Examining the impact of artificial intelligence on hotel employees through job insecurity perspectives

Artificial intelligence is another advance in technology for the hotel industry and its role is undetermined at this time. The overarching purpose of this treatise was to examine hotel employees’ perception of AI and its impact by identifying the critical role of job insecurity, job engagement, and turnover intention through a pragmatic approach. An explanatory sequential mixed-methods design was used by conducting a quantitative study with an empirical survey method followed by a qualitative study with a case study method. The results from the quantitative study demonstrated that perceived job insecurity significantly affected perceived job engagement and perceived job insecurity indirectly affected turnover intention through intermediary variable of perceived job engagement. There were no statistical differences between non-managerial positions and managerial positions. These results were fully supported by the qualitative study. The implications from these findings were provided to articulate the influence of AI on hotel employees.     

Using machine learning and big data for efficient forecasting of hotel booking cancellations

Cancellations are a key aspect of hotel revenue management because of their impact on room reservation systems. In fact, very little is known about the reasons that lead customers to cancel, or how it can be avoided. The aim of this paper is to propose a means of enabling the forecasting of hotel booking cancellations using only 13 independent variables, a reduced number in comparison with related research in the area, which in addition coincide with those that are most often requested by customers when they place a reservation. For this matter, machine-learning techniques, among other artificial neural networks optimised with genetic algorithms were applied achieving a cancellation rate of up to 98%. The proposed methodology allows us not only to know about cancellation rates, but also to identify which customer is likely to cancel. This approach would mean organisations could strengthen their action protocols regarding tourist arrivals.     

Exploring hotel guests' perceptions of using robot assistants

The growing popularity of robot services blurs the boundaries of robotics and human life. Concomitant to the trend, many hotel brands have adopted a robot-based automation system in their properties. This study attempted to understand the underlying perceptions of the hotel guests' robot-using behaviors. A sample of 494 potential users of a hotel robot assistant was examined and analyzed. The result showed six factors, including three functional aspects (i.e., facilitating conditions, performance expectancy, and innovativeness) and three emotional aspects (i.e., social presence, hedonic motivation, and perceived importance). Moreover, this study categorized the respondents into cohesive groups that show similar characteristics. Based on different levels of perceptions and demographic information, four clusters were named as ‘The ordinary,’ ‘Enthusiastic adopter,’ ‘Tech laggard,’ and ‘Value seeker.’ The result of this study is expected to help the hotel industry to better target potential customers by understanding the different types of users of robotic technology.     

Determinants of using operating lease in the hotel industry

This study investigated the determinants of using operating lease in the hotel industry. The hotel industry has utilized operating lease not only for operating equipment but also as a financing instrument through ‘sales and lease back.’ This study found that hotel firms with less internal funds and/or with higher debt ratios are more likely to use operating lease. Contrary to the studies of other industries, hotel firms with less financially distressed are more likely to use operating lease. This study indicated that operating lease decrease as firm size increases, but only up to a certain level, after that level operating lease increase as firm size increases. Contrary to our expectations, the growth opportunity of hotel firms appeared to have no relationship to use of operating lease. These findings contribute to further understandings of hotel industry-specific information regarding what drives hotel firms to use operating lease.     

Reducing burnout and enhancing job satisfaction: Critical role of hotel employees’ emotional intelligence and emotional labor

Despite its strong theoretical relevance with emotional labor, employees’ ability to understand and regulate emotions (i.e., emotional intelligence, EI) has seldom been studied, especially how it affects hotel employees responding to the firm's display rules (i.e., emotional labor) and experiencing burnout and job satisfaction. Thus, this study investigated direct and indirect effects of employees’ EI on two different forms of emotional labor (i.e., emotional effort: EE; emotional dissonance: ED): burnout and job satisfaction. Data were collected from 309 customer-contact hotel employees and managers in the United States. Results of structural equation modeling showed that EI had a direct, positive effect on EE and personal accomplishment and a direct, negative effect on ED and depersonalization. EI was also found to indirectly affect job satisfaction and emotional exhaustion through the mediating roles of personal accomplishment and ED, respectively. Additionally, ED was found to directly affect depersonalization and indirectly affect job satisfaction through emotional exhaustion while EE directly affects personal accomplishment and indirectly affects job satisfaction through personal accomplishment. Finally, personal accomplishment was found to mediate the depersonalization–job satisfaction relationship. Managerial implications for human resource practices are provided.     

