United States

TOUR 2021

Panel Discussion 2 - Digital Busines Models and Data-Driven Decision Making in Hospitality and Tourism

Dear Delegates, 

On behalf of the organizing committee at UCF Rosen College of Hospitality Management and Elsevier, I have the greatest pleasure to welcome you to the **6th World Research Summit for Tourism and Hospitality: Resilience, Adaptability, and Innovation.** 

Though we cannot host you this year owing to Covid-19 at our beautiful resort-like campus in Orlando, Florida, we believe this virtual and live-streamed conference will provide an interactive, dynamic, and shared international platform for global academics and practitioners to discuss how to enhance research applications and knowledge management through resilience, adaptability, digital intelligence, innovation, and smart knowledge in bringing our industry and research back to normal. This summit particularly offers unique opportunities to unfold and embrace various repercussions of COVID-19 pandemic with various stakeholders, including academic researchers, industry professionals, and government officials, through dialogues on how to better utilize research outputs for the benefits of the industry, in a resilient, intelligent and innovative way. 

I hope you will agree that we have put together a wonderful program including keynote speeches, panel discussions, concurrent presentations, poster sessions, and best paper recognition and award ceremony. We hope you will take advantage of these activities and engage yourself with great learning and sharing opportunities during the two days of the Summit. Thank you for joining us and we look forward to our discussions! 

Sincerely, 
Dr. Youcheng Wang 
Dean and Preeminent Chair Professor

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Despite the fact that researchers agree that AI technologies offer a huge opportunities for firms to analyze data and identify patterns for decision making, many firms utilize these technologies for operational purposes and limit their uses for employee productivity and cost saving (Ivanov, 2019; R. Leung, 2019). The utilization of AI technologies in the systems of the firms is an ongoing process (Law et al., 2019). Compared to other leading industries in AI adoption, tourism and hospitality industry found to have low adoption rates (Bughin et al., 2017). The study of Bughin et al. (2017) indicated that among 14 industries across ten countries around the globe, tourism and hospitality industry was ranked as the lowest in terms of assets (depth of AI technologies, AI spends, and supporting digital assets), usage (product development, operations, supply chain and distribution, customer experience, financial and general management), and labor (exposure to AI in workplace and AI resources per worker. Tourism and hospitality industry is a massive industry that comprises a number of key stakeholders (government, tourism and hospitality organizations and operators, SMEs, NGOs, suppliers, employees, tourists, utilities and infrastructure, education, communities, and transport) who involve with the industry (Stainton, 2021). Hence, the aim of the current study is to investigate the perception of tourism and hospitality stakeholders on motivators, enablers and barriers of the implementation of AI technologies in the tourism and hospitality firms in the UAE. This study will adopt mixed method. It will start with qualitative approach (focus group) followed by a quantitative approach (questionnaire).

Strategic implementation of artificial intelligence in the UAE tourism and hospitality industry

As there is scarce research on how hotels are building capacity for supporting a smart destination, this study aims at uncovering current efforts of the hotel sector in joining and building the smart destination challenge, by answering the questions: are hotels prepared to be part of a smart destination? And how can technology support hotel engagement with customers adopting a co-creation approach? To address these questions, the following objectives were defined: i) to analyze adoption of enabling technologies by hotels, ii) to explore how technologies are helping hotels to enhance co-creation with guests; and iii) to classify hotel innovation adoption in the near future. A survey will be conducted to managers of Iberian hotels. Madrid ranks 25th and Lisbon 52th in the IESE Cities in Motion Index (IESE, 2020). And according to UNWTO’s (2019) ranking of countries with the largest surplus in the travel balance ranking, Spain ranks 2nd and Portugal 9th. These data indicate an unbalanced performance of the two Iberian countries in terms of city socio-economic dynamics and tourism. Accordingly, the study will focus on Lisbon and Madrid as capital cities of Portugal and Spain and examine hotel capacity to support their transition to the smart city paradigm. Results will allow identification of hotels  integration of new technologies and orientation to smartness and insights on best practices for enhancement of Lisbon and Madrid as smart destinations will also be provided.

Boosting smart destinations through adoption of new technologies: An Iberian perspective

Study Propose:

Senior living communities (SLC) promote a sense of community for their residents as seniors’ supportive arrangements. Sense of community is positively related to residents’ successful aging when they reside in these communities. The purpose of this study was to investigate the impacts of the four sense of community dimensions— reinforcement of needs, membership/sense of belonging, influence, and social and emotional connections—on SLC residents’ satisfaction with the community. Additionally, the study examined the impacts of residents’ satisfaction with the SLC on satisfaction with life, word-of-mouth (WOM) for the SLC (where seniors currently reside), and WOM for moving to a SLC in general.

