Intertemporal pricing, supply chain design, and consumer behavior

My dissertation explores the interaction between consumer behaviors and the design, pricing and management of products and services. The dissertation is comprised of four chapters. The first chapter studies how a seller's pricing strategy can be affected by behaviors of non-fully rational consumers. These consumers are dynamically inconsistent and exhibit probabilistic decision making behaviors, which have been documented in experimental studies in economics and marketing literature. I show that consumers' dynamic inconsistency can explain why flexible pricing plans are offered by service providers. Moreover, when fully rational consumers and non-fully rational consumers co-exist, a single pricing scheme is optimal. Such a result complements existing literature in mechanism design, as classic models suggest the seller should use a menu of pricing plans to differentiate the consumers. Numerical results are provided to demonstrate that the same result hold when both types of consumers non-fully rational and under mild conditions./nThe second chapter examines how a seller should design the prices and qualities of products sold through his direct and indirect channels. I show that under the revenue sharing scheme, the seller's optimal design depends on consumers' sensitivities to price and quality. If the consumers are sufficiently sensitive, the seller should provide the product exclusively in the direct channel. If the consumers are sufficiently insensitive, the seller is better off providing a high quality product at a premium price in the direct channel while offering a low quality product in the indirect channel. Such quality differentiation can be eliminated in a profit sharing scheme. I also demonstrate that even when consumers are heterogeneous with privately observed sensitivities, offering a menu to induce self-selection may not be optimal for the seller's profit./nIn the third chapter, I use a two-period model to show that demand uncertainty can be the sole driver for the common practice of intertemporal pricing in the travel industry. Moreover, both increasing and decreasing pricing patterns can emerge as optimal strategies. I also identify the intrinsic incentive for service providers to deliberately create capacity shortage to induce early purchases. In the extended model, new arrivals are permitted in the second period enhance the competition. Contrary to intuition, the service provider's expected profit is hurt since the additional arrival exacerbates his price commitment issue and results consumers strategically delay their purchases./nThe last chapter investigates the effect of consumers' limited knowledge of products on their purchasing behavior. Though online retailers put intense effort in improving web functionalities over the years, some product attributes (product quality, user friendliness, fit to consumers' taste) cannot be communicated using the internet and must be examined physically by the consumers. Thus, their product valuations are not fully revealed until after they make the purchase. I show that when consumers are subject to both valuation uncertainty and future price uncertainty, their purchasing decisions are largely influenced by the return policies. A generous refund policy induces high-valued consumers to purchase early. However, it also invites some consumers to wait for the returns. This suggests that capacity rationing can be dampened. On the other hand, since neither the seller nor consumers can predict how many products will be returned, allowing consumer returns strengthens the seller's credibility in not committing to pre-announced prices. This implies that the additional source of valuation uncertainty can be desirable for the seller when dealing with forward-looking consumers. A rationale for retailers do not actively engage in recertifying or remanufacturing returned products is also provided: when returns are perceived as low-quality products, the retailers can facilitate market segmentation without creating new product lines.

Advisor: Shen, Zuo-Jun
Chen, Ying-Ju