The impact of supply chain complexities on supply chain resilience: the mediating effect of big data analytics

References

• Adriana, L., B. Irineu de Jr., P. Eduardo Queiroz, B. Tábata Rejane, and Y. Hugo Tsugunobu Yoshida. 2014. “Literature Review of Humanitarian Logistics Research: trends and Challenges.” Journal of Humanitarian Logistics and Supply Chain Management 4: 95–130.
   Google Scholar
• Agarwal, Sunil, Raghu Nandan Sengupta, and Kripa Shanker. 2009. “Impact of Information Sharing and Lead Time on Bullwhip Effect and on-Hand Inventory.” European Journal of Operational Research 192 (2): 576–593. doi:10.1016/j.ejor.2007.09.015.
   Web of Science ®Google Scholar
• Aitken, J., C. Bozarth, and W. Garn. 2016. “To Eliminate or Absorb Supply Chain Complexity: A Conceptual Model and Case Study.” Supply Chain Management: An International Journal 21 (6): 759–774. doi:10.1108/SCM-02-2016-0044.
   Web of Science ®Google Scholar
• Akter, S., S. F. Wamba, A. Gunasekaran, R. Dubey, and S. J. Childe. 2016. “How to Improve Firm Performance Using Big Data Analytics Capability and Business Strategy Alignment?” International Journal of Production Economics 182: 113–131. doi:10.1016/j.ijpe.2016.08.018.
   Web of Science ®Google Scholar
• Ali, A.,. A. Mahfouz, and A. Arisha. 2017. “Analysing Supply Chain Resilience: integrating the Constructs in a Concept Mapping Framework via a Systematic Literature Review.” Supply Chain Management: An International Journal 22 (1): 16–39.
   Web of Science ®Google Scholar
• Ali, I., and I. Gölgeci. 2019. “Where is Supply Chain Resilience Research Heading? A Systematic and co-Occurrence Analysis.” International Journal of Physical Distribution & Logistics Management 49 (8): 793–815. doi:10.1108/IJPDLM-02-2019-0038.
   Web of Science ®Google Scholar
• Ali, I., A. Arslan, Z. Khan, and S. Y. Tarba. 2021. “The Role of Industry 4.0 Technologies in Mitigating Supply Chain Disruption: empirical Evidence from the Australian Food Processing Industry.” IEEE Transactions on Engineering Management 1–11.
   Web of Science ®Google Scholar
• Ali, I., and M. G. S. Aboelmaged. 2021. “Implementation of Supply Chain 4.0 in the Food and Beverage Industry: perceived Drivers and Barriers.” International Journal of Productivity and Performance Management. doi:10.1108/IJPPM-07-2020-0393.
   Web of Science ®Google Scholar
• Ali, I., and K. Govindan. 2021. “Extenuating Operational Risks through Digital Transformation of Agri- Food Supply Chains.” Production Planning & Control 1–13. doi:10.1080/09537287.2021.1988177.
   Web of Science ®Google Scholar
• Ambulkar, S., J. Blackhurst, and S. Grawe. 2015. “Firm's Resilience to Supply Chain Disruptions: Scale Development and Empirical Examination.” Journal of Operations Management 33: 111–122.
   Web of Science ®Google Scholar
• Angrave, D., A. Charlwood, I. Kirkpatrick, M. Lawrence, and M. Stuart. 2016. “HR and Analytics: why HR is Set to Fail the Big Data Challenge.” Human Resource Management Journal 26 (1): 1–11. doi:10.1111/1748-8583.12090.
   Web of Science ®Google Scholar
• Armstrong, R. 1977. “The Right to Life.” Journal of Social Philosophy 8 (1): 13–19. doi:10.1111/j.1467-9833.1977.tb00662.x.
   PubMedGoogle Scholar
• Arunachalam, D., N. Kumar, and J. P. Kawalek. 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 114: 416–436. doi:10.1016/j.tre.2017.04.001.
   Web of Science ®Google Scholar
• Ashkenas, R. 2007. “Simplicity-Minded Management. A Practical Guide to Stripping Complexity out of Your Organization.” Harvard Business Review 85 (12): 101–109, 146.
   PubMed Web of Science ®Google Scholar
• Ateş, M. A., and H. Memiş. 2021. “Embracing Supply Base Complexity: The Contingency Role of Strategic Purchasing.” International Journal of Operations & Production Management 41 (6): 830–859. doi:10.1108/IJOPM-09-2020-0662.
   Web of Science ®Google Scholar
• Ateş, M. A., R. Suurmond, D. Luzzini, and D. Krause. 2021. “Order from Chaos: A Meta‐Analysis of Supply Chain Complexity and Firm Performance.” Journal of Supply Chain Management 58 (1): 3–30. doi:10.1111/jscm.12264.
   Web of Science ®Google Scholar
• Azadegan, A.,. P. C. Patel, A. Zangoueinezhad, and K. Linderman. 2013. “The Effect of Environmental Complexity and Environmental Dynamism on Lean Practices.” Journal of Operations Management 31 (4): 193–212. doi:10.1016/j.jom.2013.03.002.
   Web of Science ®Google Scholar
• Bag, S., S. Gupta, and C. Foropon. 2019. “Examining the Role of Dynamic Remanufacturing Capability on Supply Chain Resilience in Circular Economy.” Management Decision 57 (4): 863–885. doi:10.1108/MD-07-2018-0724.
   Web of Science ®Google Scholar
• Bagozzi, R. P., and Y. Yi. 1988. “On the Evaluation of Structural Equation Models.” Journal of the Academy of Marketing Science 16 (1): 74–94. doi:10.1007/BF02723327.
   Google Scholar
• Behzadi, G., M. J. O'Sullivan, T. L. Olsen, F. Scrimgeour, and A. Zhang. 2017. “Robust and Resilient Strategies for Managing Supply Disruptions in an Agribusiness Supply Chain.” International Journal of Production Economics 191: 207–220. doi:10.1016/j.ijpe.2017.06.018.
   Web of Science ®Google Scholar
• Belhadi, A., S. Kamble, S. Fosso Wamba, and M. M. Queiroz. 2021. “Building Supply-Chain Resilience: An Artificial Intelligence-Based Technique and Decision-Making Framework.” International Journal of Production Research 1–21. doi:10.1080/00207543.2021.1950935.
