basis for the development of the theoretical models that follow. This literature

review is presented in three main sections. 2.1 reviews relevant buyer-supplier relationship

theory and attempts to position supplier portfolio management theory as a logical extension of

transaction cost economic and relational exchange theories. Drawing from recent research in

supplier portfolio management theory, this research posits that the development of inter-firm

relational norms, use of supply management practices, and intensity of inter-firm business

process integration must be aligned with exchange conditions in order to realize superior

performance within the buyer-supplier relationship. As such, 2.2 reviews supply

management practices, with particular focus on negotiation, cost management, and supplier

development literature, in order to adequately define constructs used in model development.

Similarly, 2.3 provides a comprehensive review of three inter-firm business processes:

supplier suggestion participation, logistics integration, and supplier involvement in new

product development. As suggested in the introduction, these supplier-supported inter-firm

activities represent the extent to which the supplier is engaged in the buyer-supplier

relationship. Finally, 2.4 suggests that organizational competence is a pre-condition for

successful buyer-supplier joint effort.


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2.1 Buyer-Supplier Relationship Theory

This section explores buyer-supplier relationship theory within the context of transaction cost

economic and relational exchange theory, describes relationship closeness, and identifies

supplier portfolio management theory as a viable lens to study buyer-supplier relationship

management practices. In 2.1.1, the key attributes of transaction cost economic theory are

cited and the complementary nature of relational exchange theory is introduced. In 2.1.2,

buyer-supplier relationship closeness is discussed within the context of a relationship

continuum. In addition, this sub-section describes relationship closeness in terms of relational

norms, supply management activities, and inter-firm business process integration. In 2.1.3,

supplier portfolio management theory is reviewed and positioned as a logical extension of

transaction cost economic and relational governance theories.

2.1.1 Exchange Theory

Transaction cost economic (TCE) theory focuses on the costs associated with exchange

governance, i.e., those costs associated with the organization and coordination of successive

stages of the value creation process (Heide, 1994). Heide (1994, p. 72) describes governance

as a multidimensional phenomenon that encompasses the initiation, termination, and ongoing

relationship maintenance between a set of parties. With its roots in comparative contracting,

TCE theory seeks the minimization of transaction costs by identifying governance

mechanisms that are most appropriate for a given set of exchange conditions (Williamson,

1991a). The selection of appropriate governance structure is primarily guided by three key

transaction characteristics the degree to which transaction-specific assets are used to support

exchange (asset specificity), frequency of exchange, and the degree of uncertainty

(Williamson, 1991a). Incorporated into the TCA theory developed by Williamson are two


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behavioral assumptions: (1) actors are bounded rationally, i.e., they are limited by their

information processing capabilities, and (2) actors may behave in a self-interested,

opportunistic manner.

Given the assumed behavior of actors in an exchange, TCA predicts that under

specific exchange conditions markets (or hierarchies) are more attractive modes of

governance. For example, in an uncertain environment, where actors find it difficult to

anticipate future events or the behavior of their exchange partner, transaction-specific assets

cause markets to be less effective at curbing opportunistic behavior due to the lock-in

problems associated with specialized investment. As a result of the difficulty in redeploying

highly specific assets, switching costs render alternate exchange partners less attractive

(Teece, 1984). Similarly, transactions characterized by greater frequency may be more

efficiently executed within hierarchies, as the cost of specialized governance structures will

be easier to recover for large transactions of a recurring kind (Williamson, 1985, p. 60).

However, when transactions are characterized by a limited need for adaptation, coordination,

and safeguarding, actors will favor markets.

