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.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1210 |
| Date | 01 January 2020 |
| Creators | Farboudi Jahromi, Melissa |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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