Exploring Bidirectional Performance of Hotel Attributes through Online Reviews Based on Sentiment Analysis and Kano-IPA Model

As people increasingly make hotel booking decisions relying on online reviews, how to effectively improve customer ratings has become a major point for hotel managers. Online reviews serve as a promising data source to enhance service attributes in order to improve online bookings. This paper employs online customer ratings and textual reviews to explore the bidirectional performance (good performance in positive reviews and poor performance in negative reviews) of hotel attributes in terms of four hotel star ratings. Sentiment analysis and a combination of the Kano model and importance-performance analysis (IPA) are applied. Feature extraction and sentiment analysis techniques are used to analyze the bidirectional performance of hotel attributes in terms of four hotel star ratings from 1,090,341 online reviews of hotels in London collected from TripAdvisor.com (accessed on 4 January 2022). In particular, a new sentiment lexicon for hospitality domain is built from numerous online reviews using the PolarityRank algorithm to convert textual reviews into sentiment scores. The Kano-IPA model is applied to explain customers’ rating behaviors and prioritize attributes for improvement. The results provide determinants of high/low customer ratings to different star hotels and suggest that hotel attributes contributing to high/low customer ratings vary across hotel star ratings. In addition, this paper analyzed the Kano categories and priority rankings of six hotel attributes for each star rating of hotels to formulate improvement strategies. Theoretical and practical implications of these results are discussed in the end.

Impact of website interface on customer experience and engagement intention in online hotel booking

This study aims to examine the impacts of a website interface on customer experience and engagement intention in online hotel booking services. A research model was proposed to discuss the interrelationships among website interface attributes, online customer experience, and customer engagement intention. The moderating effects of self-efficacy were also included. A quantitative approach of collecting 608 usable online questionnaires was conducted, and SPSS and AMOS were used to analyze the measurement model and proposed hypotheses. The results demonstrated that customer experience was affected by the information attributes, service attributes, and technical attributes of the booking website interface. Furthermore, customer experience was found to be positively related to customer engagement intention on booking websites. Moderating effects of web self-efficacy on these relationships were suggested.

Hotel Booking Website Quality, Travel Agent Satisfaction and Purchase Intention

Website quality is one of the features that organisations increasingly use to maintain a competitive advantage. In the hospitality sector in particular, the growing use of a website as a sales channel has necessitated that hotel distribution companies understand the influence of website quality on their customers’ purchase behaviour. The purpose of this study was to assess the impact of Business-to-Business (B2B) third-party hotel booking website quality features on travel agents’ satisfaction, and their subsequent purchase intention. Quantitative data was collected from South African travel agents using an online survey. Three website quality dimensions namely ease of use, information quality and visual appearance, as well as customer satisfaction and purchase intention were measured. Results indicate that there is a positive relationship between website quality and customer satisfaction, and between customer satisfaction and purchase intention. Information quality appears to have the strongest relationship with customer satisfaction. Regression analyses revealed that the relationship between website quality and purchase intention is mediated by customer satisfaction. The study makes a predominantly empirical contribution as there does not appear to be a similar study conducted within an African context. From a practical contribution perspective, the findings may assist third-party hotel distribution companies with meeting the demands of travel agents, and thereby improve their overall business performance.

The role of key online reviews in affecting online hotel booking: an empirical investigation

Purpose The importance of online reviews on online hotel booking has been widely acknowledged. However, not all online reviews affect consumers equally. Compared with common online reviews, key online reviews (KORs) have a greater influence on consumers' decisions and online hotel booking. This study takes the first step to investigate the factors affecting the identification of KORs and the role of KORs in online hotel booking.Design/methodology/approach To test the research hypotheses, this study develops a crawler to obtain 551,600 online reviews of 650 hotels in ten representative large cities in China. This study first uses a binary logistic regression to identify KORs by combining review content quality and reviewer characteristics and then uses a log-regression model to investigate the role of KORs in online hotel booking.Findings This study mined the factors affecting the identification of KORs by analyzing review contents and reviewer characteristics. Our results revealed that KORs play a mediating role in the effects of review content and reviewer characteristics on online hotel booking.Originality/value This study focuses on KORs, which have received limited attention in research but are important to practitioners. Specifically, this study investigates the antecedents and consequences of KORs. Our results enable hotel managers to manage online reviews effectively, particularly KORs.

