CUSTOMER EXPERIENCE AND CUSTOMER SATISFACTION: ASSESSING LINKS AND THEMES IN THE HOTEL INDUSTRY

EXPERIENCIA Y SATISFACCIÓN DEL CLIENTE: EVALUACIÓN DE VÍNCULOS Y TEMAS EN LA INDUSTRIA HOTELERA

Carlos Sampaio (Instituto Politécnico de Castelo Branco Polytechnic University & NECE-UBI, Portugal)*1

Mónica Régio (Instituto Politécnico de Castelo Branco Polytechnic University, Portugal)2

Abstract

Hotel industry provides several services simultaneously to customers and plays a relevant role within the tourist sector and overall economic development. This study seeks to explore the interaction between customer experience and customer satisfaction in the hotel industry and to analyse factors affecting customer satisfaction and purchasing intentions. To conduct the analysis, a thematic and a co-citation analysis have been applied to scientific literature output. Results show that word-of-mouth has been mostly replaced by electronic word-of-mouth and online reviews gained relevance in influencing customer behaviour. Purchasing decisions, determinants of service quality, particularly those related with physical settings and environments, are critical to customer experience and customer satisfaction, and employees and job-satisfaction are among the most relevant themes within the research stream. This study also provides several relevant implications and guidance to academics and practitioners and some hints for further research.

Keywords: guest experience, hotel industry, customer satisfaction, service quality.

JEL classifcation: L83, Z32

Resumen

La industria hotelera ofrece varios servicios simultáneamente a los clientes y tiene un papel fundamental en sector turístico y en el desarrollo económico. Este trabajo tiene como objetivo principal explorar como la experiencia del cliente y la satisfacción del cliente se relacionan en la industria hotelera. Además, procura también analizar los factores que afectan la satisfacción del cliente y las intenciones de compra. Para realizar el análisis, se aplican un análisis temático y un análisis de co-citación a la producción de literatura científica. Los resultados muestran que el boca a boca ha sido mayormente reemplazado por el boca a boca electrónico, las reseñas en línea han ganado relevancia en influenciar el comportamiento del cliente y las decisiones de compra, los determinantes de la calidad del servicio, particularmente aquellos relacionados con entornos y configuraciones físicas, son críticos para la experiencia y la satisfacción del cliente, y los empleados y la satisfacción laboral están entre los temas más relevantes dentro del ámbito de investigación. Este estudio también proporciona varias implicaciones relevantes y orientaciones para académicos y profesionales, y algunas sugerencias para investigaciones futuras.

Palabras clave: experiencia del huésped, industria hotelera, satisfacción del cliente, calidad del servicio.

Clasificación JEL: L83, Z32

1. INTRODUCTION

The hotel industry is characterized by a wide range of services provided to customers. Companies within this sector are not homogeneous and generic strategies adopted indiscriminately by firms can generate different results according to the company’s context (Becker & Olsen, 1995). Hotels present a high complexity of their operations, involving several operations like accommodation, food, beverage, event management, and transportation that require a high degree of coordination and skilled staff. However, firms have high fixed costs and often face seasonal, fluctuate, and uncertain demand (Mullins, 1993).

Hotel companies are critical for the tourism industry as they provide a set of services needed to maintain tourist flow. Tourists are expected to be provided with accommodation, food, transportation, and a set of related services. The hotel industry is also relevant in supporting economic development due to its effect on job creation and supporting trade and commerce (UNWTO, 2024). For instance, in the European Union (EU), which is a major tourist destination with four member states among the top ten world destinations, 2.92 billion nights were spent in 2023, similar to values recorded before the COVID-19 pandemic, which contributes to the overall growth of the sector (Eurostat, 2024).

Demand fluctuations are among the major threats for hotel companies since they are substantially influenced by external and internal factors affecting the industry. Crises such as the United States (US) September 11, 2001, terrorist attack, the 2007-08 global financial crisis, (Cohen, 2012; Papatheodorou et al., 2010), or the COVID-19 pandemic (Gössling et al., 2021; Ioannides & Gyimóthy, 2020) showed the industry reliance on tourist demand.

Nevertheless, companies can address, at least partially, the effect on demand due to internal factors like the price level and service quality. A customer’s decision to stay in a hotel is influenced by several factors, including the accommodation price, purchasing power, which depends on economic cycles, price fairness (Heo & Lee, 2011), competition (Chattopadhyay & Mitra, 2019), hotels’ characteristics and proximity to attractions like beaches (Espinet et al., 2003), hotel features, customer experience, and competition (Sánchez-Pérez et al., 2019), location (Chan & Wong, 2006; Zhang et al., 2011), rating (Rigall-I-Torrent et al., 2011), and perceptions of service quality and value (Ye et al., 2012), among other aspects.

