Title of article :
Implementing Bounded Linear Programming and Analytical Network Process Fuzzy Models to Motivate Employees: a Case Study
Author/Authors :
Mostafaeipour, ali Yazd University, Yazd, Iran , Khademi-zare, hasan Yazd University, Yazd, Iran , Aliheidari, tahereh Yazd University, Yazd, Iran , Sedaghat, ahmad Austalian College in Kuwait
Abstract :
In this research, the factors affectinguniversity employees’ motivation and productivity are identified and classified in seven groups;
the impact of each motivation factor on the productivity is presented by ANP fuzzy model.Eight universities in Iran were analyzed in
this research work. The aim of this study is to explore the productivity of employees. This paper attempts to give new insights into
designing the portfolio factors, motivating employees for productivity improvement by implementing BLP and
ANP fuzzy models.The research results show that there is a positive and significant relationship among reward system,
motivation factors, and human resources productivity. In addition, among the options of reward system, the factors of
internal (inherent) reward, non-financial external reward, and financial external reward had the highest impact on
increasing motivation and productivity factors. At the next stage, a BLP model is designed according to the importance and
impact of each reward system option on motivation and productivity factors and organization limitations, including budget,
facilities, and conditions to design portfolio factors motivating employees with the aim of improving productivity. The
research results show that actualizing performance evaluation, receiving the feedback from the results of doing tasks by
different ways, providing an opportunity for all employees to progress, coordination between job specifications and
employees’ abilities, and a manager competency are very critical for improving the organization productivity.
Keywords :
ANP fuzzy , BLP , Reward system;Productivity , Motivation , University
Journal title :
Astroparticle Physics