Re-examining the market structure effects on hotel performance using market share inequality

Previous studies have suggested that the Herfindahl–Hirschman Index (HHI) does not adequately account for market structure. To remedy this problem, this article further decomposes the HHI into two components: the number of competitors and market share inequality. Using the metropolitan-level data of tourist hotels in Taiwan, this article estimates the effect of these variables on hotels’ profits. This article shows that while a single measure of the HHI does not have a significant effect on hotels’ profits, decomposing HHI leads to different results. It shows that increasing the number of competitors may improve hotels’ profitability, and by contrast, greater inequalities in market shares may be detrimental to the profit in the room market.     

The effects of emotional intelligence on counterproductive work behaviors and organizational citizen behaviors among food and beverage employees in a deluxe hotel

The purpose of this study is to understand the interrelationships among the emotional intelligence of employees in a deluxe hotel, their counterproductive work behaviors, and organizational citizen behaviors. The sample of this study consists of 319 food and beverage (F&B) employees of a five-star hotel in Korea. The results showed that as elements of emotional intelligence, others’ emotion appraisal, use of emotion, and self-emotion appraisal significantly affected counterproductive work behaviors, whereas self-emotion appraisal and use of emotion affected organizational citizen behaviors. In addition, moderating effects were evident related to job positions in the causal relationships among emotional intelligence, counterproductive work behaviors, and organizational citizen behaviors. Limitations of this study and future research directions are also discussed.     

Profiling satisfied and dissatisfied hotel visitors using publicly available data from a booking platform

We develop a set of models for predicting hotel visitor satisfaction and the probability of complaints about various service aspects. Our empirical analysis is based on 3630 reviews from one of the Dubai hotels. We identify profiles of visitors who are likely to be dissatisfied with the hotel service and need special attention, as well as of visitors, who are likely to be satisfied with the service and, therefore, do not require extra attention. The predictions are based on observable characteristics of visitors, thus making it possible for hotel managers to apply the models in their everyday work. Using content analysis we also reveal specific problems that different groups of visitors encountered and infer which of the problems has the highest impact on the overall satisfaction with the hotel.     

Predicting future trends of media elements in hotel marketing by using Change Propensity Analysis

The purpose of this study is to examine a moderating effect of demographic factors on the relationship between the importance of media elements and their propensity of utilization. Change propensity analysis (CPA) is utilized to examine the current use and predict future trends of media elements in media marketing activities of hotel companies. A survey is conducted with a focus on domestic media users with a previous experience of acquiring domestic and international hotel information through media. The results indicate that certain demographic factors moderate the relationship of certain media elements. In addition, the results of CPA demonstrate which media elements have high importance as well as utilization and which ones have not. For instance, emoticons are found to be the least effective media element used in media marketing. Future trends of media elements in media marketing activities of hotel companies are evaluated using CPA and suggest a number of activities that will emerge. Finally, implications and suggestions for the future research are discussed based on the results.     

A study of critical factors of the job involvement for hotel employees—Taking hotels in Taiwan as an example

The selection of staff is always a critical success factor for managers in the hospitality service sector. This work focuses on the front-line employees and supervisors of international tourist hotels as the study subjects to explore the direct effects of the individual guanxi networks and POS (perceived organizational support) of hotel staff on their job involvement, and examines the indirect effects of these via personality characteristics. For this paper, questionnaire surveys were utilized; 246 questionnaires returned, of which 221 were deemed valid samples appropriate for further analysis. Reliability analysis, EFA, CFA, and SEM were used to examine the data.     

A dynamic linear model to forecast hotel registrations in Puerto Rico using Google Trends data

Recently, studies have used search query volume (SQV) data to forecast a given process of interest. However, Google Trends SQV data comes from a periodic sample of queries. As a result, Google Trends data is different every week. We propose a Dynamic Linear Model that treats SQV data as a representation of an unobservable process. We apply our model to forecast the number of hotel nonresident registrations in Puerto Rico using SQV data downloaded in 11 different occasions. The model provides better inference on the association between the number of hotel nonresident registrations and Google Trends SQV than using Google Trends data retrieved only on one occasion. Furthermore, our model results in more realistic prediction intervals of forecasts. However, compared to simpler models we only find evidence of better performance for our model when making forecasts on a horizon of over 6 months.     