Service quality is mostly dependent on firms’ decision-making once they can manage how to position themselves. Service quality can be addressed from several dimensions or determinants of service quality including reliability, courtesy, communication, responsiveness, credibility, security, competence, knowledge of customer, physical evidence of service, courtesy, communication, and competence (Parasuraman et al., 1985). However, the way and the strength of how each determinant affects customer’s assessment of service quality varies, some being associated with dissatisfaction while others being satisfiers (Johnston, 1995). The former includes intangible aspects of service, like commitment, care, courtesy, friendliness, and attentiveness and the latter usually includes tangible or systemic aspects of service, like security, reliability, functionality, cleanliness, integrity, and aesthetics (Johnston, 1997). Likewise, service quality has been identified as an antecedent of customer satisfaction and as a source of purchasing intention (Cronin & Taylor, 1992), which is recognized as a major determinant of positive word-of-mouth, loyalty, and customer retention (Bearden & Teel, 1983). However, customers’ service expectation and perceived service also affect customer satisfaction (Grönroos, 1984) and customer needs vary, which means customer perceptions of service quality varies (Garvin, 1984).

Service quality is also highly related to a hotel’s guest experience. Among the underlying dimensions of guest experience in hotels, previous research found several similar aspects to determinants of customer satisfaction, including environment, accessibility, driving benefit and incentive (Knutson et al., 2009). Similarly, customer experience of quality involves factors such as emotional related experiences, staff-customer contact, customer-customer contact, learning, lifestyle, guest safety, and atmospherics, which are a strong predictor of client satisfaction, perceived value, and brand loyalty (Alnawas & Hemsley-Brown, 2019), warm and welcoming staff, comfortable rooms, location near tourist attractions, and food (Sthapit, 2019), physical environment and human interactions (Walls et al., 2011), ambiance, escapism, personalization, and convenience, all positively affecting positive word-of-mouth and customer retention (Shahid & Paul, 2022).

Consequently, hotel customer experience and service quality are highly related, showing significant evidence that service quality in hotels enhances customer satisfaction, by positively influencing customer experiential value (Kang et al., 2004; Oh, 1999; Wu & Liang, 2009). Following this reasoning and the perceived role of service quality in hotel customer experience and customer satisfaction (or dissatisfaction), this paper seeks to evaluate the existing literature on customer satisfaction and hotel customer experience, and how these themes interact within hotel industry, using bibliometric methods. To conduct the research, an approach based on a thematic analysis and an analysis of co-citations is employed. Previous research on these topics has been mostly focused on one of these themes, customer experience (Kim & So, 2022; Rehman et al., 2022) on the one hand, and the link between service quality and customer satisfaction (Shyju et al., 2023) on the other hand. Furthermore, while this study employs bibliometric methods incorporating thematic analysis and co-citation analysis, which allow for a comprehensive mapping of the intellectual structure of the research field, identifying key themes and the interrelations between service quality, customer experience, and satisfaction in the hotel industry, other studies have conducted systematic reviews focusing on customer satisfaction and sentiment analysis (Ameur et al., 2023; Castanha et al., 2023).

This paper is outlined as follows, the next section addresses the research methodology, section three presents the obtained results, and section four delves into the results discussion, implications, and main conclusions.

2. DATA AND METHODS

Bibliometric methods are useful to evaluate and understand the evolution of a research stream as portrayed in scientific literature (Hood & Wilson, 2001). This type of analysis seeks to assemble and interpret statistics regarding written communications, to uncover trends, and assess their development (Pritchard, 1969; Raisig, 1962). Therefore, it helps researchers in literature analysis to portray the evolution of the scientific field without analytical bias (Zupic & Čater, 2015) further depicting the research stream evolution. Bibliometric analyses have two main scopes: performance analysis, based on counting citations, and science mapping, seeking to represent the evolution of the research field (Cobo et al., 2011; Noyons et al., 1999).

This study conducts a thematic analysis and an analysis of co-citations. It seeks to understand how customer satisfaction and hotel customer experience research streams evolved in scientific literature. Data was obtained through a search on the Web of Science (WoS) database on March 11, 2024. Document type “article”, written in English language, containing the words “hotel” and “experience” and “satisfaction” within the document’s author keywords, keyword plus, title, or abstract, published in all available years until the end of 2023, were searched. The exact query was TS=(“hotel” AND (“experience” AND “satisfaction”)), “index date”: “1900-01-01” to “2024-03-11”, “Refined By”: “NOT Publication Years: 2024”, “Document Types: Article”, and “Languages: English”. Results returned 644 documents. The WoS database was chosen due to its relevance to the scientific community and reliability as a source of data. Furthermore, the use of a single database as a source of data enables the use of standardized data (Donthu et al., 2021).

