Learning in a hiring logic and optimal contracts

• Ano de defesa: 2022
• Autor(a) principal: SILVA, José Iranildo Barbosa Sales da
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Pernambuco; UFPE; Brasil; Programa de Pos Graduacao em Engenharia de Producao
• Palavras-chave em Português: Engenharia de produção; Aprendizado; Contratação; Teoria dos jogos; Modelo do principal-agente
• Link de acesso: https://repositorio.ufpe.br/handle/123456789/48439

The concept of learning has always been a fascinating factor in scientific analysis and investigation, and game theory has as its basic instrument the interpretation of the various factors that influence the decision-making process of agents involved in the game. Utilities, perceptions, preferences and decisions have been the subject of research and analysis around the world in the last two centuries. In addition, employment contracts are being formed daily for the most different branches of activity with completely different demands and offers in terms of quantity and variability. Markets also interfere in the hiring logic, as they reflect the bargaining power of each individual inserted in this context of strategic interaction. Therefore, this study involves exactly strategic interaction models that structure the intentions and preferences of decision makers in the game. The principal-agent model, classically known for structuring contracts in search of optimality, will be modified by introducing the concept of learning in non-linear, repeated versions and with cycles of economic interference in player preferences, and, accordingly, will be developed and analyzed the non-linear and repeated learning models of the main agent bringing very strong results for the research such as variation of gains and costs of the principal and agents by the insertion of learning as can be observed in the proposed model and guiding new ways to model the employment contracts for players who always learn with the scenario.