EURO 2024 Copenhagen
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2649. Incentivising-sharing-enabled optimal placement strategy on a reusable transport item rental platform

Invited abstract in session TA-23: Policy and legislation for a circular economy, stream Circular Economy, Remanufacturing and Recycling .

Tuesday, 8:30-10:00
Room: 82 (building: 116)

Authors (first author is the speaker)

1. Min Guo
Nottingham University Business School China, University of Nottingham Ningbo China
2. Hing Kai Chan
Nottingham University Business School China, University of Nottingham Ningbo China
3. Xiang T. R. Kong
College of Economics, Shenzhen University

Abstract

A rental platform offering customised reusable transport items (RTIs) grapples with placement challenges impacting RTI availability and usability. Notably, RTIs often stay idle in customer warehouses, adding no value. Thus, incentivising the business customers’ sharing and optimising the platform placement decision are worth further research, but have not been well discussed in previous literature. Therefore, this study introduces an optimisation decision framework aimed at encouraging B2B sharing and refining RTI placement and customer incentives, innovatively using empirical and optimisation models. A quantitative model evaluates business customers’ willingness to share (WTS) under varied incentive schemes and RTI needs. Incorporating WTS, we develop a bi-objective optimisation model with a large-scale heuristic algorithm to determine optimal RTI purchasing and sharing incentives pricing. Our real-case analysis illustrates that an RTI-sharing strategy reduces operational costs by 18.5% and boosts customer welfare, achieving a win-win scenario. Additionally, our findings suggest the platform's strategies on sharing incentives and resource procurement should adapt based on customer WTS preference, RTI reusability, and holding durations. This research could extend to similar rental networks or sharing platforms, underlining the significance of strategic resource placement and sharing incentives.

Keywords

Status: accepted

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