A proposed method for third-party reverse logistics partner selection and order allocation in the cellphone industry

2021 ◽  
Vol 162 ◽  
pp. 107719
Author(s):  
Sunil Kumar Jauhar ◽  
Saman Hassanzadeh Amin ◽  
Hossein Zolfagharinia
Keyword(s):  
Reverse Logistics ◽  
Partner Selection ◽  
Third Party ◽  
Order Allocation

scholarly journals A Hesitant Fuzzy Combined Compromise Solution Framework-Based on Discrimination Measure for Ranking Sustainable Third-Party Reverse Logistic Providers

2021 ◽  
Vol 13 (4) ◽  
pp. 2064
Author(s):  
Arunodaya Raj Mishra ◽  
Pratibha Rani ◽  
Raghunathan Krishankumar ◽  
Edmundas Kazimieras Zavadskas ◽  
Fausto Cavallaro ◽  
...  
Keyword(s):  
Reverse Logistics ◽  
Hybrid Approach ◽  
Third Party ◽  
Illustrative Case ◽  
Primary Concern ◽  
Compromise Solution ◽  
Fuzzy Environment ◽  
Criteria Weights ◽  
Reverse Logistic ◽  
Illustrative Case Study

Customers’ pressure, social responsibility, and government regulations have motivated the enterprises to consider the reverse logistics (RL) in their operations. Recently, companies frequently outsource their RL practices to third-party reverse logistics providers (3PRLPs) to concentrate on their primary concern and diminish costs. However, to select the suitable 3PRLP candidate requires a multi-criteria decision making (MCDM) process involving uncertainty owing to the presence of many associated aspects. In order to choose the most appropriate sustainable 3PRLP (S3PRLP), we introduce a hybrid approach based on the classical Combined Compromise Solution (CoCoSo) method and propose a discrimination measure within the context of hesitant fuzzy sets (HFSs). This approach offers a new process based on the discrimination measure for evaluating the criteria weights. The efficiency and practicability of the present approach are numerically demonstrated by solving an illustrative case study of S3PRLPs selection under a hesitant fuzzy environment. Moreover, sensitivity and comparative studies are presented to highlight the robustness and strength of the introduced methodology. The result of this work concludes that the introduced methodology can recommend a more feasible performance when facing with determinate and inconsistent knowledge and qualitative data.

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

2021 ◽  
Vol 13 (13) ◽  
pp. 7354
Author(s):  
Jiekun Song ◽  
Xiaoping Ma ◽  
Rui Chen
Keyword(s):  
Shapley Value ◽  
Reverse Logistics ◽  
Service Providers ◽  
Third Party ◽  
Output Data ◽  
Profit Distribution ◽  
Logistics Service ◽  
Input And Output ◽  
Value Model ◽  
Fuzzy Dea

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.

Analysis of third party reverse logistics provider using interpretive structural modeling

2012 ◽  
Vol 140 (1) ◽  
pp. 204-211 ◽  
Author(s):  
Kannan Govindan ◽  
Murugesan Palaniappan ◽  
Qinghua Zhu ◽  
Devika Kannan
Keyword(s):  
Reverse Logistics ◽  
Structural Modeling ◽  
Third Party ◽  
Interpretive Structural Modeling

Product Resynthesis as a Reverse Logistics Strategy for an Optimal Closed-Loop Supply Chain

2013 ◽  
Author(s):  
Chinmay Sane ◽  
Conrad S. Tucker
Keyword(s):  
Supply Chain ◽  
Reverse Logistics ◽  
Closed Loop ◽  
Manufacturing Firms ◽  
Third Party ◽  
High Tech ◽  
Closed Loop Supply Chain ◽  
Supply Chain Strategy ◽  
Logistics Strategy ◽  
Original Product

With continued emphasis on sustainability-driven design, reverse logistics is emerging as a vital competitive supply chain strategy for many of the global high-tech manufacturing firms. Various original equipment manufacturers (OEMs) and multi-product manufacturing firms are enhancing their reverse logistics strategies in order to establish an optimal closed-loop supply chain through which they can introduce refurbished variants of their products back into the market. While a refurbished product strategy helps to mitigate environmental impact challenges as well as provide additional economic benefits, it is limited to an existing product market, possibly a subset of the existing market, and fails to commercialize/target new markets. In addition to refurbishing, the alternatives available for utilizing End-Of-Life (EOL) products are currently restricted to recycling and permanent disposal. In this work, the authors propose employing a new EOL option called “resynthesis” that utilizes existing waste from EOL products in a novel way. This is achieved through the synthesis of assemblies/subassemblies across multiple domains. The “newly” synthesized product can then be incorporated into the dynamics of a closed-loop supply chain. The proposed methodology enables OEMs to not only offer refurbished products as part of their reverse logistics strategy, but also provide them with resynthesized product concepts that can be used to expand to new/emerging markets. The proposed methodology provides a general framework that includes OEMs (manufacturers of the original product), retailers (distributors of the original product and collectors of the EOL products) and third-party firms (managers of the EOL products) as part of a closed-loop supply chain strategy. The proposed methodology is compared with the existing methodologies in the literature wherein a third-party supplies the OEM only with refurbished products and supplies products unsuitable for refurbishing to another firm(s) for recycling/disposal. A case study involving a multi-product electronics manufacturer is presented to demonstrate the feasibility of the proposed methodology.

A New Look at Selecting Third-Party Reverse Logistics Providers

2012 ◽  
pp. 246-254
Author(s):  
Reza Farzipoor Saen
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Reverse Logistics ◽  
Third Party ◽  
Data Envelopment ◽  
Weight Restrictions ◽  
Use Of Data ◽  
Available Information ◽  
Nondiscretionary Factors ◽  
Decision Making Criteria

The use of Data Envelopment Analysis (DEA) in many fields is based on total flexibility of the weights. However, the problem of allowing total flexibility of the weights is that the values of the weights obtained by solving the unrestricted DEA program are often in contradiction to prior views or additional available information. Also, many applications of DEA assume complete discretionary of decision making criteria. However, they do not assume the conditions that some factors are nondiscretionary. To select the most efficient third-party reverse logistics (3PL) provider in the conditions that both weight restrictions and nondiscretionary factors are present, a methodology is introduced. A numerical example demonstrates the application of the proposed method.

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