Evaluation of robustness of supply chain information-sharing strategies using a hybrid Taguchi and multiple criteria decision-making method

Ta-Ho Yang, Yuan Feng Wen, Fang Fang Wang

Research output: Contribution to journalArticle

39 Citations (Scopus)

Abstract

The advances in information technology have prompted the development of many supply chain information-sharing strategies, including electronic point of sales (EPOS), vendor-managed inventory (VMI), e-shopping, emergency transshipments, and so on. However, variations in the business environment can produce uncertainty and increase decision-making complexity for enterprises selecting from various supply chain information-sharing strategies. An effective and efficient supply chain strategy should be capable of reducing costs and raising customer-service levels, and should be capable of enhancing the robustness of the supply chain. In this study, the robustness of different supply chain strategies under various uncertain environments is studied using the simulated beer game. Techniques included Taguchi methodology and multiple criteria decision-making methods (MCDMs), including simple multiple attribute rating technology (SMART), technique for order performance by similarity to ideal solution (TOPSIS), and grey relational analysis (GRA). The signal-to-noise (S/N) ratio for each criterion is calculated to indicate the robustness of performance. This S/N ratio is used to determine an overall evaluation among various supply chain information-sharing strategies. The simulation results show that e-shopping has the most robust performance in uncertain environments.

Original languageEnglish
Pages (from-to)458-466
Number of pages9
JournalInternational Journal of Production Economics
Volume134
Issue number2
DOIs
Publication statusPublished - 2011 Jan 1

Fingerprint

Supply chains
Decision making
Signal to noise ratio
Beer
Information technology
Information sharing
Multiple criteria decision making
Supply chain
Robustness
Evaluation
Industry
Sales
Supply chain strategy
E-shopping
Costs

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Cite this

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Evaluation of robustness of supply chain information-sharing strategies using a hybrid Taguchi and multiple criteria decision-making method. / Yang, Ta-Ho; Wen, Yuan Feng; Wang, Fang Fang.

In: International Journal of Production Economics, Vol. 134, No. 2, 01.01.2011, p. 458-466.

Research output: Contribution to journalArticle

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