   Web of Science ®Google Scholar
• Birkie, S. E., and P. Trucco. 2020. “Do Not Expect Others Do What You Should! Supply Chain Complexity and Mitigation of the Ripple Effect of Disruptions.” International Journal of Logistics Management 31 (1): 123–144. doi:10.1108/IJLM-10-2018-0273.
   Web of Science ®Google Scholar
• Birkie, S. E., P. Trucco, and P. F. Campos. 2017. “Effectiveness of Resilience Capabilities in Mitigating Disruptions: leveraging on Supply Chain Structural Complexity.” Supply Chain Management: An International Journal 22 (6): 506–521.
   Web of Science ®Google Scholar
• Blackhurst, J., K. S. Dunn, and C. W. Craighead. 2011. “An Empirically Derived Framework of Global Supply Resiliency.” Journal of Business Logistics 32 (4): 374–391. doi:10.1111/j.0000-0000.2011.01032.x.
   Web of Science ®Google Scholar
• Bode, C., and J. R. Macdonald. 2017. “Stages of Supply Chain Disruption Response: Direct, Constraining, and Mediating Factors for Impact Mitigation.” Decision Sciences 48 (5): 836–874. doi:10.1111/deci.12245.
   Web of Science ®Google Scholar
• Bode, C., and S. M. Wagner. 2015. “Structural Drivers of Upstream Supply Chain Complexity and the Frequency of Supply Chain Disruptions.” Journal of Operations Management 36 (1): 215–228. doi:10.1016/j.jom.2014.12.004.
   Web of Science ®Google Scholar
• Bode, C., S. M. Wagner, K. J. Petersen, and L. M. Ellram. 2011. “Understanding Responses to Supply Chain Disruptions: Insights from Information Processing and Resource Dependence Perspectives.” Academy of Management Journal 54 (4): 833–856. doi:10.5465/amj.2011.64870145.
   Web of Science ®Google Scholar
• Bowman, C., and V. Ambrosini. 2003. “How the Resource-Based and the Dynamic Capability Views of the Firm Inform Corporate-Level Strategy.” British Journal of Management 14 (4): 289–303. doi:10.1111/j.1467-8551.2003.00380.x.
   Web of Science ®Google Scholar
• Bozarth, C. C., D. P. Warsing, B. B. Flynn, and E. J. Flynn. 2009. “The Impact of Supply Chain Complexity on Manufacturing Plant Performance.” Journal of Operations Management 27 (1): 78–93. doi:10.1016/j.jom.2008.07.003.
   Web of Science ®Google Scholar
• Brandon-Jones, A., and D. Knoppen. 2018. “The Role of Strategic Purchasing in Dynamic Capability Development and Deployment: A Contingency Perspective.” International Journal of Operations & Production Management 38 (2): 446–473. doi:10.1108/IJOPM-10-2015-0656.
   Web of Science ®Google Scholar
• Brandon-Jones, E., B. Squire, and Y. G. Van Rossenberg. 2015. “The Impact of Supply Base Complexity on Disruptions and Performance: The Moderating Effects of Slack and Visibility.” International Journal of Production Research 53 (22): 6903–6918. doi:10.1080/00207543.2014.986296.
   Web of Science ®Google Scholar
• Brandon-Jones, E., B. Squire, C. Autry, and K. Petersen. 2014. “A Contingent Resource-Based Perspective of SC Resilience and Robustness.” Journal of Supply Chain Management 50 (3): 55–73. doi:10.1111/jscm.12050.
   Web of Science ®Google Scholar
• Brusset, X., and C. Teller. 2017. “SC Capabilities, Risks, and Resilience.” International Journal of Production Economics 184: 59–68. doi:10.1016/j.ijpe.2016.09.008.
   Web of Science ®Google Scholar
• Byrne, D. 2002. Complexity Theory and the Social Sciences: An Introduction: Routledge.
   Google Scholar
• Caridi, M., L. Crippa, A. Perego, A. Sianesi, and A. Tumino. 2010. “Do Virtuality and Complexity Affect Supply Chain Visibility?” International Journal of Production Economics 127 (2): 372–383. doi:10.1016/j.ijpe.2009.08.016.
   Web of Science ®Google Scholar
• Chang, W. S., and Y. T. Lin. 2019. “The Effect of Lead-Time on Supply Chain Resilience Performance.” Asia Pacific Management Review 24 (4): 298–309. doi:10.1016/j.apmrv.2018.10.004.
   Web of Science ®Google Scholar
• Chavez, R., W. Yu, M. A. Jacobs, and M. Feng. 2017. “Data-Driven Supply Chains, Manufacturing Capability and Customer Satisfaction.” Production Planning & Control 28 (11-12): 906–918. doi:10.1080/09537287.2017.1336788.
   Web of Science ®Google Scholar
• Chen, I. J., and A. Paulraj. 2004. “Towards a Theory of Supply Chain Management: The Constructs and Measurements.” Journal of Operations Management 22 (2): 119–150. doi:10.1016/j.jom.2003.12.007.
   Web of Science ®Google Scholar
• Chen, P.-T., C.-L. Lin, and W.-N. Wu. 2020. “Big Data Management in Healthcare: Adoption Challenges and Implications.” International Journal of Information Management 53: 102078. doi:10.1016/j.ijinfomgt.2020.102078.
   Web of Science ®Google Scholar
• Chen, Y., H. Chen, A. Gorkhali, Y. Lu, Y. Ma, and L. Li. 2016. “Big Data Analytics and Big Data Science: A Survey.” Journal of Management Analytics 3 (1): 1–42. doi:10.1080/23270012.2016.1141332.
   Web of Science ®Google Scholar
• Cheng, J. H., M. C. Chen, and C. M. Huang. 2014. “Assessing Inter-Organizational Innovation Performance through Relational Governance and Dynamic Capabilities in Supply Chains.” Supply Chain Management: An International Journal 19 (2): 173–186.
   Web of Science ®Google Scholar
• Chin, W. W. 1998. “Commentary: Issues and Opinion on Structural Equation Modeling.” MIS Quarterly 22 (1): 7–16.
