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The purpose of this paper is to develop a set of criteria and an instrument for evaluating upscale hotel web sites and test these in a comparative study of South Korean and the US upscale hotel web sites.

The hotel web sites are assessed by a team of 25 trained evaluators. The study measures and compares the overall effectiveness of upscale hotel web sites and checks the correlation between overall web site effectiveness and size of upscale hotels in South Korea and the US by using balanced scorecard (BSC) approach. To evaluate and analyze upscale hotel web site performance or effectiveness, 14 upscale hotels in both South Korea and the USA are selected. These hotels are selected through Expedia.com or Hotels.com and are rated as either four‐ to five‐star.

The results show that there is no significant difference in the overall effectiveness of the upscale hotel web sites in South Korea and the USA. However, the web sites of the Korean upscale hotels perform slightly better than their US counterparts. The main conclusion drawn is that most upscale hotels in both countries are not effectively using web sites from the marketing and upscale hotel perspectives.

The first objective of this research study is to develop a web site evaluation tool for upscale hotels. The modified BSC approach for performance measurement is adopted as the overall framework for the evaluation process. Therefore, BSC performance measurements are adapted and developed to reflect the specific context of upscale hotel online marketing, with an upscale hotel perspective being added to the critical success factors. Also, this study compares actual upscale hotels web page in two different countries and that approach is unique.

This research aims to investigate the impacts of misleading hotel website photos on consumers’ brand trust, emotional responses and negative word-of-mouth (WOM) intention. The magnitude of these impacts in different contexts was examined.

This study employed a 2 (hotel segment: economy vs upscale) × 2 (expected product experience: hedonic vs utilitarian) scenario-based experimental design. A total of 240 consumers participated in this study.

The study results show that, in the case of misleading hotel website photos, brand trust was lower for the upscale hotel. Consumers experienced greater anger and regret in the upscale hotel situation and were most angry if they stayed at an upscale hotel for a hedonic purpose. The eWOM intention was higher in the upscale hotel situation. In addition, it was found that hotel physical environment was more important for female and married consumers.

A hypothetical brand name was used in this study. Therefore, brand attitude changes and the influences of brand loyalty on consumers’ responses to misleading website photos were not examined.

Upscale hotels and hotels that target leisure consumers need to make an effort to use truthful website photos and ensure that the physical environment is well maintained.

No prior research investigated the impact of misleading hotel website photos. This research fills this gap in the hospitality literature.

The aim of this paper is twofold. First, clustering patterns of urban hotels are explored, and, second, clustering effects on performance for upscale urban hotels are estimated.

Local indicators of spatial association (LISA) were computed using geographic information system (GIS) techniques. Clustering for the entire population of hotels in Madrid was explored visualizing LISA statistics. Then, a system generalized method of moments regression was applied to test a set of hypotheses about the performance effects of LISA statistics for a sample of upscale urban hotels.

Two significantly distinct types of clusters are identified: dense “cold spots” or clusters containing many low-priced hotels and quiet “hot spots” or clusters only containing a few high-priced hotels. And, estimates confirmed two important results: evidence of adverse selection when clustering and evidence of positive location economies for upscale hotels.

This study has a number of relevant implications for making better hotel location decisions. Specifically, the paper shows the applicability of GIS to find statistically significant clustering in the data. In the hotel sector, knowing exactly where hotel clustering occurs and of what type is of vital importance.

This paper’s novel application of LISA based on GIS techniques for hotel clustering sheds light on the effects of clustering on performance to convey the subtle nuances of the relationship for upscale urban hotels.

This study aims to develop a parsimonious model to estimate US aggregate hotel industry revenue using domestic trips, consumer confidence index, international inbound trips, personal consumption expenditure and number of hotel rooms as predictor variables. Additionally, the study applied the model in six sub-segments of the hotel industry – luxury, upper upscale, upscale, upper midscale, midscale and economy.

Using monthly aggregate data from the past 22 years, the study adopted the auto-regressive distribute lags (ARDL) approach in developing the estimation model. Unit root analysis and cointegration test were further utilized. The model showed significant utility in accurately estimating aggregate hotel industry and sub-segment revenue.

