Implementing Bounded Linear Programming and Analytical Network Process Fuzzy Models to Motivate Employees: a Case Study

Document Type: Original Manuscript


1 Industrial Engineering Department, Yazd University, Yazd, Iran

2 Austalian College in Kuwait.



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 intodesigning 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 highestimpact 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.

Graphical Abstract

Implementing Bounded Linear Programming and Analytical Network Process Fuzzy Models to Motivate Employees: a Case Study


  • Combination of linear programming model and network analysis process in fuzzy conditions is performed.
  •  Introducing a linear programming model with limited variables for designing a motivational factor basket is done.
  •  Relationship between motivational factors and employee productivity through the network analysis process is performed.


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