The current form of TCE theory acknowledges an intermediate mode of governance

that focuses on how governance problems can be managed without common ownership

(Rindfleisch and Heide, 1997, p. 40 see also Powell, 1987). Bolstered by relational exchange

theory, this stream of literature suggests that advanced coordination, adaptation, and

protection may be achieved through the establishment of close, long-term ties between buyer

and supplier (Dwyer, Schurr, and Oh, 1987 Heide and John, 1990 Ring and Van De Ven,

1992, 1994). Relational exchange theory suggests that economic exchange occurs within a

social context and espouses a view of inter-firm governance that represents a departure from


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and supplier, (4) buyer-supplier partnership high levels of mutual interdependence and

limited supplier competition, and (5) strategic alliances partnership in which buyer and

supplier align strategic, long-term goals. Several empirical and conceptual studies support the

concept of a relationship closeness continuum (Goffin et al., 2006 Lambert, Emmelhainz, and

Gardner, 1996 McCutcheon and Stuart, 2000 Monczka et al., 1998 Stuart, 1993).

While the general notion of relationship closeness is well-developed, extant research is

in its incipient stages of understanding the specific attributes that characterize a close buyer-

supplier relationship. As shown in Table 2 below, most prior definitions of close buyer-

supplier relationships recognize the role of longevity and the cooperative nature, in terms of

information sharing, and risk and reward sharing, of close relationships. Additionally, extant

research suggests that close relationships are strategic (Li, Rao, Ragu-Nathan, and Ragu-

Nathan, 2005 Monczka et al., 1998 Webster, 1992), involve inter-firm dependency (Mohr

and Spekman, 1994 Stuart, 1993 Zaheer and Venkatraman, 1995), and lead to competitive

advantage (Goffin et al., 2006 McCutcheon and Stuart, 2000 Monczka et al., 1998 Webster,

1992).

Consistent with their definition of partnering (see Table 2.1), Ellram and Hendrick

(1995) suggest that a futuristic orientation, risk and benefit sharing, and communication issues

such as computer linkages, corporate communication, and information sharing are important

attributes of a close buyer-supplier relationship. In their cross-industry study, Ellram and

Hendrick (1995) studied relationships between manufacturers and their closest suppliers and

used matched dyad data to assess differences in buyers and suppliers perspectives of

relationship closeness. Results from their study suggest that both buyers and their supplier

partners desire a longer-term, orientation, greater risk and benefit sharing, more integrated


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computer integration, and more frequent face-to-face communication and overall information

sharing.

Table 2.1: Definitions of close buyer-supplier relationships

Research Study Term Definition

Ellram (1995a, p. 10,

1995b, p. 37)

Ellram and Hendrick(1995, p. 41)

Partnering On-going relationship between two firms that involves acommitment over an extended time period, and a mutualsharing of information and the risks and rewards of the

relationship.

Goffin et al.

(2006, p. 193)

Partnership-like

Relationship

A close cooperation between manufacturers and theirsuppliers, which bring many advantages including betterquality, lower costs, and reliable delivery

Li et al.(2005, p. 622)

StrategicSupplier

Partnership

Long-term relationship between the organization and itssuppliers designed to leverage the strategic andoperational capabilities of individual organizations to

help them achieve significant ongoing benefits

McCutcheon andStuart (2000, p. 285)

StrategicSupplierAlliance

Long-term buyer-supplier relationship that offerssustained competitive advantages for both firms through

benefit sharing and joint problem solving

Mohr and Spekman(1994, p. 135)

Partnership Strategic relationship between independent firms whoshare compatible goals, strive for mutual benefit, andacknowledge a high level of mutual interdependence

Monczka et al.

(1998, p. 555)

Strategic

SupplierAlliance

Long-term, cooperative relationships designed to

leverage the strategic and operational capabilities ofindividual participating companies to achieve significant

ongoing benefits to each party

Stuart (1993, p. 23) SupplierPartnering

Strong inter-company dependency relationships withlong-term planning horizons

Webster (1992) 1 StrategicAlliance

Relationship that takes place within the context of acompanys long-term strategic plan and seeks toimprove or dramatically change a companyscompetitive position.

Zaheer andVenkatraman

(1995, p. 375)

Quasi-verticalIntegration

Close relationship which is based primarily upon onefirms dependence for a significant portion of its total

business upon another firm1 Webster cites the definition of Devlin and Bleakley (1988, p. 18).