All predictor variables except number of rooms showed significant positive influences on aggregate hotel industry revenue. Substantial variations were noted regarding estimating sub-segment revenue. Consumer confidence index positively affected all sub-segment revenues, except for upper upscale hotels. Inbound trips by international tourists and personal consumption expenditure positively influenced revenue for all sub-segments but economy hotels. Domestic trips by US residents added significant explanatory power to only upper upscale, upscale and economy hotel revenue. Number of hotel rooms only had significant negative effect on luxury and upper upscale hotel sub-segment revenues.

Hotel operators can make marketing and operating decisions regarding pricing, inventory allocation and strategic management based on the revenue estimation models specific to their segments.

It is the first study that adopted the ARDL bound approach and analyzed the predictive capacity of macroeconomic variables on aggregate hotel industry and sub-segment revenue.

This study bridges the gap between sensory marketing and the use of the internet of things (IoT) in upscale hotels. This paper aims to investigate how stimulating guests’ senses through IoT devices influenced their emotions, affective experiences, eudaimonism (well-being), and ultimately, guest behavior. The authors examined the potential moderating effects of gender.

Research conducted comprised an exploratory study, which consisted of interviews with hotel managers (Study 1) and an online confirmatory survey (n = 357) among hotel guests (Study 2).

The results showed that while the senses of smell, hearing and sight had an impact on guests’ emotions, the senses of touch, hearing and sight impacted guests’ affective experiences. The senses of smell and taste influenced guests’ eudaimonism. The sense of smell had a greater effect on eudaimonism and behavioral intentions among women compared to men.

This study concentrated on upscale hotels located in Europe. Further research may explore the generalizability of the findings (e.g. in other cultures, comparison between high-end and low-end hotels).

Managers of upscale hotels should apply congruent sensory stimuli from all five senses. Stimuli may be customized (“SoCoIoT” marketing). IoT in hotels may be useful in the aftermath of the COVID pandemic, as voice commands help guests avoid touching surfaces.

IoT can be applied in creating customized multi-sensory hotel experiences. For example, hotels may offer unique and diverse ambiances in their rooms and suites to improve guest experiences.

Most of the cross-cultural empirical research in hospitality has focused on Western and Eastern differences and has neglected cultural diversity in Europe. As cultural differences in Europe do exist and have important implications for managers operating in hotel industry, the purpose of this paper is to examine perceived quality in upscale (four- and five-star) hotels in two Mediterranean countries: Italy and Croatia.

Data were collected among 335 guests in upscale hotels in Italy and 475 hotel guests in Croatia. This work adopts a cross-cultural approach in two different ways. First, perceived quality is assessed in hotels in two different countries. Second, national culture of guests is considered in their evaluations of perceived quality in each country.

Surprisingly, hotels in Croatia, an emerging tourist destination, performed better than hotels in Italy, a top worldwide destination. The results show significant differences in perceived quality evaluations according to national cultures of hotel guests in each country. However, while in Croatia domestic guests perceived higher levels of quality than other guests, in Italy, perceived quality was rated lower by Italians than by their American counterparts.

The results of this study contribute to better understanding of perceived quality in cross-cultural research in hospitality.

Implications are discussed for both Italian and Croatian hotel managers, two direct competitors in the Mediterranean area.

This paper covers several research gaps: lack of cross-cultural research in hospitality marketing, poor examination of perceived quality in hotels from the cross-cultural perspective, and poor consideration of cultural diversity within European countries.

This study aims to present and empirically examines an expanded service model that incorporates green hotel practices together with a multidimensional/higher-order measurement model of service quality, as well as perceived value and satisfaction, to examine the relationships among these variables and hotel consumers’ loyalty/behavioral intentions (BI).

The model was examined using partial least squares structural equation modeling (PLS-SEM) using data gathered in August 2018 from 200 surveys completed by UK subjects who stayed at upscale European hotels.

The results of PLS-SEM found that hotel service quality has a direct and positive effect on perceived value, satisfaction and BI. There is also an indirect effect of service quality on BI through perceived value and satisfaction, while green practices only had a direct effect on perceived value, not satisfaction or BI.

