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Date of Award
Doctor of Philosophy (PhD)
Chapter 1: Dynamic Pricing and Price Commitment of New Experience Goods
An important problem for a firm selling new experience goods is how to credibly signal its high quality. This chapter develops a dynamic model to examine how a firm with a non-durable experience good can signal its quality with dynamic spot-pricing or future-price commitment. I find that when consumers do not believe the firms price commitment to be credible, the high-quality firms most profitable equilibrium outcome is to pool in the first period and separate in the second period. In contrast, when price commitment is credible, the high-quality firm may signal its quality with either a lower-than-first-best first-period price or a higher-than-first-best second-period price. Credible price commitment will benefit the high-quality firm by lowering its signaling cost and hurt the low-quality firm, but can either increase or decrease consumer surplus and social welfare depending on the quality difference between the two types of firms.
Chapter 2: Dynamic Pricing of Experience Goods in Markets with Demand Uncertainty
This chapter studies a firms optimal dynamic pricing strategies for its experience goods in markets, where the distribution of consumers valuations is ex ante unknown. I find several interesting findings. First, a high-quality firm can signal its quality with either a skimming-pricing strategy or a penetration-pricing strategy in the early period. Second, though a firm with higher quality benefits more from learning market demand, in equilibrium the low-quality firm not the high-quality firm will learn demand if consumers have very different willingness to pay. Third, although consumers have higher willingness to pay for the high-quality product, in the first period the high-quality firm may actually charge a lower price than the low-quality firm. Lastly, the firm may earn higher profits when its initial pricing decision is made under demand uncertainty than under no demand uncertainty. The underlying reason is that the presence of demand uncertainty can sufficiently lower the high-quality firms signaling cost, allowing it to make higher profits by setting future prices based on its high quality.
Chapter 3: Who Benefits from Big Data Collected by In-Vehicle Data Recorders?
The car insurance market is plagued with problems of adverse selection and moral hazard. In-vehicle data recorders can collect massive amount of information (or big data) about the drivers risk factors and driving behaviors. This monitoring technology allows the firm to set its insurance premium based on better estimates of the drivers risk factors, alleviating the adverse selection problem. In addition, the firm can charge a premium based on the customers recorded driving behaviors; this helps to reduce the drivers moral hazard. I provide an analytical framework to examine the impact of such monitoring technology on the insurance firms and the consumers. My analysis shows that in a duopoly one firms adoption of the monitoring technology may benefit both firms because of the less severe competition in the market. Finally, I show that if one firm has adopted the monitoring technology, its competitor may have no incentive to adopt that technology even if it is free.
Chair and Committee
Baojun John, Jiang Nachbar
George-Levi Gayle, Paulo E. Natenzon, Bruce C. Petersen,
Chen, Yu-Hung, "Essays on Economics and Marketing" (2016). Arts & Sciences Electronic Theses and Dissertations. 753.
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