Redefining competitive industrial performance indicator: a multiplicative data envelopment analysis approach

Abstract

The competitive industrial performance (CIP) index is introduced to assess countries’ capacity to produce and export manufactured goods, technological upgrading and deepening, and impact on world production and trade. In this research, these dimensions are reflected by eight sub-indicators which are integrated into a comprehensive composite indicator (CI). However, the value of the weight corresponding to each sub-indicator may significantly affect the value of the CI. In the meantime, the ignorance of the benchmark construction and consideration of decision makers’ preference and attitude may restrict the application of CIP. Therefore, a comprehensive CI evaluation and benchmark-generating system with an objective weighting incorporating process is needed. This research aims to propose a geometric CI evaluation based on a multiplicative data envelopment analysis (DEA) model without explicit input (Multiplicative-WEI) where the benchmark can be represented by a projection point. We propose the generalized Multiplicative-WEI model whose linear representation is under the unified non-radial measure framework. The proposed model is further extended to the closest target model to reflect an optimistic evaluation strategy and super-efficiency model to increase the discriminant power. Within the introduction of parametric regarding decision makers’ preferences and attitudes, we apply our comprehensive CI framework to 153 countries to evaluate their CIP in year 2016 and year 2021. The results provide countries with more valuable insights regarding their performance change based on the weight of the sub-indicator, benchmark, and CI score.