Measuring hotel performance using the balanced scorecard: A theoretical construct development and its empirical validation

A key contribution to the performance measurement literature was the introduction of the balanced scorecard (BSC) in 1992. However, despite its appealing rationale in capturing different aspects of performance and its wide and increasing use in a range of industries, there has been no rigorous psychometric development and testing of performance scales from the BSC perspective in the hospitality industry. In order to contribute to fill this gap, this study adopted a two-stage design seeking to develop and test a scale of organizational performance using the BSC in the hotel sector. In Stage 1, the authors generated and refined the scale items, recognizing unique characteristics of the hotel sector. In Stage 2, the scale has been assessed in terms of dimensionality, validity, and reliability. The findings suggest that managers do make a meaningful distinction between five aspects of hotel performance. Unexpected results, contributions, limitations, directions for future research, and managerial implications are all discussed.     

Comparing differences in the spatiotemporal patterns between resident tourists and non-resident tourists using hotel check-in registers

Previous research studied the spatiotemporal patterns in different visitor segments but lacks evidence of the segmentation of resident tourists and non-resident tourists in multi-city travel. To fill this gap, this study conducts a big data study using hotel check-in registers. The exploratory data analysis visualizes the spatiotemporal patterns and the differences between resident tourists and non-resident tourists. Then, the spatiotemporal patterns are measured by the length of stay and the number of visited cities. The regression shows that both the length of stay and the number of visited cities of non-resident tourists are higher than those of resident tourists. Moreover, non-resident tourists reduce their length of stay and their number of visited cities more than resident tourists on three-day holidays, while they increase their number of visited cities less than resident tourists on seven-day holidays. This study has significant implications for understanding spatiotemporal patterns and visitors' segmentations.     

Exploring the visitors' decision-making process for Airbnb and hotel accommodations using value-attitude-behavior and theory of planned behavior

Accommodation purchase decision is a complex field that makes predictions of revisit intentions hard to examine. Our work explores psychological factors motivating visitors' decision-making concerning accommodation purchases by integrating the theory of planned behavior and value-attitude-behavior model. Using a group of multiple informants in Swiss universities, we performed partial least squares structural equation modeling to assess the impacts of subjective norm, attitude and perception of quality on visitors' revisit intention and loyalty in Airbnb and hotel contexts. Although the influence of said factors on purchase decisions varies in the two contexts, results suggest that subjective norm has an indispensable role in prompting revisit intention towards Airbnb and hotel accommodations. This paper's findings advance our understanding of visitors' decision-making processes concerning traditional hotels and accommodation establishments operating in sharing economy platforms.     

The theory of repurchase decision-making (TRD): Identifying the critical factors in the post-purchase decision-making process

A theory particularly designed to explain re-buying decision formation is lacking. This research developed and tested a theory of repurchase decision-making (TRD) that more comprehensively explains individuals’ post-purchase decision-making processes. Two studies were conducted in a full-service restaurant setting for the development of this theory. Specifically, important factors generating the repurchasing intention were identified through an exploratory qualitative approach in Study 1. In this qualitative approach, a new set of belief items and salient referents in a re-buying decision-making process were also identified. The proposed model merging the model of goal-directed behavior (MGB) with identified factors and belief constructs from Study 1 were tested in the second study. Our results demonstrated that incremental amounts of total variance in the re-buying decision were explained by the TRD. Newly integrated constructs in combination with the original variables in the MGB were found to play a critical role in the re-buying decision-making process. The implications of this study are presented and discussed.     

The sacred and the profane: Identifying pilgrim traveler value orientations using means-end theory

This study explores the values exhibited by travelers along the Camino de Santiago pilgrimage route in Spain. Drawing upon data that were collected en route, pilgrim value systems are identified and explored using the hard laddering method and applying means-end chain (MEC) theory. The researchers examine the hierarchical relationship between pilgrimage attributes, the benefits that pilgrims subsequently acquire and the fulfillment of personal values as ends. The strongest associations are found between attributes, consequences, and values with social bonds that are acquired by socializing with peer pilgrims, followed by the search for happiness through an appreciation of natural beauty and the pursuit of contemplation during the pilgrimage walk. These findings provide novel insights into the profane and sacred dimensions of the pilgrimage experience.