Dynamic search models with multiple items

Rebecca Dizon-Ross () and Sheldon M. Ross ()
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Rebecca Dizon-Ross: University of Chicago Booth School of Business
Sheldon M. Ross: University of Southern California

Annals of Operations Research, 2020, vol. 288, issue 1, No 8, 223-245

Abstract: Abstract We generalize the classic dynamic single-item search model to a setting with multiple items and vector offers for subsets of items. We first show a computationally feasible way to solve the dynamic optimization problem, and then prove structural results. Although assignment is not generally monotonically increasing in offer value, we show that, in a special case “additive” model, monotonicity holds if costs are submodular. We examine how the thresholds for assignment change with the remaining items, and whether there are gains to grouping searches. Finally, we consider a stopping rule version of the problem with no subsets for sale, showing the optimal policy is myopic.

Keywords: Dynamic programming; Job search; Multiple applicants; Optimal stopping; Stochastic assignment problem (search for similar items in EconPapers)
JEL-codes: C61 D83 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10479-019-03472-z

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