Analysis of the innovation capacity of Mexican regions with the multiple criteria hierarchy process. (December 2022)

• Record Type: Journal Article
• Authors: Alvarez, Pavel Anselmo; Valdez, Cuitláhuac; Dutta, Bapi
• Is Part Of: Socio-economic planning sciences. Number 84(2023)
• Publication Date: 2022-12
• Subjects: Multiple criteria decision analysis -- Multiple criteria hierarchy process -- Electre III -- Simos' Revised Procedure (SRF) -- Innovation capacity; Planning -- Periodicals; Economic policy -- Periodicals; Social policy -- Periodicals; Planification -- Périodiques; Politique économique -- Périodiques; Politique sociale -- Périodiques; ECONOMIC PLANNING; SOCIAL PLANNING; DECISION-MAKING; 361
• DOI: 10.1016/j.seps.2022.101418
• Languages: English
• ISSNs: 0038-0121

Abstract

Abstract: This study attempts to use multicriteria decision aiding (MCDA) tools to analyse the innovation capacity of 32 regions in Mexico. In today's competitive world, innovation in science and technology is the key to the growth and productivity of the regions. Understanding the current state of innovation capacity and identifying the factors that influence said capacity allows the government to make region-specific policies for future growth and development. However, measuring such a complex concept involves a large number of criteria, and to understand the impact of a region's innovation capacity under a subset of criteria or with respect to high-level views it is necessary to gain in-depth insight for future policy design. To address this issue, we adopt the multicriteria hierarchy process (MCHP), which allows the decision-maker to express preferences of sub- group criteria and individual analysis by using subsets of criteria and different dimensions of the problem. Further, with the aim of managing the weighting of criteria and preference aggregation within the MCHP framework, we employ the hierarchical version of the deck of cards method for weight definition, the hierarchical ELECTRE III to aggregate preferences, and the distillation procedure to exploit the preference model. Using this methodological framework, the innovation capacity of 32 regions in Mexico is analysed under 52 decision criteria. Highlights: Assessment of the performance of innovation capacity in different regions in Mexico. Regions with highest innovation capacity in different dimensions. Available computational tools: The Electre III and the distillation method in the MCHP context, and SRF method.