Learning in a Hiring Logic and Optimal Contracts

This paper examines a hiring logic problem in which all players involved in this game are exposed to scenarios where they can learn from the changes and these modifications influence their preferences; consequently, their decision-making differs from the classical agency theory proposed by <xref...

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Autores principales:	Jose Iranildo Sales, Francisco de Sousa Ramos
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Agency theory hiring logic learning nonlinearity repeated games Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/cfbc1d78b3794e97b3b6fd6c960c7a8d
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id	oai:doaj.org-article:cfbc1d78b3794e97b3b6fd6c960c7a8d
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spelling	oai:doaj.org-article:cfbc1d78b3794e97b3b6fd6c960c7a8d2021-11-25T00:01:02ZLearning in a Hiring Logic and Optimal Contracts2169-353610.1109/ACCESS.2021.3128039https://doaj.org/article/cfbc1d78b3794e97b3b6fd6c960c7a8d2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9614129/https://doaj.org/toc/2169-3536This paper examines a hiring logic problem in which all players involved in this game are exposed to scenarios where they can learn from the changes and these modifications influence their preferences; consequently, their decision-making differs from the classical agency theory proposed by <xref ref-type="bibr" rid="ref1">[1]</xref>. Therefore, how this new learning approach of the agents involved in the delegation of activities changes the methodology of the hiring logic. Concepts such as nonlinear preferences, partial understanding of performances by repetition, and economic cycles of employability are introduced into the classical model, bringing a series of significant changes in the structuring of the game according to the perception and knowledge of the agents involved in the model. As a result, the model indicates that there is a different way to understand hiring logic using the principal-agent model, in which the optimal contract is adapted for learning agents, due to the natural change of behavior by changing perception and preferences in the game.Jose Iranildo SalesFrancisco de Sousa RamosIEEEarticleAgency theoryhiring logiclearningnonlinearityrepeated gamesElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 154540-154552 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Agency theory hiring logic learning nonlinearity repeated games Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Agency theory hiring logic learning nonlinearity repeated games Electrical engineering. Electronics. Nuclear engineering TK1-9971 Jose Iranildo Sales Francisco de Sousa Ramos Learning in a Hiring Logic and Optimal Contracts
description	This paper examines a hiring logic problem in which all players involved in this game are exposed to scenarios where they can learn from the changes and these modifications influence their preferences; consequently, their decision-making differs from the classical agency theory proposed by <xref ref-type="bibr" rid="ref1">[1]</xref>. Therefore, how this new learning approach of the agents involved in the delegation of activities changes the methodology of the hiring logic. Concepts such as nonlinear preferences, partial understanding of performances by repetition, and economic cycles of employability are introduced into the classical model, bringing a series of significant changes in the structuring of the game according to the perception and knowledge of the agents involved in the model. As a result, the model indicates that there is a different way to understand hiring logic using the principal-agent model, in which the optimal contract is adapted for learning agents, due to the natural change of behavior by changing perception and preferences in the game.
format	article
author	Jose Iranildo Sales Francisco de Sousa Ramos
author_facet	Jose Iranildo Sales Francisco de Sousa Ramos
author_sort	Jose Iranildo Sales
title	Learning in a Hiring Logic and Optimal Contracts
title_short	Learning in a Hiring Logic and Optimal Contracts
title_full	Learning in a Hiring Logic and Optimal Contracts
title_fullStr	Learning in a Hiring Logic and Optimal Contracts
title_full_unstemmed	Learning in a Hiring Logic and Optimal Contracts
title_sort	learning in a hiring logic and optimal contracts
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/cfbc1d78b3794e97b3b6fd6c960c7a8d
work_keys_str_mv	AT joseiranildosales learninginahiringlogicandoptimalcontracts AT franciscodesousaramos learninginahiringlogicandoptimalcontracts
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Learning in a Hiring Logic and Optimal Contracts

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