Pay Now or Pay Later: The Impact of Time on Payment Preference in Hotel Booking

The “book now, pay later” phenomenon is one form of payment which has flow-on effects such as increasing last-minute cancelations. To encourage prepayment, some hotels have been offering a price discount or free upgrade for choosing the “pay now” option, but little is known about which incentives can generate better outcomes. This study aims to examine what types of payment options are preferable based on the time between booking and check-in (i.e. temporal distance), and to investigate how the payment options and temporal distance jointly influence perceived risks. The findings demonstrate that while people prefer the pay now with monetary incentive option when traveling time is in the near future, they mostly prefer the pay later option when traveling time is distant. In addition, people planning a trip in the distant future perceive significantly higher risks from the pay now with non-monetary and monetary incentive options than from the pay later option.

Reconnoitering enablers of travelers' online hotel booking intention: moderation of service affordability and perceived pandemic risk

PurposeThe meddling of foreign players into the Indian hotel industry has triggered fervent competitiveness, and therefore, consumers' attitude, intention and behavior have been the epicenter of all activities. This study endeavors to explicate enablers of online hotel booking intention (OHBI) in the Indian hospitality industry.Design/methodology/approachThe study examined OHBI of 560 travelers during the first wave of COVID-19 pandemic in India using structural equation modeling and an extended technology acceptance model. Direct and indirect associations were explored using mediation and moderation.FindingsThe results manifest that hotel website credibility, perceived website interactivity and perceived ease of use (PEU) aggrandize perceived usefulness (PU), which, in turn, considerably magnifies travelers' OHBI. PEU and PU partially mediate the relationship in the model. Into the bargain, service affordability reinforces the relationship, while perceived pandemic risk enfeebles the relationship between PU and OHBI.Research limitations/implicationsThe study unfurls pressing determinants of PEU, PU and OHBI that may facilitate hoteliers to lure travelers and enhance profitability.Originality/valueThere is a paucity of literature on “hotel website credibility” and “perceived pandemic risk” in the hospitality industry. Hence, the study enriches literature by assimilating underlying constructs through an epigrammatic conceptual model. The study is distinctive because it unearths the possibilities of mediation and moderation amongst the aforementioned constructs and posits the calamitous effects of the COVID-19 pandemic on the tourism and hospitality sector.

How do online hotel consumers perceive room rates?

While it has been perceived that hotel consumers using online travel agencies (OTAs) are overall price sensitive, a dominant use of OTAs in hotel booking suggests that there are more diverse consumers in terms of price perception. As such, this study investigates the price sensitivity of the Online Travel Agency (OTA) consumer segments, using price sensitivity measurement (PSM) by using factor analysis and cluster analysis. The results showed four OTA consumer segments, i.e., planned bargain seekers, enthusiastic shoppers, deal hunters, and apathetic shoppers. Differences in price sensitivity was confirmed among these segments. This study uncovers the characteristics of OTA consumers who are more (less) price sensitive. By using PSM, this study presents and compares the optimal pricing points across the customer segments in terms of monetary values. Based on the findings, this study provides theoretical and practical implications.

Interoperable Multi-Blockchain Platform Based on Integrated REST APIs for Reliable Tourism Management

The tourism industry can significantly benefit from the blockchain since its implementation can build trust among stakeholders and improve customer satisfaction. However, most of the existing tourism-specified blockchain platforms are single-chains that provide business support for enterprises without guaranteeing transaction information privacy. Besides, these platforms are specified to a single use case and lack interoperability with other platforms to support heterogenous tourism services. This paper aims to address this issue by introducing a multi-chain architecture that utilizes multiple blockchains to enhance processing capability and provide various business services for the tourism industry. The proposed multi-chain architecture improves the interoperability between the activities in different chains by providing functional requirements in practical applications and supports the inter-ledger application. In addition, the private blockchain will be made available to allow users to access the network through central authorization. It also increases the transaction processing capability by distributing multiple tasks across the chains for large-scale applications. To demonstrate the usability and efficiency of the developed approach, a case study on hotel booking is conducted using the blockchain frameworks Winding Tree and Hyperledger Fabric. A comprehensive evaluation experiment is conducted, and the results show the significance of the proposed system.