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Exploring the relationship between supplier development, big data analytics capability, and firm performance

Author

Listed:
  • Vicky Ching Gu

    (University of Houston Clear Lake)

  • Bin Zhou

    (University of Houston Downtown)

  • Qing Cao

    (University of Houston Downtown)

  • Jeffery Adams

    (Roosevelt University)

Abstract

Extant research shows that big data analytics (BDA) capability is often employed as a part of organizational resources to enhance firm performance. Drawing upon the resource-based view, dynamic capabilities, and contingency theory, this study endeavors to examine the alignment between BDA capability and a specific type of procurement strategies (i.e., supplier development) and its impact on firm performance. The study extends the BDA capability research by investigating the direct impact of BDA capability on supplier development and firm performance, respectively, and by exploring both mediating and moderating effects on the relationship between supplier development and firm performance. The main results show that a firm’s BDA capability has not only a direct positive significant impact on supplier development, but also a direct positive significant impact on its business performance. More importantly, the results indicate strong moderating and mediating effects of BDA capability on supplier development, which in turn affects the improvement of firm performance. Theoretical and managerial implications along with future research directions are provided in the end.

Suggested Citation

  • Vicky Ching Gu & Bin Zhou & Qing Cao & Jeffery Adams, 2021. "Exploring the relationship between supplier development, big data analytics capability, and firm performance," Annals of Operations Research, Springer, vol. 302(1), pages 151-172, July.
    • Handle: RePEc:spr:annopr:v:302:y:2021:i:1:d:10.1007_s10479-021-03976-7
    DOI: 10.1007/s10479-021-03976-7
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    as
    1. Davide Luzzini & Stefano Ronchi, 2016. "Cinderella purchasing transformation: linking purchasing status to purchasing practices and business performance," Post-Print hal-01289902, HAL.
    2. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    3. Michael Katehakis & Laurens Smit, 2012. "On computing optimal (Q,r) replenishment policies under quantity discounts," Annals of Operations Research, Springer, vol. 200(1), pages 279-298, November.
    4. David J. Ketchen & Christopher W. Craighead & Li Cheng, 2018. "Achieving Research Design Excellence Through the Pursuit of Perfection: Toward Strong Theoretical Calibration," Journal of Supply Chain Management, Institute for Supply Management, vol. 54(1), pages 16-22, January.
    5. Gang Wang & Angappa Gunasekaran & Eric W. T. Ngai, 2018. "Distribution network design with big data: model and analysis," Annals of Operations Research, Springer, vol. 270(1), pages 539-551, November.
    6. Steve Bin Zhou & Fiona Xiaoying Ji, 2015. "Impact of Lean Supply Chain Management on Operational Performance: A Study of Small Manufacturing Companies," International Journal of Business Analytics (IJBAN), IGI Global, vol. 2(3), pages 1-19, July.
    7. Barbara Flynn & Mark Pagell & Brian Fugate, 2018. "Editorial: Survey Research Design in Supply Chain Management: The Need for Evolution in Our Expectations," Journal of Supply Chain Management, Institute for Supply Management, vol. 54(1), pages 1-15, January.
    8. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    9. Knoppen, Desirée & Sáenz, María J., 2015. "Purchasing: Can we bridge the gap between strategy and daily reality?," Business Horizons, Elsevier, vol. 58(1), pages 123-133.
    10. Dey, Prasanta Kumar & Bhattacharya, Arijit & Ho, William, 2015. "Strategic supplier performance evaluation: A case-based action research of a UK manufacturing organisation," International Journal of Production Economics, Elsevier, vol. 166(C), pages 192-214.
    11. Wu, De-Min, 1973. "Alternative Tests of Independence Between Stochastic Regressors and Disturbances," Econometrica, Econometric Society, vol. 41(4), pages 733-750, July.