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Table 2.2: Key attributes of close buyer-supplier relationships 1

Construct Description

Personal relationship There exists an extensive and familiar contact between themanufacturer and supplier at the human level

Special product capability Supplier delivers parts specially designed parts that fulfill thespecific requirements of the manufacturer

Dependency Switching from this supplier is too time consuming as this supplierholds a monopoly position

Size of supplier organization Supplier is a public company with more than 500 employeesworldwide, many subsidiaries, and a significant global presence

Relationship maintenanceeffort

Relationship is very interactive both the manufacturer and thesupplier nurture the relationship by regularly contacting the

partner and visiting on a regular basis

Volume of turnover aspurchased from the supplier,

Supplier delivers a high volume of turnover to the manufacturerannually the manufacturer considers that supplier as a main, A-list

supplier

Speed of supplier feedback Supplier responds to all inquiries promptly

Suppliers new productdevelopment capabilities

Supplier leverages is technical expertise and is involved indeveloping and enhancing new products

Supplier complaint handling Supplier accepts faults in a product, reacts quickly, and completelyeliminates fault

1 Paraphrased and directly quoted from Goffin et al. (2006, p. 201, Table 5 and p. 206-207, Appendix A)

Recent research validates the notion that buyer-supplier relationship closeness is a

multidimensional construct. Using structured interviews, Goffin et al. (2006) explored the

concept of relationship closeness with a sample of 39 purchasing and operations managers

from 18 medium-sized German companies. In their study, the researchers used repertory grid

analysis to identify 411 constructs that characterize buyer-supplier relationships. Using

frequency of mention and variability measures to determine the importance of each construct,

Goffin et al. (2006, p. 201) determined that relationship closeness may be characterized by 9

key constructs: personal relationship, special product capability, dependency, size of supplier

organization, relationship maintenance effort, volume of turnover as purchased from the

supplier, speed of supplier feedback, suppliers new product development capabilities, and


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supplier complaint handling. A preliminary description of each key construct, based on the

findings of Goffin et al. (2006), is listed in Table 2.2 above.

Synthesizing their findings with related research, Goffin et al. (2006, Figure 4, p. 203)

posit a conceptual model of supplier partnerships. A review of this model suggests that

exchange conditions, supply management practices, inter-firm business processes, and

relational norms are integral to the development of close buyer-supplier relationships. In

particular, Goffin et al. (2006) note the importance of (1) exchange conditions dependency

(viewed as market thinness), supplier importance, and product customization, (2) supply

management practices joint problem solving, supplier training, non-tender price agreements,

and single or parallel sourcing policy, (3) inter-firm business processes joint new product

development and logistics integration, and (4) relational norms trust, commitment,

information sharing, reward sharing, personal relationships, and communication openness. In

accordance with the conceptual model of Goffin et al., each of these relationship dimensions

is expected to directly or indirectly influence the short and long-term performance of the

buying firm.

Additional understanding of relationship closeness may be gained by exploring the

process in which close relationships are created. Dwyer et al. (1987) develop a conceptual

model of relationship development in which relationship closeness evolves through five

successive stages of inter-firm interaction: awareness, exploration, expansion, commitment,

and dissolution. In the awareness stage, potential exchange partners become aware of each

other and each firm attempts to position itself as an attractive partner in advance of exchange.

In the second stage, exploration, firms initiate exchange under the pretense of an initial trial,

allowing the buyer and supplier to assess the risks and benefits associated with the exchange.


