Antecedents of Tendency to Help the Victims of Human Trafficking from the Perspective of High-Contact Service Employees in the Lodging Industry

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\u27 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\u27 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\u27 sympathy, feelings of compassion towards the victims, is the key factor to their likelihood to help. Also, employees\u27 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\u27 prosocial tendency towards victims of trafficking

Customers’ Behavioural Immune System Responses to Pathogen Cues at Tourism and Hospitality Facilities During the COVID-19 Pandemic

The COVID-19 pandemic has imposed various obstacles and restrictions for the tourism and hospitality industry. This paper adopts the concept of the behavioural immune system to discuss tourism and hospitality customers\u27 potential behaviours during the pandemic and provide business strategies that can address these behaviours. The behavioural immune system is a motivational system that determines individuals\u27 behaviours to pathogen infection. First, this study introduces the mechanism of the behavioural immune system including environmental evaluation and aversive perception, aversive emotional and cognitive responses, and avoidance behaviours. It also provides examples in the guest service context to better portray the mechanism. Second, the study suggests specific measures for tourism and hospitality businesses that may help them to prevent the aversive and avoidance responses of customers triggered by their behavioural immune system during the pandemic. Then, the study integrates customers\u27 responses and businesses\u27 measures in a framework, which extends the literature on customers\u27 behaviour in the hospitality and tourism context. To the authors\u27 knowledge, this is the first time the concept of behavioural immune system is adopted to discuss customers\u27 behaviours towards tourism and hospitality services during a pandemic

Understanding the Determinants of Intention to Stay at Medical Hotels: A Consumer Value Perspective

This study proposed and tested a theoretical framework that investigated the impacts of perceived benefits (i.e., perceived convenience and potential for savings) and perceived risks (i.e., physical risk, psychological risk, and performance risk) on patients\u27 perceived value of staying at medical hotels. In addition, the current study examined the influence of perceived value on patients\u27 intention to stay at medical hotels. Structural equation modeling (SEM) was performed to test the study model by utilizing data comprised of 351 patients who stayed in a hospital overnight to receive a medical treatment. The results revealed that perceived convenience and potential for savings positively; performance risk and psychological risk negatively influenced perceived value. In addition, perceived value positively impacted intention to stay at medical hotels. The study findings offer valuable contributions to the hospitality, healthcare and medical tourism literature, and important practical implication for hotel and hospital operators

Developing an Overarching Framework on Theme Park Research: A Critical Review Method

This paper presents a critical review of prior research on theme parks. By critically reviewing 195 academic publications in major hospitality and tourism journals as well as other journals covering theme park-related disciplines, a total of 138 studies were included in the final analysis. The results propose a conceptual framework that delineates the concepts, theoretical foundations, and multi-relations among critical stakeholders within the theme park arena. The proposed framework indicates the links between the theoretical concept and industry practices and provides a holistic view for industry practitioners to understand the fundamental concepts and visitors\u27 demands. Accordingly, this study provides a benchmark to help industry practitioners design their theme park products. Furthermore, the framework identifies vital mediators (social factor, technical factor, economic factor, environmental factor, and political factor) in theme park destinations, guiding macro policies to promote the local theme park industry. Given the fragmented understanding of theme park research\u27s conceptualization and its emerging popularity in hospitality and tourism research, this paper provides valuable contributions to the knowledge base of theme park research

Employees\u27 Helping Behavior Toward the Victims of Human Trafficking in the Lodging Industry

Purpose: This study aims to examine the factors that influence hotel/motel employees\u27 helping behavior toward the victims of human trafficking. Design/methodology/approach: Using a survey-based quantitative method, this study examines and compares two models of helping behavior based on egoism and altruism theories to measure the helping tendencies of lodging employees toward victims of human trafficking. Findings: The study results show that perceived intrinsic rewards of helping and empathy with the victims are the major antecedents of employees\u27 likelihood to help the victims. Research limitations/implications: The study contributed to the egoism school of thought and the Cost-Reward Model by showing that only perceived intrinsic rewards drive individuals\u27 intention to help in risky covert situations, such as human trafficking, while perceived extrinsic rewards may demotivate people to help in these situations. Originality/value: Previous studies overlooked the role of the lodging industry in human trafficking. This study focuses on service employees as potential helpers of the victims as they notice in hotels/motels

Value Co-Creation In A Sharing Economy: The End Of Price Wars?

The growing phenomenon of the sharing economy facilitates collaborative production and consumption, which highlights the concept of value co-creation. The current study aims to investigate the role of value co-creation in a sharing economy with an examination of consumers’ willingness to pay a premium price. Three types of functional, social, and emotional co-created values were explored through an online survey that focused on the pre-consumption, mid-consumption, and post-consumption stages. Four hundred and ninety-nine valid surveys were collected. The results showed that activities that involve functional and social values in the pre-consumption stage are stimulators of paying a premium price. In the mid-consumption stage, emotional value is also important for customers. However, in the post-consumption stage, only social-value-based activities are associated with willingness to pay a premium price

Agent-Based Modelling for Tourism Research

Managing tourism destinations has become increasingly challenging due to the tourism ecosystem\u27s complex nature. Tourism destinations can be seen as complex systems consisting of interactive agents such as tourists, tourism attractions, service providers, destination marketing organizations (DMOs), and the local communities. These agents have various types of interactions with each other in real-time. This paper introduces how the Agent-Based Modelling (ABM) approach can be used in tourism research. ABM is a computational modelling approach that examines the tourism system\u27s dynamic behaviour based on the agents\u27 interactions and simulates how the microscopic interactions lead to macroscopic phenomena. ABM can be leveraged with existing behavioural theories and various types of data to address complex topics such as sustainability and social equity. This study reviewed existing literature that adopts ABM throughout tourism planning, development, and management stages. We identified seven themes where ABM would be appropriate for studying tourism: sustainable tourism, tourist decision-making behaviour, tourist flow management, crisis management, cultural tourism management, natural tourism management, and transportation management. We further propose an agent-based modelling framework with key agents and attributes to guide the modelling process for tourism researchers and practitioners

Leveraging Data Analytics to Understand the Relationship Between Restaurants\u27 Safety Violations and COVID-19 Transmission

This paper leverages natural language processing, spatial analysis, and statistical analysis to examine the relationship between restaurants\u27 safety violations and COVID-19 cases. We used location-based consumers\u27 complaints data during the early stage of business reopening in Florida, USA. First, statistical analysis was conducted to examine the correlation between restaurants\u27 safety violations and COVID-19 transmission. Second, a neural network-based deep learning model was developed to perform topic modeling based on consumers\u27 complaints. Third, spatial modeling of the complaints\u27 geographic distributions was performed to identify the hotspots of consumers\u27 complaints and COVID-19 cases. The results reveal a positive relationship between consumers\u27 complaints about restaurants\u27 safety violations and COVID-19 cases. In particular, consumers\u27 complaints about personal protection measures had the highest correlation with COVID-19 cases, followed by environmental safety measures. Our analytical methods and findings shed light on customers\u27 behavioral shifts and hospitality businesses\u27 adaptive practices during a pandemic. • We leverage data analytical approaches to understand the relationship between restaurants\u27 safety violations and COVID-19 cases. • A positive relationship between restaurants\u27 safety violations and COVID-19 cases is confirmed. • Complaints about personal safety measures are most associated with the COVID-19 cases. • Consumers\u27 complaints and COVID-19 cases are distributed unevenly across Florida