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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.

Based on the main studies presented in the literature, this work aims to examine the level of student satisfaction towards the on-campus accommodation service provided by an Italian university. Notably, the objectives of the study are twofold: (1) to examine the mediating role of student satisfaction on the relationship between university on-campus accommodation service quality and word-of-mouth and (2) to determine whether there is any significant difference in students' satisfaction towards on-campus accommodation in terms of gender and the halls of residence.

The study is based on the results of a survey carried out through an online questionnaire by 381 students living on campus at the University of Urbino.

The findings revealed that the quality perceived by university students in relation to individual services had a positive impact on their general satisfaction towards the halls of residence experience.

The study presents some limitations such as lack of temporal comparisons, a focus on specific service quality items and the fact that it refers to a single Italian university.

The findings of this study will help the management of public universities to improve the quality of services in their halls of residence for the satisfaction of their students.

To the authors' knowledge, there have been no previous studies about on-campus accommodation service quality conducted in Italy. The study contributes to enrich the service quality literature, confirming both that the sum of the quality of individual elements is not as the overall satisfaction and the outcome intention of positive WOM depends not only on service quality attributes, but also from an overall evaluation of satisfaction.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

The purpose of this paper is to identify the critical success factors of emblematic hotels from the perspective of the guest, by analysing the direct activities that make up the value chain of these types of establishments.

The authors use the case study methodology to derive conclusions that contribute to the development of a theory about the success factors of emblematic hotels. The case selected is the Spanish Tourist Parador chain. The authors carried out over a period of two years a data mining analysis of the online comments posted by its guests.

The results indicate that the attributes of location and facilities are critical success factors expected a priori given the nature of the business of such establishments, based on the singular nature of the buildings. Another critical success factor is personnel, which seems to indicate that the Paradors support their business model by employing highly qualified staff, but give less attention to restaurant services or the room, according to guest perceptions.

The paper provides required evidence on the critical success factors of emblematic hotels adapting Porter’s value chain, for the tourism accommodation sector, through the analysis of direct value chain activities. In addition, the existing literature is broadened by taking a perspective scarcely studied, the guest perception of hotel establishments, online content posted by the user on the establishment’s website, rather than simply considering the traditional views of the experts/managers, through structures questionnaires. Besides, the results provide practical and useful implications for the managements of the emblematic hotels under study.

The purpose of this paper is to use the case of an international luxury hotel chain in Hong Kong to illustrate general environmentally-friendly practices in housekeeping. Six in-depth interviews were conducted with the housekeeping department staff to evaluate the effectiveness of the Hotel’s environmental sustainability practices by analysing their benefits and limitations. Results reveal that all informants acknowledged the environmental sustainability strategies adopted by the Hotel, which can benefit stakeholders. Despite multiple green practices in hotel housekeeping, several strategies may not be as significant as expected with misaligned expectations from the management and the actual practices may create excessive workload for frontline room attendants with a lack of policy enforcement and supportive policies. Therefore, hotels should keep a mutual communication between the management and frontline employees prior to conducting environmentally- and employee-friendly practices. Given the labour-intensive nature of the hotel industry, the housekeeping department should ensure employment equality policy is in place with adequate environmentally friendly support for employees.

Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study aims to apply the signaling theory to the booking of Airbnb listings and explore the influence of quality signals on the odds of an Airbnb listing being booked.

A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt.

Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments.

This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.

The different dimensions and contexts within which value is co-created has generated varied views of how value is understood or formed. This study aims to examine employee-guest perceived value as important factors for the successful implementation of value co-creation (VCC).

The study employs an interpretive paradigm, using in-depth interviews, focus group discussions and participant observation in a qualitative design to increase understanding of employee-guest perceived value to aid the implementation of VCC at the dyadic level.

Findings highlight eight value perceptions including value for money, hotel location, physical evidence, mutual respect, appreciation, safety & security, quality & varieties of food and technological characteristics of service as important factors for the successful implementation of VCC at the dyadic level.

Generalisability of the findings is a limitation not only due to the smaller sample size but also due to industry-specific context. The study follows rigorous procedures to minimise biases, yet research limitation is acknowledged from the researcher’s participation in the research process.

