Research about suppliers' selection upon entropy weight and TOPSIS in the perspective of supply chain

2014 ◽  
Author(s):  
Kening Da ◽  
Jingru An ◽  
Zongsheng Chen
Keyword(s):  
Supply Chain ◽  
Entropy Weight

Green supplier selection using an AHP-Entropy-TOPSIS framework

2015 ◽  
Vol 20 (3) ◽  
pp. 327-340 ◽  
Author(s):  
James Freeman ◽  
Tao Chen
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Selection Criteria ◽  
Second Phase ◽  
Structured Interviews ◽  
Entropy Weight ◽  
Two Phase ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Green Supplier Selection

Purpose – This paper aims to focus on development of a green supplier selection model using an index system based on a combination of traditional supplier and environmental supplier selection criteria. Strategies that balance economic and environmental performance are increasingly sought after as enterprises that increasingly focus on the sustainability of their operations. Green supply chain management (GSCM) in particular, enables the integration of environmentally friendly suppliers into the supply chain to be systematised to fit with specific environmental regulations and policies. More persuasively, GSCM allows enterprises to improve profits whilst lowering impacts on the global environment. Design/methodology/approach – A two-phase survey approach was adopted for the research. For the first phase, semi-structured interviews with senior management representatives of the case company – a Chinese-based electronic machinery manufacturer – were used to determine green supplier selection criteria. For the second phase, a two-part questionnaire survey was undertaken, the first part providing the data for an analytic hierarchy process (AHP) analysis of the first-phase criteria and the second with collecting data for an Entropy weight analysis. The resultant AHP and Entropy weights were then combined to form compromised weights – which, using technique for order preference by similarity to the ideal solution (TOPSIS) methodology, were translated into preferential rankings of suppliers. Findings – Senior managers were found to rank traditional criteria more highly than environmental alternatives – the implication being that for the company, concerned, it may take some time before environmental awareness is fully assimilated into GSCM practice. Originality/value – The paper moves us a significant step closer to the application more widely, of innovative AHP-Entropy/TOPSIS methodology to real-world SCM problems.

Research about Suppliers Selection upon Entropy Weight and TOPSIS in the Perspective of Supply Chain

2014 ◽  
Vol 638-640 ◽  
pp. 2455-2459
Author(s):  
Ke Ning Da ◽  
Jing Ru An ◽  
Zong Sheng Chen
Keyword(s):  
Supply Chain ◽  
Efficient Method ◽  
Evaluation System ◽  
Entropy Weight ◽  
Evaluation Standards ◽  
Low Level ◽  
Evaluation Mode ◽  
Ideal Matrix ◽  
Topsis Model

This paper discusses the targets and evaluation standards for suppliers selection, and sets a evaluation mode, combined entropy weight and TOPSIS model. The basic idea of this model is use entropy weight to confirm the weight of each evaluated index, and then ensure the most suitable supplier through TOPSIS model that close to ideal matrix, so as to well avoid the subjectivity assured by low level and multi-factors. The paper introduces this model into detailed practical cases, which aims to state that the combination of entropy weight and TOPSIS model is a very efficient method for suppliers’ selection in supply chain evaluation system.

Data Processing in Project Supply Chain Vendor Selection Based on Improved Entropy Weight - Grey Correlation - TOPSIS

2014 ◽  
Vol 1046 ◽  
pp. 545-549 ◽  
Author(s):  
Qiu Qin Lu ◽  
Qiao Zhao
Keyword(s):  
Supply Chain ◽  
Entropy Method ◽  
Evaluation Index System ◽  
Ideal Solution ◽  
Entropy Weight ◽  
Weighting Method ◽  
Grey Correlation ◽  
Related Data ◽  
Relative Closeness ◽  
Index Weight

On the basis of the establishment of evaluation index system, an improved entropy weight – grey correlation – TOPSIS model is put forward to select project supply chain vendor, and process the related data. The each index weight is obtained from subjective weighting method and objective entropy method. The positive and negative distance between each evaluation object and ideal solution is calculated, and the grey correlation grade between each evaluation object and ideal solution is obtained. Then the relative closeness of each evaluation object can be gained that we can select the best vendor according to it.

scholarly journals Research on the Spatio-Temporal Impacts of Environmental Factors on the Fresh Agricultural Product Supply Chain and the Spatial Differentiation Issue—An Empirical Research on 31 Chinese Provinces

2021 ◽  
Vol 18 (22) ◽  
pp. 12141
Author(s):  
Xuemei Fan ◽  
Ziyue Nan ◽  
Yuanhang Ma ◽  
Yingdan Zhang ◽  
Fei Han
Keyword(s):  
Supply Chain ◽  
Environmental Factors ◽  
Critical Role ◽  
Generalized Method Of Moments ◽  
Spatial Differentiation ◽  
Weighted Regression ◽  
Agricultural Product ◽  
Entropy Weight ◽  
Comprehensive Development ◽  
Spatio Temporal

Environmental factors in time and space play a critical role in advancing the sustainable development of the fresh agricultural product supply chain. This paper, availing the panel data of 31 Chinese provinces from 2008 to 2019, constructs a system of indicators assessing the development of the fresh agricultural product supply chain, and obtains the comprehensive development level in the Entropy Weight Method (EWM). Furthermore, it establishes a comparison between optimal solutions generated by the Instrumental Variables Method (IVM) and the Generalized Method of Moments (GMM) over the endogeneity issue of variables, creates the comparison between the weighted regression methods of Geographically Weighted Regression (GWR) and Multi-scale Geographic Weighted Regression (MGWR), and obtains the relationship among the 14 environmental factors in their spatio-temporal impacts on the development of the fresh agricultural product supply chain. The results indicate that: (1) the environmental influencing factors in this paper have significant endogenous problems and various environmental factors impact on the fresh agricultural product supply chain in different trends and to different degrees. (2) With different bandwidths, the environmental factors could impact the fresh agricultural product supply chain to greatly varied degrees, demonstrating a strong attribute of regional correlation.

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