[
Akter, S., Wamba, S.F., Gunasekaran, A., Dubey, R., Childe, S.J., 2016. How to improve organization performance using big data analytics capability and business strategy alignment? Int. J. Prod. Econ. 182, 113–131.
]Search in Google Scholar
[
Ayvaz, B., Bolat, B., & Aydın, N. (2015). Stochastic reverse logistics network design for waste of electrical and electronic equipment. Resources, conservation and recycling, 104, 391-404.
]Search in Google Scholar
[
Bag, S., Wood, L. C., Xu, L., Dhamija, P., & Kayikci, Y. (2020). Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. Resources, Conservation and Recycling, 153, 104559.
]Search in Google Scholar
[
Baidya, R., Debnath, B., Ghosh, S. K., & Rhee, S. W. (2020). Supply chain analysis of e-waste processing plants in developing countries. Waste Management & Research, 38(2), 173-183.
]Search in Google Scholar
[
Baldé, C. P., Wang, F., Kuehr, R., & Huisman, J. (2017). The Global E-waste Monitor 2017: Quantities, Flows and Resources. United Nations University, International Telecommunication Union, & International Solid Waste Association. https://www.itu.int/en/ITU-D/Climate-Change/Documents/GEM%202017/Global-E-waste%20Monitor%202017.pdf
]Search in Google Scholar
[
Braganza, A., Brooks, L., Nepelski, D., Ali, M., Moro, R., 2017. Resource management in big data initiatives: processes and dynamic capabilities. J. Bus. Res. 70, 328–337.
]Search in Google Scholar
[
Cooper, D. R., and P. S. Schindler. “Business Research Methods International Edition McGraw Hill.” (2003).
]Search in Google Scholar
[
Danish, A., Mosaberpanah, M. A., Ozbakkaloglu, T., Salim, M. U., Khurshid, K., Bayram, M., ... & Qader, D. N. (2023). A compendious review on the influence of e-waste aggregates on the properties of concrete. Case Studies in Construction Materials, 18, e01740.
]Search in Google Scholar
[
Daugherty, P.J., Autry, C.W. and Ellinger, A.E. (2001), “Reverse logistics: the relationship between resource commitment and program performance”, Journal of Business Logistics, Vol. 22 No. 1, pp. 107-123.
]Search in Google Scholar
[
Davenport, Thomas H., Paul Barth, and Randy Bean. “How big data is different.” MIT Sloan Management Review 54, no. 1 (2012): 43.
]Search in Google Scholar
[
Demajorovic, J., Augusto, E. E. F., & Souza, M. T. S. D. (2016). Reverse logistics of e-waste in developing countries: challenges and prospects for the Brazilian model. Ambiente & Sociedade, 19(2), 117-136.
]Search in Google Scholar
[
Dries, N., Van Acker, F., Verbruggen, M., 2012. How ‘boundaryless’ are the careers of high potentials, key experts and average performers? J. Vocat. Behav. 81 (2), 271–279.
]Search in Google Scholar
[
Easterby-Smith, M., Thorpe, R., & Jackson, P. R. (2012). Management research. Sage.
]Search in Google Scholar
[
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
]Search in Google Scholar
[
Forti, V., Baldé, C. P., Kuehr, R., & Bel, G. (2020). The Global E-waste Monitor 2020: Quantities, Flows and the Circular Economy Potential. United Nations University, International Telecommunication Union, & International Solid Waste Association. https://www.itu.int/en/ITU-D/Environment/Documents/Toolbox/GEM_2020_def.pdf
]Search in Google Scholar
[
Garlapati, V. K. (2016). E-waste in India and developed countries: Management, recycling, business and biotechnological initiatives. Renewable and Sustainable Energy Reviews, 54, 874-881.
]Search in Google Scholar
[
Golicic, Susan L., and Carlo D. Smith. “A meta‐analysis of environmentally sustainable supply chain management practices and firm performance.” Journal of supply chain management 49, no. 2 (2013): 78-95.
]Search in Google Scholar
[
Gunasekaran, Angappa, and Bulent Kobu. “Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995–2004) for research and applications.” International journal of production research 45, no. 12 (2007): 2819-2840.
]Search in Google Scholar
[
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data analysis 7th Edition. Pearson Prentice Hall. New Jersey.
]Search in Google Scholar
[
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
]Search in Google Scholar
[
Huang, Y. C., & Yang, M. L. (2014). Reverse logistics innovation, institutional pressures and performance. Management research review, 37(7), 615-641.
