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Despite the fact that both reserchers and managers agree that consumer satisfactions is a key factor for the success of hotels, little research has been done to reveal what aspects of the hotel operation the guests consider as important when evaluating the hotel experience. Literature on total quality management often argue that all aspects of the operation should be focused on, in order to achieve high levels of consumer satisfaction. Based on a sample of business travellers, we found that most of the variance in overall satisfaction with a hotel experience is eXplained by two core factors in the hotel operation, namely intangible aspects of the reception and tangible aspects of the houskeeping department. This calls for a more focused approach to the management of guest satisfaction than generally recommended in the literature. Implications for managers and recommendations for future research are presented.

From the perspective of two-sided review systems, this study aims to investigate how guests’ prior reputation influences their subsequent satisfaction on Airbnb.

This study applied a conceptual framework based on social capital theory to explain the effect of guests’ reputation decided by hosts’ prior evaluations on their subsequent satisfaction. The authors collected 96,204 guest reviews posted for 17,325 properties on Airbnb and used the review polarity to measure guest satisfaction. All historical evaluations generated by hosts for each guest were collected and treated as a proxy of guest reputation. Ordinary least squares regressions were conducted to estimate the effect of guests’ reputation on their subsequent satisfaction.

Results show that guests whose historical evaluations have higher valences or larger variations tend to be more satisfied in their subsequent bookings. However, the number of reviews that guests received from hosts in the past does not influence their subsequent satisfaction.

This study provides new insights into the hospitality literature by identifying the influencing factors of guest satisfaction on peer-to-peer rental platforms from the perspective of two-sided review systems. Results also present practical implications to property owners and website designers to gain a deeper understanding of the determinants of guest satisfaction and the consequences of social interactions between hosts and guests.

This study is a novel attempt that analyzes the effect of guests’ reputation on their satisfaction with subsequent bookings based on two-sided review systems on peer-to-peer rental platforms. Thus, this study provides a starting point for investigating how two-sided review systems affect use behavior on peer-to-peer rental platforms.

Building on the three-factor theory, this study aims to unravel how the role of hotel attributes such as basic, excitement and performance factors could differ in accordance with different hotel star ratings and distinct customer segments.

This study explores the asymmetric effects of hotel attributes on customer satisfaction by extracting 412,784 consumer-generated reviews from TripAdvisor across different cities in China.

By taking into account the origins of customers and hotel star ratings, the study uncovers that guests’ expectations of hotel performance differ with respect to their origins (domestic and international guests) and the star ratings of the hotels being reviewed, thereby moderating the asymmetric impact of hotel attributes on customer satisfaction.

The study compares and contrasts the determinants of customer satisfaction for domestic and international guests in the context of Chinese hotels. Care should still be exercised when generalizing the insights gleaned from this study to other contexts.

The findings from this study translate into actionable guidelines for hotel operators to make informed decisions regarding service improvement.

The study extends previous work by offering a deeper understanding of the asymmetric impact of hotel attributes on customer satisfaction. Specifically, this study provides a deep understanding of the different hotel attributes such as basic, performance and excitement factors in explaining customer satisfaction among different hotel customer segments. Findings from this study can not only inform hotel operators on the significance of various hotel attributes in determining customer satisfaction but also guide the formulation of business strategies to retain customers by inducing delight and not frustration.

The paper aims to identify the emergent themes of hotel guests’ satisfaction, to compare the distribution of the attributes of the themes between Chinese and North American guests and to compare the importance of the themes for different satisfaction levels between Chinese and North American guests from a cross-cultural perspective.

By adopting Python (a computer language), the word-frequency method was used to identify emergent themes of hotel guests’ satisfaction. Topic modeling was adopted to compare the attributes distribution of each theme and the features of satisfaction between Chinese and North American guests.

First, three themes were identified including functionality, staff and price. Functionality can be further categorized into five subthemes, namely, room, travel, food, environment and hotel facility. Second, the distribution of the attributes of the themes between Chinese and North American guests was compared from a cross-cultural perspective. Chinese guests tend to mention both lifestyles- and social norms–related attributes and expect personalized service, while North American guests mainly prefer to describe lifestyle-related attributes and prefer standardized service. Third, the study compared the changing importance of the themes (functionality, staff and price) for different satisfaction levels between Chinese and North American guests. As the satisfaction level decreases, the importance of functionality decreases, that of staff increases and that of price remain stable for Chinese guests. In contrast, the importance of each theme has fluctuated mildly from the high to the low satisfaction level for North American guests.

