GUEST EXPERIENCE IN THE HOTEL INDUSTRY AND THE PRACTICE OF HOSPITALITY IN THE POST-PANDEMIC ERA

Purpose – This study examines the impact of service automation (SA) on value creation (VC) and guest experience (GE) in the hotel industry to provide recommendations on how the hotel industry can rebuild from the impact of Covid-19 and meet future growth challenges. Design – The constructs of the variables were considered from previous literature. A twostep questionnaire was created to first identify demographics, years of experience, etc., and a later portion of the questionnaire was based on a 5-point Likert scale to identify our intended proposal. Methodology – A sample of 290 Indian hotel customers was considered. The focus of the preliminary study was on the psychometric properties of the scale constructs. This study focused heavily on the validity and reliability of the scales. The first-order constructs, SA Practises, Service VC, and GE, were tested for validity and reliability. Structural equation modelling (SCM) is used to determine the effects of SA on VC and GE. Approach – The identified factors were confirmed with confirmatory factor analysis (CFA) and the SEM technique was applied to reveal the exclusive as well as the complex relationships between SA, VC and GE. Findings – The results show that both SA and the service VC have a positive influence on GE. SA has an indirect and significant influence on GE, with the service VC playing a mediating role. The results show that both factors, SA and VC, have a positive influence on GE in the hotel industry, but SA has an indirect and significant influence on GE, and VC plays a mediating role. Originality of the research – the study suggests that SA may be able to improve GE in the hotel industry through its influence on VC

This study examines AI's role in enhancing guest satisfaction and efficiency in the hotel industry. Employing a mixedmethods approach, it analyzes guest feedback and interviews staff at AI-integrated hotels. The findings aim to identify key AI applications that boost satisfaction and efficiency, and outline challenges and best practices for AI implementation. This research offers a holistic view of AI's influence on hospitality, enriching understanding and guiding industry practices. As the hotel industry continues to evolve, the integration of artificial intelligence (AI) technologies has become increasingly prevalent, aiming to enhance guest experience. This research investigates the impact of AI integration on guest experience enhancement within the hotel industry. The purpose of this study is to comprehensively explore how AI technologies influence various aspects of guest satisfaction in hotels. A mixed-methods approach is employed, combining quantitative analysis of guest feedback data with qualitative methods by interviewing the guests staying in the hotel. Data is collected from a diverse range of hotels that have implemented AI technologies, allowing for a nuanced understanding of the impacts across their establishments. This research is expected to provide valuable insights into the multifaceted effects of AI integration in the hotel industry. Specifically, it aims to identify the specific AI applications that most significantly contribute to guest satisfaction levels. Additionally, the study seeks to uncover potential challenges and limitations associated with AI implementation, as well as best practices for successful integration. This topic lies in its comprehensive examination of AI's impact on both guest experience within the hotel industry. While previous research has explored AI's role in hospitality, few studies have undertaken such a holistic analysis, considering its implications for guests. By addressing this gap, this research contributes to a deeper understanding of the transformative effects of AI in the hotel sector, providing practical insights for industry practitioners and stakeholders.

This paper explores the evolution of academic research in green hospitality, with a focus on how sustainability, innovation, and guest experience converge under the guiding framework of the European Green Deal (EGD). Through a bibliometric analysis of 181 peer-reviewed articles published between 2019 and 2025 and indexed in the Scopus database, the study provides a comprehensive overview of global research trends in sustainable hospitality. Using VOSviewer and Biblioshiny, the analysis identified key thematic clusters—sustainability, hotel industry, and corporate social responsibility—alongside the most prolific countries, authors, and journals contributing to the field. The United States, China, Saudi Arabia, India, and the United Kingdom emerged as top contributors, while Sustainability (Switzerland) and the International Journal of Hospitality Management were highlighted as leading publication sources. Authors such as Han, who has focused extensively on green consumer behavior and sustainable tourism decisionmaking, Fayyad, recognized for his work on strategic sustainability practices in hospitality, and Azazz, noted for his contributions to green marketing and authenticity in hotels, were recognized for their influential work. The findings reveal a growing academic and industry-wide interest in integrating green practices and innovative strategies to enhance guest experience and operational performance. This research is one of the few to systematically align bibliometric insights with the priorities of the EGD, thereby adding original value to both academic literature and practical decision-making. The study’s results offer meaningful guidance for hospitality managers, policymakers, and researchers by identifying strategic areas for investment and collaboration in sustainable innovation. It underscores the importance of aligning green practices with guest satisfaction and long-term value creation in the hospitality sector.

