Incentivising-by-penalty: The optimal return strategy for a reusable transport item rental platform

Min Guo, Hing Kai Chan, Xiang T.R. Kong, Dimple R. Thadani

Research output: Journal PublicationArticlepeer-review

Abstract

The sustainability of modern supply chains is intricately linked to the efficiency of reusable transport items (RTI). This study addresses the challenge of ensuring the timely return of RTIs by customers, as the underutilisation of RTIs leads to increased environmental impacts. By introducing a data-driven penalty scheme designed to incentivise timely returns through customised penalties, the study offers an innovative, tailored approach for RTI behavioural operations management. Real-case results showcase the potential of the scheme to enhance return rates, reduce RTI stockpiling, improve customer relations and mitigate environmental degradation. Our findings reveal diverse impacts associated with the implementation of balanced penalties that align with customers’ heterogeneous penalty sensitivity and demand level variability, thereby enhancing the effectiveness of the penalty scheme. These insights also offer valuable guidance for practitioners and policymakers seeking to enhance management efficiency and promote environmental stewardship in RTI supply chain operations.

Original languageEnglish
Article number104339
JournalTransportation Research Part D: Transport and Environment
Volume134
DOIs
Publication statusPublished - Sept 2024

Keywords

  • Behaviour operations management
  • Data-driven penalty scheme
  • RTI return management
  • Rental platform
  • Sustainable closed-loop supply chain

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation
  • General Environmental Science

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