   Web of Science ®Google Scholar
• Choi, T. Y., S. Narayanan, D. Novak, J. Olhager, J. B. Sheu, and F. Wiengarten. 2021. “Managing Extended Supply Chains.” Journal of Business Logistics 42 (2): 200–206. doi:10.1111/jbl.12276.
   Web of Science ®Google Scholar
• Choi, T. Y., and D. R. Krause. 2006. “The Supply Base and Its Complexity: implications for Transaction Costs, Risks, Responsiveness, and Innovation.” Journal of Operations Management 24 (5): 637–652. doi:10.1016/j.jom.2005.07.002.
   Web of Science ®Google Scholar
• Chopra, S., and M. S. Sodhi. 2014. “Reducing the Risk of Supply Chain Disruptions.” MIT Sloan Management Review 55 (3): 73–80.
   Web of Science ®Google Scholar
• Chowdhury, P., S. K. Paul, S. Kaisar, and A. Moktadir. 2021. “COVID-19 Pandemic Related Supply Chain Studies: A Systematic Review.” Transportation Research Part E 148.
   Google Scholar
• Chowdhury, M. M. H., M. Quaddus, and R. Agarwal. 2019. “Supply Chain Resilience for Performance: role of Relational Practices and Network Complexities.” Supply Chain Management: An International Journal 24 (5): 659–676.
   Web of Science ®Google Scholar
• Churchill, G. A. 1979. “A Paradigm for Developing Better Measures of Marketing Constructs.” Journal of Marketing Research 16 (1): 64–73. doi:10.1177/002224377901600110.
   Web of Science ®Google Scholar
• Colicchia, C.,. F. Dallari, and M. Melacini. 2010. Increasing Supply Chain Resilience in a Global Sourcing Context. Production Planning & Control 21 (7): 680–694.
   Web of Science ®Google Scholar
• Collinson, S., and M. Jay. 2012. From Complexity to Simplicity: Unleash Your Organisation’s Potential. Palgrave Macmillan.
   Google Scholar
• Craighead, C. W., J. Blackhurst, M. J. Rungtusanatham, and R. B. Handfield. 2007. “The Severity of Supply Chain Disruptions: design Characteristics and Mitigation Capabilities.” Decision Sciences 38 (1): 131–156. doi:10.1111/j.1540-5915.2007.00151.x.
   Web of Science ®Google Scholar
• Day, J. M. 2014. “Fostering Emergent Resilience: The Complex Adaptive Supply Network of Disaster Relief.” International Journal of Production Research 52 (7): 1970–1988. doi:10.1080/00207543.2013.787496.
   Web of Science ®Google Scholar
• Dev, N. K., R. Shankar, R. Gupta, and J. Dong. 2019. “Multi-Criteria Evaluation of Real-Time Key Performance Indicators of Supply Chain with Consideration of Big Data Architecture.” Computers & Industrial Engineering 128: 1076–1087. doi:10.1016/j.cie.2018.04.012.
   Web of Science ®Google Scholar
• Dittfeld, H., K. Scholten, and D. P. Van Donk. 2018. “Burden or Blessing in Disguise: interactions in Supply Chain Complexity.” International Journal of Operations & Production Management 38 (2): 314–332. doi:10.1108/IJOPM-03-2017-0158.
   Web of Science ®Google Scholar
• Dolgui, A., D. Ivanov, and B. Sokolov. 2018. “Ripple Effect in the Supply Chain: An Analysis and Recent Literature.” International Journal of Production Research 56 (1–2): 414–430. doi:10.1080/00207543.2017.1387680.
   Web of Science ®Google Scholar
• Donaldson, L. 2001. The Contingency Theory of Organizations. Thousand Oaks, CA: Sage.
   Google Scholar
• Dong, Y., K. Skowronski, S. Song, S. Venkataraman, and F. Zou. 2020. “Supply Base Innovation and Firm Financial Performance.” Journal of Operations Management 66 (7–8): 768–796. doi:10.1002/joom.1107.
   Web of Science ®Google Scholar
• Dubey, R., A. Gunasekaran, S. Childe, S. Fosso Wamba, D. Roubaud, and C. Foropon. 2019. “Empirical Investigation of Data Analytics Capability and Organizational Flexibility as Complements to SC Resilience.” International Journal of Production Research 59 (1): 1–19.
   Web of Science ®Google Scholar
• Dubey, R., Z. Luo, A. Gunasekaran, S. Akter, B. T. Hazen, and M. A. Douglas. 2018. “Big Data and Predictive Analytics in Humanitarian Supply Chains: Enabling Visibility and Coordination in the Presence of Swift Trust.” The International Journal of Logistics Management 29 (2): 485–512. doi:10.1108/IJLM-02-2017-0039.
   Web of Science ®Google Scholar
• Fan, S., R. Y. Lau, and J. L. Zhao. 2015. “Demystifying Big Data Analytics for Business Intelligence through the Lens of Marketing Mix.” Big Data Research 2 (1): 28–32. doi:10.1016/j.bdr.2015.02.006.
   Web of Science ®Google Scholar
• Fernandes, R., B. Gouveia, and C. Pinho. 2013. “Integrated Inventory Valuation in Multi-Echelon Production/Distribution Systems.” International Journal of Production Research 51 (9): 2578–2592. doi:10.1080/00207543.2012.737947.
   Web of Science ®Google Scholar
• Fernández Campos, P., P. Trucco, and L. Huaccho Huatuco. 2019. “Managing Structural and Dynamic Complexity in Supply Chains: insights from Four Case Studies.” Production Planning & Control 30 (8): 611–623. doi:10.1080/09537287.2018.1545952.
   Web of Science ®Google Scholar
• Ferraris, A., A. Mazzoleni, A. Devalle, and J. Couturier. 2019. “Big Data Analytics Capabilities and Knowledge Management: Impact on Firm Performance.” Management Decision 57 (8): 1923–1936. doi:10.1108/MD-07-2018-0825.
   Web of Science ®Google Scholar
• Finke, G. R., M. Singh, and P. Schönsleben. 2012. “Production Lead Time Variability Simulation-Insights from a Case Study.” International Journal of Industrial Engineering 19 (5): 213–220.
