Tourists’ preferences for hotel booking

This paper analyzes tourists’ preferences for hotel booking mode using a sample of 17,921 tourists visiting a Northern Spanish region during 2005–2016. Four different booking modes are considered: telephone, the internet, travel agency and other non-market-based intermediaries. We estimate a Finite Mixture Multinomial Logit Model that allows us to define three classes of tourists. Our results show that leisure tourists coming from distant locations and lodged at luxury hotels have higher likelihood of online hotel booking in class 1. Travel agencies are preferred by offseason tourists with longer stays, while those travelling by public transit modes and staying at luxury hotels opt for non-market-based intermediaries in class 2. In class 3, first-time tourists choose the internet, telephone is more prevalent among those staying at economy hotels and travel agencies are preferred among those travelling in the offseason and by public transit modes.     

The impact of hotel CSR for strategic philanthropy on booking behavior and hotel performance during the COVID-19 pandemic

During the novel coronavirus (COVID-19) pandemic, some hotels have engaged in corporate social responsibility (CSR) activities to help overcome the crisis. Given that most existing research examines the impact of hotel CSR on a single stakeholder, how hotel CSR activities in a crisis are perceived by multiple stakeholders is unknown. Drawing on the concept of strategic philanthropy, this study examines the impact of hotel CSR activities during the pandemic, such as providing accommodations to healthcare workers, on hotel firms' market value and prospective hotel customers’ booking behavior. Adopting mixed-methods approach, this study finds negative impacts of hotel CSR for strategic philanthropy on firm market value and customer booking behavior. The study result indicates that the value of hotel CSR depends on the nature and environmental contexts of CSR. Specific theoretical and practical implications are provided.     

Impact of hotel website quality on online booking intentions: eTrust as a mediator

Growing competitiveness in the marketplace pushes hoteliers to fully take advantage of their websites as a marketing tool. This study proposed that a trusting relationship with customers could be developed by investing in hotel website development. A research model that incorporates hotel website quality, eTrust, and online booking intentions was put forward. The software AMOS 20.0 was adopted to analyze the proposed inter-variable relationships. Statistical results demonstrated that hotel website quality is a strong predictor of eTrust which then also mediates the relationship between website quality and consumers’ online booking intentions. Implications were offered for practitioners based on the results.     

The effects of choice set size and information filtering mechanisms on online hotel booking

Online booking is one of the most popular ways of making reservations for hotel guests. Thus, hoteliers are paying increasing attention to hotel website information presentation and design. The purpose of this study, then, is to examine the joint influence of choice set size and information filtering mechanisms on consumers’ decision confidence towards online hotel booking. Choice set size was operationalized through 3-, 9-, and 30-hotel room choice sets. Through experimental design, this study shows that the presence of an information filtering mechanism reduces consumers’ perceptions of choice overload with a large number of choices (30 choices), whereas its impact is attenuated with smaller choice sets (3 and 9 choices). In addition, choice overload mediates the impact of choice set size on decision confidence. Theoretical contribution and managerial implications are also discussed.     

The determinants of hotel room rates: Another visit with Singapore's data

In this research note, volatility clustering modeling framework is used to examine the determinants of hotel room rates in Singapore. Using monthly data from January 1985 to June 2009, GARCH-M(1, 1) is identified as the appropriate model used to capture volatility clustering. The results suggest that total inbound tourists and economic performance have positive effects on hotel room rates. The main findings are (a) the occurrences of terrorist activities in the neighboring countries have negative impacts and (b) the volatility of hotel room rates has a positive effect, on hotel room rates.     

Determinants of consumers’ choices in hotel online searches: A comparison of consideration and booking stages

Using a stated choice experiment, this study uncovers how hotel review- and price-related attributes affect consumers’ formation of consideration sets and hotel bookings based on online search results alongside a two-stage model of consideration and choice. Empirical findings indicate that consumers’ evaluations of certain attributes vary across these stages. During the consideration stage, the listed hotel price, promotional discount, overall rating, review volume, and booking popularity are significant attributes for prospective guests, whereas price disparities across websites are not. Insignificant interaction effects among these determinants imply that in this stage, consumers employ fast-frugal heuristics and a noncompensatory strategy. During the booking stage, listed price, promotional discount, overall rating, and review volume inform consumers’ booking decisions. Furthermore, the interaction effects point to consumers’ adoption of a compensatory strategy in making a final booking decision. Finally, this study concludes with implications for hotel pricing and system optimization of online platforms.     