]Search in Google Scholar
[
Hult, G. Tomas M., David J. Ketchen, David A. Griffith, Brian R. Chabowski, Mary K. Hamman, Bernadine Johnson Dykes, Wesley A. Pollitte, and S. Tamer Cavusgil. “An assessment of the measurement of performance in international business research.” Journal of International Business Studies39, no. 6 (2008): 1064-1080.
]Search in Google Scholar
[
Hunt, S.D. and Morgan, R.M. (1996), “The resource-advantage theory of competition: dynamics, path dependencies, and evolutionary dimensions”, Journal of Marketing, Vol. 60 No. 4, pp. 107-114.
]Search in Google Scholar
[
Ikhlayel, M. (2018). An integrated approach to establish e-waste management systems for developing countries. Journal of Cleaner Production, 170, 119-130.
]Search in Google Scholar
[
Ilankoon, I. M. S. K., Yousef Ghorbani, Meng Nan Chong, Gamini Herath, Thandazile Moyo, and Jochen Petersen. “E-waste in the international context–A review of trade flows, regulations, hazards, waste management strategies and technologies for value recovery.” Waste Management 82 (2018): 258-275.
]Search in Google Scholar
[
Islam, M. T., & Huda, N. (2018). Reverse logistics and closed-loop supply chain of Waste Electrical and Electronic Equipment (WEEE)/E-waste: A comprehensive literature review. Resources, Conservation and Recycling, 137, 48-75.
]Search in Google Scholar
[
Jack, E.P., Powers, T.L. and Skinner, L. (2010), “Reverse logistics capabilities: antecedents and cost savings”, International Journal of Physical Distribution & Logistics Management, Vol. 40 No. 3, pp. 228-246.
]Search in Google Scholar
[
Janssen, M., van der Voort, H., Wahyudi, A., 2017. Factors influencing big data decisionmaking quality. J. Bus. Res. 70, 338–345.
]Search in Google Scholar
[
John, S. T., Sridharan, R., & Kumar, P. R. (2018). Reverse logistics network design: a case of mobile phones and digital cameras. The International Journal of Advanced Manufacturing Technology, 94(1-4), 615-631.
]Search in Google Scholar
[
Kahhat, R., Kim, J., Xu, M., Allenby, B., Williams, E., & Zhang, P. (2008). Exploring e-waste management systems in the United States. Resources, conservation and recycling, 52(7), 955-964.
]Search in Google Scholar
[
Kang, K. D., Kang, H., Ilankoon, I. M. S. K., & Chong, C. Y. (2020). Electronic waste collection systems using Internet of Things (IoT): Household electronic waste management in Malaysia. Journal of cleaner production, 252, 119801.
]Search in Google Scholar
[
Khalili-Damghani, K., Tavana, M., & Najmodin, M. (2015). REVERSE LOGISTICS AND SUPPLY CHAINS: A STRUCTURAL EQUATION MODELING INVESTIGATION. International Journal of Industrial Engineering, 22(3).
]Search in Google Scholar
[
Khetriwal, D. S., Kraeuchi, P., & Widmer, R. (2009). Producer responsibility for e-waste management: key issues for consideration–learning from the Swiss experience. Journal of environmental management, 90(1), 153-165.
]Search in Google Scholar
[
Kinobe, J. R., Gebresenbet, G., & Vinnerås, B. (2012). Reverse logistics related to waste.
]Search in Google Scholar
[
Lara, P., Sánchez, M., Herrera, A., Valdivieso, K., & Villalobos, J. (2019, June). Modeling Reverse Logistics Networks: A Case Study for E-Waste Management Policy. In International Conference on Advanced Information Systems Engineering (pp. 158-169). Springer, Cham.
]Search in Google Scholar
[
Leclerc, S. H., & Badami, M. G. (2020). Extended producer responsibility for E-waste management: Policy drivers and challenges. Journal of Cleaner Production, 251, 119657.
]Search in Google Scholar
[
Mahdi Ikhlayel, 2017, An integrated approach to establish e-waste management systems for developing countries, Elsevier Ltd0959-6526/© 2017, https://doi.org/10.1016/j.jclepro.2017.09.137]. Industry 4.0 framework facilitates the high data driven-ness in address disposal strategies.
]Search in Google Scholar
[
Malik, A.R., Singh, P., 2014. ‘High potential’ programs: let’s hear it for ‘B’ players. Hum. Resour. Manag. Rev. 24 (4), 330–346.
]Search in Google Scholar
[
Manyika, James, Michael Chui, Jacques Bughin, Richard Dobbs, Peter Bisson, and Alex Marrs. Disruptive technologies: Advances that will transform life, business, and the global economy. Vol. 180. San Francisco, CA: McKinsey Global Institute, 2013.
