IEEE Access (Jan 2022)

Optimization of the Recruitment Quota Allocation in Intra-Organizational Networks

  • Jianjun Miao,
  • Jiexun Liu,
  • Rui Feng,
  • Yi Zhang,
  • He Zhu,
  • Lin Bai

DOI
https://doi.org/10.1109/ACCESS.2022.3230717
Journal volume & issue
Vol. 10
pp. 134525 – 134535

Abstract

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In a decentralized organization such as a university, recruitment is critical for the development of departments. With the limited resources for recruitment, how to allocate the recruitment quotas to different departments is an essential problem for the human resource management center of the organization. Specifically, for a recruitment process that includes multiple phases, a proper number of quotas should be allocated to different departments at each recruitment phase to guarantee the recruitment performance of the whole organization. However, it is difficult since the performance of the whole recruitment process is prior unknown at each recruitment phase. Traditionally, a recruitment quota allocation scheme that evenly allocates recruitment quotas at different phases of a recruitment process is generally adopted, which is somewhat subjective due to the lack of quantitative analysis and may not achieve satisfying recruitment performance. Therefore, in this paper, a recruitment quota allocation scheme is proposed to provide a more objective and theoretical method that may achieve optimal performance. In the proposed scheme, we evaluate its performance by considering the competence of applicants and the number of potential applicants and obtain an improved recruitment quota allocation policy using the Markov decision process approach. Specifically, we first define the recruitment utility as the performance metric for the recruitment process. The recruitment quota allocation problem is formulated using the Markov decision process approach, where the effect of the information of potential applicants is innovatively taken into account. Then, the recruitment quota allocation is optimized by maximizing the recruitment utility to achieve optimal recruitment performance. In addition, a scheme that evenly allocates recruitment quotas at different phases of a recruitment process, which is traditionally adopted in the recruitment of a university, is used for comparison with the optimized scheme of the paper. Simulation results show that it is better to appropriately allocate more recruitment quotas in the early phases of a recruitment process than to allocate the quotas evenly over phases. Besides, it is also shown that the proposed scheme can improve the efficiency of recruitment quota allocation significantly.

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