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During the exploration phase, the attractiveness of the relationship is assessed, parties engage

in communication and bargaining, concessions based on bargaining power are granted, and

initial relational norms that set expectations for future exchange are established. According to

Dwyer et al. (1987), the third phase of relationship development involves the expansion of

available rewards that result from the buyer-supplier relationship. In the expansion stage,

trust and inter-firm relational satisfaction encourage increased risk-taking within the dyad

increased investment in transaction-specific assets leads to further interdependence between

the exchange partners. The fourth stage of relationship development is marked by inter-firm

commitment. As defined by Dwyer et al. (1987, p. 19) commitment refers to an implicit or

explicit pledge of relationship continuity between exchange partners. Elements of inter-firm

commitment include bilateral investment in the relationship and shared belief in the

attractiveness of the relationship. The final stage of relationship development is dissolution,

which involves the termination of personal and commercial aspects of the inter-firm

relationship.

Drawing from dependence theory, transaction cost economic theory, and relational

governance theory, Heide (1994) posits a similar model of relationship development that

consists of three primary dimensions: relationship initiation, relationship maintenance, and

relationship termination. In Heides conceptual model, relationship initiation involves the

comprehensive evaluation of potential exchange partners. To ensure inter-firm goal

alignment, partner evaluation involves the comprehensive assessment of technical capabilities

as well as partner attitudes and values. Relationship management involves the determination

of decision rights, development of contingency plans and adjustment processes that allow

adaptation to future uncertainties, performance monitoring, alignment of incentive systems


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with inter-firm goals, and selective use of enforcement mechanisms. Consistent with the

approach of Dwyer et al. (1987) the final dimension of Heides model of relationship

development involves termination.

A salient attribute of Heides (1994) model of relationship development is explicit

recognition that each stage of relationship development may vary in accordance with the

nature of the relationship. To this point, Heide (1994) notes the distinction between market

(discrete exchange) and non-market exchanges, and further segments non-market exchange

into unilateral and bilateral forms. Unilateral non-market exchange involves asymmetry of

power and dependence and describes an exchange in which one partner imposes direction on

the other (Heide, 1994). Conversely, bilateral exchange recognizes the joint development of

policy toward the attainment of mutually beneficial goals (Heide, 1994). As such, market

exchange, unilateral non-market exchange, and bilateral non-market exchange represent inter-

firm relationships of increasing closeness. Importantly, as relationships move from unilateral

to bilateral, Heide (1994) suggests that selection becomes more comprehensive, plans become

more flexible and facilitate mutual adjustment, monitoring becomes proactive and self-

performed, and incentives are longer-term in nature leading to an open-ended relationship.

Ring and Van de Ven (1994) advance a closed-loop process model of the development

of cooperative inter-firm relationships that consists of three repetitive stages: negotiation,

commitment, and execution. In the negotiation stage, the parties develop joint expectations

about their motivations, possible investments, and perceived uncertainties of a potential

business deal (Ring and Van de Ven, 1994, p. 97). This stage of the relationship is

characterized by formal bargaining, in which the terms of the relationship are identified, roles

and responsibilities are considered, and partners trustworthiness is assessed. Assuming


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negotiations lead to congruent expectations, parties enter the commitment stage of the

relationship, in which the parties agree to an initial course of action. In this stage, agreement

regarding roles, responsibilities, and rules of interaction is established. In the final stage, each

party executes its roles and responsibilities in accordance with the established agreement.

In their conceptual model of the development of cooperative inter-firm relationships,

Ring and Van de Ven (1994) highlight several important attributes. First, the authors note

that while the depiction of discrete relationship stages facilitates analysis, these stages are

overlap in practicality. Second, the closed-looped nature of the model offers a means by

which relationships may grow closer through repeated cycles of negotiation, commitment, and

execution. Third, Ring and Van de Ven (1994) advance a contingency view of relationship

development by explicitly noting that the duration of each stage may be influenced by

exchange conditions such as environmental uncertainty, partner trustworthiness, and role

responsibilities of the parties. Adding further insight into the development of inter-firm

cooperative relationships, Ring and Van de Ven (1994) suggest that most cooperative

relationships emerge slowly and incrementally over time through repeated interaction

characterized by increasing levels of inter-firm commitment prior cycles of fair and equitable

exchange motivate risk-taking behavior in the form of increased transaction-specific

investment, building higher levels of trust into the relationship. Increased reliance on trust

mitigates the need for complex/complete contracts and monitoring, facilitates greater

flexibility, and decreases transaction costs (Ring and Van De Ven, 1994).

