References
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.
Choi, T. M., Wallace, S. W., & Wang, Y. (2017). Big data analytics in operations management. Production and Operations Management. https://doi.org/10.1111/poms.12838.
Dubey, R., & Gunasekaran, A. (2015). Education and training for successful career in big data and business analytics. Industrial and Commercial Training, 47(4), 174–181.
Fosso Wamba, S., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (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.
Fosso Wamba, S., Angappa, G., Papadopoulos, T., & Ngai, E. (2018). Big data analytics in logistics and supply chain management. The International Journal of Logistics Management, 29(2), 478–484.
Fosso Wamba, S., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365.
Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S. F., Childe, S. J., Hazen, B., et al. (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.
Hazen, B. T., Boone, C. A., Ezell, J. D., & Jones-Farmer, L. A. (2014). Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications. International Journal of Production Economics, 154, 72–80.
Kiron, D., Prentice, P. K., & Ferguson, R. B. (2014). The analytics mandate. MIT Sloan Management Review, 55(4), 1–25.
Papadopoulos, T., Gunasekaran, A., Dubey, R., Altay, N., Childe, S. J., & Fosso-Wamba, S. (2017). The role of big data in explaining disaster resilience in supply chains for sustainability. Journal of Cleaner Production, 142, 1108–1118.
Sanders, N. R., & Ganeshan, R. (2015). Special issue of production and operations management on “big data in supply chain management”. Production and Operations Management, 24(7), 1193–1194.
Schoenherr, T., & Speier-Pero, C. (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.
Srinivasan, R., & Swink, M. (2017). An investigation of visibility and flexibility as complements to supply chain analytics: An organizational information processing theory perspective. Production and Operations Management. https://doi.org/10.1111/poms.12746.
Waller, M. A., & Fawcett, S. E. (2013a). 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.
Waller, M. A., & Fawcett, S. E. (2013b). Click here for a data scientist: Big data, predictive analytics, and theory development in the era of a maker movement supply chain. Journal of Business Logistics, 34(4), 249–252.
Wang, G., Gunasekaran, A., Ngai, E. W., & Papadopoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International Journal of Production Economics, 176, 98–110.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Fosso Wamba, S., Gunasekaran, A., Dubey, R. et al. Big data analytics in operations and supply chain management. Ann Oper Res 270, 1–4 (2018). https://doi.org/10.1007/s10479-018-3024-7
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-018-3024-7