Optimal demand shaping strategies for dual-channel retailers in the face of evolving consumer behavior


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Virginia Tech


The advent of the Internet has not only enabled traditional brick-and-mortar retailers to open online channels, but also provided a platform that facilitated consumer-to-consumer information exchange on retailers and/or products. As a result, the purchasing decisions of today's consumers are often affected by the purchasing decisions of other consumers. In this dissertation, we adopt an interdisciplinary approach that brings together tools and concepts from operations management, economics, systems dynamics and marketing literatures to create analytical models in order to address a dual-channel retailer's optimal demand shaping strategy, through e-commerce advertisement efforts, store service levels, and pricing, in this new environment. Our findings show that the retailer's optimal demand shaping strategy, in terms of store service levels and e-commerce advertisement effort, critically depends on the product's e-commerce adoption phase. We also show that in the presence of higher operating costs for the store channel compared to the online channels, a channel-tailored pricing policy always dominates a uniform pricing strategy. Our work sheds light on the benefits of channel integration for multi-channel retailers. We show that the retailer can leverage the online channels to provide in-store pricing and inventory availability information in order to enable a more transparent shopping experience for consumers, and this strategy results in a "win-win" situation for all parties.



Dual-channel retailing, e-commerce adoption, adaptive learning, consumer choice, multi-period inventory, pricing