Using dyadic data from manufacturers and their matched distributors, Anderson and

Weitz (1992) study the development of close relationships through the escalation of bilateral

transaction-specific investment. In their study of commitment and pledges, Anderson and


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Weitz (1992) found that one partys perception of the other partys commitment is positively

related to that partys commitment to the dyad. Furthermore, that partys commitment to the

dyad is positively related to the other partys perception of that partys commitment. As such,

this study provides initial empirical support for a process in which close, interdependent

buyer-supplier relationships are developed through reciprocal pledges and mutual

commitments defined in part by investment in transaction-specific assets. Though not

empirically tested, Anderson and Weitz (1992, p. 18) assert that mutual commitment

facilitates inter-firm coordination such that mutual profitability is enhanced.

Several subsequent studies have empirically examined the role of transaction-specific

investment and relational norms within buyer-supplier relationships. In a study of U.S. and

Japanese automaker-supplier relationships, Dyer (1996c) assesses the effects of human asset

specificity, physical asset specificity, and site specificity on operational, and subsequently,

firm performance. Using scatter plots to test hypothesized relationships, Dyer (1996c) finds

preliminary evidence that suggests that both site specificity (measured as the distance between

buyer and supplier manufacturing facilities) and human asset specificity (measured as the

number of man-days of face-to-face contact between buyer and supplier personnel and the

number of supplier engineers co-located on the customers site) are positively related to

operational performance. Further, Dyer (1996c) finds a positive relationship between asset

specificity and buyer-supplier combined profitability. In a study of automaker-supplier

relationships in the U.S., Korea, and Japan, Dyer and Chu (2000) show a positive relationship

between transaction-specific investment and trust. In the pooled sample of suppliers,

automaker assistance to the supplier and the number of man-days of face-to-face buyer-

supplier contact were positively associated with higher levels of trust. In a later study of


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automaker-supplier relationships in the U.S., Korea, and Japan, Dyer and Chu (2003) propose

that buyer-supplier trust facilitates more efficient exchange by attenuating the need for

complex contracts, monitoring, and enforcement. Within the pooled sample, results from

their study indicate that trust effectively reduces costs ofex postgovernance mechanisms, but

has no effect on ex ante transaction costs. In a study of the U.S. insurance industry, Zaheer

and Venkatraman (1995) posited that asset specificity and trust affect the degree of principal-

agent quasi-integration, and that trust and quasi-integration are antecedents of joint action. In

their study, asset specificity is measured in terms of procedural specificity (extent to which

workflows and procedures were customized for a particular exchange partner) and human

asset specificity (degree to which employees skills are customized for a particular exchange

partner). Findings suggest that asset specificity and trust are positively related to quasi-

integration, and that trust and quasi-integration are positively related to joint action.

In aggregate, empirical evidence from extant buyer-supplier relationship research

suggests that close relationships lead to improved firm performance by attenuating the need

for traditional and costly safeguarding mechanisms. Consistent with relational governance

theory, the development of close inter-firm relationships allows buyers and suppliers to rely

on relational norms, such as trust and information sharing, rather than complex contracting,

re-negotiations, and strict monitoring, to facilitate coordination, adaptation, and safeguarding

within an exchange relationship. Consequently, ex ante and ex posttransaction costs may be

reduced. Additionally, the presence of strong relational norms encourages risk-taking

behavior on behalf of an exchange partner that may be manifested in the investment of

transaction-specific assets that facilitate further efficiency gains.