Proposed managerial implications are to highlight lifestyle- and social norms-related attributes, as well as personalized service for Chinese guests. However, lifestyle-related attributes and standardized service should be facilitated for North American guests. Specific suggestions were made to help improve hotel performance such as the good performance of functional-related attributes, which could enhance satisfaction and better staff performance, which would reduce dissatisfaction.

By mining big data, this study investigated hotel guests’ satisfaction from a dynamic instead of a static perspective. This study provides some rare insights into differences in key attributes influencing satisfaction levels of Chinese versus North American guests staying in luxury hotels in China. This study also takes a novel approach to examine the dynamics of the importance of the various themes at different satisfaction levels, and contrast these dynamics between Chinese and North American guests. The findings offer valuable insight into market segmentation and management in the hospitality industry.

The purpose of this paper is to identify the antecedents of satisfaction and revisit intentions for full-service restaurants. The economic crisis is known to have had a deep impact on consumer behavior with regards to restaurants and this study is primarily focussed on exploring the effects on the traditional antecedents of satisfaction and revisit intentions as full-time restaurants attempt to reposition their offer.

The study involved 218 respondents who were guests of full-service restaurants. In terms of statistical analyses, confirmative factor analysis was used to test the suitability of the proposed model for measuring satisfaction and revisit intentions, while structural equation modeling was employed to analyze the relationship among variables of the conceptualized model.

The results confirmed the significant impact of atmosphere and quality of interaction on guest satisfaction. It was interesting to notice that perceived price has no statistically significant impact on guest satisfaction. In addition, satisfaction, along with atmosphere and perceived price emerged as a significant trigger of revisit intentions. While measuring impact of atmosphere and perceived price on revisit intentions, both direct and indirect effects were measured.

This study emphasizes in particular, the significance of revisit intention as an important behavioral reaction and reveals its antecedents. In a limited number of studies, models for understanding triggers of revisit intention were developed as separate variables, rather than as components of behavioral reactions. In that context, the tested model identifies causal relationships between latent variables. Restaurants involved in the survey are full-service restaurants dealing with the changing behavior of guests who are heavily impacted by the economic crisis. Guests show a tendency to reduce their visits to restaurants in these circumstances, forcing restaurants to reformulate their service offering in order to align with changing customers’ needs.

The purpose of this paper is to illustrate new methods of examining structural differences among segmented markets beyond comparing merely univariate variable mean scores, so as to help marketers and researchers gain better insights into segment differences for meaningful strategy development.

A comprehensive dataset covering various lodging market segments was constructed from Tripadvisor.com. The data then were sorted into lodging customer segments by star rating, type of operation, and level of price charged. Structural equation modeling with the −2 log‐likelihood difference test was conducted to illustrate how effectively the differences, if any, of market segments could be assessed in contrast to the traditional mean‐score comparison approach.

Guest satisfaction was influenced by the same performance variable to the same magnitude and direction across different lodging segments examined. Such stability in the amount of influence of performance on guest satisfaction was true even in the fact that the variable mean scores were significantly different across the market segments.

The traditional approach to examining segment differences via univariate mean scores could be one set of results, while the effect‐based difference assessments in this paper resulted in another. Developing marketing strategies based on the effect‐based segment differences, as illustrated in this paper, is considered more effective than the traditional mean‐based approach. One limitation of this paper could be use of a secondary dataset with limited scope of the model employed for an illustrative purpose. Another limitation is that the sample characteristics are unknown due to the nature of a secondary dataset. The examination of the market segments was also limited to those based on only three popular variables.

The paper is a fresh attempt to examine market segment differences through the effect of one variable on another. The paper advances the methods of hospitality and tourism research for examining segment differences beyond the traditional univariate mean‐based examination approach. The methodological illustration is applicable to a vast majority of different theoretical frameworks known in the hospitality and tourism field. Use of the assessment method illustrated in this paper also requires future market segmentation studies to rely more on theories than data.

Electronic word of mouth in the form of user-generated content (UGC) in social media plays an important role in influencing customer decision-making and enhancing service providers’ brand images, sales and service innovations. While few research studies have explored real content generated by hotel guests in social media, business analytics techniques are still not widely seen in the literature and how such techniques can be deployed to benefit hoteliers has not been fully explored. Thus, this study aims to explore the significant factors that affect hotel guest satisfaction via UGC and business analytics and also to showcase the use of business analytics tools for both the hospitality industry and the academic world.

This study uses big data and business analytics techniques. Big data and business analytics enable hoteliers to develop effective and efficient strategies improving products and services for guest satisfaction. Therefore, this study analyzes 200,431 hotel reviews on Tripadvisor.com through business analytics to explore and assess the significant factors affecting guest satisfaction.

The findings show that service, room and value evaluations are the top-three factors affecting overall guests’ satisfaction. While brand type and negative emotions are negatively associated with guests’ satisfaction, all other factors considered were positively associated with guests’ satisfaction.

