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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
UMI Microform
Copyright
All rights reserved. This microform edition is protected againstunauthorized copying under Title 17, United States Code.
ProQuest Information and Learning Company300 North Zeeb Road
P.O. Box 1346Ann Arbor, MI 48106-1346
All rights reserved.
by ProQuest Information and Learning Company.
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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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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
5.4.1 Unidimensionality................................................................................... 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 Unidimensionality................................................................................... 190
5.5.1 Reliability ............................................................................................... 193
5.5.3 Convergent and Discriminant Validity .................................................... 194
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5.6 Supply Management Practices Construct Validity............................................ 208
5.6.1 Unidimensionality................................................................................... 208
5.6.2 Reliability ............................................................................................... 210
5.6.3 Convergent and Discriminant Validity .................................................... 212
5.7 Operational Benefits Construct Validity........................................................... 215
5.7.1 Unidimensionality................................................................................... 2155.7.2 Reliability ............................................................................................... 217
5.7.3 Convergent and Discriminant Validity .................................................... 219
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