Abstract:

Webrooming， a shopping process in which consumers use online channels to browse product information while completing purchases in offline channels， is an increasingly common type of consumer cross-channel （separation of channels for browsing and purchasing products） behavior in the multi-channel retail environment of the mobile Internet era. According to a report in the 2019 China New Retail White Paper， this webrooming phenomenon is becoming increasingly common， with the product categories in which it occurs involving mother and baby products （39%）， skin care and makeup （32%）， personal care （32%）， alcohol （32%） and cleaning products （31%）. Platform companies have also identified in practice the negative impact of this webrooming phenomenon on their sales conversion rates and economic efficiency， and have started to actively adjust their sales models to cope with the increasing retail competition and consumer webrooming behavior. For example， Amazon in the U.S.， Taobao in China， and Flipkart in India have adopted a reseller model for most categories of products， while leading U.S. footwear platform Zappos and digital content platforms such as Comcast， Apple's iTunes， and Netflix sell their products through a reseller model. Whereas existing studies have explored platform sales model choice in multiple contexts， the impact of consumer cross-channel behavior， especially the most prevalent webrooming behavior today， on sales models has not been reported， and there has been little discussion of the willingness of other supply chain members to cooperate after the platform has made the optimal sales model choice. To this end， the impact of the webrooming phenomenon on the platform's optimal sales model choice is explored in the context of multichannel retailing for a platform-based supply chain consisting of a manufacturer， a platform-based retailer， and a brick-and-mortar retailer. Four differential game models are constructed： reselling model with webrooming （model S）， reselling model without webrooming （model NS）， reselling model with webrooming （model A） and reselling model without webrooming （model NA）. The impact of the webrooming phenomenon is analyzed by comparing the level of quality improvement of manufacturers， the service level of brick-and-mortar stores， the big-data marketing of the platform retailer， and the brand goodwill and corporate profits under the four models. Using numerical examples， our previous findings are validated and the conditions are explored under which the platform-optimal sales model holds true. The results show that when the webrooming phenomenon does not exist， the platform chooses the reselling model when the commission rate is relatively low and the online retail price is relatively high， and the reselling model in other cases. When the webrooming phenomenon is present， the platform also chooses reselling when both commission rates and online retail prices are enough high， and this area widens with the degree of webrooming. An important result is that the supply chain has a globally dominant sales model only when the webrooming phenomenon is present. In addition， it is shown that the presence of the webrooming phenomenon does not affect the decisions of the manufacturer and the brick-and-mortar retailer， but it inhibits the incentive of the platform to offer online services. The presence of the webrooming phenomenon consistently hurts the platform's profitability， and it is more severe as the intensity of the webrooming phenomenon increases. As the intensity of the webrooming phenomenon increases， the brick-and-mortar retailer’s profit first increases and then decreases， with the greatest profits occurring when the intensity of the webrooming phenomenon is moderate. For the manufacturer， the impact of changes in the intensity of the webrooming phenomenon is analyzed in the context of platform commission rates and online retail prices.

Key words: webrooming phenomenon, sales format, reselling, agency selling, big-data marketing