Mobile Clinics & Bundled Healthcare: An Exploration of Patient Perceptions of the SughaVazhvu Approach to Chronic Care Management

As the burden of non-communicable diseases increases worldwide, it is imperative that health systems adopt delivery approaches that will enable them to provide accessible, high-quality, and low-cost care to patients that need consistent management of their lifelong conditions. This is especially true in low- and middle-income country settings, such as India, where the disease burden is high and the health sector resources to address it are limited. The subscription-based, managed care model that SughaVazhvu Healthcare—a non-profit social enterprise operating in rural Thanjavur, Tamil Nadu—has deployed demonstrates potential for ensuring continuity of care among chronic care patients in resource-strained areas. However, its effectiveness and sustainability will depend on its ability to positively impact patient health status and patient satisfaction with the care management they are receiving. Therefore, this study is not only a program appraisal to aid operational quality improvement of the SughaVazhvu Healthcare model, but also an attempt to identify the factors that affect patient satisfaction among individuals with chronic conditions actively availing services.

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.