Date Available


Year of Publication


Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation


Business and Economics


Business Administration

First Advisor

Dr. Clyde W. Holsapple

Second Advisor

Dr. Scott Ellis


Supplier development (SD) has been intensively and increasingly used in practice and studied in academia. Many studies find that SD can generate operational, capability-based, attitudinal, and financial performance measures for both the supplying firm (supplier) and the buying firm (buyer), but very few studies systematically explain why SD yields supplier’s performance improvements and, in turn, buyer’s performance improvements. Using a meta-analysis approach, this dissertation finds that SD does lead to positive outcomes, but SD is found to have very weak or even negative relationship with performance improvements in some cases. Such findings further support the importance of examining the main research question: why SD works.

In order to answer the main research question, this dissertation adopts a multiphase triangulation approach: theoretical construction, conceptual examination, and empirical examination. Doing so, this dissertation constructs and validates a knowledge management (KM) view of SD.

The purpose of theoretical construction (Chapter 3) is to develop a KM view of supplier development via a systematic view of previous studies. Presented in Chapter 4, conceptual examination reveals that all SD activities can be subsumed into KM activities, and further conceptually supports the feasibility of the KM view in SD. Empirical examination, including a survey of 39 SD scholars and a survey of 295 SD practitioners (156 complete responses), is presented in Chapters 5 and 6. Most hypotheses are strongly supported, demonstrating the importance of the knowledge-management view of SD.

Overall, this dissertation has both theoretical contributions for KM and SD sides, and practical contributions for researchers, practitioners, and educators/students. First, it contributes by supporting the addition of KM variables to other theories when explaining why SD works, confirming the role of KM in SD, providing a complete KM view of SD, and revealing why SD works. Second, it contributes by implementing mixed research methods, integrating multiple disciplines, and exemplifying collecting data on LinkedIn. Third, it contributes by offering a catalog of SD activities and guidance for designing, implementation, and evaluation of SD initiatives. Fourth, it contributes by advancing a mental model to understand SD literature. Conclusions, limitations, and future research directions are also discussed.