   Google Scholar
• Fornell, C., and D. F. Larcker. 1981. Structural Equation Models with Unobservable Variables and Measurement Error. Algebra and statistics.
   Google Scholar
• George, G.,. M. R. Haas, and A. Pentland. 2014. “Big Data and Management.” Academy of Management Journal 57 (2): 321–326. doi:10.5465/amj.2014.4002.
   Web of Science ®Google Scholar
• Giannoccaro, I., and A. Iftikhar. 2020. “Mitigating Ripple Effect in Supply Networks: The Effect of Trust and Topology on Resilience.” International Journal of Production Research 1–18. doi:10.1080/00207543.2020.1853844.
   Web of Science ®Google Scholar
• Giannoccaro, I., A. Nair, and T. Choi. 2018. “The Impact of Control and Complexity on Supply Network Performance: An Empirically Informed Investigation Using NK Simulation Analysis.” Decision Sciences 49 (4): 625–659. doi:10.1111/deci.12293.
   Web of Science ®Google Scholar
• Gölgeci, I., and O. Kuivalainen. 2020. “Does Social Capital Matter for Supply Chain Resilience? The Role of Absorptive Capacity and Marketing-Supply Chain Management Alignment.” Industrial Marketing Management 84: 63–74. doi:10.1016/j.indmarman.2019.05.006.
   Web of Science ®Google Scholar
• Gölgeci, I., and S. Y. Ponomarov. 2015. “How Does Firm Innovativeness Enable Supply Chain Resilience? The Moderating Role of Supply Uncertainty and Interdependence.” Technology Analysis & Strategic Management 27 (3): 267–282. doi:10.1080/09537325.2014.971003.
   Web of Science ®Google Scholar
• Grötsch, V. M., C. Blome, and M. C. Schleper. 2013. “Antecedents of Proactive Supply Chain Risk Management–A Contingency Theory Perspective.” International Journal of Production Research 51 (10): 2842–2867. doi:10.1080/00207543.2012.746796.
   Web of Science ®Google Scholar
• Gu, V. C., B. Zhou, Q. Cao, and J. Adams. 2021. “Exploring the Relationship between Supplier Development, Big Data Analytics Capability, and Firm Performance.” Annals of Operations Research 302: 1–22.
   Web of Science ®Google Scholar
• Gunasekaran, A., Y. Y. Yusuf, E. O. Adeleye, and T. Papadopoulos. 2018. “Agile Manufacturing Practices: The Role of Big Data and Business Analytics with Multiple Case Studies.” International Journal of Production Research 56 (1–2): 385–397. doi:10.1080/00207543.2017.1395488.
   Web of Science ®Google Scholar
• Guo, C., and X. Li. 2014. “A Multi-Echelon Inventory System with Supplier Selection and Order Allocation under Stochastic Demand.” International Journal of Production Economics 151: 37–47. doi:10.1016/j.ijpe.2014.01.017.
   Web of Science ®Google Scholar
• Habermann, M., J. Blackhurst, and A. Y. Metcalf. 2015. “Keep Your Friends Close? Supply Chain Design and Disruption Risk.” Decision Sciences 46 (3): 491–526. doi:10.1111/deci.12138.
   Web of Science ®Google Scholar
• Hair, J. F., C. M. Ringle, and M. Sarstedt. 2011. “PLS-SEM: Indeed a Silver Bullet.” Journal of Marketing Theory and Practice 19 (2): 139–152. doi:10.2753/MTP1069-6679190202.
   Google Scholar
• Hair, J. F., Jr., Black, W. C., Babin, B. J., Anderson, R. E. & L. Tatham 2006. Multivariant Data Analysis. Pearson International Edition.
   Google Scholar
• Hamel, G., and L. Välikangas. 2003. “The Quest for Resilience.” Harvard Business Review 81 (9): 52–63.
   PubMed Web of Science ®Google Scholar
• Han, J. H., Y. Wang, and M. Naim. 2017. “Reconceptualization of Information Technology Flexibility for Supply Chain Management: An Empirical Study.” International Journal of Production Economics 187: 196–215. doi:10.1016/j.ijpe.2017.02.018.
   Web of Science ®Google Scholar
• Hayes, A. F., and M. Scharkow. 2013. “The Relative Trustworthiness of Inferential Tests of the Indirect Effect in Statistical Mediation Analysis: Does Method Really Matter?” Psychological Science 24 (10): 1918–1927. doi:10.1177/0956797613480187.
   PubMed Web of Science ®Google Scholar
• Heim, G., D. Peng, and A. Jayanthi. 2014. “Longitudinal Analysis of Inhibitors of Manufacturer Delivery Performance.” Decision Sciences 45 (6): 1117–1158. doi:10.1111/deci.12102.
   Web of Science ®Google Scholar
• Hulland, J. 1999. “Use of Partial Least Squares (PLS) in Strategic Management Research: A Review of Four Recent Studies.” Strategic Management Journal 20 (2): 195–204. doi:10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7.
   Web of Science ®Google Scholar
• Iftikhar, A., L. Purvis, and I. Giannoccaro. 2021. “A Meta-Analytical Review of Antecedents and Outcomes of Firm Resilience.” Journal of Business Research 135: 408–425. doi:10.1016/j.jbusres.2021.06.048.
   Web of Science ®Google Scholar
• Iftikhar, A., I. Ali, and A. Shah. 2021. “The Impact of Big Data Analytics and Firm’s Operational Performance: mediating Role of Knowledge Management Process.” In: 2nd Asia Pacific International Conference on Industrial Engineering and Operations Management, 14–16 September Surakarta, Indonesia.
   Google Scholar
• Isik, F. 2010. “An Entropy-Based Approach for Measuring Complexity in Supply Chains.” International Journal of Production Research 48 (12): 3681–3696. doi:10.1080/00207540902810593.
   Web of Science ®Google Scholar
• Ivanov, D. 2017. “Simulation-Based Ripple Effect Modelling in the Supply Chain.” International Journal of Production Research 55 (7): 2083–2101. doi:10.1080/00207543.2016.1275873.
   Web of Science ®Google Scholar
• Ivanov, D., A. Dolgui, B. Sokolov, and M. Ivanova. 2017. “Literature Review on Disruption Recovery in the Supply Chain.” International Journal of Production Research 55 (20): 6158–6174. doi:10.1080/00207543.2017.1330572.