Purpose: This paper presents a review of the current state and potential capabilities for application of robots, artificial intelligence and automated services (RAISA) in hotel companies.Design/methodology/approach: A two-step approach was applied in this study. First, the authors make a theoretical overview of the robots, artificial intelligence and service automation (RAISA) in hotels. Second, the authors make a detailed overview of various case studies from global hotel practice.Findings: The application of RAISA in hotel companies is examined in connection with the impact that technology has on guest experience during each of the five stages of the guest cycle: pre-arrival, arrival, stay, departure, assessment.Research implications: Its implications can be searched with respect to future research. It deals with topics such as how different generations (guests and employees) perceive RAISA in the hotel industry and what is the attitude of guests in different categories of hotels (luxury and economy) towards the use of RAISA. It also shows what is the attitude of different types of tourists (holiday, business, health, cultural, etc.) and what kinds of robots (androids or machines) are more appropriate for different types of hotel operations.Practical implications: The implications are related to the improvement of operations and operational management, marketing and sales, enhancement of customer experience and service innovation, training and management.Originality/value: This book chapter complements and expands research on the role of RAISA in the hotel industry and makes some projections about the use of technologies in the future.

PurposeThis paper aims to identify potential avenues for innovation in urban hotel management by analyzing self-reported data from visitors regarding their experience with interior design.Design/methodology/approachA qualitative exploratory computer-assisted content analysis was conducted to identify the impact of interior design on the guest experience. Leximancer 4.0 software analyzed 2,562 reviews from urban hotels collected through a reservation website.FindingsThe findings reveal that data reported by guests on interior design play a crucial role in shaping guest experiences, both positively and negatively. The esthetic appeal of interior design is shown to impact resting and comfort, affecting overall performance significantly. The study also highlights how different star categories of hotels and variations in visitors' purposes for their stay lead to distinct guest experiences and different opportunities to innovate.Research limitations/implicationsThe study’s results provide evidence for researchers and practitioners of the potential of the guest-reported interior design experience as a valuable source for fostering innovation. In addition, in the hotel industry, innovation may eventually be attained through interior design renovation.Practical implicationsSelf-reported data from guests on interior design is an effective tool for innovation. Making interior design a priority throughout the establishment and ongoing management of a hotel is crucial. By integrating interior design, not only can potential negative experiences be avoided, but greater guest satisfaction can also be achieved during their stay, promoting memorable experiences that align with the hotel category and customer expectations.Social implicationsThis research emphasizes the importance of interior design as a catalyst for innovation and improved social experiences in the hospitality industry. Innovation in interior design can improve hotel performance in several dimensions, including attracting more visitors to the hotel and the area, increasing tourism revenue for local businesses and contributing to the broader societal goal of reducing environmental impact and promoting sustainability.Originality/valueThis article adopts a guest-centered methodology to provide valuable insights for hotel managers to leverage interior design as a tool for innovation in the hospitality industry after showing that interior design enhances guests' experiences, comfort and hotel differentiation.

This study aims to examine the effects of brand image, perceived value, customer service, and hotel location on word of mouth (WOM) among hotel customers. Additionally, it posits that purchase intention mediates the relationship between the independent variables. Primary quantitative data were collected through an online survey using the SurveyMonkey platform, with established scales measuring the variables under study. A total of 110 participants responded to the survey. Data were analyzed using multiple regression and the Macro PROCESS Model 4. The findings demonstrate that brand image, perceived value, and services emerged as critical factors influencing WOM. However, location does not seem to affect WOM and purchase intention. This indicates that customers are more inclined to book a hotel room and recommend it to others when they perceive high value in the services offered, even though the location is unfavorable. Excellent customer service enhances the overall guest experience, leading to higher satisfaction and an increased likelihood of recommending the hotel to others

Generative AI is making hospitality frictionless by changing how hotels tailor and optimize guests' experiences. This article will address a new approach to bettering service customization through methods under the umbrella of Generative AI, which in turn strengthens operational efficiency and customer happiness. Each guest's preferences can be dynamically set, service requests can be automated, and real-time needs can be anticipated by employing machine learning algorithms and natural language processing. The ability to process large amounts of consumer data and render useful insights is the premise on which mathematical models such as customization frameworks and recommendation algorithms are developed and justified. This demonstrates how a number of use cases, from chatbots to tailored room configurations, can enhance guest experiences by examining them. After AI-driven solutions were implemented, operational KPIs and customer satisfaction both increased statistically significantly. This research illustrates the way Generative AI can transform the hotel sector by opening the door for more effective and adaptable service delivery.

