Some of the most vulnerable areas across the world have started experiencing the consequences of climate change, with action to deal with it long overdue. Florida, one of the most visited tourist destinations in the world, holds one of the most 'unenviable' positions in terms of its vulnerability to climate change with the effects already visible, particularly on its coastal areas. Climate is one of the major factors in affecting travel motivations and destination choice, and as such the implications of climate change for tourist behavior and demand patterns are significant. Beside the physical impacts of climate change, society's perception of climate change, and the response to it at various decision-making levels, have become critical issues. This dissertation presents the perspective of tourists who have previously visited Florida, in a hypothetical scenario of changed climatic conditions. It is proposed that existing social representations about climate change, and therefore individuals' attitudes, views and beliefs concerning this phenomenon, need to be taken into account when examining tourists' stated intentions regarding their prospective visitation intentions and potential changes in future tourism demand. Using social representation theory as a theory of reference, this dissertation presents an analysis of visitors' responses to climate change impacts and adaptation measures, in consideration of their attitudes towards climate change. The main purpose of the study was to understand whether, with the implementation of adaptation strategies directed to limit negative impacts of climate change, the likelihood of tourists to return to Florida would improve in comparison with a future in which no action is taken at the state level to address climate change. In this scenario, the filter of social representations in shaping tourists' perspectives was used as a system of explanation of different tourist responses. This study contributes to the tourism and climate change body of knowledge by advancing a further step toward understanding potential responses of tourists in a scenario in which a destination's most appealing climatic and natural resources are impacted by climate change. The existence of a relationship between tourist's visitation intentions and the social representations they hold with respect to climate change offers a different way to look at tourists' stated responses. In fact, this study shows that predicting shifts in tourism demand based on stated visitation intentions requires caution. The findings of this study can encourage future researchers to pursue a more critical way of exploring the meaning behind tourists' stated responses, which could lead to expanding our current understanding of how climate change will transform tourism demand across different destinations.

The purpose of this dissertation is to create a holistic diversity management measurement scale and to analyze the impact of diversity management on employees' attitudes and behavior in the hospitality and tourism industry. Effective diversity management can have a multitude of positive outcomes in the hospitality and tourism industry. However, there is little research conducted regarding the direct and indirect impacts of diversity management on the attitudes and behavior of hospitality and tourism industry employees. This dissertation used a mixed-method approach to create a measurement scale to evaluate diversity management practices for the hospitality and tourism field. The first study of this dissertation included a scale development process using a qualitative and then a quantitative phase. Literature review and semi-structured interviews were conducted for developing the items for the diversity management scale. These items were then refined to finalize the diversity management measurement scale through a quantitative phase using exploratory factor analyses. The impact of diversity management on hospitality and tourism industry employees' job performance, service innovation behavior, and engagement were analyzed through a quantitative study using this measurement instrument. Structural equation modeling was used to test the hypothesized research model. The present research is the first of its kind in the hospitality and tourism field. The measurement scale developed in this study will expand the boundaries of diversity management research in the hospitality and tourism industry. This current research further establishes a link between diversity management and positive employee-related outcomes in the hospitality and tourism industry. The assessment of these relationships should extend the literature and open new models of academic research with additional organizational outcomes. Leaders in the hospitality and tourism industry can gain vital insight regarding the importance of effective diversity management through the study results.

International Labor Organization estimated that 40.3 million people were victims of human trafficking in 2016. The high rate of human trafficking has drawn policymakers' attention to this issue and made them enforce anti-trafficking laws and regulations. However, their legal measures have not been based on solid empirical evidence due to the lack of academic research on human trafficking. The scant research available on human trafficking has been mainly descriptive or an investigation of sex trafficking cases to provide help to survivors. Thus, there is a need for research to explore human trafficking as a human rights issue through various perspectives such as sociology and psychology and within various contexts such as hospitality and tourism. To respond to the above-mentioned need, the current research aims to examine the antecedents of hotel employees' likelihood to help the victims of human trafficking. The U.S. lodging industry is the selected setting of the current study since it is recognized as one of the top venues of human trafficking. A conceptual framework was developed and a survey-based quantitative study was conducted to test it. Data were analyzed using Structural Equation Modeling. Findings showed that employees' sympathy, feelings of compassion towards the victims, is the key factor to their likelihood to help. Also, employees' familiarity with human trafficking and perceived susceptibility of the lodging industry to human trafficking play an important role in their decision-making process to help. The present study provides important theoretical and practical implications. Theoretically, the study addresses the research gap by focusing on the psychological and sociological aspects of human trafficking and integrating egoism and altruism schools of thought. Practically, the study provides insights for the lodging industry practitioners on the increase of employees' prosocial tendency towards victims of trafficking.

