A special price just for you: effects of personalized dynamic pricing on consumer fairness perceptions

Abstract

Personalized dynamic pricing (PDP) involves dynamically setting individual-consumer prices for the same product or service according to consumer-identifying information. Despite its profitability, this pricing provokes strong negative fairness perceptions, explaining why managers are reluctant to implement it. This research provides important insights into the effect of two PDP dimensions (price individualization level and segmentation base) on fairness perceptions and the moderating role of privacy concerns. The results of two experimental studies indicate that consumers perceive individual prices as less fair than segment prices. They also evaluate location-based pricing as less fair than purchase history-based pricing. Consumer privacy concerns moderate these effects.

A Systematic Literature Review of Dynamic Pricing Strategies

“…The synthesis of over 50 articles revealed eight different research streams (see table 2), which show that dynamic pricing strategies affect customer perceptions and behaviors in positive and negative ways (e.g., Abrate et al (2012); van Boom, van der Rest, van den Bos and Dechesne, (2020); and Wang et al, (2016)). Consumers' view on dynamic pricing varies depending on the industry, resource availability (e.g., Kessels et al, 2016), their personal circumstances (e.g., Priester et al, 2020), as well as the degree to which they believe a supplier is acting in a fair manner (e.g., Lastner et al, 2019). Consumers accept dynamic pricing, if they understand the reasons for price differences (e.g.…”

Value creation in an algorithmic world: Towards an ethics of dynamic pricing

“…The empirical focus many papers in this area relates to the use of differential pricing within highly regulated markets for pharmaceuticals (Danzon, 2018) and electricity generation (Dutta & Mitra, 2017;Faruqui & Sergici, 2010). The second relates to broader ethical issues around consumer facing technologies, including privacy and data collection and the implications of autonomous decision-making (Lee et al, 2011;Priester et al, 2020).…”

China's Regulatory Framework for Dynamic and Personalized Pricing in the Digital Economy

“…There are many factors in personalized pricing that affect consumers' perceptions of price fairness. The higher the degree of personalized pricing, the closer to first-degree price discrimination, the lower the consumer's perception of price fairness; personalized pricing based on consumer purchase history is more common, such as giving price discounts to loyal customers, the consumer's perception of price fairness is higher than personalized pricing based on location data alone; the higher the privacy concern, the lower the consumer's perception of price fairness will be (Priester et al, 2020).In addition, the specific implementation of personalized pricing can also highly influence consumers' perception of price fairness, e.g., by giving personalized discounts (e.g., by giving personalized coupons), by involving consumers in the price formation process (e.g., through online auctions), and by combining it with second-degree price discrimination (e.g., through customized products) will enhance consumers' perception of price fairness.By improving consumers' perception of price fairness, the acceptance of personalized pricing can be increased.…”