Assessing shoring strategies based on efficiency

With globalization, companies are increasingly employing offshoring strategies or establishing subsidiaries with external partners in foreign countries. However, many companies have difficulty strategizing because of increasing complexity of corporate activity and environmental uncertainty. On the supply side, it implies that it is difficult to assess a supplier's performance. Eventually, offshoring has caused undesirable outcomes for a firm's business. We provide a quantitative supplier evaluation model based on data envelopment analysis (DEA). The model includes two different variant of DEA models. malmquist productivity index (MPI) is used to determine whether objects are performing well over time and uncertain factors are considered stochastically by employing chance-constrained data envelopment analysis (CCDEA). By analyzing a numerical example, the suggested model demonstrates consistent results indicating whether subsidiary performance has improved or not. In addition, coherent outcomes are observed in two different return-to-scale suppositions, except that a subsidiary performance has changed significantly. In theoretical respect, this is the first attempt to combine the two DEA variations. Practically, the model's analysis reflects stochastic data and measures time series changes in performance so that it can provide more useful information for practitioners.

Automated summary

This article proposes a supplier evaluation model based on data envelopment analysis (DEA), which can effectively measure and evaluate supplier performance, considering uncertainty factors and performance changes. The model is of great significance in both theoretical and practical aspects.