Study Method:

243 senior citizens who were living in SLCs in the United States were surveyed. Structural equation modeling (SEM) was utilized to test the study hypotheses.

Study Findings:

The study results indicated that all four of the sense of community dimensions significantly impacted residents’ satisfaction with the SLC. The results also indicated that social and emotional connections had the strongest impact on residents’ satisfaction with the SLC, followed by membership, reinforcement, and influence. The study results further showed that residents’ satisfaction with the SLC positively impacted satisfaction with life, WOM for the SLC (where seniors currently reside), and WOM for moving to a SLC in general.

Theoretical Implications:

The findings of this study demonstrated the applicability of the sense of community in the senior living domain. In addition, the study results confirmed the positive impact of residents’ satisfaction on satisfaction with life, WOM for the SLC, and WOM for moving to SLC by providing valuable insights for researchers in the context of aging.

Practical Implications:

This study offers significant practical contributions for SLC owners and practitioners to enhance their residents’ sense of community level.

Sense of community among residents in senior living communities

The COVID-19 pandemic caused unprecedented furloughs and layoffs throughout the global hospitality industry. As a result, new policies in the hospitality industry altered the way employees interact with their work environment (Huang et al., 2020). This study examined laid-off and furloughed workers’ intention to return to their organization and to the hospitality industry. The literature has not yet investigated the effects of anticipated workplace changes on return intent. The purpose of this study was to determine which changes were the most impactful in shaping hospitality workers’ return to their organization and to the industry.




Participants were recruited through Prolific.com targeting those who were laid off or furloughed from their hospitality job due to COVID-19 at the time of data collection. In total, the analyses included 219 laid-off or furloughed hospitality workers from various industry sub-sectors (56.4% food service, 14.1% lodging, 28.7% other). A summary of our measures is provided in Table 1.




Descriptive statistics and correlations among study variables are located in Table 2. Stepwise regression analysis with forward selection was used to identify the worries that predicted intention to return to their job and intention to return to industry. Regression analysis revealed that (a) worry about sick leave policies (b= -.17,p< .001) and (b) worry about workload intensification (b= -.15,p< .001) were the strongest predictors of intent to return to the hospitality organization. The only significant predictor of intent to return to the hospitality industry was worry about enforcing COVID-19 policies (b= .20,p< .001). Detailed regression results are in Table 3 and 4.




Implications of this study highlight a greater responsibility that hospitality industry stakeholders must acknowledge for implementing systems and policies that take returning employee perspectives into consideration, addressing their concerns around sick leave, workload intensification, and worry about enforcement policies.




Tables [https://drive.google.com/file/d/15TReEod5TBApEk9K7nk4oTuCravX8spY/view?usp=sharing]

Predictors of return intent in the hospitality industry in the age of COVID-19

In recent years positive tourism has become an emerging trend, which has not yet been sufficiently examined. Positive tourism as such is grounded in positive psychology, that primarily studies human well-being, or more precisely what makes one's life worth living. However, as of now there are only a few studies that are focusing on happiness in the tourism context. Even though tourism is one of the crucial determinants of overall life satisfaction and happiness. Furthermore, recent studies found that visitors' happiness has a substantial influence on their satisfaction, behavior in the particular destination and even their loyalty perception.

Therefore, the main focus of this study lies in the examination of visitors' happiness in the loyalty context among domestic visitors of the Moravian wine region (the largest wine region in the Czech Republic). Hence, the influence of 17 loyalty factors on two happiness indicators (the stay in destination made visitors happy and the stay in the destination contributed to visitors' happiness) was examined.

Based on the multiple regression analysis, there are seven loyalty factors that have an influence on happiness indicators. Namely, these factors are: relaxation, quality of wine, natural attractions, information about wine, friendly acceptance by the locals, wine culture and traditions as well as vineyard excursion. Furthermore, based on Kruskal-Wallis test, gender and income have a substantial impact on both happiness indicators.

In conclusion, what made visitors mostly happy were some of the key features of the Moravian wine region, which might consequently lead to the higher level of perceived happiness in this particular destination. That might also potentially add to a stronger emotional tie with that destination. Consequently, it could help the destination to distinguish itself from other competitors as well as the visitors might be more inclined to recommend it to their acquaintances.

Panel Discussion 2 - Digital Busines Models and Data-Driven Decision Making in Hospitality and Tourism

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