The thematic approach uses a co-word analysis to assess the course and evolution of themes in published literature (He, 1999). This type of analysis is an automated content analysis technique to assess the corpus of texts and it is based on the co-occurrence of pairs of words, aggregated into networks, to study the evolution of the research field (Callon et al., 1983).

The co-citation analysis is a quantitative method that evaluates the frequency at which authors or documents are cited together. This method enables the classification of scientific literature into smaller thematic groups, including documents addressing similar and specific problems. According to this technique, two documents are considered co-cited when both are cited together by a third document, even in the absence of a direct citation between them (Marshakova-Shaikevich, 1973; Small, 1973). Data was computed using R Studio software (R Core Team, 2023) and results were extracted using the bibliometric package “bibliometrix” (Aria & Cuccurullo, 2017).

3. RESULTS

As mentioned in section 2, data was collected from the WoS database on March 11, 2024, and 644 articles were retrieved for analysis. Table 1 presents the descriptive statistics about data.

TABLE 1. DESCRIPTIVE STATISTICS

Description

Results

Analysed period

1999:2023

Sources

202

Documents

644

References

30612

Keywords Plus (ID)

1232

Source: Own Elaboration

The thematic analysis is conducted through a co-word analysis. This method aggregates groups of words to uncover connections among themes. This approach enables the detection of clusters of interrelated terms that correspond to centres of interest in a research stream (Callon et al., 1991). These relevant areas are organized in diagrams structured around concepts of centrality and density (Callon et al., 1991; Cobo et al., 2011).

According to Cobo et al. (2011), thematic analysis involves the use of strategic maps to understand the dynamics of a research field. These maps aggregate the constructs of co-words according to concepts of density and centrality to visualise and assess the development of various research themes, according to four quadrants. Clusters included within the upper-right quadrant are labelled as “motor themes”, presenting high centrality and high density; clusters included within the lower-right quadrant are labelled as “basic themes” and show high centrality and low density; clusters included within the upper-left quadrant are labelled as “niche themes” and present low centrality, and high density; and clusters included in the lower-left quadrant are labelled as “emerging or declining themes”, presenting low centrality and low density.

To conduct the thematic analysis, data was split into three time slices, the first one representing themes resulting from the production output over the period 1999-2009, the second one representing the themes resulting from the analysis of documents published over the period 2010-2019, and the third one, representing themes extracted from documents published over the period 2020-2023. Documents were split to analyse periods of one decade, although the first document published fulfilling the search criteria was published in 1999. Hence, these papers were included within the first period. Additionally, the third period (2020-2023) sought to evaluate if and how the COVID-19 pandemic affected the research field.

Table 2 shows themes extracted from the first analysed period based on a set of 16 articles published over the above-mentioned period (1999-2009).

TABLE 2. THEMES WITHIN THE FIRST PERIOD - 1999-2009

Quadrant

Themes

Motor Themes

model

Basic Themes

-- Absent --

Niche Themes

-- Absent --

Emerging or Declining Themes

attitudes

Centred themes

experience

Source: Own Elaboration

Results concerning the first analysed period (Table 2) show three clusters: attitudes, experience, and model. Analysing the frequency of words within each cluster enables one to identify patterns and relationships that may reveal insights about the research themes.

The experience cluster occupies on a central position, suggesting it is well-established within the literature. This cluster includes words like experience, dimensions, and physical surroundings, suggesting that, according to literature, the nature of customer experience in hotels was focused on the service provided and also on the tangible aspects such as the physical environment. This evidence may also suggest that customer experience encompasses various factors that contribute to build a decision regarding a guest’s stay in a hotel. Cluster model is identified as a motor theme. This cluster presents a strong interconnectivity with further themes. The term model occurs more frequently, followed by a set of words including service, customer perceptions, quality, customer satisfaction, impact, market orientation, and satisfaction. These terms may imply an emphasis on understanding and predicting customer satisfaction and service quality in hotels and a focus on how hotels align customer and market needs to improve customer satisfaction, as showed by the emphasis on market orientation. The cluster attitudes is labelled as an emerging or declining theme and is represented by only one word, which may indicate that it can only be assessed over a longitudinal perspective within the scope of the following period.

