American households spend over $30 billion on tourism and take over 177 million long-distance leisure trips each year. These trips, and the subsequent vehicle miles traveled, have a significant impact on the transportation systems at major destinations across the country, especially those destinations that are still improving their transportation systems. Surprisingly, not much is known related to this type of travel. This dissertation expands the current knowledge of tourism travel behavior, in terms of how people make decisions regarding long-distance leisure activities and time use. Specifically, this dissertation develops and comprehensively examines a behavioral framework for household tourism time use and activity patterns. This framework combines (and builds upon) theory and methods from both transportation and tourism research fields such that it can be used to improve tourism demand modeling. This framework takes an interdisciplinary approach to describe how long distance leisure travelers allocate and maximize their time use across various types of activities. It also considers the many levels of tourism time use and activity patterns, including the structuring the broad annual leisure activity and time budget, forming individual tourism trips within the defined budget, and selecting specific activities and timing during each distinct tourism trip. Subsequently, this dissertation will additionally apply the time use and activity participation behavioral framework to four critical tourism research topics to demonstrate how the tourism behavioral framework can effectively be used to provide behavioral insights into some of the most commonly studied critical tourism issues. These application topics include household participation in broad tourism travel activities, travel parties’ tourism destination and travel mode selection, individuals’ loyalty towards daily and tourism activities, and travel parties’ participation in combinations of specific tourism trip activities. These application studies incorporate a variety of data sources, decision makers, study scales, situation-appropriate modeling techniques, and economic/individual/environmental factors to capture all aspects of the decision and travel activity-making process. / text

Active asthma and asthma-related health care utilization are higher among adult females than they are among adult males in Puerto Rico. The purpose of this study was to examine the determinants of the risk of active asthma and associated health care utilization and asthma control among women in Puerto Rico. Guided by the Andersen behavioral model, the study included data from the Asthma Call-Back Survey (ACBS) during 2011 and 2012 in Puerto Rico. The associations between active asthma and behavioral, demographic, and environmental factors were assessed using logistic regression. The relationship between asthma-related health care utilization and predisposing, enabling, and need factors was examined using multiple linear regression. The association between achieved level of asthma control and asthma-related healthcare utilization was investigated using multinomial logistic regression. Results of the logistic regression indicated that being out of work, being in a middle income category, and being obese significantly increased the odds of active asthma. Being self-employed and being in the income category of $15,000-$25,000 significantly predicted the frequency of emergency room visits (ERVs). Results of the multinomial logistic regression indicated that physician urgent visit and ERV were significantly associated with poorly controlled asthma symptoms. The positive social change implication of these findings is that the identified risk factors can be used to develop asthma management plans to prevent and control asthma attacks in at-risk populations and reduce asthma-related health care utilization cost