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2.1.3 Supplier Portfolio Management Theory

While investment in closer buyer-supplier relationships may yield significant gains, a

developing body of research suggests that there are considerable risks and costs associated

with the development and maintenance of partner relationships. As noted in the

aforementioned relationship development models, close relationships tend to develop slowly

over time through a process of reciprocating transaction-specific investment and

strengthening relational norms. Highlighting the opportunistic risk associated with

partnering, Spekman et al. (1999, p. 104) note that many companies (and their procurement

managers) openly fear becoming too reliant on their suppliers and worry that these so-called

partners might take advantage based on that dependency. Costs of creating and

developing a close relationship may be excessive relational costs may include travel, supplier

education, and establishing and planning operational and strategic links between buying and

supplying firms (Cavinato, 1992). White and Lui (2005) examine costs of cooperative

alliances and posit that joint task complexity, inter-partner diversity, and the threat of

opportunism positively influence cooperative and transaction costs, increasing the time and

effort required to manage the alliance. Empirical results suggest that the likelihood of

spending substantial time and effort to coordinate with a partner is: (1) positively affected by

the threat of opportunism and inter-partner diversity and (2) non-linearly related to joint task

complexity. Based on their findings, White and Lui (2005) conclude that the governance

decision should not be driven solely by transaction cost analysis, but must also consider the

costs of coordination. Further, White and Lui (2005) propose that coordination costs may be

particularly salient within hybrid governance structures.


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Given the cost and risk implications associated with close relationships, several

researchers suggest that the uniform pursuit of close relationships across a supply base may

have a deleterious effect on a buyers performance and posit that supplier relationships may

be best managed using a portfolio approach (Dyer et al., 1998 Gadde and Snehota, 2000

Goffin et al., 2006 McCutcheon and Stuart, 2000). Adapting a definition from Wagner and

Johnson (2004, p. 717), supplier portfolio management involves the management of an array

of supplier relationships, each having various characteristics and each serving the [buying]

firm in different ways. Drawing from its financial underpinnings (Markowitz, 1952), the

portfolio approach to supplier relationship management holds that supply risks orreturns may

be optimized by managing the supply base as a whole (Wagner and Johnson, 2004). The

portfolio approach, as applied to buyer-supplier relationships, suggests that firms must

judiciously manage external relationships and commitments of resources toward relationships

in accordance with the benefits derived from each relationship (Turnbull, 1989). Similarly,

Olsen and Ellram (1997) argue that portfolio models may be used to guide the allocation of

scarce internal resources across relationships by identifying specific groups of relationships

that warrant greater investment. Thus, supplier portfolio management theory suggests that

transaction-specific assets may be differentially distributed across the set of a firms supplier

relationships in order to efficiently allocate scarce internal resources in accordance with

exchange conditions. As such, a central thrust of supplier portfolio management is the

determination of the role of each relationship and the pursuit of appropriate mechanisms to

govern each relationship.

Importantly, the logic advanced by portfolio theory is consistent with that of

transaction cost economic (TCE) theory and relational exchange theory. Similar to TCE


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theory, supplier portfolio management logic explicitly recognizes the costs associated with

inter-firm coordination. In particular, supplier portfolio management theory suggests that

buying firms consist of limited internal resources and espouses the allocation of these limited

resources across relatively homogeneous subsets of suppliers in order to maximize gains (or

minimize risks) across the entire supply base. As with relational contracting theory, supplier

portfolio management theory advocates high-levels of inter-firm coordination through the

deployment of transaction-specific investments and the development of relational norms.

However, whereas selective relational literature implies the unconditional pursuit of closer,

more integrated buyer-supplier relationships, supplier portfolio management theory seeks to

define the contextual factors in which close buyer-supplier relationships may be appropriate.

As such, this research positions supplier portfolio as a logical extension of TCE and relational

contracting theory.

When contrasting TCE and relational exchange theories with supplier portfolio

management theory, a primary point of departure is the procedural orientation that supplier

portfolio management theory maintains. Whereas TCE and relational contracting theory offer

general guidance to practitioners, supplier portfolio management theory outlines a process for

supplier relationship management. Owed to its operational roots, the execution of supplier

portfolio management consists of two primary steps: (1) supply base segmentation and (2)

differential management of each relationship segment (Nellore and Soderquist, 2000).