The second analysed period refers to the 2010-2019 time slice and includes 13 clusters as shown in Table 3. Over this period, 256 articles fulfilling the search criteria were published.

TABLE 3. THEMES WITHIN THE SECOND PERIOD - 2010-2019

Quadrant

Themes

Motor Themes

-- Absent --

Basic Themes

word-of-mouth, job-satisfaction, behavioral intentions, performance, intentions, satisfaction

Niche Themes

access, strategies, value dimensions, perceived justice, arousal, resources

Emerging or Declining Themes

-- Absent --

Centred themes

services

Source: Own Elaboration

Results (Table 3) show 13 clusters involving various aspects of the hotel industry customer experience and customer satisfaction, qualified as basic themes or niche themes and one centred theme.

The quadrant qualified as basic themes includes six clusters. The cluster job satisfaction includes terms such as mediating role, turnover, motivation, and organizational commitment, which show a close relationship with factors affecting employee’s satisfaction. Cluster performance includes terms like management, commitment, and engagement, suggesting a focus on organizational performance, the role of employee involvement and management strategies. Additionally, this cluster also includes terms such as green hotel and corporate social responsibility, which may reflect the increasing relevance of sustainable practices and their impact on hotel business performance. Cluster intentions includes terms such as online, customers, and moderating role. On the one hand, results point towards customer intentions research. On the other hand, terms like recovery and responses may indicate a growing interest in understanding how companies respond to service failure and manage customer intentions. Cluster satisfaction includes the largest number of terms. Among them, experience, impact, quality, and loyalty appear as the most relevant, suggesting a wide range of factors affecting and contributing to customer satisfaction, from physical environments to service quality. Cluster behavioural intentions includes terms such as co-creation, brand equity, and utilitarian, reflecting factors that affect customer behavioural intentions. It further suggests an interest on the effects of brand perception and the usefulness aspects of hospitality services. Word-of-mouth (WOM) represents the remaining cluster classified as basic theme. This theme encompasses terms like online reviews and user-generated content, emphasising the relevance of eWOM and its impact on the hotel industry.

The quadrant labelled as niche themes includes 6 clusters. Among them, cluster resources include terms such as burnout, conflict, and conservation, which suggests a focus on employee well-being and human resources management in the hotel industry on the one hand, and on the effect of the industry on the environment on the other hand. Cluster strategies involve terms like behavioural, conceptual-model, and service innovation, suggesting an emphasis on innovative approaches to providing services in the hotel industry and on the methodological approaches of research. Cluster access involves terms such as attitudes, cost, and travel, implying a focus on how cost structures affect the hotel industry and how companies positioning affect guest attitude. Cluster arousal includes terms like e-loyalty, personality, and music. Together, these themes seem to address emotional and psychological aspects of customer experience and their implications for customer loyalty. Cluster value dimensions seem to emphasise the experiential value of hotels and how it affects sales and customer behaviour. Cluster perceived justice includes terms such as consumer responses and moderating. These themes seem to imply, on the one hand, customers’ perceptions of fairness of service and, the other hand, the methodological aspects of the scientific research output, particularly the moderating effects.

The time frame 2010-2019 also included a centred theme, labelled as services, involving terms like big data, purchase, and sharing economy, which may emphasize a focus on the evolving nature of the hotel industry, over a period of technological advances and changing consumer behaviours.

The third analysed timeframe represents the period 2020-2023, encompassing a period of high turbulence for the hotel industry due to the COVID-19 pandemic. This period was also characterized by a higher scientific research output, comprising a total of 354 articles included in the database, addressing hotel customer experience and customer satisfaction. Table 4 presents themes resulting from the thematic analysis of the 2020-2023 period.

TABLE 4. THEMES WITHIN THE THIRD PERIOD - 2020-2023

Quadrant

Themes

Motor Themes

-- Absent --

Basic Themes

performance, satisfaction

Niche Themes

e-commerce, job-satisfaction

Emerging or Declining Themes

-- Absent --

Centred themes

customer satisfaction

Source: Own Elaboration

Results from the third analysed period (Table 4) show a consolidation of the research stream themes in five clusters, with clusters performance and satisfaction qualified as basic themes. Cluster performance involves a wide range of terms, including antecedents, consequences, and mediating role. It further includes resources and gender, suggesting an emphasis on the measurement of the effects among variables involving customer satisfaction and hotel customer experience. Additionally, these terms may also suggest an emphasis on methodological aspects regarding the research output. Furthermore, the cluster satisfaction also emerged as a basic theme. This theme is similar to customer satisfaction (a centred theme), although it represents a broader cluster, including terms like experience, tourism, hospitality, loyalty, perceptions, behaviour, perceived value, emotions, determinants, physical-environment, and price, suggesting that may have been given an emphasis on the determinants of customer satisfaction and its impact on loyalty and customer behaviour.

