دانلود رایگان مقاله انگلیسی تنظیم بهینه سازی منابع انسانی بر اساس شبکه ناهمگن پویا - الزویر 2018

abstract

The human resources network, involves enterprise social networks and job networks, can be abstracted as heterogeneous networks or multi-layers networks. Adjusting the position assignments to maximize employee productivity and minimize the company’s cost is the goal of organization optimization. Taking the churn and interaction among the staff into account, this paper puts forward a dynamic optimization model for human resource adjustment, which is based on heterogeneous network, to describe the influence among individuals who are in personal relationship or professional relationship. More specifically, intimacy and loyalty are constructed to form the basis of churn rate, which indicate the influence of the personal and professional relationship respectively. With the operation of the organization, the change of intimacy and loyalty leads to the churn process, which are simulated with Monte Carlo method in a dynamic process among the heterogeneous network. After churning, an optimal strategy of recruitment and position adjustment is obtained using the Genetic Algorithm. In general, the human resource optimization process consists three periodic parts: loyalty and intimacy transformation, staff churn simulation and position assignment. Finally, a case study of an organization with 370 employee positions is carried out to demonstrate the whole process.

Conclusions

In this paper, we constructed a human resource network model to describe the relationship among persons, the structure of organization positions and the matching between employees and positions. It is worth mentioning that the heterogeneous network is used to construct the model of the human resource adjustment problem. When considering the time and the change of individuals’ intimacy and loyalty, a dynamic human resource management network is established. Then, a churn and recruitment simulation was done based on staff’s possibility to churn. After that, a genetic algorithm was designed to assign individuals to new positions in minimum cost. That is, the mapping problem between employees and positions is solved by the genetic algorithm and a reasonable adjusting scheme of human resources with as less as possible cost is obtained. Finally, we carried out a case study to analyze an organization’s human resource structure development in two years. According to the finding, increasing employees’ loyalty and minimizing private communication between employees can reduce the probability of leaving a job [23–25], thereby reducing the company’s spending on staff recruitment and training. Obviously, this article does not take the matching degree of the job and its required skills into account. The proposed method is suitable for those jobs that require low professional skills and employees can do the job after a period of training. In the future work, the matching problem should be considered. In addition, the structure of department in an organization has a significant impact on the analysis of managing human capital.