The chapter undertakes to provide in depth knowledge on emerging smart technologies that will aim to reshape and redefine the hotel industry. Tourism sector is one of the growing and prospect sectors, which remains positive. Keeping in mind the rising demands of the tourism there is a need of an hour to adapt, innovate, identify and explore next generation’s technological solutions to enhance the experience of the owner and the guest in the hotel industry. The objective of the study is to explore the smart technologies that will benefit hotel industry and enhance experience of the guest. The attempt is made to understand the challenges and opportunities in adopting smart technological solutions and to understand the role of smart technologies in enhancing owners and guest experiences and thus contributing to the concept of smart hotels. The study will explore the latest technologies that can be adopted by hotel owners to fulfill the demands and expectations of the techno-savvy guests. Thus the smart hotel experience can be made possible through the smart digital technology and can aid hotels overcome current issues and prepare for future trends. Keywords: Smart hotel technology; Artificial intelligence; Predictive analysis; Internet of things; Self-service technology; Biometric recognition; Video analytics

A Supervised Guest Satisfaction Classification with Review Text and Ratings

PurposeAccommodations providers in the sharing economy are increasingly competing with the hotel industry vis-à-vis the guest experience. Additionally, experience-related research remains underrepresented in the hospitality and tourism literature. This paper aims to develop and test a model of experiential consumption to provide a better understanding of an emerging phenomenon in the hospitality industry. In so doing, the authors also expand Pine and Gilmore’s original experience economy construct.Design/methodology/approachUsing data from a survey of 630 customers who stayed at a hotel or an Airbnb in the previous three months, the authors performed a multi-step analysis procedure centered on structural equation modeling to validate the model.FindingsThe authors demonstrate that the dimensions of serendipity, localness, communitas and personalization represent valuable additions to Pine and Gilmore’s original experience economy construct. Airbnb appears to outperform the hotel industry in the provision of all experience dimensions. The authors further define the pathways that underlie the creation of extraordinary, memorable experiences, which subsequently elicit favorable behavioral intentions.Practical implicationsThe findings suggest the need for the hotel industry to adopt a content marketing paradigm that leverages various dimensions of the experience economy to provide customers with valuable and relevant experiences. The industry must also pay greater attention to its use of branding, signage and promotional messaging to encourage customers to interpret their experiences through the lens of these dimensions.Originality/valueThe study expands a seminal construct from the field of services marketing in the context of the accommodations industry. The Accommodations Experiencescape is offered as a tool for strategic experience design. The study also offers a model of experiential consumption that explains customers’ experiences with accommodations providers.

External business environmental challenges such as the effects of climate change and sustainable operation required hotel managers to take strategically planned action. All of this was exacerbated by the COVID-19 pandemic, which appeared in several waves from 2020, and the energy crisis resulting from the Ukrainian-Russian armed conflict. The periodic return of the pandemic has created a high level of uncertainty not only for operators but also for workers. The energy price boom that unfolded from the second half of 2021 required cost-saving solutions from market players that typically necessitate a significant investment and provide a long-term return. In the planning process, the guest experience and value-added approach became paramount, as the long payback period required forward thinking and good prediction of the future. In this article, focusing on relevant literature sources and using a constructivist grounded theory strategy, data mostly from the period between 2020 and 2022 has been collected and analysed, . The purpose of these two research questions is to answer what challenges Hungarian hotel market players face and what factors negatively impact their business during the period of 2020 and2022, as well as how hotel operators respond to the identified challenges and how these responses relate to the global best practices. In addition to studying general cost-saving practices in Hungarian hotels, the focus is on improving the guest experience and providing operators with real cost-effective operational solutions. Value creation occurs in all areas of hotel operations, including front and back-of-house work areas. Solutions such as heating system modernisation, digitalisation, organisational development and outsourcing of activities will be presented.

Purpose The study examines the hotel industry’s digital transformation, emphasizing its impact on customer interaction, operational efficiency, and competitive advantage. It highlights the vital role of Artificial Intelligence, digital technologies, and digital platforms in maintaining relevance, enhancing service delivery, and increasing profitability. Design/methodology/approach The study utilized the Scopus database to identify 239 articles related to the keywords “Digital Transformation,” “digital technology,” “digitalization,” and “hotel,” or “Hospitality.” It used VOS viewer and R studio biblioshiny software to analyze publication and citation patterns, integrating bibliometric factors and bibliographic coupling. Findings Findings reveal a significant increase in research on digital transformation since 2018, with prominent contributors like Buhalis D and Dwivedi YK. Key research hubs include the UK, US, and India, but collaboration with developing countries remains limited and needs more. The study highlights the integration of digital technologies in fostering sustainable development in the hotel sector. Six main research clusters focus on future study topics Virtual Avatar, Digital platform and sharing economy, Artificial Intelligence and Big Data, Digital travelers and hospitality, IoTs in travel, and Hospitality and Tourism education. Research limitations/implications This review paper lacks primary data advantage, highlighting limitations in methodology and generalizability. Future research should consider primary data studies to address these limitations. Practical implications This research offers insights into digital transformation in the hotel industry, which can enhance pricing, guest experiences, and operational efficiency by optimizing pricing, personalizing experiences, and enhancing digital customer engagement through mobile apps, chatbots, and social media platforms highlighting key trends and strategies for improving service delivery and growth, thereby guiding industry stakeholders to stay competitive. Social implications Digital transformation in hotels can improve service but raises concerns like privacy breaches and environmental impacts. To foster trust, equity, and sustainability, hotels must promote balanced technology use and preserve cultural authenticity, enhancing guest and employee satisfaction. Originality/value The examination of research from the Scopus database from 2004 to 2024 bibliometric analysis was conducted to highlight the study’s contribution. Through a comprehensive assessment of the research clusters in this study, essential trends concerning digital transformation in the hotel sector are revealed. Additionally, recommendations for prospective research avenues are put forth.

