Sequential search with adaptive intensity

This article studies sequential search problems, where a searcher chooses search intensity adaptively in each period. We fully characterize the optimal search rule and value, decomposing the intertemporal change of search intensity into the fall-back value effect and the deadline effect. We show that the optimal search intensity (value) is submodular (supermodular) in fall-back value and time. It follows that the fall-back value effect increases when the deadline approaches, and the deadline effect decreases when a searcher's fall-back value gets higher. We further investigate the connection between search with full and no recall to quantify the value of recall.