Exploring Big Data Analytical Capabilities Influence on Supply Chain Performance: Mediating Role of Supply Chain Resilience
DOI:
https://doi.org/10.61506/Keywords:
Resilience, Performance, Capabilities, PLS-SEM, Competitive edgeAbstract
Big Data Analytics (BDA) capabilities has transformed supply chain performance and emphasizing need in pharmacy industry supply chain. Moreover, resilient approach is necessary given the supply chains dynamic nature. This study explores Supply Chain Resilience (SCR) mediating role in relation among BDA capabilities & Supply Chain Performance (SCP). Using cross-sectional survey of 295 supply chain professionals from pharmacy industry and also employed PLS-SEM to judge hypothetical relationships. Our findings reveal that BDA capabilities positively influence SCP and that SCR significantly mediates this relationship. The findings are expected to offer valuable insights for practitioners seeking to leverage BDA to build more resilient and high-performing.
References
Ali, A., Haq, F., Marwat, A., Khan, S., & Adnan, A. (2024). Empirical Research on the Mediating Impact of Integration between Supply Chain Management Practices and Supply Chain Management Performance. Qlantic Journal of Social Sciences, 5(1), 363-373.
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment?. International journal of production economics, 182, 113-131.
Asghar, F., Farooq, P., Nadim, M., ul Abidin, Z., & Wadood, F. (2023). Global Financial Crisis: A critical study on Role of Auditor’ s and Stakeholder. Journal of Policy Research (JPR), 9(2), 452-458.
Awan, U., Shamim, S., Khan, Z., Zia, N. U., Shariq, S. M., & Khan, M. N. (2021). Big data analytics capability and decision-making: The role of data-driven insight on circular economy performance. Technological Forecasting and Social Change, 168, 120766.
Bag, S., Dhamija, P., Luthra, S., & Huisingh, D. (2021). How big data analytics can help manufacturing companies strengthen supply chain resilience in the context of the COVID-19 pandemic. The International Journal of Logistics Management, 34(4), 1141–1164.
Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities. Technological Forecasting and Social Change, 163, 120420.
Bahrami, M., Shokouhyar, S., & Seifian, A. (2022a). Big data analytics capability and supply chain performance: the mediating roles of supply chain resilience and innovation. Modern Supply Chain Research and Applications, 4(1), 62–84.
Bahrami, M., Shokouhyar, S., & Seifian, A. (2022b). Big data analytics capability and supply chain performance: the mediating roles of supply chain resilience and innovation. Modern Supply Chain Research and Applications, 4(1), 62–84.
Behl, A., Gaur, J., Pereira, V., Yadav, R., & Laker, B. (2022). Role of big data analytics capabilities to improve sustainable competitive advantage of MSME service firms during COVID-19 – A multi-theoretical approach. Journal of Business Research, 148, 378–389.
Belhadi, A., Kamble, S., Jabbour, C. J. C., Gunasekaran, A., Ndubisi, N. O., & Venkatesh, M. (2021). Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries. Technological Forecasting and Social Change, 163, 120447.
Chatterjee, S., Chaudhuri, R., Gupta, S., Sivarajah, U., & Bag, S. (2023). Assessing the impact of big data analytics on decision-making processes, forecasting, and performance of a firm. Technological Forecasting and Social Change, 196, 122824.
Christopher, M., & Peck, H. (2020). Building the Resilient Supply Chain. International Journal of Logistics Management, 31(1), 3-25.
Côrte-Real, N., Ruivo, P., & Oliveira, T. (2020). Leveraging internet of things and big data analytics initiatives in European and American firms: Is data quality a way to extract business value?. Information & Management, 57(1), 103141.
Dubey, R., Gunasekaran, A., Childe, S. J., Fosso Wamba, S., Roubaud, D., & Foropon, C. (2021). Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience. International Journal of Production Research, 59(1), 110-128.
