Abstract
According to evidence from research and practice, the seasonal demand variation exists in the banking sector and significantly affects the commercial bank's operation. Thus, the bank needs to adopt a seasonal staffing policy to ensure that the human resources can match the customer demands in different seasons. Otherwise, a shortage or surplus of human resource will occur and negatively affect bank operations. In this paper, we develop a seasonal staffing method to help the bank find the optimal staffing policy under seasonality. To capture the characteristics of bank operations, we model the service systems of n branches in a bank as a n-dimensional M/M/c/N queueing system with balking and reneging. Then a profit maximizing model based on the queueing system is constructed, and it is further simplified through linearization so that the model can be solved in a short time period. In addition, we conduct a set of numerical experiments that not only prove the superiority of our method compared with the traditional methods, but also explore the effects of some key factors on the optimal seasonal policy.
Highlights
It is undoubtedly crucial for service institutions to enable their resources for services to match the customer demands
This paper focus on the issue with respect to making staffing policy under a common type of customer demand variation faced with commercial banks — the seasonal demand variation
NUMERICAL EXPERIMENTS we explore the effects of parameters on the optimal seasonal staffing policy derived from model M1, and compare our seasonal staffing method based on M1 with the traditional methods of dealing with seasonal demand variation, including the rough seasonal staffing method and the unseasonal staffing method
Summary
It is undoubtedly crucial for service institutions to enable their resources for services to match the customer demands. This paper focus on the issue with respect to making staffing policy under a common type of customer demand variation faced with commercial banks — the seasonal demand variation. The source of this seasonality is in the economy and society. Y. Chen et al.: Optimal Staffing Policy in Commercial Banks Under Seasonal Demand Variation servers and additional staff based on a relatively rough estimation of the customer demands in different seasons. Aiming at helping the commercial bank avoid such loss and damage, we construct a theoretical profit maximizing model that can help the bank quantitatively optimize the staffing policy under seasonal demand variation.
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