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首页> 外文期刊>International journal of production economics >The value of the Physical Internet on the meals-on-wheels delivery system
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The value of the Physical Internet on the meals-on-wheels delivery system

机译：The value of the Physical Internet on the meals-on-wheels delivery system

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摘要

Driven by innovative technologies such as the Internet of Things, blockchain, and mobile applications, meals-on wheels (MOW) delivery services have shifted from a self-delivery (SD) model to outsourcing-delivery (OD) and volunteer-delivery (VD) models. The OD model is implemented by for-profit on-demand food-delivery platforms, and the VD model is implemented by non-profit service-sharing time banks designed for older adults. This work explored the concept of the Physical Internet (PI) to MOW delivery. First, we integrated recyclable PI-containers, smart lockers, and a PI-management system into SD, VD, and OD models to develop PI-enabled models. Second, we proposed simplified novel multi-objective mixed-integer linear programming models combined with a hierarchical clustering algorithm for the MOW delivery problem. The optimal planning decision minimizes the service providers' costs while maximizes customer satisfaction. Third, we compared different PI-enabled models in terms of service cost and customer satisfaction and conduct sensitivity analyses of key parameters, such as objective-related parameters (i.e., cost of traveling and dispatching) and constraint-related parameters (i.e., number of parking sites and geographical distributions of demand). Finally, we verified the proposed solution through a real-life case. Our results indicate that the VD model exhibited strong adaptability to PI. The OD model is more sensitive to the marginal traveling cost, the VD model is more sensitive to the fixed dispatching cost, and both the SD and VD models are sensitive to the geographical demand distribution and number of clusters. PI in the VD model improves meal quality in almost all situations. This study can guide IHC centers on the adoption of PI and MOW models.

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