Search results

This paper aims to investigate the links between daily review sentiment and the hotel performance measures of occupancy rate (OR), average daily rate (ADR) and revenue per available room (RevPAR).

The authors conducted review sentiment analyses in three moments (−1, −7 and −14 days) before arrival time using a data set of budget hotel performance and online reviews. The aim was to identify the effect of review sentiment in the budget hotel market on the three performance metrics.

Daily sentiment positively affects ADR and negatively affects OR and RevPAR, but only up to a certain threshold, after which the trend reverses. Prices increase with the level of sentiment, and high prices lead to low OR and RevPAR only when the sentiment scores are low. When they are high, they are associated with low rates, which lead to high OR and RevPAR.

Daily review sentiment can be viewed as a valuable “barometer” indicating a hotel’s daily operational effectiveness. Daily sentiment can thus allow hotel managers to adjust their dynamic pricing strategies more accurately.

This study identifies daily sentiment as an alternative predictor of hotel performance. In addition to the roles of valence and volume in the decision-making process, the authors found that daily review sentiment can be an “in-the-moment” factor with a high impact, encouraging consumers to complete their transactions. This study suggests that aggregated measures such as the total number of reviews and overall ratings of the hotel should not be the sole consideration in reputation management.

The purpose of this paper is to examine the evolution of travel information search literature over the past 75 years to outline research needs for the upcoming decades.

This paper conducts a literature review based on the descriptive textual analysis of article abstracts from a sample of representative tourism journals on the subject of travel information search.

The analysis shows that the literature reflects the mounting complexity in the tourism information landscape and the increasing diversity in available channels. It also reveals lack of theoretical advancement in terms of reconceptualizing travel information search to better accommodate current and future technological advances.

This paper offers a systematic review of literature on travel information search and identifies areas of interest and directions for future research.

This paper aims to outline the development of online tourism-related text with particular focus on the role of technology in transforming this text. It also offers a vision of this ongoing development for the next 75 years, followed by a discussion of its implications for tourism research.

This paper offers a critical analysis and synthesis of the literature and brings a number of conceptual and theoretical frameworks to present a rich, in-depth discussion of the subject.

There have been important transformations in online tourism-related text because of the development of information technology. Particularly, the internet, along with more recent social media and the smartphone, has produced vast amount of text in a variety of formats and modalities. Computer programs are increasingly smarter in collecting, processing, understanding and even generating textual content in the context of tourism. Future communications will likely be mediated and dominated by artificial intelligence-based technologies, emerging interfaces and a mix of text and visual contents.

Tourism research entails a paradigm shift that recognizes the changing characteristics of online tourism-related text and the importance of new conceptual and methodological tools for understanding the new language of tourism.

This paper offers a unique view that connects the socio-linguistic basis of tourism with the development of information technology. It may serve as the conceptual foundation for tourism research that uses text as data in understanding a range of marketing and managerial problems in tourism.

Guest experience and satisfaction have been central constructs in the hospitality management literature for decades. In recent years, the use of big data as an increasing trending practice in hospitality research has been characterised as a modern approach that offers valuable insights into understanding and enhancing guest experience and satisfaction. Recognising such potential, both researchers and practitioners need to better understand big data’s application and contribution in the hospitality landscape. The purpose of this paper is to critically review and synthesise the literature to shed light on trends and extant patterns in the application of big data in hospitality, particularly in research focusing on hotel guest experience and satisfaction.

This research is based on a Preferred Reporting Items for Systematic Reviews and Meta-analysis literature review of academic journal articles in Google Scholar published up to the end of 2020.

By data types, user-generated content, especially online reviews and ratings, was at the centre of attention for hospitality-related big data research. By variables, the hospitality-related big data fell into two crucial factor categories: physical environment and guest-to-staff interactions.

This paper shows that big data research can create new insights into attributes that have been extensively researched in the hospitality field. It facilitates a thorough understanding of big data studies and provides valuable insights into future prospects for both researchers and practitioners.

The pace of booking is a critical element in the accuracy of revenue management (RM) systems. Anecdotal evidence suggests that booking windows exhibit persistent shifts due to a variety of macro and micro factors. The article outlines several causes and tests the impact of the shifts on forecasting accuracy.

A novel methodological approach is utilized to empirically shift hotel reservation windows into smaller increments. Forecasts are then estimated and tested on the incremental shifts with popular RM techniques characteristic of advance booking data. A random effects model assesses the impact of the shifts on forecast accuracy.

The results show that shifts in booking behavior can cause the accuracy of forecasting models to deteriorate. The findings stress the importance of considering these shifts in model estimation and evaluation.

The results demonstrate that changes in booking behavior can be detrimental to the accuracy of RM forecasting algorithms. It is recommended that revenue managers monitor booking window shifts when forecasting with advanced booking data.

This study is the first to systematically assess the impact of booking window shifts on forecasting accuracy. The demonstrated approach can be implemented in future research to assess model accuracy as booking behavior changes.

This study aims to extract knowledge of ancient Chinese scientific and technological documents bibliographic summaries (STDBS) and provide the knowledge graph (KG) comprehensively and systematically. By presenting the relationship among content, discipline, and author, this study focuses on providing services for knowledge discovery of ancient Chinese scientific and technological documents.