The current study serves as a great starting point to further explore the relationship between specific evaluation factors and guests’ overall satisfaction by analyzing user-generated online reviews through business analytics so as to assist hoteliers to resolve performance-related problems by analyzing service gaps that exist in these influential factors.

以消费者评论为主体的社交网络口碑营销对于影响消费者决策和提高服务提供商的品牌形象、销量、和服务创新起到重要作用。然而, 很少研究探索社交媒体上的真正酒店客人评论。因此, 商务分析技术在文献中还是很少使用的, 这种技术应该更多得到科研上的应用以给酒店从业人员给与启示。因此, 本论文旨在探究影响酒店顾客满意度的因素, 通过消费者评论和商务分析, 以展示商务分析技术是如何为酒店业和科研界来使用的。

本论文使用大数据和商务分析技术来进行数据分析。大数据和商务分析能够为酒店从业人员开发有效战略以提高产品和服务质量, 最后达到顾客满意。因此, 本论文分析了Tripadvisor.com的200, 431酒店评论数, 通过商务分析技术, 以探索和审视影响顾客满意度的重要因素。

研究结果显示服务、客房、和价值比成为影响顾客满意度的前三项因素。品牌类型和负面情绪是影响顾客满意度的负面因素。其他因素成为影响顾客满意度的正面因素。

本论文是利用消费者评论的商务分析来探究影响顾客满意度与具体衡量因素之间关系的起点范例, 以此, 帮助酒店从业商来解决服务中的欠缺因素, 提高绩效。

The literature claims that respondents who fill in guest satisfaction questionnaires do not form a truly representative sample of the hotel guests because they do so on a voluntary basis. This study explores the distribution of guest satisfaction questionnaires and the biases that employees bring to the process. Data were gathered via in‐depth, semi‐structured interviews. Individuals with different characteristics were selected in an attempt to reduce the risk of producing findings specific to a certain hotel settings. The results suggest that sampling procedures that were supposed to be carried out systematically are more often done at the convenience of hotel employees or for other, self‐presentational reasons. It is suggested that the employees' intervention is a factor that biases the data and renders it less than informative. Recommendations for hotel operators are provided.

The purpose of this study was to investigate relationships among the experiential value of hotel apps, the cognitive and affective evaluation of hotel apps users, hotel apps users’ satisfaction and their endorsement for the hotel apps. Specifically, this study examined the relationships that enhance hotel guests’ experiences through hotel apps.

The measurement items were developed through extensive literature review. This study used a web-based survey to test an integrated model of the experiential value. With a total of 320 usable samples, partial least squares structural equation modeling was carried out to identify key “driver” constructs and validate the proposed model.

A significant relationship was found in the playfulness of hotel apps and hotel guests’ cognitive and affective evaluations of the hotel apps, which positively influence hotel guests’ satisfaction and their endorsement for the hotel apps. Hotel apps should create fun and entertainment features in the hotel apps so that the users of hotel apps can be enjoyable during their usage. In addition, providing hotel apps users with time saving and easy use of the hotel apps can affect their satisfaction and endorsement for the hotel apps.

This study confirmed the positive links among hotel apps users’ experiential value, their cognitive and affective evaluation of the hotel apps, their satisfaction of using the hotel apps and their endorsement for the hotel apps. This study also revealed that hotel apps can be hotels’ effective communication tool that enhances existing and potential customers’ overall experiences.

项关于体验价值的综合模型

摘要

本论文旨在研究关于酒店APP体验价值, 对酒店APP用户的认知和情感评估, 用户满意度以及用户支持之间的关系。具体而言, 本研究探索了如何通过酒店手机APP使用来提高用户体验的理论关系。

测量条目通过详尽的文献综述来产生。本研究运用了网络调研来测量体验价值的一项综合模型。由320项有效样本, 偏最小二乘法结构方程建模（PLS-SEM）来鉴定关键“驱动”构象以及验证提出的模型。

研究发现酒店APP的娱乐性对顾客的APP的认知和情感评估都起到了显著性作用, 进而对顾客满意度和酒店APP支持度产生正面影响。研究建议酒店APP创造有趣以及娱乐产品功能, 从而让酒店APP用户从使用中获得乐趣。此外, 为酒店APP用户提供省时方便的服务可以影响用户满意度和对酒店APP的支持。

本研究验证了酒店APP用户体验价值, 对酒店APP的认知和情感评估, 用户对使用酒店APP的满意程度, 以及对酒店APP支持的正相关性。本研究进而发现酒店APP可以作为提升酒店现有和未来用户全面体验的有效工具.

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.