Authors: Aluizio Filho 1 ; Simone Sartori 2 ; Hércules Antônio do Prado 3 ; Edilson Ferneda 3 and Paulo Koehntopp 4

Affiliations: 1 Laboratory of Applied Intelligence, University of the Itajaí Valley (UNIVALI), Rua Uruguay, 458, Itajaí, Brazil, University Center of Brusque (UNIFEBE), Brusque and Brazil ; 2 University Center of Brusque (UNIFEBE), Brusque and Brazil ; 3 Catholic University of Brasilia (UCB), Brasilia and Brazil ; 4 Catarinense Association of Educational Foundations (ACAFE), Florianópolis and Brazil

ISBN: 978-989-758-372-8

Keyword(s): Dynamic Motivational Analysis, Herzberg Theory, Decision-making, Human Resources, Sentiment Analysis.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Industrial Applications of Artificial Intelligence ; Strategic Decision Support Systems

Abstract: In the past decades, a significant number of researches have sought to determine which factors make a worker satisfied and productive. Currently, there are intensive efforts to develop efficient systems for motivational analysis and performance evaluation. Current approaches of measuring motivation are very focused on questionnaires and periodic interviews. These periods are most often greater than 6 months, and in most cases performed annually. With today's communication dynamics, employees can be influenced at any time by external factors of market supply and demand, as well as communications with peers and colleagues in the device mesh. It is becoming increasingly important to obtain real-time information to take preventive or corrective measures in a timely manner. This paper proposes a framework for real-time motivational analysis using artificial intelligence techniques in order to evaluate employee’ motivation at work. The motivation is evaluated from different groups of indica tors: a static and periodic group (interviews and questionnaires), and two other dynamic groups that collect information in real time. With the results generated by the system, it is possible to make important decisions, such as understanding the emotional interactions among employees, improving working conditions, identifying indicators of dissatisfaction and lack of motivation, encouraging promotions, salary adjustments and other situations. (More)

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Paper citation in several formats:
Haendchen Filho, A.; Sartori, S.; Antônio do Prado, H.; Ferneda, E. and Koehntopp, P. (2019). An Evaluation Model for Dynamic Motivational Analysis.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-372-8, pages 446-453. DOI: 10.5220/0007744304460453

author={Haendchen Filho, A. and Simone Sartori. and Hércules Antônio do Prado. and Edilson Ferneda. and Paulo Ivo Koehntopp.},
title={An Evaluation Model for Dynamic Motivational Analysis},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS,},


JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - An Evaluation Model for Dynamic Motivational Analysis
SN - 978-989-758-372-8
AU - Haendchen Filho, A.
AU - Sartori, S.
AU - Antônio do Prado, H.
AU - Ferneda, E.
AU - Koehntopp, P.
PY - 2019
SP - 446
EP - 453
DO - 10.5220/0007744304460453

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