FAMILY CHARACTERISTICS, STATE PROGRAM EFFECTIVENESS, AND REPORT OF INADEQUATE CARE AMONG FAMILIES OF YOUNG CHILDREN WITH HEARING LOSS

Approximately 1.6 per 1,000 newborns in the U.S. are born with hearing loss. Congenital hearing loss poses a risk to their speech, language, cognitive, and social-emotional development. Early detection and intervention can improve outcomes. Every state has an Early Hearing Detection and Intervention program (EHDI) to promote and track screening, audiological assessments and linkage to early intervention. However, a large percentage of children are “lost to system (LTS),” meaning that they did not receive recommended care or that it was not reported. This study used data from the 2009-2010 National Survey of Children with Special Health Care Needs and data from the 2011 EHDI Hearing Screening and Follow-Up Survey to examine how 1) family characteristics; 2) EHDI program effectiveness, as determined by LTS percentages; and 3) the family conditions of education and poverty are related to parental report of inadequate care. The sample comprised 684 children between the ages of 0 and 5 years with hearing loss. The results indicated that living in states with less effective EHDI programs was associated with an increased likelihood of not receiving early intervention services (EIS) and of reporting poor family-centered communication. Sibling classification was associated with both receipt of EIS and report of unmet need. Single mothers were less likely to report increased difficulties accessing care. Poor and less educated families, assessed separately, who lived in states with less effective EHDI programs, were more likely to report non-receipt of EIS and less likely to report unmet need as compared to similar families living in states with more effective programs. Poor families living in states with less effective programs were more likely to report less coordinated care than were poor families living in states with more effective programs. This study supports the conclusion that both family characteristics and the effectiveness of state programs affect quality of care outcomes. It appears that less effective state programs affect disadvantaged families’ service receipt report more than that of advantaged families. These findings are important because they may provide insights into the development of targeted efforts to improve the system of care for children with hearing loss.

UNDERSTANDING CUSTOMER CHOICES IN SERVICE OUTSOURCING AND REVENUE MANAGEMENT

This dissertation investigates customer behavior modeling in service outsourcing and revenue management in the service sector (i.e., airline and hotel industries). In particular, it focuses on a common theme of improving firms’ strategic decisions through the understanding of customer preferences. Decisions concerning degrees of outsourcing, such as firms’ capacity choices, are important to performance outcomes. These choices are especially important in high-customer-contact services (e.g., airline industry) because of the characteristics of services: simultaneity of consumption and production, and intangibility and perishability of the offering. Essay 1 estimates how outsourcing affects customer choices and market share in the airline industry, and consequently the revenue implications from outsourcing. However, outsourcing decisions are typically endogenous. A firm may choose whether to outsource or not based on what a firm expects to be the best outcome. Essay 2 contributes to the literature by proposing a structural model which could capture a firm’s profit-maximizing decision-making behavior in a market. This makes possible the prediction of consequences (i.e., performance outcomes) of future strategic moves. Another emerging area in service operations management is revenue management. Choice-based revenue systems incorporate discrete choice models into traditional revenue management algorithms. To successfully implement a choice-based revenue system, it is necessary to estimate customer preferences as a valid input to optimization algorithms. The third essay investigates how to estimate customer preferences when part of the market is consistently unobserved. This issue is especially prominent in choice-based revenue management systems. Normally a firm only has its own observed purchases, while those customers who purchase from competitors or do not make purchases are unobserved. Most current estimation procedures depend on unrealistic assumptions about customer arriving. This study proposes a new estimation methodology, which does not require any prior knowledge about the customer arrival process and allows for arbitrary demand distributions. Compared with previous methods, this model performs superior when the true demand is highly variable.