nep-mkt New Economics Papers
on Marketing
Issue of 2021‒07‒12
three papers chosen by
Marco Novarese
Università del Piemonte Orientale

  1. Behavior-Based Personalized Pricing: When Firms Can Share Customer Information By Chongwoo Choe; Noriaki Matsushima; Mark J. Tremblay
  2. Predicting choice-averse and choice-loving behaviors in a field experiment with actual shoppers By Ong, David
  3. Price discrimination with inequity-averse consumers: A reinforcement learning approach By Buchali, Katrin

  1. By: Chongwoo Choe; Noriaki Matsushima; Mark J. Tremblay
    Abstract: We study a model of behavior-based price discrimination where asymmetric firms can agree to share customer information that can be used for personalized pricing. We show that information sharing is individually rational for firms as it softens upfront competition when information is gathered, consumers are worse off as a result, but total surplus can increase thanks to the improved quality of matching between firms and consumers. These findings are robust to firm asymmetries and varying discount factors for consumers and firms.
    Date: 2020–03
  2. By: Ong, David
    Abstract: A large body of chiefly laboratory research has attempted to demonstrate that people can exhibit choice-averse behavior from cognitive overload when faced with many options. However, meta-analyses of these studies, which are generally of one or two product lines, reveal conflicting results. Findings of choice-averse behavior are balanced by findings of choice-loving behavior. Unexplored is the possibility that many consumers may purchase to reveal their tastes for unfamiliar products, rather than attempt to forecast their tastes before purchase. I model such ‘sampling-search’ behavior and predict that the purchases of unfamiliar consumers increase with the available number of varieties for popular/mainstream product lines and decrease for niche product lines. To test these predictions, I develop a measure of popularity based on a survey of 1,440 shoppers for their preferences over 24 product lines with 339 varieties at a large supermarket in China. 35,694 shoppers were video recorded after the varieties they faced on shelves were randomly reduced. As found in the meta-studies, choice-averse behavior was balanced by choice-loving behavior. However, as predicted, the probability of choice-loving behavior increases with the number of available varieties for popular product lines, whereas choice-averse behavior increases with available varieties for niche product lines. These findings suggest that increasing the number of varieties has predictable opposing effects on sales, depending upon the popularity of the product line, and opens the possibility of reconciling apparently conflicting prior results.
    Keywords: field experiment, choice overload, choice-aversion, consumer search
    JEL: C93 D83 M31
    Date: 2021–06–21
  3. By: Buchali, Katrin
    Abstract: With the advent of big data, unique opportunities arise for data collection and analysis and thus for personalized pricing. We simulate a self-learning algorithm setting personalized prices based on additional information about consumer sensitivities in order to analyze market outcomes for consumers who have a preference for fair, equitable outcomes. For this purpose, we compare a situation that does not consider fairness to a situation in which we allow for inequity-averse consumers. We show that the algorithm learns to charge different, revenue-maximizing prices and simultaneously increase fairness in terms of a more homogeneous distribution of prices.
    Keywords: pricing algorithm,reinforcement learning,Q-learning,price discrimi-nation,fairness,inequity
    JEL: D63 D91 L12
    Date: 2021

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