Presenting a Comprehensive Smart Model of Job Rotation as a Corporate Social Responsibility to Improve Human Capital

Abstract

Providing job rotation schedules among certain individuals of organizations has been the research focus in the field of job rotation. Obviously, any movement of people will cause a change in the position of others and if there are no properly defined criteria for movement, the resulting job rotation not only is not effective in the long run but also may cause serious damage to the organization. In this regard, the main purpose of this research is to find the best model developed for job rotation and solve the "job rotation scheduling problem" with respect to the factors influenced by the job. So, Health and Safety Executive (HSE) standard questionnaire was used for measuring job stress among the population of nurses in Iranian health centers (n=1221 of a 6148 population) to form databases required for the implementation of data mining. In order to make a smart model, the use of internal rules and patterns of existing data is considered and with the development of meta-heuristic models for this kind of problem, the model is solved with genetic algorithms. The current job rotation model has been developed compared to previous models because of using smart limitations resulting from the process of knowledge discovery by data mining method. In contrast with the results of the previous studies on job rotation, our results are applicable to all organizations need to have different leadership styles in order to practice corporate social responsibility(CSR) and use capabilities to identify rules that allow easy use of meta-heuristic algorithms.

Keywords

• job rotation
• genetic algorithm
• data mining
• job stress
• corporate social responsibility(csr)
• leadership style