竞争对手分析
竞赛(生物学)
采样(信号处理)
微观经济学
定价策略
业务
经济
产业组织
营销
计量经济学
计算机科学
生态学
计算机视觉
生物
滤波器(信号处理)
作者
WU Ling-li,Shiming Deng
摘要
Abstract When firms launch new products, consumers may be uncertain about whether these products fit their individual preferences before they have any personal experience with them. Such consumer fit uncertainty is very common for products sold online. To resolve this uncertainty, firms may provide fit‐revelation sampling along with competitive pricing depending on their competitors' strategies. In this paper, we formulate a game‐theoretical model to study the fit‐revelation sampling strategies for two competing firms of substitute products in a market consisting of switchers and nonswitchers. We derive equilibrium sampling and pricing strategies and provide conditions under which the two firms adopt symmetric or asymmetric sampling strategies. Our analysis provides possible explanations on why different sampling strategies are observed among competing firms in practice. We show that fit‐revelation sampling can be an important market differentiation tool. Adopting asymmetric sampling strategies, the two firms can take advantage of the market differentiation effect to avoid head‐on competition and make both of them better off. Counter‐intuitively, the profits of both firms can be increasing in the degree of competition (i.e., the size of switchers), and decreasing in the size of nonswitchers. We also provide new insights on the cause of price dispersion for competing firms facing consumer fit uncertainty. This would help firms to adjust their promotion strategies in accordance with their sampling campaigns. We extend the model to consider a more general case in which firms have different sizes of nonswitchers. We show that the firm with a larger size of nonswitchers is more willing to provide fit‐revelation sampling if the benefit from dropping low‐value consumers through sampling is large. Targeted sampling and pricing strategies are further examined in this paper. We show that firms always prefer asymmetric sampling strategies when targeting the group of switchers.
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