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Impact of commitment, information sharing, and information usage on supplier performance: a Bayesian belief network approach

  • S.I.: Data Mining and Decision Analytics
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Abstract

Due to the proliferation of information systems and technology, supply chains have the capability of acquiring an enormous amount of supplier data in their databases. However, much of the useful supplier-specific insights in terms of supplier performance metrics are mostly hidden and untouched. The current emphasis on supplier performance makes relationship commitment and information management functions an ideal application area to benefit from the use of data-mining tools for the decision-making process and improving supplier performance. By employing Bayesian belief networks, this study investigates the role of the major variables of commitment, information sharing, quality of shared information, and information usage in relation to supplier performance in the U.S. aircraft manufacturing supply chain. The results provide insightful guidance to managers on how to enhance performance.

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Authors and Affiliations

  1. Supply Chain Management Department, Palumbo-Donahue School of Business, Duquesne University, 600 Forbes Ave. Rockwell Hall, Pittsburgh, PA, 15282, USA

    Abdurrezzak Sener

  2. Department of Finance, Real Estate, and Decision Sciences, Barton School of Business, Wichita State University, 1845 North Fairmount Street, Wichita, KS, 67260-0077, USA

    Mehmet Barut

  3. Business Intelligence and Analytics Department, Heider College of Business, Creighton University, 602 N 20th St, Omaha, NE, 68102, USA

    Ali Dag

  4. Department of Industrial, Systems and Manufacturing Engineering, College of Engineering, Wichita State University, 1845 North Fairmount Street, Wichita, KS, 67260-0035, USA

    Mehmet Bayram Yildirim

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  1. Abdurrezzak Sener
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Sener, A., Barut, M., Dag, A. et al. Impact of commitment, information sharing, and information usage on supplier performance: a Bayesian belief network approach. Ann Oper Res 303, 125–158 (2021). https://doi.org/10.1007/s10479-019-03504-8

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