The purpose of this study was to estimate the drivers' travel time with the occurrence of an incident on freeway. Three approaches, which were shock wave analysis, queuing theory and cellular automata models, were initially considered, however, the first two macroscopic models were indicated to underestimate travel time by previous literature. A microscopic simulation model based on cellular automata was developed to attain the goal. The model incorporated driving behaviors on the freeway with the presence of on-ramps, off-ramps, shoulder lanes, bottlenecks and incidents. The study area was a 16 mile eastbound section of I-66 between US-29 and I-495 in northern Virginia. The data for this study included loop detector data and incident data for the road segment for the year 2007. Flow and speed data from the detectors were used for calibration using quantitative and qualitative techniques. The cellular automata model properly reproduced the traffic flow under normal conditions and incidents. The travel time information was easily obtained from the model. The system is promising for travel time estimation in near real time. / Master of Science

One of the ways to define mobility in a transportation system is total travel time for all travelers using the transportation network. A good assessment of the mobility is essential for knowing the points of congestion in the network and the factors responsible for the congestion. Also the change in mobility from the baseline to the horizon year would give the modeler an idea of the effectiveness of the various transportation systems. One of the applications of the mobility measurement is the evaluation of aviation technologies proposed by FAA to ease the congestion. This paper addresses a method to estimate the mobility of the air transportation network in the baseline year (2000). Also presented is a method to estimate the mobility to the horizon year by considering congestion on the roadway. / Master of Science

The purpose of this study was to employ a network perspective to detect fluctuations in tourism (at the level of tourism areas and by inbound tourism markets) that co-occur with hazardous events. Specifically, the study focuses on the Air Travel Tourism (ATT) network of the Hawaiian Islands and its changes with the incidence of nine hazardous events from 2015 to 2021. The three main aspects of the ATT network, which include tourism connections, island preferences, and concentrations of inbound tourism markets were analyzed for a total of eighty-four monthly and seven annual network models. The results suggest that the network perspective provides insights that are especially applicable to the study of prolonged hazardous events such as the COVID-19 pandemic. Among local hazardous events, the volcanic eruption and Hurricane Lane, both occurring in 2018, were associated with a decrease in visitors and preferences for Hawaii and Molokai Island. During the COVID-19 pandemic, uneven fluctuations were detected for all groups of the Hawaiian Islands. The peripheral islands had the most interrupted tourism connections during the pandemic period, while the core and semi-core islands had the most fluctuations in preference. International travel restrictions favored increases in concentrations of both domestic markets in Oahu Island, and only of the U.S. West market in the other islands. Interestingly, the mix of pandemic-related travel restrictions and recovery policies corresponded with asymmetrical tourism fluctuations for each island. The annual results suggested more stability in the aspects of the ATT network compared to the monthly results. The current study advances the tourism literature on hazardous events with insights from a network perspective. Additionally, the findings serve as a starting point for the development of new propositions and hypotheses to be tested in future research. In terms of practical implications, the results suggest that the network perspective may be beneficial for tourism practitioners to evaluate the differentiated results of policies issued in times of hazardous events. Furthermore, the unevenness of the detected fluctuations in the ATT network underscores the value of tailored planning, management, and marketing strategies in times of turbulence.

Hotel reward programs have been in existence for three decades. These programs were originally established as a customer relationship management tool to reward loyal guests for their patronage. Over time, there have been indications that the programs that are intended to inspire loyalty to the company have actually inspired loyalty to the program itself. The aim of this study was to analyze the antecedents of program satisfaction and program loyalty in hotels to determine the relationship between the program attributes and the impact on program loyalty. Switching costs were also analyzed to determine if they played a moderating role in the relationship between program satisfaction and program loyalty. Data was collected using an online questionnaire based upon measures from previous studies on the following variables: functional value, external value, utilitarian value, hedonic value, symbolic value, program satisfaction, switching costs, and program loyalty. Using the statistical software SPSS and SmartPLS, the data was empirically tested. The results indicated that program satisfaction is a driver of program loyalty. Switching costs did not have a statistically significant impact on the relationship between program satisfaction and program loyalty. Of great interest is the indicators of perceived value. As utilitarian value has been used as a dominant portion of reward programs in the past, in this study, it did not have a significant impact on the perceived value of the program. As the needs of customers change, it is necessary for industry to change as well. The research presented in this study has both theoretical and practical implications, as the results can provide a greater understanding of the value of hotel rewards from the customers viewpoint.

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The purpose of this research project was to evaluate the techniques outlined in the National Cooperative Highway Research Program Technical Report 255 Highway Traffic Data for Urbanized Area Project Planning and Design (NCHRP-255), published in 1982 by the Transportation Research Board. This evaluation was accomplished by using a regional travel demand forecast model calibrated and validated for the year 1990 and developing a highway forecast for the year 2000. The forecasted volumes along the Capital Beltway (I-495/I-95) portion located in the State of Maryland were compared to observed count data for that same year. A series of statistical measures were used to quantitatively evaluate the benefits of the techniques documented in NCHRP-255. The primary research objectives were: • To critically evaluate the ability of a regional travel demand forecast model to accurately forecast freeway corridor volumes by comparing link forecast volumes to the actual count data. • To evaluate and determine the significance of post-processing techniques as outlined in NCHRP-255. The most important lesson learned from this research is that although it was originally written in 1982, NCHRP-255 is still a very valuable resources for supplementing travel demand forecast model output. The "raw" model output is not reliable enough to be used directly for highway design, operational analysis, nor alternative or economic evaluations. The travel demand forecast model is a tool that is just part of the forecasting process. It is not a turn-key operation, and travel demand forecasts cannot be done without the application of engineering judgment. / Master of Science