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Joint B2B supply chain decision-making: Drivers, facilitators and barriers

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  • Nurhayati, Kartika
  • Tavasszy, Lóránt
  • Rezaei, Jafar

Abstract

Joint decision-making is one of the coordination mechanisms to address the inherent complexity of business-to-business (B2B) processes within a supply chain. Joint decision-making can be helpful to define shared goals and objectives, identify supply chain failures and opportunities, and consolidate supply chain success. Parties may benefit directly from a partnership's potential and synergies by collaboratively making decisions. However, specific business conditions need to be in place to enable joint decision-making. This paper investigates how companies in a dyadic relationship arrive at joint and individual supply chain decision-making structure. We examine the drivers, facilitators, and barriers of making joint as well as individual decisions within the supplier-buyer dyad and frame our arguments borrowing perspectives from resource dependency theory, transaction cost economics, collaboration theory, and social exchange theory. The paper presents a case study of Dutch high-tech companies, analysing experiences of supply chain managers via semi-structured interviews. High-tech firms often collaborate and share supply chain decisions due to the high-value capital equipment as well as a shared dependency on highly specific scarce resources. Our study provides new empirical insight into how firms cope with conflicting drivers, facilitators, and barriers in collaborations, controlling their decision-making structure. From the case study, we identify the combinations of facilitators and drivers that tend to promote the existence of joint decisions. We conclude with providing a list of suggestions for decision-makers and future research.

Suggested Citation

  • Nurhayati, Kartika & Tavasszy, Lóránt & Rezaei, Jafar, 2023. "Joint B2B supply chain decision-making: Drivers, facilitators and barriers," International Journal of Production Economics, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:proeco:v:256:y:2023:i:c:s0925527322003036
    DOI: 10.1016/j.ijpe.2022.108721
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    2. Li, Lixu & Liu, Yaoqi & Jin, Yong & Cheng, T.C. Edwin & Zhang, Qianjun, 2024. "Generative AI-enabled supply chain management: The critical role of coordination and dynamism," International Journal of Production Economics, Elsevier, vol. 277(C).
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