   Web of Science ®Google Scholar
• Jeble, S., R. Dubey, S. J. Childe, T. Papadopoulos, D. Roubaud, and A. Prakash. 2018. “Impact of Big Data and Predictive Analytics Capability on Supply Chain Sustainability.” The International Journal of Logistics Management 29 (2): 513–538. doi:10.1108/IJLM-05-2017-0134.
   Web of Science ®Google Scholar
• Kaplan, R. S., and D. P. Norton. 2008. “Mastering the Management System.” Harvard Business Review 86 (1): 1–17.
   Web of Science ®Google Scholar
• Kauffman, S. A. 1993. The Origins of Order: Self-Organization and Selection in Evolution. Oxford University Press.
   Google Scholar
• Ketokivi, M. 2009. “Elaborating the Contingency Theory of Organizations: The Case of Manufacturing Flexibility Strategies.” Production and Operations Management 15 (2): 215–228. doi:10.1111/j.1937-5956.2006.tb00241.x.
   Google Scholar
• Kleindorfer, P. R., and G. H. Saad. 2009. “Managing Disruption Risks in Supply Chains.” Production and Operations Management 14 (1): 53–68. doi:10.1111/j.1937-5956.2005.tb00009.x.
   Web of Science ®Google Scholar
• Kock, N. 2015. “Common Method Bias in PLS-SEM.” International Journal of e-Collaboration 11 (4): 1–10. doi:10.4018/ijec.2015100101.
   Web of Science ®Google Scholar
• Koufteros, X., M. Vonderembse, and J. Jayaram. 2005. “Internal and External Integration for Product Development: The Contingency Effects of Uncertainty, Equivocality, and Platform Strategy.” Decision Sciences 36 (1): 97–133. doi:10.1111/j.1540-5915.2005.00067.x.
   Web of Science ®Google Scholar
• Lai, Y., H. Sun, and J. Ren. 2018. “Understanding the Determinants of Big Data Analytics (BDA) Adoption in Logistics and Supply Chain Management: An Empirical Investigation.” The International Journal of Logistics Management 29 (2): 676–703. doi:10.1108/IJLM-06-2017-0153.
   Web of Science ®Google Scholar
• Lamba, K., and S. P. Singh. 2017. “Big Data in Operations and Supply Chain Management: Current Trends and Future Perspectives.” Production Planning & Control 28 (11-12): 877–890. doi:10.1080/09537287.2017.1336787.
   Web of Science ®Google Scholar
• Latif, Z., M. Z. Tunio, Z. H. Pathan, Z. Jianqiu, L. Ximei, and S. K. Sadozai. 2018. “A Review of Policies concerning Development of Big Data Industry in Pakistan: Subtitle: Development of Big Data Industry in Pakistan.” Paper presented at the 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET). doi:10.1109/ICOMET.2018.8346315.
   Google Scholar
• Lempogo, F., E. O. Yeboah-Boateng, and W. L. Brown-Acquaye. 2021. “Big Data Analytics in Developing Economies: Harnessing Insights and Creating Value.” In Digital Technology Advancements in Knowledge Management, 149–166. IGI Global.
   Google Scholar
• Li, H., and M. Amini. 2012. “A Hybrid Optimisation Approach to Configure a Supply Chain for New Product Diffusion: A Case Study of Multiple-Sourcing Strategy.” International Journal of Production Research 50 (11): 3152–3171. doi:10.1080/00207543.2011.597789.
   Web of Science ®Google Scholar
• Lu, G., and G. Shang. 2017. “Impact of Supply Base Structural Complexity on Financial Performance: Roles of Visible and Not-so-Visible Characteristics.” Journal of Operations Management 53: 23–44.
   Web of Science ®Google Scholar
• Mandal, S., S. Bhattacharya, V. Korasiga, and R. Sarathy. 2017. “The Dominant Influence of Logistics Capabilities on Integration: Empirical Evidence from SC Resilience.” International Journal of Disaster Resilience in the Built Environment 8 (4): 357–374. doi:10.1108/IJDRBE-05-2016-0019.
   Web of Science ®Google Scholar
• Manhart, P., J. K. Summers, and J. Blackhurst. 2020. “A Meta‐Analytic Review of Supply Chain Risk Management: Assessing Buffering and Bridging Strategies and Firm Performance.” Journal of Supply Chain Management 56 (3): 66–87. doi:10.1111/jscm.12219.
   Web of Science ®Google Scholar
• Manuj, I., and F. Sahin. 2011. “A Model of Supply Chain and Supply Chain Decision‐Making Complexity.” International Journal of Physical Distribution & Logistics Management 41 (5): 511–549. doi:10.1108/09600031111138844.
   Web of Science ®Google Scholar
• Marler, J. H., and J. W. Boudreau. 2017. “An Evidence-Based Review of HR Analytics.” The International Journal of Human Resource Management 28 (1): 3–26. doi:10.1080/09585192.2016.1244699.
   Web of Science ®Google Scholar
• Maroufkhani, P., M. L. Tseng, M. Iranmanesh, W. K. W. Ismail, and H. Khalid. 2020. “Big Data Analytics Adoption: Determinants and Performances among Small to Medium-Sized Enterprises.” International Journal of Information Management 54: 102190. doi:10.1016/j.ijinfomgt.2020.102190.
   Web of Science ®Google Scholar
• Marr, B. 2016. Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results. John Wiley & Sons.
   Google Scholar
• Mason, R., L. Iosif, G. MacKerron, and J. Fernie. 2007. “Managing Complexity in Agile Global Fashion Industry Supply Chains.” The International Journal of Logistics Management 18 (2): 238–254. doi:10.1108/09574090710816959.
   Google Scholar
• Matsuo, H. 2015. “Implications of the Tohoku Earthquake for Toyota’s Coordination Mechanism: Supply Chain Disruption of Automotive Semiconductors.” International Journal of Production Economics 161: 217–227. doi:10.1016/j.ijpe.2014.07.010.
   Web of Science ®Google Scholar
• McAfee, A., E. Brynjolfsson, T. H. Davenport, D. J. Patil, and D. Barton. 2012. “Big Data: The Management Revolution.” Harvard Business Review 90 (10): 60–68.
