In this paper, we study an e-grocer’s tactical problem of differentiated time slot pricing in attended home delivery. The purpose of differentiating delivery prices is to influence customers’ choice behavior concerning the offered time slots, such that cost-effective delivery schedules on an operational level can be expected and overall profit is maximized. We present a mixed-integer linear programming formulation of the problem, in which delivery costs are anticipated by explicitly incorporating routing constraints, and we model customer behavior by a general nonparametric rank-based choice model. Concerning cost anticipation, we also propose a model-based approximation that enables application to real-world problem sizes. In a setup inspired by an industry partner operating in urban areas, we then perform a comprehensive computational study that reveals the value of the model-based approximation as a supporting instrument for an e-grocer’s pricing decisions in practice. In particular, we demonstrate the superiority of the model-based approximation for real-world problem sizes to several benchmark approaches applied in the scientific literature and in practice (e.g., a unit price approach and other standard pricing heuristics). The online appendix is available at https://doi.org/10.1287/trsc.2017.0738 .
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While flexible products have been popular for many years in practice, they have only recently gained attention in the academic literature on revenue management. When selling a flexible product, a firm retains the right to specify some of its details later. The relevant point in time is after the sale, but often before the provision of the product or service, depending on the customers' need to know the exact specification in advance. The resulting flexibility can help to increase revenues if capacity is fixed and the demand to come difficult to forecast. We present several revenue management models and control mechanisms incorporating this kind of flexible products. An extensive numerical study shows how the different approaches can mitigate the negative impact of demand forecast errors.
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This paper provides an overview of the literature on dynamic pricing with strategic customers. In the past, research on dynamic pricing was mostly concerned with optimally pricing products over time in a market with myopic customers. In recent years, the consideration of strategic customers, who can delay a purchase to take advantage of a future discount, has dramatically increased. This paper's main contribution is the development of a comprehensive classification scheme to structure the field of research and, based upon this, a systematic overview of all relevant papers. We then present in detail the various aspects considered in the literature together with their motivation from industry and state the major findings of the most relevant papers. Further attention is given to important problem extensions proposed in the literature that have been considered in only a few papers and are usually motivated by specific practical applications. Finally, promising directions for future research are indicated.
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