4.5 Article

The Online Retailer's Randomized Pricing Strategy to Compete With an Offline Retailer

Journal

INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE
Volume 27, Issue 2, Pages 210-235

Publisher

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/10864415.2023.2184239

Keywords

online retailing; channel competition; randomized pricing; price discrimination; online-offline competition

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Online businesses are important within the retail industry and have fierce competition with offline retailers. This study compares pricing strategies, profits, consumer surplus, and social welfare between online and offline retailers in scenarios with and without a randomized pricing strategy for the online retailer. The model suggests that randomized pricing can benefit both offline retailers and social welfare, but not consumer surplus. Consumer behavior and offline retailer adjustment strategies are also discussed.
Online businesses have become an important sector of the retail industry, generating fierce competition with traditional offline retailers. In light of the growing online retail channels, we have designed a randomized pricing strategy for the online retailer, as the offline retailer's price remains unchanged over an infinite period. This study compares two competing retailers' pricing strategies, profits, consumer surplus, and social welfare, in two different scenarios-one in which the online retailer will implement a randomized pricing strategy, and one in which it will not. Conventional wisdom holds that online retailers possess greater flexibility when it comes to offering online promotions that attract more consumers to buy online at lower prices, negatively impacting offline retailers' profits. Our model suggests that the randomized pricing can also benefit offline retailers and social welfare, but not consumer surplus. We also discuss how consumers' strategic behavior affects retailers' pricing strategies and profits. It has been suggested that online retailers should not consider offline transaction costs when formulating promotion probabilities. Finally, we consider cases in which an offline retailer can adjust its strategy. A price-matching policy can help the offline retailer significantly increase profits, but can also benefit the online retailer when consumers are very patient and the utility discount factor is sufficiently small. An offline retailer can benefit from adding an online store only when the offline transaction costs are sufficiently high.

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