   PubMed Web of Science ®Google Scholar
• McMillan, E. 2008. Complexity, Management and the Dynamics of Change: Challenges for Practice. Routledge.
   Google Scholar
• Melnyk, S. A., D. J. Closs, S. E. Griffis, C. W. Zobel, and J. R. Macdonald. 2014. “Understanding Supply Chain Resilience.” Supply Chain Management Review 18 (1): 34–41.
   Web of Science ®Google Scholar
• Mikalef, P., J. Krogstie, I. O. Pappas, and P. Pavlou. 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. doi:10.1016/j.im.2019.05.004.
   Web of Science ®Google Scholar
• Moktadir, M. A., S. M. Ali, S. K. Paul, and N. Shukla. 2019. “Barriers to Big Data Analytics in Manufacturing Supply Chains: A Case Study from Bangladesh.” Computers & Industrial Engineering 128: 1063–1075. doi:10.1016/j.cie.2018.04.013.
   Web of Science ®Google Scholar
• Moretto, A., S. Ronchi, and A. S. Patrucco. 2017. “Increasing the Effectiveness of Procurement Decisions: The Value of Big Data in the Procurement Process.” International Journal of RF Technologies 8 (3): 79–103. doi:10.3233/RFT-171670.
   Google Scholar
• Mubarik, M. S., N. Naghavi, M. Mubarik, S. Kusi-Sarpong, S. A. Khan, S. I. Zaman, and S. H. A. Kazmi. 2021. “Resilience and Cleaner Production in Industry 4.0: Role of Supply Chain Mapping and Visibility.” Journal of Cleaner Production 292: 126058. doi:10.1016/j.jclepro.2021.126058.
   Web of Science ®Google Scholar
• Nguyen, T., Z. Li, V. Spiegler, P. Ieromonachou, and Y. Lin. 2018. “Big Data Analytics in Supply Chain Management: A State-of-the-Art Literature Review.” Computers & Operations Research 98: 254–264. doi:10.1016/j.cor.2017.07.004.
   Web of Science ®Google Scholar
• Opresnik, D., and M. Taisch. 2015. “The Value of Big Data in Servitization.” International Journal of Production Economics 165: 174–184. doi:10.1016/j.ijpe.2014.12.036.
   Web of Science ®Google Scholar
• Papadopoulos, T., A. Gunasekaran, R. Dubey, and S. Fosso Wamba. 2017. “Big Data and Analytics in Operations and Supply Chain Management: Managerial Aspects and Practical Challenges.” Production Planning & Control 28 (11–12): 873–876. doi:10.1080/09537287.2017.1336795.
   Web of Science ®Google Scholar
• Pavlou, P. A., H. Liang, and Y. Xue. 2007. “Understanding and Mitigating Uncertainty in Online Exchange Relationships: A Principal-Agent Perspective.” MIS Quarterly 31 (1): 105–136. doi:10.2307/25148783.
   Web of Science ®Google Scholar
• Peng, D. X., and F. Lai. 2012. “Using Partial Least Squares in Operations Management Research: A Practical Guideline and Summary of past Research.” Journal of Operations Management 30 (6): 467–480. doi:10.1016/j.jom.2012.06.002.
   Web of Science ®Google Scholar
• Podsakoff, P. M., and D. W. Organ. 1986. “Self-Reports in Organizational Research: Problems and Prospects.” Journal of Management 12 (4): 531–544. doi:10.1177/014920638601200408.
   Web of Science ®Google Scholar
• Podsakoff, P. M., S. B. MacKenzie, J. Y. Lee, and N. P. Podsakoff. 2003. “Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies.” The Journal of Applied Psychology 88 (5): 879–903.
   PubMed Web of Science ®Google Scholar
• Ponomarov, S., and M. Holcomb. 2009. “Understanding the Concept of SC Resilience.” The International Journal of Logistics Management 20 (1): 124–143. doi:10.1108/09574090910954873.
   Web of Science ®Google Scholar
• Prahalad, C. K., and M. S. Krishnan. 2002. “The Dynamic Synchronization of Strategy and Information Technology.” Sloan Management Review 43 (4): 24–33.
   Google Scholar
• Prasad, S., R. Zakaria, and N. Altay. 2018. “Big Data in Humanitarian Supply Chain Networks: A Resource Dependence Perspective.” Annals of Operations Research 270 (1–2): 383–413. doi:10.1007/s10479-016-2280-7.
   Web of Science ®Google Scholar
• Preacher, K. J., and A. F. Hayes. 2008. “Asymptotic and Resampling Strategies for Assessing and Comparing Indirect Effects in Multiple Mediator Models.” Behavior Research Methods 40 (3): 879–891.
   PubMed Web of Science ®Google Scholar
• Queiroz, M. M., D. Ivanov, A. Dolgui, and S. F. Wamba. 2020. “Impacts of Epidemic Outbreaks on Supply Chains: mapping a Research Agenda amid the COVID-19 Pandemic through a Structured Literature Review.” Annals of Operations Research. doi:10.1007/s10479-020-03685-7.
   PubMed Web of Science ®Google Scholar
• Ramanathan, R.,. E. Philpott, Y. Duan, and G. Cao. 2017. “Adoption of Business Analytics and Impact on Performance: A Qualitative Study in Retail.” Production Planning & Control 28 (11–12): 985–998. doi:10.1080/09537287.2017.1336800.
   Web of Science ®Google Scholar
• Reinartz, W., M. Haenlein, and J. Henseler. 2009. “An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM.” International Journal of Research in Marketing 26 (4): 332–344. doi:10.1016/j.ijresmar.2009.08.001.
   Web of Science ®Google Scholar
• Romano, P., and M. Formentini. 2012. “Designing and Implementing Open Book Accounting in Buyer–Supplier Dyads: A Framework for Supplier Selection and Motivation.” International Journal of Production Economics 137 (1): 68–83. doi:10.1016/j.ijpe.2012.01.013.
   Web of Science ®Google Scholar
• Romero, C. D. G., J. K. D Barriga, and J. I. R. Molano. 2016. June. “Big Data Meaning in the Architecture of IoT for Smart Cities.” In International Conference on Data Mining and Big Data (pp. 457–465). Cham: Springer.
