ABSTRACT
Despite the important role of suppliers in R&D activity, the supply chain relationships involved in R&D value creation have been under-investigated in previous research. Supplier involvement in R&D necessitates a model that examines how the buyer–supplier relationship influences the relationship between R&D investment and a company’s market value. With a large-scale sample of 4,704 firm-year observations within the Chinese manufacturing sector, this study investigates the relationships among R&D investment, supplier-base concentration, and firm value. The results indicate that there is a non-linear, inverted U-shaped relationship between R&D intensity and Tobin’s q, with the specific shape of this relationship dependent on supplier-base concentration. By highlighting the moderating effect of supplier-base concentration on the curvilinear relationship between R&D investment and firm value, this study contributes to the existing literature on technology, innovation, and supply chain management by shedding new light on value creation achieved through the interface between R&D and supply chains in the context of emerging markets. Our findings emphasise the importance of supplier relationship management to ensure successful R&D value creation activity in the manufacturing sector.
Acknowledgments
The authors would like to thank the Editor-in-Chief Professor Patarapong Intarakumnerd, Managing Editor Seona Lee, and the two anonymous reviewers for their extremely helpful thoughts concerning the development of this manuscript. We would also like to thank Dr. Jian Xu for his comments on earlier versions of the manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 In order to assess multicollinearity, a baseline model including all continuous variables was estimated and the variance inflation factors (VIFs) derived. We found that the mean value of the VIFs was 1.24, and all values were smaller than the recommended threshold of 10, suggesting that multicollinearity was not a serious concern in this study.
2 We thank an anonymous reviewer for suggesting the use of the three-step procedure, which improved the robustness of the findings.
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Notes on contributors
Feng Liu
Feng Liu is an assistant professor at Business School, Shandong University, Weihai, China. He got his Ph.D. from the Department of Logistics, Service and Operations Management (LSOM) from Korea University Business School (KUBS) in Feb. 2020. His current research interests include SME Management, Supply Chain Management, and Operations Management. He has published several articles in journals such as International Journal of Production Economics, Journal of Business & Industrial Marketing, Technology Analysis & Strategic Management, and Journal of Competitiveness.
Byung Cho Kim
Byung Cho Kim is Professor of Logistics, Service & Operations Management at the Korea University Business School. He received his PhD in Industrial Administration from Carnegie Mellon University. His primary research interests include technology management, technology commercialization, and platform economics. Before joining Korea University, he served as an Assistant Professor of Business Information Technology at the Pamplin College of Business at Virginia Tech. His research has appeared in prestigious academic journals including MIS Quarterly, Production and Operations Management, European Journal of Operational Research, Decision Sciences, Marketing Letters, Decision Support Systems, International Journal of Electronic Commerce, Computational Economics, and others.
Kwangtae Park
Kwangtae Park is a professor of Korea University Business School (KUBS) in Seoul, Korea. He received Ph.D. from University of California, Berkeley in IEOR. His current research interests include Service Management and Supply Chain Management.