An algorithm to identify the most motivated employees

• Published in: Management decision Vol. 51; no. 4; pp. 813 - 823
• Main Author: Canós-Darós, Lourdes
• Format: Journal Article
• Language: English
• Published: London Emerald Group Publishing Limited 26-04-2013
• Subjects: Algorithms; Behavior; Career development planning; Communication; Decision making; Employees; Fuzzy logic; Fuzzy sets; Human resources; Incentives; Knowledge management; Managers; Mathematical models; Motivation; Performance management; Set theory; Studies; Subjectivity; Wages & salaries; Decision support systems; Fuzzy sets; Employees attitudes; Motivation (psychology); Decision making; Human resource management
• ISSN: 0025-1747; 1758-6070
• DOI: 10.1108/00251741311326581

Purpose - In this paper, the aim is to present an algorithm to identify the most motivated employees according to the corporate human resources policies applied in a knowledge-based company.Design methodology approach - First, the author presents a complete table with motivation factors found in the literature. Then, a fuzzy tool, i.e. an adequacy index, is used in order to include subjectivity and uncertainty from personal perceptions both from employees and managers in the model.Findings - An algorithm to identify the most motivated employees according to corporate motivation policies designed by managers is found.Practical implications - Results provide information that can be used as a support for helping managers in decision making about training, promotion, leadership practices or team management.Originality value - An exhaustive list that does not exist in the literature about motivation factors is presented as well as the proposal of measure and identification on most-motivated employees is also a new idea.