This study offers new insights into the network of causal relationships among determinants of hotel consumers’ BI. The results offer hotel operators a better understanding of specific green practices and service quality attributes they can use to more favorably influence consumers’ intentions to revisit the property and recommend them through positive word-of-mouth.

This research is particularly relevant in today’s reality characterized by travelers’ growing concern for green issues and business’ responsibilities toward the environment. Moreover, unlike previous studies, this study assumes a multidimensional scheme for service quality, further enhancing the understanding of hotel consumers’ BI relationships.

Extending the technology acceptance model (TAM) to a new context, the purpose of this paper is to propose an integrative model of the brand of artificial intelligence-enabled voice assistants (AI-EVA) and customers’ perceptions and behavioral intentions of using AI-EVA in hotels. Moderating effects of construal levels and hotel scales were examined.

This paper adopted a mixed method approach. A qualitative and phenomenological methodology was adopted in Study 1 to explore hotel customers’ experience with AI-EVA. Study 2 applied experimental design to investigate the effects of the brand of AI-EVA and construal level on customers’ perceptions and behavioral intentions of using AI-EVA. Based on Studies 1 and 2 results, Study 3 examined how the brand of AI-EVA and hotel scale affect customers’ perceptions and behavioral intentions of using AI-EVA during hotel stays.

This research found that customers perceive a higher level of perceived usefulness, perceived ease of use and anthropomorphism when AI-EVA is branded (vs off-brand). Perceived usefulness positively affects customers’ intention to use and to spread positive word-of-mouth. Anxiety of using AI-enabled devices and privacy concerns inhibit customers’ intention to use AI-EVA. Anthropomorphism increases customers’ willingness to spread positive word-of-mouth. Construal level moderates the effect of the brand of AI-EVAs on perceived ease of use and anthropomorphism. Hotel scale moderates the effect of brand on perceived usefulness.

This paper is one of the first attempts to uncover and integrate different factors underlying customers’ perceptions of using AI-EVA in an extended TAM in hotel settings. This paper provides an integrative model extending the TAM to a new context by deploying a mixed-method approach across three studies.

The purpose of this paper is to explore business travelers’ sleep experience in hotels by measuring sleep quality and determining the extent to which hotel attributes, demographic characteristics, and hotel quality level influence their sleep quality while staying in hotels.

This study utilized a self-reported survey to obtain data from business travelers who have stayed in a hotel at least two nights for a business trip in the past 30 days. A total of 304 business travelers were surveyed in this study.

The results indicated that there was a difference in the factors that influenced business travelers’ overall satisfaction with sleep in mid-scale (2.5-3.5 stars) vs upscale hotels (4+stars). The findings showed that business travelers generally had lower sleep quality at hotels and they were more likely affected by noise both outside and inside the guestroom, as well as material elements inside the room.

This study represents a pioneering attempt at exploring business travelers’ sleep quality and satisfaction with sleep in hotels. Furthermore, this study contributes to the limited research addressing sleep quality as a fundamental function of hotel services. Also, this is the first study to measure business travelers’ sleep quality in hotels by using the sleep quality scale.

This study explores the short- and medium-term effects generated by the Milan Expo 2015, adopting a microeconomic approach. The focus is on the hospitality sector. The study embraces nine years, identifying three intervals: pre- (2011–2014), during- (2015) and post-Expo (2016–2019). The time span does not include the Covid-19 pandemic period, which started in 2020. The dataset is composed of daily data. Three research questions are explored. First, an overall evaluation of the short- and medium-term effects is performed. Second, the seasonal effects are measured. Finally, the impacts for different classes of hotels are considered. The findings are supportive for the legacy generated by the Milan Expo. The results confirm the ability of the Milan Expo to strengthen the leisure segment. Positive results have been observed for all classes of hotels, relevantly augmenting the real revenue per available room (RevPAR). Luxury hotels achieved the highest increase of RevPAR, while economy class hotels registered the highest percentage of increase of RevPAR.