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

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.