TY - JOUR
T1 - Incentivising-by-penalty: The optimal return strategy for a reusable transport item rental platform
AU - Guo, Min
AU - Chan, Hing Kai
AU - Kong, Xiang T.R.
AU - Thadani, Dimple R.
N1 - This work was supported by the National Natural Science Foundation of China [Grant No. 72371168]; Humanities and Social Science Foundation of the Ministry of Education in China [Grant No. 22YJC630052]; Guangdong Office of Philosophy and Social Science [Grant No. GD22YGL07]; Social Science 2035 Plan of Shenzhen University [ZYQN2306]; The third phase of high-level university construction of interdisciplinary innovation team project of Shenzhen University [24JCXK03]; and Li Dak Sum Innovation Fellowship for the project [LDS202310] “Research on the operation optimisation and application of the decision support system for the reusable packaging sharing platform”.
Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/9
Y1 - 2024/9
N2 - 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.
AB - 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.
KW - Behaviour operations management
KW - Data-driven penalty scheme
KW - Rental platform
KW - RTI return management
KW - Sustainable closed-loop supply chain
UR - http://www.scopus.com/inward/record.url?scp=85199898327&partnerID=8YFLogxK
U2 - 10.1016/j.trd.2024.104339
DO - 10.1016/j.trd.2024.104339
M3 - Journal article
AN - SCOPUS:85199898327
SN - 1361-9209
VL - 134
JO - Transportation Research Part D: Transport and Environment
JF - Transportation Research Part D: Transport and Environment
M1 - 104339
ER -