Dubey, R., Bryde, D. J., Dwivedi, Y. K., Graham, G., Foropon, C., & Papadopoulos, T. (2023). Dynamic digital capabilities and supply chain resilience: The role of government effectiveness. International Journal of Production Economics, 258, 108790.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., . . . Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S. F., Childe, S. J., Hazen, B., & Akter, S. (2017). Big data and predictive analytics for supply chain and organizational performance. Journal of Business Research, 70, 308-317.
Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049-1064.
Hafeez, A., Asghar, F., Ali, W., Rashid, M., & Ali, W. (2023). Laws Governed Role Of Artificial Intelligence And Machine Learning In Supply Chain Management. Russian Law Journal, 11(4), 955-962.
Helo, P., & Thai, V. V. (2024). Logistics 4.0 – digital transformation with smart connected tracking and tracing devices. International Journal of Production Economics, 275, 109336.
Huang, K., Wang, K., Lee, P. K., & Yeung, A. C. (2023). The impact of industry 4.0 on supply chain capability and supply chain resilience: A dynamic resource-based view. International Journal of Production Economics, 262, 108913.
Ivanov, D., & Dolgui, A. (2021). A Digital Supply Chain Twin for Managing the Disruption Risks and Resilience in the Era of Industry 4.0. Production Planning & Control, 32(9), 775-790.
Kumar, D., Singh, R. K., Mishra, R., & Vlachos, I. (2023). Big data analytics in supply chain decarbonisation: a systematic literature review and future research directions. International Journal of Production Research, 62(4), 1489–1509.
Lin, J., Lin, S., Benitez, J., Luo, X., & Ajamieh, A. (2023). How to build supply chain resilience: The role of fit mechanisms between digitally-driven business capability and supply chain governance. Information & Management, 60(2), 103747.
Liu, H., & Wei, S. (2024). Bridging versus buffering: how IT capabilities and dependence advantage shape responses to supply chain disruptions? Industrial Management & Data Systems, 124(5), 1795–1822.
McMaster, M., Nettleton, C., Tom, C., Xu, B., Cao, C., & Qiao, P. (2020). Risk Management: Rethinking Fashion Supply Chain Management for Multinational Corporations in Light of the COVID-19 Outbreak. Journal of Risk and Financial Management, 13(8), 173.
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information & Management, 57(2), 103169.
Nazir, M. W., Haq, F., Naeem, Z., Suarez, V. O., Asghar, F., & Marwat, A. (2024). Understanding green marketing strategies effects on Consumers’ Purchase Behavior: Insights from Pakistan. Remittances Review, 9(S2 (May 2024)), 278-297.
Raguseo, E. (2018). Big Data Technologies: An Empirical Investigation on Their Adoption, Benefits, and Risks for Companies.International Journal of Information Management, 38(1), 187-195.
Rialti, R., Zollo, L., Ferraris, A., & Alon, I. (2019). Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model. Technological Forecasting and Social Change, 149, 119781.
Safari, A., Al-Ismail, V. B., Parast, M. M., Golgeci, I., & Pokharel, S. (2022). Supply Chain Risk and Resilience Among Startups, Smes, and Large Enterprises in Different Industries: A Systematic Review, Analysis, and Future Research Directions. SSRN Electronic Journal.
Tambe, P., Hitt, L. M., & Brynjolfsson, E. (2019). Artificial Intelligence in Business and Economics. National Bureau of Economic Research Working Paper, No. 26371.
Talebkhah, M., Sali, A., Gordan, M., Hashim, S. J., & Rokhani, F. Z. (2023). Comprehensive Review on Development of Smart Cities Using Industry 4.0 Technologies. IEEE Access, 11, 91981–92030.
Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J., Dubey, R., & Childe, S. J. (2020). Big Data Analytics and Firm Performance: Effects of Dynamic Capabilities.Journal of Business Research, 70(1), 356-365.
Yasmin, M., Tatoglu, E., Kilic, H. S., Zaim, S., & Delen, D. (2020). Big data analytics capabilities and firm performance: An integrated MCDM approach. Journal of Business Research, 114, 1–15.