Modeling Supply Risk in the New Business Era: Supply Chain Competition and Cooperation

Li, Xiang; Li, Yongjian; Zhao, Linghua

doi:10.1007/978-3-319-53518-0_8

Cited by 1 publication

(2 citation statements)

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“…where L f (x): 1] is continuous and strictly decreasing, then T is called left and right fuzzy number, that is L − R fuzzy number, denoted as (A L , A R , α L , α R ). Especially when L f (x) and R f (x) are both linear functions, T is called a trapezoidal fuzzy number.…”

Section: Dea Model With L-r Fuzzy Numbersmentioning

confidence: 99%

“…The problems of resource waste and environmental pollution have become increasingly serious, which has attracted great attention of the international community. In January 2016, the United Nations proposed 17 sustainable development goals in the 2030 Agenda for Sustainable Development, of which the 12th is to ensure sustainable consumption and production patterns [1]. Reverse logistics (RL) is an effective way to achieve this goal.…”

Section: Introductionmentioning

confidence: 99%

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A Profit Distribution Model of Reverse Logistics Based on Fuzzy DEA Efficiency—Modified Shapley Value

Song

Chen

2021

Sustainability

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Reverse logistics is an important way to realize sustainable production and consumption. With the emergence of professional third-party reverse logistics service providers, the outsourcing model has become the main mode of reverse logistics. Whether the distribution of cooperative profit among multiple participants is fair or not determines the quality of the implementation of the outsourcing mode. The traditional Shapley value model is often used to distribute cooperative profit. Since its distribution basis is the marginal profit contribution of each member enterprise to different alliances, it is necessary to estimate the profit of each alliance. However, it is difficult to ensure the accuracy of this estimation, which makes the distribution lack of objectivity. Once the actual profit share deviates from the expectation of member enterprise, the sustainability of the reverse logistics alliance will be affected. This study considers the marginal efficiency contribution of each member enterprise to the alliance and applies it to replace the marginal profit contribution. As the input and output data of reverse logistics cannot be accurately separated from those of the whole enterprise, they are often uncertain. In this paper, we assume that each member enterprise’s input and output data are fuzzy numbers and construct an efficiency measurement model based on fuzzy DEA. Then, we define the characteristic function of alliance and propose a modified Shapley value model to fairly distribute cooperative profit. Finally, an example comprising of two manufacturing enterprises, one sales enterprise, and one third-party reverse logistics service provider is put forward to verify the model’s feasibility and effectiveness. This paper provides a reference for the profit distribution of the reverse logistics.

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Section: Dea Model With L-r Fuzzy Numbersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%