An New Evaluation Model for Synchronized Supply Chain Based on Entropy Weight and TOPSIS

Purpose – Assessing a measure of sustainable supply chain management (SSCM) performance is currently a key challenge. The literature on SSCM is very limited and performance measures need to have a systematic framework. The recently developed balanced scorecard (BSC) is a measurement system that requires a balanced set of financial and non-financial measures. The purpose of this paper is to evaluate the SSCM performance based on four aspects i.e. sustainability, internal operations, learning and growth, and stakeholder. Design/methodology/approach – This paper developed a BSC hierarchical network for SSCM in a close-loop hierarchical structure. A generalized quantitative evaluation model based on the Fuzzy Delphi Method (FDM) and Analytical Network Process (ANP) were then used to consider both the interdependence among measures and the fuzziness of subjective measures in SSCM. Findings – The results of this study indicate that the top-ranking aspect to consider is that of stakeholders, and the top five criteria are green design, corporate sustainability, strategic planning for environmental management, supplier cost-saving initiatives and market share. Originality/value – The main contributions of this study are twofold. First, this paper provides valuable support for supply chain stakeholders regarding the nature of network hierarchical relations with qualitative and quantitative scales. Second, this paper improves practical performance and enhances management effectiveness for SSCM.

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Autonomous evolution of service system in cluster supply chain

Kybernetes ◽

10.1108/k-01-2014-0005 ◽

2015 ◽

Vol 44 (1) ◽

pp. 139-158

Author(s):

Xiao Xue ◽

Shufang Wang ◽

Hao Chao

Keyword(s):

Supply Chain ◽

Service Composition ◽

Service System ◽

Evaluation Model ◽

Service Component ◽

Evolution Mechanism ◽

Content Type ◽

External Customer ◽

Qos Evaluation ◽

Autonomous Evolution

Purpose – The purpose of this paper is to provide strong theoretical and technical support for the dynamic evolution of service system in “Cluster Supply Chain”(CSC), which can deal with two kinds of context changes: the internal service component changes and the external customer requirement changes. Design/methodology/approach – A “feedback-based” evolution mechanism of service system for CSC is proposed in this study. By means of the feedback update of enterprise service’s Quality of Service (QoS) attribute and the adjustment of the assumed QoS evaluation model, the evolution of service system can be achieved to suit the dynamic market demands. Findings – Results of the study suggest: by means of the “feed-back” evolution mechanism of service system, the enterprises in CSC can handle the context changes effectively to maintain the optimized operation status. Practical implications – The implementation of evolution mechanism in service system can keep the effectiveness of enterprise service composition to face the frequent service component changes and the unpredictable market turbulence. Originality/value – This paper proposes a method to realize the autonomous evolution of service system in CSC, which can support the flexibility and adaptability of enterprise service composition in the changing environment.

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Application of Unascertained Measure-Entropy Evaluation Model for Program Selection of Shaft Construction under Complex Conditions

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.225-226.407 ◽

2011 ◽

Vol 225-226 ◽

pp. 407-410 ◽

Cited By ~ 1

Author(s):

Wan Qing Li ◽

Mu Jie Chen ◽

Wen Qing Meng

Keyword(s):

Decision Making ◽

Evaluation Model ◽

Entropy Weight ◽

Program Selection ◽

Effective Decision ◽

Effective Decision Making ◽

Measure Entropy ◽

Selection Of

An unascertained measure-entropy evaluation model for the program selection of shaft construction under complex conditions is established so that a scientific and effective decision making method is provided in this paper, the evaluation model of shaft construction is established based on unascertained measure and entropy weight theory, then, the model proposed in this paper is applied to evaluate three shaft construction program comprehensively, and the evaluation results show validity and applicability of the model.

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Analysis of regional economic evaluation based on machine learning

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189575 ◽

2020 ◽

pp. 1-11

Author(s):

Xiaoying Xu ◽

Zhijian Zeng

Keyword(s):

Economic Development ◽

Economic Evaluation ◽

Regional Economy ◽

Comprehensive Evaluation ◽

Evaluation Model ◽

Real Data ◽

Entropy Weight ◽

Regional Economic ◽

Economic Strategy ◽

Table Data

The regional economic evaluation and analysis has guiding significance for the subsequent economic strategy formulation. Due to the influence of various factors, the volatility of some current economic evaluation models is relatively large. According to the needs of regional economic evaluation, this study uses computer technology combined with regional economic development to build an economic development evaluation model to evaluate and analyze the regional economy. Through comparative analysis, this study selects the entropy weight-TOPSIS model as the comprehensive evaluation model of regional economy, uses the entropy weight method to determine the weight of each index, and then uses the TOPSIS method to conduct comprehensive evaluation. In addition, this study designs a control experiment to analyze the performance of this study model. Moreover, this study uses the model proposed in this study to conduct regional economic evaluation in recent years, and compares it with real data, and observes the test results with statistical charts and table data. The research results show that this research model has a certain effect, which can provide analytical tools for the follow-up economic strategy research and analysis.

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