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225. Personalized dynamic pricing: pearls or perils?
Invited abstract in session WB-40: Experimental economics and game theory 1, stream Experimental economics and game theory.
Wednesday, 10:30-12:00Room: 96 (building: 306)
Authors (first author is the speaker)
1. | Baile Lu
|
College of Systems Engineering, National University of Defense Technology | |
2. | Hongyan Dai
|
Central University of Finance and Economics | |
3. | Weihua Zhou
|
Zhejiang University |
Abstract
Leveraging large-scale data sources to employ personalized dynamic pricing has been a prominent practice in the retail industry. However, the outcome of this pricing strategy could be mixed. Therefore, this study aims to empirically investigate the impact of personalized dynamic pricing on store performance and individual consumer behavior under different conditions. We obtain unique access to a large data set from a leading on-demand delivery platform that has launched a personalized dynamic pricing strategy through price discounts in some of its grocery stores. Employing a quasi-experimental setting, we utilize the difference-in-differences method to estimate the causal impact of personalized dynamic pricing. First, we conduct store-level analyses and find that personalized dynamic pricing decreases store revenue. Then, to understand the underlying mechanism, we proceed with individual-level analyses and find that personalized dynamic pricing increases the individual transaction amount and frequency while increasing consumer churn. Finally, we investigate the moderating effects of an essential feature of personalized dynamic pricing: the price fluctuation over time. We find that a bit more fluctuation can mitigate the negative consequences of personalized dynamic pricing by reducing consumer churn and increasing consumer transaction activities. However, too much price fluctuation intensifies the negative consequences of personalized dynamic pricing.
Keywords
- E-Commerce
- Service Operations
- Analytics and Data Science
Status: accepted
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