This study compiles ancient Chinese STDBS and designs a knowledge mining and graph visualization framework. The authors define the summaries' entities, attributes, and relationships for knowledge representation, use deep learning techniques such as BERT-BiLSTM-CRF models and rules for knowledge extraction, unify the representation of entities for knowledge fusion, and use Neo4j and other visualization techniques for KG construction and application. This study presents the generation, distribution, and evolution of ancient Chinese agricultural scientific and technological knowledge in visualization graphs.

The knowledge mining and graph visualization framework is feasible and effective. The BERT-BiLSTM-CRF model has domain adaptability and accuracy. The knowledge generation of ancient Chinese agricultural scientific and technological documents has distinctive time features. The knowledge distribution is uneven and concentrated, mainly concentrated on C1-Planting and cultivation, C2-Silkworm, and C3-Mulberry and water conservancy. The knowledge evolution is apparent, and differentiation and integration coexist.

This study is the first to visually present the knowledge connotation and association of ancient Chinese STDBS. It solves the problems of the lack of in-depth knowledge mining and connotation visualization of ancient Chinese STDBS.

This study examines the impact of corporate performance and corporate size on corporate environmental information disclosure of A-share listed enterprises in Shanghai and Shenzhen during the period 2008–2017. In this study, corporate size (size) is represented by total assets, and corporate performance (Jzc) is represented by return on net assets. Environmental information disclosure quality (EID) is measured by the Environmental Information Disclosure Index (EIDI). Non-balanced panel data models are used. In order to eliminate the influence of unobservable factors during the sample period, year fixed effects and industry fixed effects are included. The results show that corporate size and performance both promote the improvement of EID quality. Measures such as improving corporate management efficiency and setting clear environmental performance indicators can help improve corporate competitiveness and core values, thus providing important support for improving EID quality. Future research is recommended to focus on the influence of internal corporate characteristics such as corporate nature (state-owned or not), equity structure, and executive background on EID quality.

In recent years, research on children's tourism experiences has gained prominence, as children are becoming an increasingly vital market for the tourism industry. While events are a main sector of the industry and host millions of children every year, there is a lack of research specifically focussed on children's experiences in events. This chapter focusses on children's entertainment events which can provide children with a satisfying, memorable and educational experience. This study has developed a framework to facilitate deeper mixed studies on children's experiences in event tourism. The framework is composed of four pillars based on various social, tourism and event theories and models, including the Cognition–Affect–Behaviour (CAB) theoretical framework, the Orchestra Model of Experience, the Event Experience Scales (EES), the Theory of Child Well-being and the Transtheoretical Model of Behaviour Change (TTM). The framework can be used by future researchers as an analytical evaluation tool to study children's experiences in different types of events and understand the mechanisms of behaviour change in this context.

Purpose: This study analyses the mediating effect of parasocial interaction (PSI) in the link between hedonic motivation and impulsive buying intention (IBI) in fashion vlogging about sustainable cosmetics.

Need for the Study: Due to the mass popularity of YouTube, vlogging has led to an augmented level of PSI of vloggers with consumers, which strongly impacts a consumer’s behavioural consequences and persuades consumers to indulge in impulsive buying. Thus, marketers need to comprehend the changing behavioural patterns, including sustainable products, as this new communication medium serves the future of promotion and advertising.

Methodology: Online questionnaires were administered to 349 Gen Z female fashion vlog followers. Structural equation modelling and Hayes Process macros were employed to test the model relationships.

Findings: Results indicate that PI with the fashion vlogger partially mediates between hedonic motivation and impulse buying intention for sustainable cosmetic products. Fashion consciousness (FC) was also established as a significant moderator between all the model relationships.

Practical Implications: The findings of the study would be helpful for fashion brands in the content development of visual marketing communications, which would tap the female Gen Z consumer. Improving the PSI between the follower and the fashion vlogger can be easily enhanced by delivering the right content through the vlogger’s videos.

Although prior studies have studied the relationship between online consumers' attitudes and buying behaviour, the research focussing on online consumers' impulse buying behaviours and exploring the role of celebrity endorsement is limited. Drawing on the social presence and the social facilitation theory, this paper establishes a research model based on the stimuli–organism–response (S–O–R) model and the motivation theory. It explores how live streamers impact online consumers' impulse buying behaviours under specific social and cultural backgrounds, with celebrity endorsement as a moderating variable.

To test the research model, the online questionnaire method has been conducted in this study. This paper utilises Chinese online consumers as samples and promotes an online survey. Using the variance-based structural equation modelling and partial least squares path modelling (SEM-PLS), 433 valid questionnaires have been analysed on SmartPLS.

First, live streamers' attractive appearance positively correlates with online consumers' hedonic attitude and positively impacts their utilitarian attitude to live shopping. Second, live streamers' real-time interaction positively affects consumers' utilitarian attitudes because of their professional marketing and communication skills. Third, their hedonic and utilitarian attitudes positively influence online consumers' impulse buying behaviours. Finally, this paper presents that celebrity endorsement negatively moderates the relationship between online consumers' hedonic attitudes and impulse buying during live shopping.

This research combines the S–O–R model and the motivation theory and analyses related social influencing factors to study online consumers' impulse buying behaviours. Meanwhile, it explores the celebrity endorsement factor as a moderate role and identifies the different effects between live streamers and celebrities in live shopping, which is of great significance to the strategy of live shopping marketing and the literature on online consumers' behaviours.