Tax-subsidy or reward-penalty? Determining optimal strategy in sustainable closed-loop supply chain under quality-dependent return

Abstract

In today's competitive business world, focusing solely on financial considerations can limit market demand in any industry. Keeping this in mind, this study deals with a sustainable closed-loop supply chain (CLSC) comprising an environmentally conscious manufacturer, a retailer, and a third-party collector (TPC) under the influence of government intervention. The manufacturer offers a return policy for the defective product up to a certain time, and the TPC offers an acquisition price to consumers for returning their used products. The government can offer no intervention or a tax-subsidy policy in the forward logistics, or a reward-penalty mechanism (RPM) in the reverse logistics, or both. Relying on different government policies, four models are developed first. After that, two collaborative models, viz. manufacturer-retailer collaboration and manufacturer-TPC collaboration, are developed for improving channel performance under the manufacturer-led Stackelberg gaming approach. Numerical results disclose that the government subsidy to consumers provides better functionality to channel individuals, consumers, and the environment. If the government considers imposing a tax, the RPM can help to improve channel execution marginally. A collaborative strategy between the manufacturer and the retailer under government taxation and RPM becomes the most efficient strategy for enhancing the triple bottom line of sustainability.

Keywords:

• Closed-loop supply chain
• sustainability
• product quality
• collection rate of used products
• tax-subsidy
• reward-penalty mechanism (RPM)

Acknowledgments

The authors are sincerely thankful to the Associate Editor and the anonymous reviewers for their helpful comments and suggestions on the earlier version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data is available within the article. The authors confirm that the data supporting the findings of this study are available within the article.

Additional information

Funding

This work was supported by the University Grants Commission [F. No. 16-9(June 2017)/2018(NET/CSIR)].

Notes on contributors

Chirantan Mondal

Chirantan Mondal is a Research Scholar in the Department of Mathematics, Jadavpur University, Kolkata, India. He did his B.S. and M.S. in Mathematics both from University of Calcutta. His area of interest is green supply chain management. He has published papers in Journal of Cleaner Production, Computers & Industrial Engineering, Operational Research, Flexible Services and Manufacturing Journal, CIRP Journal of Manufacturing Science and Technology, Journal of Industrial & Management Optimization, RAIRO Operations Research and so on.

Bibhas C. Giri

Bibhas C. Giri is a Professor in the Department of Mathematics, Jadavpur University, Kolkata, India. He did his M.S. in Mathematics and Ph. D. in Operations Research both from Jadavpur University, Kolkata, India. His research interests include inventory/supply chain management, production planning and scheduling, reliability and maintenance. Professor Giri has published more than 100 research papers in the journal of international repute. His papers have appeared in journals such as Naval Research Logistics, Journal of Cleaner Production, International Journal of Production Research, OMEGA, Journal of the Operational Research Society, European Journal of Operational Research, International Journal of Production Economics and so on. He was a JSPS Research Fellow at Hiroshima University, Japan during the period 2002–2004 and Humboldt Research Fellow at Mannheim University, Germany during the period 2007–2008.