Conditions Influencing Salary of the Automotive Industry in Mexico City—A Linguistic Fuzzy-Set Approach

Abstract

Decision making in wages is generally a hard task. The aim of this work is to identify government conditions, personal conditions of the businessperson, and organizational circumstances that affect wage levels in the automotive industry in Mexico City using a linguistic fuzzy-set approach. We conducted a questionnaire, consisting of 23 observation variables with a five-point Likert scale. Independent variables were measured from 1 (“not important”) to 5 (“very important”). Based on the literature review and results of interviews, a total of 169 questionnaires were sent to participants using Google Forms. The results of the linguistic fuzzy-set approach identify three main conditions influencing the salary levels in the automotive industry in Mexico City, including unskilled manpower, the neoliberal economic model, and political and trade reforms. On the other hand, organizational conditions are not considered relevant in determining wage levels. Based on the findings, some recommendations have been proposed to help government, firm leaders, and businesspeople design appropriate personnel policies to achieve better salary satisfaction for employees in the future. This work shows a model based on the fuzzy-set approach that is a potential tool to overcome the difficulties posed by a complex environment.