Search Models And Applications With Behavioral Factors Consideration

Search theory is the study of dynamic decision making problems involving deci-sion makers’optimal search strategy and optimal stopping rule under incomplete infor-mation. In the real market, some behavioral factors of participants also have influence on decision makers’optimal strategies except for incomplete information. Therefore, introducing behavioral factors into search theory has important academic significance and practical application value. This dissertation investigates recruitment firms, job applicants and consumers’search and decision making problems under the influence of behavior factors. In order to maximize the benefit of decision makers, the optimal search strategies are presented by adopting the dynamic programming method, which can provide theoretical reference and technical support for search decisions. The main contents and contributions are as follows.A dynamic recruitment problem that firms face possible loss of candidates is in-vestigated, in which the probabilistic loss of candidates can induce a loss cost to firms. From the perspective of recruitment firm, the discrete-time stochastic optimal stopping decision model with a finite planning horizon is established based on the principle of optimality. According to properties of optimality equation, an optimal decision rule is presented to maximize the benefit of the recruitment firm. By discussing the struc-ture of stopping region, this dissertation analyzes the effects of loss probability and loss cost on the recruitment threshold. In addition, it is shown that new applicants are hardly being directly employed when the remaining time to the deadline is very long.A recruitment search problem with enterprise performance is investigated in the uncertain environment. 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. From the perspective of recruitment firm, an uncertain sequential search model with enterprise performance is established to maximize the benefit of the re-cruitment firm. Furthermore, the model can be solved by dynamic programming. The optimal search strategy is presented on the basis of the principle of optimality and the reservation value rule. Moreover, the effects of search cost, enterprise performance level and risky ordering on the recruitment threshold are analyzed by comparative statics.A consumer search problem with prospect utility is studied in a hybrid uncertain environment. Hybrid uncertainty consists of the uncertainty of the consumer’s val-uation for each product and the randomness of stockout. Optimal consumer search model with prospect utility is established and compared with the benchmark model. Moreover, optimal search strategy and optimal stopping rule are designed for the con-sumer to search or buy a product. The results show that the presence of prospect utility can result in low purchase threshold. Furthermore, the effects of the risk coefficients for gains and losses on the purchase thresholds for low value and high value prod-ucts are analyzed to offer a theoretical explanation of the experimental evidence that consumers generally stop searching too early.An optimal consumption problem with reference-dependent preferences is stud-ied in on-the-job search and savings, which implies loss aversion in a worker’s con-sumption behaviors. The on-the-job search and savings models without and with loss aversion are developed by considering the reference-dependent consumption utility. The model analyzes how loss aversion affects the worker’s consumption decisions in job search. The results demonstrate that the presence of loss aversion will lead to a set of high steady-state consumption levels. Nevertheless, it shows that there is a unique steady-state consumption level, which is a lower bound of the set, in the absence of loss aversion. In addition, the effects of the strength of loss aversion on consumption level are also analyzed by contrasting consumption decisions without and with loss aversion.