Multilayer fuzzy cognitive maps for the management of the professional sports product based on the “par conditio” principle

Abstract

Multilayer Fuzzy Cognitive Maps (MFCM) represents an approach for analyzing situations, which allows the simulation, inference, theorem proving of tendencies, and verification of theories, among other things. This paper reviews the promise of this method in a novelty case study of management of professional sports clubs. Professional sports clubs have the possibility of making their management profitable through the proper management of their commercial product portfolio. This possibility is conditioned by the adequate configuration of each component of the commercial product portfolio, namely: Brand licensing, sponsorship, television and media rights, sporting and training rights, and hospitality. Each component of the commercial portfolio must maximize its attractiveness and desirability for each target customer segment. For these purposes, tools that contribute to manage the sports products will be vital to guarantee their commercial success. This article proposes a model based on MFCMs for supporting the management of products in professional sports – an intelligent decision-making system –, conceptually based on the “par conditio” principle. The model considers different aspects related to the “par conditio” principle, such as the socioeconomic environment where the sports activity is carried out, the legal bases of the professional competence, and other sporting aspects (stadium, fans, etc.), which are organized in layers, to analyze the behavior of the different components of the commercial portfolio. It is tested for the two most common sports in Latin America, football and baseball, considering countries of this region where these sports have good economic performance, both to analyze and understand the current situation of the sports products, and infer more appropriate configurations. Several specific case studies are carried out with encouraging results. The paper successfully shows the potentialities of MFCM for diverse purposes, particularly those named above.