Dr. Xuan V Tran

This study examines how antecedents, specifically dispositional factors such as Achievement, Affiliation, and Power, along with hotel class, influence revenue outcomes, including average daily rate (ADR), Revenue per Available Room (RevPAR), and Occupancy (OCC). Analyzing 699 TripAdvisor reviews from 2019 to 2024, the research employs structural equation modeling to assess the relationships between guest motivations, hotel classification, and revenue metrics. The Southeastern United States was chosen as the case study region due to its diverse mix of hotel types and guest demographics, providing a rich context for understanding the complex dynamics of hotel revenue management. Findings align with the Slutsky equation, revealing a negative substitution effect on ADR due to OCC and a positive income effect on RevPAR. This study contributes to hospitality revenue management by offering practical insights into optimizing pricing strategies based on guest behavior and market segmentation.

This study explores the adoption of facial recognition (FR) technology in hotel operations and services across various job roles. Given FR’s technological nature and the human-centric focus of hotels, perceived product and process innovations are key factors influencing its adoption. The study examines how these factors and workplace dynamics, such as organizational support and job stress, impact FR adoption. Experimental trials provided first-hand experiences with FR prototypes, and surveys assessed hoteliers’ perceptions of the benefits. Structural equation modelling tested the research model. Findings show that successful FR adoption in hotels relies on process innovation, supported by organizational and employee backing, leading to improved variety, quality, efficiency, and growth in hotel services.

This research aims to employ game theory along with price and income elasticities of demand to reveal hidden strategies for maximizing revenue among competitors in the hotel market, focusing on New York and San Francisco over 20 years. Results suggest that demand for hotels in New York is characterized by luxury-driven income but responsive pricing, while San Francisco exhibits lower income levels but demonstrates Giffen elasticity. Both markets present opportunities for maximizing revenue per available room through a mutually beneficial strategy whereby average daily rates increase in New York and decrease in San Francisco.

The connection between Average Daily Rate (ADR) and hotel room standard in both suburban and resort settings during high and low seasons remains an ongoing challenge. The purpose of this study is to craft practical cues for hotel managers to lean towards specific guiding cues for their effective decision-making of room rates. A study conducted on ADRs and guest comments from suburban and resort hotels across the United States from 2018 to 2023 utilized data from Smith Travel Research and TripAdvisor. Employing a vector error correction model and incorporating game theory, the research revealed that room standards are optimized in both types of accommodations when ADRs increase in resorts and decrease in suburban areas during peak seasons.

Purpose The purpose of this paper is to examine the hotel growth model including hotel brand, culture and life cycle phases of the Myrtle Beach, South Carolina, the fastest growing tourism destination in the United States. Design/methodology/approach Culture reflecting consuming behaviour of low-context innovators and high-context imitators is measured by the price elasticity of demand (PED). Hotel brand reflecting guests’ hotel class is measured by the income elasticity of demand. Autoregressive distributed lag has been conducted on the Smith Travel Research data in 33 years (1989–2022) to determine the relationship among hotel brand, culture and life cycles. Findings Skilled labour is the key to make hotels grow. Therefore, increase room rates when hotels possess skilled professionals and decrease room rates when hotels have no skilled professionals. During the rejuvenation in Myrtle Beach (1999–2003), hoteliers increased room rates for innovators due to skilled professionals to increase revenue. Otherwise, a decrease in room rates due to lack of skilled professionals would lead to increase revenue. Research limitations/implications (1) Although Myrtle Beach is one of the fastest growing tourism destinations in the US, it has a relatively small geographic area relative to the country. (2) Data cover over one tourist life cycle, so the time span is relatively short. Hoteliers can forecast the number of guests in different culture by changing room rates. Practical implications To optimize revenue, hoteliers can select skilled labour in professional design hotel brands which could make an increase in demand for leisure transient guests no matter what room rates increase after COVID-19 pandemic. Social implications The study has considered the applied ethical processes regarding revenue management that would maximize both revenue and customer satisfaction when it set up an increase in room rates to compensate for professional hotel room design or it decreases room rates for low-income imitators in exploration and development. Originality/value This research highlights that (1) skilled design in the luxury hotel brand is the key for the hotel growth and (2) there is a steady state of the growth model in the destination life cycle.

The purpose of the paper is to apply the Slutsky equation to the Bass diffusion model to examine the price and income elasticities of hotel demand in different tourist destinations including cultural, commercial, and coastal cities. The sample was a set of 120 points by ex-post data from the Smith Travel Research in Vietnam. Findings indicate the price in a leisure destination in the beginning of the tourist area life cycle is inelastic, whereas the prices in the business and culture destinations at the end of the cycle are elastic. This study identifies the hidden cost when demand increases in the three destinations, ultimately allowing hoteliers to effectively strategize when making price changes within their industry.

The purpose of the study is to examine the impact factors of 11 high impact practices (HIPs) of the Association of American Colleges and Universities to identify their influences on the learning experience of college students. A research model is developed based on the theory of planned behaviour to link beliefs of high impacts to the practice of learning behaviours. Structure equation modelling analysis was conducted on the performance metrics of 11 American universities from 2014-2021. Findings indicate that undergraduate research can predict the success of other high-impact practices in Florida. The results will guide administrators in higher education to make financial decisions with a reference to factors of high impact practices. Theoretical and practical implications are also presented.

This study uses the game theory to find a Nash equilibrium of price elasticities of hotel demand in the United States before and during the COVID-19 pandemic to interpret the decrease in hotel unemployment rate. The sample selected is the Oahu, Hawaii market due to its higher room rate and higher unemployment rate compared to those in the mainland US. Findings indicate that to increase hotel revenue and decrease unemployment rate, the price elasticity of hotel demand in the mainland US would be higher than the one in Oahu, Hawaii. While the government has built more value into hotels by financially supporting unemployed hotel employees, established hotel brands have maintained their excellent service for their guests during the pandemic.

The principal aim of this study was to verify which destination images of the ten most visited countries in the world in 2014 were rated by Brazilians who have never been to another country. A survey was applied to 263 respondents with the following variables: safety, the price of accommodation, the cost of transport, the duration of the trip, the economic stability of the destination, the political and social stability, the singular tourist attractions, the weather, the local infrastructure, and the friendliness of the local community. Using Partial Least Squares Path Modelling and ANOVA, six hypotheses were tested. The results obtained showed that those countries which are the nearest to Brazil were better evaluated (except for England and France). Safety, followed by the price of accommodation, and the cost of transportation, were the most important attributes of the images in the countries that were best evaluated by potential Brazilian tourists.

Although many tourist regions compete among themselves, there is a scenario of strategic interdependence between them that has not usually been considered in the literature. In this way, this present article has used Game Theory in order to analyse the competition / cooperation between two tourist destinations - namely, between Canada and the USA. In methodological terms, the study has used the Vector Autoregressive model; the Vector Error Correction model; and Granger Analyses in order to forecast the short-term and long-term impacts of tourism receipts between the USA and Canada. The article has used databases from 2007 - 2016 concerning their Gross Domestic Product (GDP). The tourism receipts were obtained from Statistics Canada and UNWTO. The findings have indicated that (1) there was no Nash equilibrium of a GDP payoff for the USA and Canada; (2) The USA has a dominant strategy when developing tourism, but Canada does not.