Essays in Industrial Organization

This dissertation extends the empirical industrial organization literature with two essays on strategic decisions of firms in imperfectly competitive markets and one essay on how inertia in consumer choice can result in significant welfare losses. Using data from the airline industry I study a well-known puzzle in the literature whereby incumbent firms decrease fares when Southwest Airlines emerges as a potential entrant, but is not (yet) competing directly. In the first essay I describe this so-called Southwest Effect and use reduced-form analysis to offer possible explanations for why firms may choose to forgo profits today rather than wait until Southwest operates the route. The analysis suggests that incumbent firms are attempting to signal to Southwest that entry is unprofitable so as to deter its entry. The second essay develops this theme by extending a classic model from the IO literature, limit pricing, to a dynamic setting. Calibrations indicate the price cuts observed in the data can be captured by a dynamic limit pricing model. The third essay looks at another concentrated industry, mobile telecoms, and studies how inertia in choice (be it inattention or switching costs) can lead to consumers being on poorly matched cellphone plans and how a simple policy proposal can have a considerable effect on welfare.

Essays in Empirical Operations Management: Bayesian Learning of Service Quality and Structural Estimation of Complementary Product Pricing and Inventory Management

This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.