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Leveraging big data analytics capabilities in making reverse logistics decisions and improving remanufacturing performance

Surajit Bag (Department of Transport and Supply Chain Management, School of Management, College of Business and Economics, University of Johannesburg, Johannesburg, South Africa) (Department of Marketing and International Business, School of Business and Economics, North South University, Dhaka, Bangladesh)
Sunil Luthra (Department of Mechanical Engineering, Ch Ranbir Singh State Institute of Engineering and Technology, Jhajjar, India)
Sachin Kumar Mangla (Jindal Global Business School, O.P. Jindal Global University, Haryana, India) (Plymouth Business School, University of Plymouth, Plymouth, United Kingdom)
Yigit Kazancoglu (Department of International Logistics Management, Yasar University, Izmir, Turkey)

The International Journal of Logistics Management

ISSN: 0957-4093

Article publication date: 29 April 2021

Issue publication date: 22 July 2021

1546

Abstract

Purpose

The study investigated the effect of big data analytics capabilities (BDACs) on reverse logistics (strategic and tactical) decisions and finally on remanufacturing performance.

Design/methodology/approach

The primary data were collected using a structured questionnaire and an online survey sent to South African manufacturing companies. The data were analysed using partial least squares based structural equation modelling (PLS–SEM) based WarpPLS 6.0 software.

Findings

The results indicate that data generation capabilities (DGCs) have a strong association with strategic reverse logistics decisions (SRLDs). Data integration and management capabilities (DIMCs) show a positive relationship with tactical reverse logistics decisions (TRLDs). Advanced analytics capabilities (AACs), data visualisation capabilities (DVCs) and data-driven culture (DDC) show a positive association with both SRLDs and TRLDs. SRLDs and TRLDs were found to have a positive link with remanufacturing performance.

Practical implications

The theoretical guided results can help managers to understand the value of big data analytics (BDA) in making better quality judgement of reverse logistics and enhance remanufacturing processes for achieving sustainability.

Originality/value

This research explored the relationship between BDA, reverse logistics decisions and remanufacturing performance. The study was practice oriented, and according to the authors’ knowledge, it is the first study to be conducted in the South African context.

Keywords

Acknowledgements

The authors would like to thank the anonymous reviewers and the Editor for their insightful comments and suggestions.

Citation

Bag, S., Luthra, S., Mangla, S.K. and Kazancoglu, Y. (2021), "Leveraging big data analytics capabilities in making reverse logistics decisions and improving remanufacturing performance", The International Journal of Logistics Management, Vol. 32 No. 3, pp. 742-765. https://doi.org/10.1108/IJLM-06-2020-0237

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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