An investigation of multiple devices and information sources used in the hotel booking process

With the growing ownership of multiple technology devices, and the contribution of mobile travel bookings to the overall travel market, it is critical to investigate the hotel searching and booking process for different device users. This research investigates four categories of device users via a survey with 383 respondents, in the context of search behaviour and information sources used. The results reveal that search engines and family and friends are the most frequently used information sources while the personal computer (PC) is the most used device for both searching and booking. However, there is a significant difference in how these device users engage with information sources, specifically online travel agents (OTAs) and search engines. Furthermore, device users favour one device and are unlikely to switch devices during the search process.     

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.     

The dynamic interactions between hotel room rates and international inbound tourists: Evidence from Singapore

Recognizing the possible existence of mutual interactions between hotel room rates and the number of international inbound tourists, this research note investigates the short-run and the long-run dynamic interactions between these two variables for Singapore. It tests for the existence of any cointegrating relationship between them using the bounds testing approach to cointegration. The causal effects between them are tested with Granger causality test. We find no evidence that Singapore's hotel room rates and international inbound tourists are cointegrated. The results also suggest that there is a bi-directional short-run causal relationship between these variables.     

Advance booking across channels: The effects on dynamic pricing

This research analyzes the effects of advance booking and channel type on hotel rates. While this relationship has been addressed in the literature, most studies take a partial approach by focusing only on one distribution channel or one destination. This study fills this gap by analyzing the price dynamics for four channels and multiple destinations. The data set consists of 39,363 bookings for 1085 hotels over 27 consecutive months. We used two-stage least squares to solve potential endogeneity issues, and the results proved that distribution channel, hotel type and hotel size have an influence on the effect of advance booking on hotel rates. Critical managerial implications are discussed.     

A demand-driven analysis of tourist accommodation price: A quantile regression of room bookings

Tourist accommodation expenditure is a widely investigated topic as it represents a major contribution to the total tourist expenditure. The identification of the determinant factors is commonly based on supply-driven applications while little research has been made on important travel characteristics. This paper proposes a demand-driven analysis of tourist accommodation price by focusing on data generated from room bookings. The investigation focuses on modeling the relationship between key travel characteristics and the price paid to book the accommodation. To accommodate the distributional characteristics of the expenditure variable, the analysis is based on the estimation of a quantile regression model. The findings support the econometric approach used and enable the elaboration of relevant managerial implications.     

The impact of online user reviews on hotel room sales

Despite hospitality and tourism researchers’ recent attempts on examining different aspects of online word-of-mouth [WOM], its impact on hotel sales remains largely unknown in the existing literature. To fill this void, we conduct a study to empirically investigate the impact of online consumer-generated reviews on hotel room sales. Utilizing data collected from the largest travel website in China, we develop a fixed effect log-linear regression model to assess the influence of online reviews on the number of hotel room bookings. Our results indicate a significant relationship between online consumer reviews and business performance of hotels.     

The search for the best deal: How hotel cancellation policies affect the search and booking decisions of deal-seeking customers

This study examined cancellation policies and their role in shaping travelers’ deal-seeking behavior, exploring the impact of cancellation fees and deadlines on three, mutually exclusive, customers’ hotel booking behavior categories: “Book”, “Book and Search”, and “Search”. 291 subjects, who participated in a week long online “booking game”, attempted to book a room in a virtual hotel and get the best deal. The results were tested using small sample t-test for comparing proportions between two independent populations, non-parametric multiple pairwise comparisons, and multinomial logit regression models. The findings indicate that the cancellation deadline affected participants’ behavior while the size of the cancellation fee had no statistically significant impact. In addition, there was no significant difference between lenient cancellation deadline and no cancellation policy.     

Consumer reviews and the creation of booking transaction value: Lessons from the hotel industry

In recent years, much has been said about online consumer-generated feedback. Concern typically emerges regarding consumer decision-making as well as the preservation of an organization's image. Additionally, a company's financial performance can be affected by customer online ratings. The present study explores the impact of a hotel's rating and number of reviews on the value generated through online transactions. Through collaboration with consulting company Travel Click, the research team gathered a sample of 178 hotels representing various companies and brands within the United States. Research results demonstrate that TripAdvisor ratings as well as the number of reviews had positive relationship with the average size of each online booking transaction. The paper concludes with theoretical and practical implications.     

The impact of online reviews on hotel booking intentions and perception of trust

A growing reliance on the Internet as an information source when making choices about tourism products raises the need for more research into electronic word of mouth. Within a hotel context, this study explores the role of four key factors that influence perceptions of trust and consumer choice. An experimental design is used to investigate four independent variables: the target of the review (core or interpersonal); overall valence of a set of reviews (positive or negative); framing of reviews (what comes first: negative or positive information); and whether or not a consumer generated numerical rating is provided together with the written text. Consumers seem to be more influenced by early negative information, especially when the overall set of reviews is negative. However, positively framed information together with numerical rating details increases both booking intentions and consumer trust. The results suggest that consumers tend to rely on easy-to-process information, when evaluating a hotel based upon reviews. Higher levels of trust are also evident when a positively framed set of reviews focused on interpersonal service.     