]Search in Google Scholar
[
Marsh, H. W., & Hocevar, D. (1985). Application of confirmatory factor analysis to the study of self-concept: First-and higher order factor models and their invariance across groups. Psychological bulletin, 97(3), 562.
]Search in Google Scholar
[
Musson, S. E., Jang, Y. C., Townsend, T. G., & Chung, I. H. (2000). Characterization of lead leachability from cathode ray tubes using the toxicity characteristic leaching procedure. Environmental science & technology, 34(20), 4376-4381.
]Search in Google Scholar
[
Olorunniwo, F.O. and Li, X.M. (2010), “Information sharing and collaboration practices in reverse logistics”, Supply Chain Management: An International Journal, Vol. 15 No. 6, pp. 454-462.
]Search in Google Scholar
[
Rekha, A. G., & Resmi, A. G. (2021). An empirical study of blockchain technology, innovation, service quality and firm performance in the banking industry. In Eurasian Economic Perspectives: Proceedings of the 29th Eurasia Business and Economics Society Conference (pp. 75-89). Springer International Publishing.
]Search in Google Scholar
[
Richey Jr, Robert Glenn, Robert Glenn Richey Jr, Tyler R. Morgan, Tyler R. Morgan, Kristina Lindsey-Hall, Kristina Lindsey-Hall, Frank G. Adams, and Frank G. Adams. “A global exploration of big data in the supply chain.” International Journal of Physical Distribution & Logistics Management 46, no. 8 (2016): 710-739.
]Search in Google Scholar
[
Richey, R.G., Genchey, S.E. and Daugherty, P.J. (2005), “The role of resource commitment and innovation in reverse logistics performance”, International Journal of Physical Distribution and Logistics Management, Vol. 35 No. 4, pp. 233-257.
]Search in Google Scholar
[
Safdar, N., Khalid, R., Ahmed, W., & Imran, M. (2020). Reverse logistics network design of e-waste management under the triple bottom line approach. Journal of Cleaner Production, 272, 122662.
]Search in Google Scholar
[
Schoenherr, Tobias, and Cheri Speier‐Pero. “Data science, predictive analytics, and big data in supply chain management: Current state and future potential.” Journal of Business Logistics 36, no. 1 (2015): 120-132.
]Search in Google Scholar
[
Shah, N., Irani, Z., Sharif, A.M., 2017. Big data in an HR context: exploring organizational change readiness, employee attitudes and behaviors. J. Bus. Res. 70, 366–378.
]Search in Google Scholar
[
Tiwari, S., Wee, H.M., Daryanto, Y., 2018. Big data analytics in supply chain management between 2010 and 2016: insights to industries. Comput. Ind. Eng. 115, 319–330.
]Search in Google Scholar
[
Waller, Matthew A., and Stanley E. Fawcett. “Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management.” Journal of Business Logistics 34, no. 2 (2013): 77-84.
]Search in Google Scholar
[
Wang, Gang, Angappa Gunasekaran, Eric WT Ngai, and Thanos Papadopoulos. “Big data analytics in logistics and supply chain management: Certain investigations for research and applications.” International Journal of Production Economics 176 (2016): 98-110.
]Search in Google Scholar
[
Weisheng Lu,2018,Big data analytics to identify illegal construction waste dumping: A Hong Kong study, Elsevier B.V. 0921-3449/© 2018, https://doi.org/10.1016/j.resconrec.2018.10.039_machine]
]Search in Google Scholar
[
Wood, L.C., Reiners, T., Srivastava, H.S., 2017. Think exogenous to excel: alternative supply chain data to improve transparency and decisions. Int. J. Logist. 20 (5), 426–443.
]Search in Google Scholar
[
Yla-Mella, J., Pongrácz, E., & Keiski, R. L. (2004, June). Recovery of waste electrical and electronic equipment (WEEE) in Finland. In Proceedings of the waste minimization and resources use optimization conference (Vol. 10, pp. 83-92).
]Search in Google Scholar
[
Zainudin, A. (2012). Research methodology and data analysis. Malaysia: Published by deesega.
]Search in Google Scholar
[
Zeng, X., Duan, H., Wang, F., & Li, J. (2017). Examining environmental management of e-waste: China’s experience and lessons. Renewable and Sustainable Energy Reviews, 72, 1076-1082.
]Search in Google Scholar
[
Zhong, R.Y., Newman, S.T., Huang, G.Q., Lan, S., 2016. Big data for supply chain management in the service and manufacturing sectors: challenges, opportunities, and future perspectives. Comput. Ind. Eng. 101, 572–591
]Search in Google Scholar
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