The development and psychometric properties of the HIV and Abuse Related Shame Inventory (HARSI).

Shame has been shown to predict sexual HIV transmission risk behavior, medication non-adherence, symptomatic HIV or AIDS, and symptoms of depression and PTSD. However, there remains a dearth of tools to measure the specific constructs of HIV-related and sexual abuse-related shame. To ameliorate this gap, we present a 31-item measure that assesses HIV and sexual abuse-related shame, and the impact of shame on HIV-related health behaviors. A diverse sample of 271 HIV-positive men and women who were sexually abused as children completed the HIV and Abuse Related Shame Inventory (HARSI) among other measures. An exploratory factor analysis supported the retention of three-factors, explaining 56.7% of the sample variance. These internally consistent factors showed good test-retest reliability, and sound convergent and divergent validity using eight well-established HIV specific and general psychosocial criterion measures. Unlike stigma or discrimination, shame is potentially alterable through individually-focused interventions, making the measurement of shame clinically meaningful.

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.