Historical tourism in Indonesia, especially destinations such as Borobudur Temple, Prambanan, and Ratu Boko Palace, has great potential to attract both domestic and international tourists. However, negative reviews that come from user-generated content in the form of testimonials are often a factor that can affect the interest of tourist visits. This study aims to analyze the impact of negative reviews on interest in tourist visits to these historical destinations. This study aims to eval_uate the extent to which negative reviews affect interest in tourist visits to three main cultural destinations in Indonesia: Borobudur Temple, Prambanan Temple, and Ratu Boko Palace. This study uses a descriptive quantitative method by collecting data through a survey of 58 respondents who have visited the three destinations. The data was processed using SPSS software to test the validity, reliability, and influence of negative reviews on the interest of tourist visits. The results of the analysis showed that negative reviews did not significantly affect the interest of tourists visiting Borobudur Temple, Prambanan, and Ratu Boko Palace. All three destinations remain the top choice for tourists, despite the negative reviews, mainly due to their strong historical reputation and visual appeal. This study concludes that negative reviews do not have a significant influence on the interest in tourist visits to the historical destinations of Borobudur, Prambanan, and Ratu Boko Palace. Therefore, destination managers are advised to continue to pay attention to negative reviews as eval_uation material but do not need to worry too much about the impact on tourist visits.

PurposeThis study provides an overview of challenges and opportunities presented by the increasingly prevalent self-service technology adoption in the hotel industry, with a focus on the post-COVID-19 pandemic era and related workplace issues.Design/methodology/approachA review of relevant literature along with references to secondary data is provided to support the viewpoints presented by the authors. A brief critical interpretation of published works on automation, self-service and similar technology-supported services in the hospitality industry, particularly the hotel industry, is outlined.FindingsPotential near- and long-term workplace challenges, in the context of automation, for hotel employees and operators are summarized. Evidence based on published scholarly works and news reports indicates that there will be a period of difficulties in the hotel industry, and the hospitality industry in general, when it comes to the adoption of transformative technology solutions that support automation and self-service. However, the authors assert that a balanced and calculated approach to embracing such technologies could create new career paths as well as job security for hotel employees and stability for hotel operators.Originality/valueThe perspectives offered in this study focus on the difficulties as well as prospects of embracing technology-supported automation in the hotel industry in the context of a unique era and the accelerated adoption of various technology solutions following the COVID-19 pandemic. The documented challenges are also framed with aligned opportunities to offer a roadmap for both practitioners and scholars.

Current research investigating the accommodation experience in the sharing economy in China is limited, especially from a cross-cultural perspective. To fill this gap, this study examined the accommodation experience of Airbnb guests using text-mining techniques and compared the accommodation experience perception between two culturally different groups: domestic Chinese and foreign English-speaking Airbnb guests. The results showed that the two groups shared eight common dimensions, including “Convenience/Location”, “Amenities”, “Feel at home”, “Check-in/out”, “Experience”, “Availability/Transportation”, “Host”, and “Style/Decoration”. However, there are differences in the relative importance of each dimension of accommodation experience between the domestic and foreign Airbnb guests. For example, the foreign guests more often mentioned homeliness, location/convenience, and availability/transportation, while the domestic guests showed greater interest in check-in procedures and style/decoration. Additionally, the two groups have several unique dimensions. The dimensions unique to foreign guests are “Recommendation” and “Booking flexibility”, while the dimensions unique to domestic guests are “Revisit” and “Cleanliness”. This study provides both theoretical and practical implications for peer-to-peer accommodation hosts and platforms. For example, Airbnb hosts can improve the satisfaction of Airbnb guests by improving several common extracted topics (e.g., amenities quality and host response) and the fact that foreign guests care more about homeliness, while domestic guests pay more attention to the check-in process and house design and decoration.