   Google Scholar
• Salvador, F., C. Forza, and M. Rungtusanatham. 2002. “Modularity, Product Variety, Production Volume, and Component Sourcing: theorizing beyond Generic Prescriptions.” Journal of Operations Management 20 (5): 549–575. doi:10.1016/S0272-6963(02)00027-X.
   Web of Science ®Google Scholar
• Sanders, N. R. 2014. Big Data Driven Supply Chain Management: A Framework for Implementing Analytics and Turning Information into Intelligence. Pearson Education.
   Google Scholar
• Sanders, N. R., and R. Ganeshan. 2018. “Big Data in Supply Chain Management.” Production and Operations Management 27 (10): 1745–1748. doi:10.1111/poms.12892.
   Web of Science ®Google Scholar
• Schoenherr, T., and C. Speier-Pero. 2015. “Data Science, Predictive Analytics, and Big Data in Supply Chain Management: Current State and Future Potential.” Journal of Business Logistics 36 (1): 120–132. doi:10.1111/jbl.12082.
   Web of Science ®Google Scholar
• Senge, P. 2006. The Fifth Discipline: The Art and Practice of the Learning Organization. New York, NY: Doubleday.
   Google Scholar
• Serdarasan, S. 2013. “A Review of Supply Chain Complexity Drivers.” Computers & Industrial Engineering 66 (3): 533–540. doi:10.1016/j.cie.2012.12.008.
   Web of Science ®Google Scholar
• Shamout, M. D. 2020. “Supply Chain Data Analytics and Supply Chain Agility: A Fuzzy Sets (fsQCA) Approach.” International Journal of Organizational Analysis 28 (5): 1055–1067. doi:10.1108/IJOA-05-2019-1759.
   Web of Science ®Google Scholar
• Sheffi, Y., and J. Rice. 2005. “A SC View of Resilient Enterprise.” MIT Sloan Management Review 47 (1): 41–48.
   Web of Science ®Google Scholar
• Simchi-Levi, D., L. Snyder, and M. Watson. 2002. “Strategies for Uncertain Times.” Supply Chain Management Review 6 (1): 11–12.
   Google Scholar
• Simon, H. A. 1962. “The Architecture of Complexity.” Proceedings of the American Philosophical Society 106 (6): 467–482.
   Google Scholar
• Singh, N. P., and S. Singh. 2019. “Building Supply Chain Risk Resilience: Role of Big Data Analytics in Supply Chain Disruption Mitigation.” Benchmarking: An International Journal 26 (7): 2318–2342. doi:10.1108/BIJ-10-2018-0346.
   Web of Science ®Google Scholar
• Sirmon, D. G., and M. A. Hitt. 2009. “Contingencies within Dynamic Managerial Capabilities: Interdependent Effects of Resource Investment and Deployment on Firm Performance.” Strategic Management Journal 30 (13): 1375–1394. doi:10.1002/smj.791.
   Web of Science ®Google Scholar
• Sivadasan, S.,. J. Efstathiou, G. Frizelle, R. Shirazi, and A. Calinescu. 2002. “An Information‐Theoretic Methodology for Measuring the Operational Complexity of Supplier‐Customer Systems.” International Journal of Operations & Production Management 22 (1): 80–102. doi:10.1108/01443570210412088.
   Web of Science ®Google Scholar
• Song, J. S., H. Zhang, Y. Hou, and M. Wang. 2010. “The Effect of Lead Time and Demand Uncertainties in (r, q) Inventory Systems.” Operations Research 58 (1): 68–80. doi:10.1287/opre.1090.0711.
   Web of Science ®Google Scholar
• Souza, G. C. 2014. “Supply Chain Analytics.” Business Horizons 57 (5): 595–605. doi:10.1016/j.bushor.2014.06.004.
   Web of Science ®Google Scholar
• Srinivasan, R., and M. Swink. 2018. “An Investigation of Visibility and Flexibility as Complements to Supply Chain Analytics: An Organizational Information Processing Theory Perspective.” Production and Operations Management 27 (10): 1849–1867. doi:10.1111/poms.12746.
   Web of Science ®Google Scholar
• Stone, J., and S. Rahimifard. 2018. “Resilience in Agri-Food SCs: A Critical Analysis of the Literature and Synthesis of a Novel Framework.” Supply Chain Management: An International Journal 23 (3): 207–238. doi:10.1108/SCM-06-2017-0201.
   Web of Science ®Google Scholar
• Tang, C., and B. Tomlin. 2008. “The Power of Flexibility for Mitigating Supply Chain Risks.” International Journal of Production Economics 116 (1): 12–27. doi:10.1016/j.ijpe.2008.07.008.
   Web of Science ®Google Scholar
• Teece, D. J., G. Pisano, and A. Shuen. 1997. “Dynamic Capabilities and Strategic Management.” Strategic Management Journal 18 (7): 509–533. doi:10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z.
   Web of Science ®Google Scholar
• Tenenhaus, M., V. E. Vinzi, Y. M. Chatelin, and C. Lauro. 2005. “PLS Path Modeling.” Computational Statistics & Data Analysis 48 (1): 159–205. doi:10.1016/j.csda.2004.03.005.
   Web of Science ®Google Scholar
• Tiwari, S., H.-M. Wee, and Y. Daryanto. 2018. “Big Data Analytics in Supply Chain Management between 2010 and 2016: Insights to Industries.” Computers & Industrial Engineering 115: 319–330. doi:10.1016/j.cie.2017.11.017.
   Web of Science ®Google Scholar
• Tukamuhabwa, B. R., M. Stevenson, J. Busby, and M. Zorzini. 2015. “Supply Chain Resilience: definition, Review and Theoretical Foundations for Further Study.” International Journal of Production Research 53 (18): 5592–5623. doi:10.1080/00207543.2015.1037934.
   Web of Science ®Google Scholar
• Turner, N., J. Aitken, and C. Bozarth. 2018. “A Framework for Understanding Managerial Responses to Supply Chain Complexity.” International Journal of Operations & Production Management 38 (6): 1433–1466. doi:10.1108/IJOPM-01-2017-0062.