The notion that actor’s assess value differently from the same service suggests that diverse service elements might be experienced differently. This study provides insights for hotel managers to recognise not only individuals’ value preferences but also service types that reflect employee-guest collective service preferences for sustainability.

This study integrates and extends extant literature by examining employees’ and guests’ individual and collective views at distinct hotel contexts to gain useful insights into value and VCC. The study proposes a framework that hospitality firms can use to address service failure and competition-related issues.

Historic architecture is one of the most prevalent human-made attractions and image attributes that the tourism industry substantially benefits from. Moreover, this attraction creates a critical value in augmenting destination competitiveness. Therefore, the purpose of this paper is to discuss historic architecture in relation to guest experience and to find out if historic buildings used as hotels are, physically, elements of attraction. The findings reveal that historic buildings used as hotels have a specific potential in attracting guests, and these buildings are mainly considered positive by guests. Hotel guests are satisfied by the physical – i.e., architectural and atmospheric – features of hotels serving in historic buildings. This paper will help readers rethink how historic architecture plays a key role in tourism consumption. The paper uniquely seeks to delve into the potential of historic hotel buildings as elements of attraction by examining over 9.8 thousand comments of hotel guests.

This article sets out to show how principles and questions about method that underlie a way of interpreting the discipline of conservation and restoration can find results in research and studies, aiming at achieving even conscious reuse process. The occasion is the very recent research performed on the former Church of Saints Gerolamo and Francesco Saverio in Genoa, Italy, the Jesuit church annexed to the 17th-century College of the order. It is a small Baroque jewel in the heart of the ancient city, former University Library and actually abandoned, forgotten for years, inaccessible and awaiting a new use.

The two-year work carried out on the monumental building was conducted according to a study and research methodology developed and refined over the years within the activities of the School of Specialisation in Architectural Heritage and Landscape of the University of Genoa. It is a multidisciplinary and rigorous approach, which aims to train high-level professionals, up-to-date and aware of the multiple problems that interventions on existing buildings, especially of a monumental nature, involve.

The biennal study has been carried out within the activities of the Post-Graduate Programme in Architectural Heritage and Landscape of the University of Genoa. The work methodology faces the challenges of the contemporary complexity, raised by the progressive broadening of the concept of cultural “heritage” and by the problems of its conservation, its active safeguard and its reuse: safety in respect of seismic risk, fire and hydro geological instability, universal accessibility – cognitive, physical and alternative – resource efficiency, comfort and savings in energy consumption, sustainability, communication and involvement of local communities and stakeholders.

The goals of the work were the following: understanding of the architectural heritage, through the correlated study of its geometries, elements and construction materials, surfaces, structures, spaces and functions; understanding of the transformations that the building has undergone over time, relating the results of historical reconstructions from indirect sources and those of direct archaeological analysis; assessment of the state of conservation of the building recognising phenomena of deterioration, damage, faults and deficits that affect materials, construction elements, systems and structures; identification of the causes and extent of damage, faults and deficits, assessing the vulnerability and level of exposure of the asset to the aggression of environmental factors and related risks; evaluation of the compatibility between the characteristics of the available spaces, the primary needs of conservation, the instance of regeneration and possible new uses; the definition of criteria and guidelines for establishing the planning of conservation, restoration and redevelopment interventions.

This is a general review study aiming to specify the key customer-based factors and technologies that influence the value co-creation (VCC) process through artificial intelligence (AI) and automation in the hospitality and tourism industry.

The study uses a theory-based general literature review approach to explore key customer-based factors and technologies influencing VCC in the tourism industry. By reviewing the relevant literature, the authors conclude a theoretical framework postulating the determinants of VCC in the AI-driven tourism industry.

This paper identifies customers' perceptions, attitudes, trust, social influence, hedonic motivations, anthropomorphism and prior experience as customer-based factors to VCC through the use of AI. Service robots, AI-enabled self-service kiosks, chatbots, metaversal tourism and new reality, machine learning (ML) and natural language processing (NLP) are technologies that influence VCC.

The results of this research inform a theoretical framework articulating the human and AI elements for future research set to expand the models predicting VCC in the tourism industry.

Few studies have examined consumer-related factors that influence their participation in the VCC process through automation and AI.