The Technological Adaptation of SMES Through Fuzzy Cognitive Maps

Abstract

SMEs are the fundamental base of the economy of Latin America and the Caribbean since they are an ideal element for the generation of jobs. However, in most of these companies, the administrative and production processes are carried out manually, which generates daily problems that, in many cases, cause them an economic imbalance that can rise to a level that can lead to failure. This work dynamic is reason enough to guide these companies towards a digital transformation, hoping to make them more competitive to stay longer in the commercial field. This research proposes novel strategies for implementing technologies based on a fuzzy logic model, where a vague cognitive map shows how each action benefits these companies. This analysis starts with a neural network simulation that learns and confirms four proposed hypotheses through specialized software created to streamline and specify the hypothesis verification operations; thus, this is available to any company, variable or, idea. The computer simulator was developed in a high-level multiplatform language with free access, allowing technology to automate processes, generate the increase or decrease of the selected variables, and improve the operation of the companies. The interpretation of the results issued by the simulator showed that process automation increases with the introduction of technology to the company. Consequently, many aspects will facilitate achieving its primary objective, which is to increase its profits in multiple elements and decrease the actions that cause problems to the company as a waste of time and money.