   Web of Science ®Google Scholar
• Vachon, S., and R. D. Klassen. 2002. “An Exploratory Investigation of the Effects of Supply Chain Complexity on Delivery Performance.” IEEE Transactions on Engineering Management 49 (3): 218–230. doi:10.1109/TEM.2002.803387.
   Web of Science ®Google Scholar
• Vanpoucke, E., A. Vereecke, and M. Wetzels. 2014. “Developing Supplier Integration Capabilities for Sustainable Competitive Advantage: A Dynamic Capabilities Approach.” Journal of Operations Management 32 (7-8): 446–461. doi:10.1016/j.jom.2014.09.004.
   Web of Science ®Google Scholar
• Vlajic, J. V., S. W. van Lokven, R. Haijema, and J. G. van Der Vorst. 2013. “Using Vulnerability Performance Indicators to Attain Food Supply Chain Robustness.” Production Planning & Control 24 (8–9): 785–799. doi:10.1080/09537287.2012.666869.
   Web of Science ®Google Scholar
• Wagner, S. M., and C. Bode. 2006. “An Empirical Investigation into Supply Chain Vulnerability.” Journal of Purchasing and Supply Management 12 (6): 301–312. doi:10.1016/j.pursup.2007.01.004.
   Google Scholar
• Waller, M. A., and S. E. Fawcett. 2013. “Data Science, Predictive Analytics, and Big Data: A Revolution That Will Transform Supply Chain Design and Management.” Journal of Business Logistics 34 (2): 77–84. doi:10.1111/jbl.12010.
   Web of Science ®Google Scholar
• Wamba, S. F., S. Akter, A. Edwards, G. Chopin, and D. Gnanzou. 2015. “How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study.” International Journal of Production Economics 165: 234–246. doi:10.1016/j.ijpe.2014.12.031.
   Web of Science ®Google Scholar
• Wamba, S. F., R. Dubey, A. Gunasekaran, and S. Akter. 2020. “The Performance Effects of Big Data Analytics and Supply Chain Ambidexterity: The Moderating Effect of Environmental Dynamism.” International Journal of Production Economics 222: 107498. doi:10.1016/j.ijpe.2019.09.019.
   Web of Science ®Google Scholar
• Wamba, S. F., A. Gunasekaran, R. Dubey, and E. W. Ngai. 2018. “Big Data Analytics in Operations and Supply Chain Management.” Annals of Operations Research 270 (1–2): 1–4. doi:10.1007/s10479-018-3024-7.
   Web of Science ®Google Scholar
• Wang, G., A. Gunasekaran, E. W. Ngai, and T. Papadopoulos. 2016. “Big Data Analytics in Logistics and Supply Chain Management: Certain Investigations for Research and Applications.” International Journal of Production Economics 176: 98–110. doi:10.1016/j.ijpe.2016.03.014.
   Web of Science ®Google Scholar
• Wang, Y., L. Kung, and T. A. Byrd. 2018. “Big Data Analytics: Understanding Its Capabilities and Potential Benefits for Healthcare Organizations.” Technological Forecasting and Social Change 126: 3–13. doi:10.1016/j.techfore.2015.12.019.
   Web of Science ®Google Scholar
• Wetzels, M., G. Odekerken-Schröder, and C. Van Oppen. 2009. “Using PLS Path Modelling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration.” MIS Quarterly 33 (1): 177–195.
   Web of Science ®Google Scholar
• Wiedmer, R., Z. S. Rogers, M. Polyviou, C. Mena, and S. Chae. 2021. “The Dark and Bright Sides of Complexity: A Dual Perspective on Supply Network Resilience.” Journal of Business Logistics 42 (3): 336–359. doi:10.1111/jbl.12264.
   Web of Science ®Google Scholar
• Wilkins, J. 2013. Big data and its impact on manufacturing [online]. Accessed 20 February 2020. http://www.dpaonthenet.net/article/65238/Big-data-and-its-impact-on-manufacturing.aspx
   Google Scholar
• Winter, S. G. 2003. “Understanding Dynamic Capabilities.” Strategic Management Journal 24 (10): 991–995. doi:10.1002/smj.318.
   Web of Science ®Google Scholar
• Wong, C. W., K. H. Lai, and E. W. Bernroider. 2015. “The Performance of Contingencies of Supply Chain Information Integration: The Roles of Product and Market Complexity.” International Journal of Production Economics 165: 1–11. doi:10.1016/j.ijpe.2015.03.005.
   Web of Science ®Google Scholar
• Wu, Y., G. Frizelle, and J. Efstathiou. 2007. “A Study on the Cost of Operational Complexity in Customer–Supplier Systems.” International Journal of Production Economics 106 (1): 217–229. doi:10.1016/j.ijpe.2006.06.004.
   Web of Science ®Google Scholar
• Wu, Z., and T. Y. Choi. 2005. “Supplier–Supplier Relationships in the Buyer–Supplier Triad: Building Theories from Eight Case Studies.” Journal of Operations Management 24 (1): 27–52. doi:10.1016/j.jom.2005.02.001.
   Web of Science ®Google Scholar
• Wu, L., B. Lou, and L. Hitt. 2019. “Data Analytics Supports Decentralized Innovation.” Management Science, 65 (10): 4863–4877.
   Google Scholar
• Yu, W., M. A. Jacobs, R. Chavez, and J. Yang. 2019. “Dynamism, Disruption Orientation, and Resilience in the Supply Chain and the Impacts on Financial Performance: A Dynamic Capabilities Perspective.” International Journal of Production Economics 218: 352–362. doi:10.1016/j.ijpe.2019.07.013.
   Web of Science ®Google Scholar
• Zhan, Y., and K. H. Tan. 2020. “An Analytic Infrastructure for Harvesting Big Data to Enhance Supply Chain Performance.” European Journal of Operational Research 281 (3): 559–574. doi:10.1016/j.ejor.2018.09.018.
   Web of Science ®Google Scholar
• Zollo, M., and S. G. Winter. 2002. “Deliberate Learning and the Evolution of Dynamic Capabilities.” Organization Science 13 (3): 339–351. doi:10.1287/orsc.13.3.339.2780.
   Web of Science ®Google Scholar