An uncertain search model for recruitment problem with enterprise performance

Chi Zhou (), Wansheng Tang () and Ruiqing Zhao ()
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Chi Zhou: Tianjin University
Wansheng Tang: Tianjin University
Ruiqing Zhao: Tianjin University

Journal of Intelligent Manufacturing, 2017, vol. 28, issue 3, No 22, 695-704

Abstract: Abstract This paper studies a dynamic recruitment problem with enterprise performance in the uncertain environment, in which a firm first interviews finite job applicants sequentially and then makes an employment decision according to results of the interview. Since the assessment of the firm about each interviewee’s capability is subjective and the interviewees are heterogeneous, it is reasonable to characterize these assessments as independent but not identically distributed uncertain variables. What’s more, an uncertain sequential search model is established to maximize the benefit of the recruitment firm. Moreover, an optimal search strategy is presented by adopting the principle of optimality and the reservation value rule. The results demonstrate that the threshold of recruitment decreases with the search cost, and increases with the enterprise performance level. In addition, we find that the low employment risk applicant will be preferred. Finally, some numerical examples are given to illustrate the effectiveness of the proposed model.

Keywords: Uncertainty theory; Sequential search; Dynamic programming; Labor market; Enterprise performance (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-014-0997-1

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