IS Atlas
ms·2019년 9월 11일

The Long-term and Spillover Effects of Price Promotions on Retailing Platforms: Evidence from a Large Randomized Experiment on Alibaba

Dennis Zhang, Hengchen Dai, Lingxiu Dong, Fangfang Qi, Nannan Zhang, Xiaofei Liu, Zhongyi Liu

Management Science

125
피인용
13.3
FWCI
24
IS/마케팅/OM 탑저널 피인용
39
IS/마케팅/OM 탑저널 참고문헌
01Abstract

Dynamic pricing through price promotions has been widely used by online retailers. We study how a promotion strategy, one that offers customers a discount for products in their shopping cart, affects customer behavior in the short and long term on a retailing platform. We conduct a randomized field experiment involving more than 100 million customers and 11,000 retailers with Alibaba Group, one of the world’s largest retailing platform. We randomly assign eligible customers to either receive promotions for products in their shopping cart (treatment group) or not receive promotions (control group). In the short term, our promotion program doubles the sales of promoted products on the day of promotion. In the long term, we causally document unintended consequences of this promotion program during the month after our treatment period. On the positive side, it boosts customer engagement, increasing the daily number of products that customers view and their purchase incidence on the platform. On the negative side, it intensifies strategic customer behavior in the posttreatment period in two ways: (1) by increasing the proportion of products that customers add to their shopping cart conditional on viewing them, possibly because of their intention to get more shopping cart promotions, and (2) by decreasing the price that customers subsequently pay for a product, possibly because of their strategic search for lower prices. Importantly, these long-term effects of price promotions on consumer engagement and strategic behavior spill over to sellers who did not previously offer promotions to customers. Finally, we examine heterogeneous treatment effects across promotion, seller, and consumer characteristics. These findings have important implications for platforms and retailers. This paper was accepted by Vishal Gaur, operations management.

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