Game theoretic pricing models in hotel revenue management: An equilibrium choice-based conjoint analysis approach

This paper explores a game-theoretically founded approach to conjoint analysis that determines equilibrium room rates under differentiated price competition in an oligopolistic hotel market. Competition between hotels is specified in terms of market share functions that can be estimated using multinomial logit models of consumer choice. The approach is based on choice-based conjoint analysis that permits the estimation of attributes weights (“part-worths”) for an additive utility formulation of the utility function. From this, room rates that equilibrate the market, conditioned on the differences in services and facilities offered by competing hotels, can be determined. The approach is illustrated by an example.     

Influences of consumer characteristics on fairness perceptions of revenue management pricing in the hotel industry

Fairness perceptions play an important role in customers’ behavior, and this study explores which consumer characteristics influence fairness perceptions of revenue management (RM) pricing in the hotel context. To examine such differentiating characteristics, the study conducts a logit analysis by comparing two groups: one group of customers who consider hotels’ RM practices to be fair and the other group considers the practices to be unfair. The findings provide an opportunity for hotel managers to identify customers’ particular characteristics that affect customer's perceptions of the fairness of hotels’ RM pricing practices.     

Compliance with eWOM: The influence of hotel reviews on booking intention from the perspective of consumer conformity

This study conducted two experiments to determine the influence of review valence, review quantity, and the interaction effects between the two among consumers designated as conformist and non-conformist.⁴ The results show that positive reviews are more effective than negative reviews in enhancing booking intentions and increasing the number of reviews can magnify the influence of review valence on booking intentions. Our analysis of valence indicated that reading positive reviews can have a stronger effect on booking intentions among individuals who are strongly inclined toward conformity. In addition, a greater number of reviews proved to be more persuasive among individuals displaying a low degree of conformity. Finally, the interaction effects among the three independent variables revealed that a larger number of negative reviews can be more damaging to the booking intentions of conformist individuals. In contrast, a larger number of positive reviews were shown to have a greater impact on non-conformists.     

Application of EMSs in a hotel context: A case study

In the last decade, hotel companies have become increasingly interested in the application of environmental management systems (EMSs). However, research on the effectiveness of EMSs in the hotel industry has been sparse. This study aims to address this research gap by exploring and evaluating the application of EMSs in a hotel context. Various approaches to EMSs are identified in the literature on environmental management and EMSs, including six core EMS elements specific to the hotel industry context. To develop a rich and deep understanding of the application of EMSs in the hotel industry, a qualitative case study was conducted in which data were collected from three levels of employees, executive, supervisory and general, from an international hotel. A series of in-depth, semi-structured interviews were conducted and relevant documents were collected for analysis. Four influential factors were identified in the formation stage of the hotel's EMS: (1) Corporate governance, (2) Piloting activities, (3) Initial gap analysis and (4) Partnership with external consultancy. It was also found that the six elements identified in the environmental management literature play important roles in the implementation of EMS in this case. In addition, although EMSs can help promote a bottom-up approach to change, a top-down approach to implementing EMSs was more suitable for a hotel with a predominantly Chinese workforce, due to cultural issues. This study identified a number of factors specifically related to EMSs to complement mainstream environmental management research.     

What is the optimal number of hotel rooms: Spain as a case study

The main contribution of the paper is that it proposes a well-defined model and an empirical estimation technique for determining an optimal targeted number of incoming tourists and for getting as close as possible to this target by controlling variables that are affected by tourism authorities policies. We assume that the planner wishes to minimize the gap between the actual and the optimal number of tourists in order to get as close as possible to the optimally desired number. The actual number of tourists from each country is affected by the cost of travel as well as by exogenous variables. We constructed a system of two simultaneous equations, where the number of tourists and the cost of travel are the endogenous variables. We estimated the system for incoming tourism to Spain from various countries and forecasted the actual number of incoming tourists. Using the forecasted equation we were able to extract the optimal number of rooms needed in order to get as close as we could to the desired number of tourists.After defining several targeted levels for the number of incoming tourists to Spain from Canada, Japan, Belgium, The Netherland, US, Italy, France, Germany and UK, we extracted the optimal number of needed hotel rooms in order to get as close as possible to the targets.This paper is important since it provide a tool for the decision makers to effect the number of incoming tourists by changing the level of variables that are under the control of the decision maker.