While extant research has identified several criteria that may be used to segment

relationships (see Table 2.3 for a review), recent research suggests that Kraljics (1983)

portfolio approach is widely used by purchasing managers. Citing the widespread adoption o f

Kraljics approach to purchasing management, Caniels and Gelderman (2005, p. 2) note that:


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(1) the Kraljic approach has received large-scale recognition and has attained an increasing

degree of adoption (2) especially in Western Europe Kraljics matrix remains the

foundation for purchasing strategies of many organizations across sectors and (3) several

purchasing and supply management textbooks advocate Kraljics logic (e.g., van Weele,

2000). Furthermore, Kraljics conceptual models have received extensive conceptual

treatment by several recent studies (Caniels and Gelderman, 2005 Dubois and Pedersen,

2002 Gelderman and van Weele, 2003, 2005 Krause, Handfield, and Scannell, 1998 Olsen

and Ellram, 1997).

Kraljic (1983) advocates a two-step approach to the management of material

procurement item segmentation and development of distinct purchasing strategies for each

item group. As illustrated in Figure 2.1 below, Kraljic proposes that purchased items may be

segmented into four groups based on the importance of the purchase and the complexity

associated with the supply market: strategic items (high importance, high complexity),

bottleneck item (low importance, high complexity), leverage items (high importance, low

complexity), and non-critical items (low importance, low complexity). Kraljic (1983, p. 110)

views the importance of the purchased item in terms of profit impact and suggests that

purchase importance may be affected by many factors, such as the profitability of the end-

product, the value of the purchased part relative to the end-product, cost of the purchased item

relative to the total cost of the end-product, and the impact of the purchased item on end-

product profitability. Alternately, Kraljic (1983, p. 110) characterizes the complexity of the

supply market as supply risk and identifies several supply risk factors: market thinness,

technology uncertainty, barriers to entry, and logistics costs and complexity.


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Table 2.3: Supplier segmentation criteria

Research Study Segmentation Criteria Type of Research

Bensaou (1999) Buyers specific investment

Suppliers specific investment

Conceptual

Caniels and Gelderman(2005)

Profit impactSupply risk

Survey-based

Dubois and Pedersen(2002)

Importance of purchasing

Complexity of supply market

Conceptual

Dwyer et al. (1987) Buyers motivational investment in relationship

Sellers motivational investment in relationship

Conceptual

Gelderman and VanWeele (2003)

Profit impact

Supply risk

Case Study

Gelderman and VanWeele (2005)

Profit impact

Supply risk

Survey-based

Gadde and Snehota

(2000) 1

Posture of relationship

(1) Business volume, (2) Relationship continuity,(3) Single sourcing

Conceptual

Anderson and Katz(1998)

Revenue Impact

Procurement complexity

Conceptual

Kaufman et al. (2000) Collaboration

Technology

Survey-based

Kraljic (1983) Importance of purchasing

Complexity of supply market

Conceptual

Krapfel et al. (1991) 1 Interest commonality

(1) Relationship value, (2) Perceived power

Conceptual

Krause et al. (1998) Supply Risk

Volume/Dollar Volume of Purchase

Survey-based

Masella and Rangone(2000)

Time horizon of the relationship

Nature of buyer-supplier interaction

Conceptual

Nellore and Soderquist(2000)

Degree of co-development

Specification generator

Case Study

Olsen and Ellram (1997) Importance of purchasing

Difficulty of managing the purchase situation

Conceptual

Spekman et al. (1999) Degree of technical management

Degree of commercial complexity

Survey-based

Svensson (2004) Suppliers commitment to vehicle manufacturer

Commoditys importance to vehicle manufacturer

Survey-based

Wynstra and ten Pierick(2000)

Degree of devel

Study of Buyer-supplier Relationships

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