    12. Srinivasan, Mahesh & Mukherjee, Debmalya & Gaur, Ajai S., 2011. "Buyer-supplier partnership quality and supply chain performance: Moderating role of risks, and environmental uncertainty," European Management Journal, Elsevier, vol. 29(4), pages 260-271, August.
    13. Bin Zhou, 2016. "Lean principles, practices, and impacts: a study on small and medium-sized enterprises (SMEs)," Annals of Operations Research, Springer, vol. 241(1), pages 457-474, June.
    14. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    15. David J. Teece & Gary Pisano & Amy Shuen, 1997. "Dynamic capabilities and strategic management," Strategic Management Journal, Wiley Blackwell, vol. 18(7), pages 509-533, August.
    16. Chiou, Tzu-Yun & Chan, Hing Kai & Lettice, Fiona & Chung, Sai Ho, 2011. "The influence of greening the suppliers and green innovation on environmental performance and competitive advantage in Taiwan," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 822-836.
    17. Souza, Gilvan C., 2014. "Supply chain analytics," Business Horizons, Elsevier, vol. 57(5), pages 595-605.
    18. Seung-Kuk Paik & Thomas Wedel & Chi-Chuan Yao, 2009. "Prioritising purchasing development in small and medium sized enterprises," International Journal of Enterprise Network Management, Inderscience Enterprises Ltd, vol. 3(4), pages 358-373.
    19. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    20. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    21. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    22. Opresnik, David & Taisch, Marco, 2015. "The value of Big Data in servitization," International Journal of Production Economics, Elsevier, vol. 165(C), pages 174-184.
    23. Shirish Jeble & Rameshwar Dubey & Stephen J. Childe & Thanos Papadopoulos & David Roubaud & Anand Prakash, 2018. "Impact of big data and predictive analytics capability on supply chain sustainability," Post-Print hal-02061341, HAL.
    24. Youngseok Choi & Habin Lee & Zahir Irani, 2018. "Big data-driven fuzzy cognitive map for prioritising IT service procurement in the public sector," Annals of Operations Research, Springer, vol. 270(1), pages 75-104, November.
    25. Kartikeya Puranam & Michael Katehakis, 2014. "On optimal bidding and inventory control in sequential procurement auctions: the multi period case," Annals of Operations Research, Springer, vol. 217(1), pages 447-462, June.
    26. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    27. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    28. Deepa Mishra & Angappa Gunasekaran & Thanos Papadopoulos & Stephen J. Childe, 2018. "Big Data and supply chain management: a review and bibliometric analysis," Annals of Operations Research, Springer, vol. 270(1), pages 313-336, November.
    29. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    30. Li, Wenli & Humphreys, Paul K. & Yeung, Andy C.L. & Cheng, T.C.E., 2012. "The impact of supplier development on buyer competitive advantage: A path analytic model," International Journal of Production Economics, Elsevier, vol. 135(1), pages 353-366.
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    7. Oduro, Stephen & De Nisco, Alessandro & Mainolfi, Giada, 2023. "Do digital technologies pay off? A meta-analytic review of the digital technologies/firm performance nexus," Technovation, Elsevier, vol. 128(C).
    8. Oesterreich, Thuy Duong & Anton, Eduard & Teuteberg, Frank & Dwivedi, Yogesh K, 2022. "The role of the social and technical factors in creating business value from big data analytics: A meta-analysis," Journal of Business Research, Elsevier, vol. 153(C), pages 128-149.
    9. Ali Ibrahim Balin & Kazim Sari, 2023. "The Effect of Green Purchasing Practices on Financial Performance under the Mediating Role of Environmental Performance: Evidence from Türkiye," Sustainability, MDPI, vol. 15(4), pages 1-15, February.
    10. Gómez-Bengoechea, Gonzalo & Jung, Juan, 2024. "The Matthew effect: Evidence on firms’ digitalization distributional effects," Technology in Society, Elsevier, vol. 76(C).
    11. Tugba Karaboga & Cemal Zehir & Ekrem Tatoglu & H. Aykut Karaboga & Abderaouf Bouguerra, 2023. "Big data analytics management capability and firm performance: the mediating role of data-driven culture," Review of Managerial Science, Springer, vol. 17(8), pages 2655-2684, November.
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