Clusters job-satisfaction and e-commerce represent niche themes. The former signals a focus on the well-being of employees within the industry, as indicated by terms such as work engagement, stress, burnout, and family conflict. Furthermore, perceived organizational support and workplace highlight organizational factors that contribute to job satisfaction. Cluster e-commerce indicates a concentrated focus. This cluster includes terms such as big data, purchase intention, and business intelligence, reflecting an interest in how e-commerce platforms are leveraged in the hotel and tourism industries, and how analytics are employed to understand and predict consumer purchasing behaviours.

Cluster customer satisfaction is represented as a centred theme and includes terms such as service quality, WOM, online reviews, and social media, which are prominent. However, it also includes sharing economy and big data, indicating an emphasis on online platforms and data analytics to understand customer satisfaction and demand predictions. Additionally, the relevance of value co-creation and sentiment analysis, highlights an emphasis in the literature on qualitative aspects of customer feedback and their implications for service improvement.

Regarding the co-citation network analysis, results were computed, and three clusters were identified. This analysis helps to identify the knowledge base of the research field and its intellectual structure, the latter involving the analysis of to the set of articles cited by the current research, disciplinary composition, influential research topics, and the pattern of interrelationships within the examined scientific domain. To compute data and provide a broader and clean representation of the intellectual structure the co-citation analysis was limited to a cut off of 50 documents, as suggested by Zupic and Čater (2015), which were included in the analysis. Three clusters emerged from the analysis.

Figure 1 represents the cluster 1 co-citation network.

FIGURE 1. CLUSTER 1 CO-CITATION NETWORK

Source: Own Elaboration

Following the obtained results from cluster 1, documents were analysed to evaluate the scope and nature of each one. Table 5 represents the documents included in the cluster 1 co-citation network.

TABLE 5. DOCUMENTS INCLUDED IN CLUSTER 1

Document

Subject

Xiang et al. (2015)

Explores the nature and trends of internet usage by travellers in planning their trips.

Guo et al. (2017)

Uses big data with Latent Dirichlet Allocation (LDA), as mining technique, to understand consumer behaviour in tourism industry and identify key dimensions of customer satisfaction.

Sparks and Browning (2011)

Examines how online hotel reviews (electronic word-of-mouth - eWOM) influence customers' intentions to stay and their trust perceptions towards the hotel.

Xu and Li (2016)

Analyses online customer reviews to identify what factors lead to satisfaction and dissatisfaction among hotel guests.

Zhou et al. (2014)

Examines online reviews of hotel services to identify insights about customer satisfaction.

Serra Cantallops and Salvi (2014)

Analyses existing literature on the impact of (eWOM) on the hotel industry.

Litvin et al. (2008)

Assesses how eWOM has transformed traditional word-of-mouth (WOM) communication. Emphasises how customers use eWOM in their purchasing decisions in hospitality and tourism industries.

Vermeulen and Seegers (2009)

Evaluates how online hotel reviews influence consumer decision-making, particularly on hotel consumer choices.

Schuckert et al. (2015)

Reviews and analyses research articles addressing the impact of online reviews in the hospitality and tourism industries.

Source: Own Elaboration

Based on the documents in cluster 1 (Table 5) , there is a clear focus on understanding how online reviews, as a form of eWOM, influence customers’ decisions (Litvin et al., 2008; Serra Cantallops & Salvi, 2014; Sparks & Browning, 2011; Vermeulen & Seegers, 2009; Xu & Li, 2016; Zhou et al., 2014). These papers underscore the critical role of eWOM in shaping potential customers’ decisions, trust, and intentions to book, and highlight the transition from traditional WOM to eWOM. Furthermore, the consensus is that online reviews are a critical source of information for consumers in their purchasing decisions, in industries where products are intangible and experiences cannot be evaluated beforehand. These papers also suggest that both positive and negative reviews significantly influence customer satisfaction and the decision making process (Guo et al., 2017)

The cluster 2 co-citation network is represented in Figure 2.

FIGURE 2. CLUSTER 2 CO-CITATION NETWORK

Source: Own Elaboration

Table 6 presents the list of documents included in the cluster 2 co-citation network, showing the document reference and main subject.

TABLE 6. DOCUMENTS INCLUDED IN CLUSTER 2

Document

Subject

Fornell and Larker (1981)

Proposes a set of alternative systems incorporating measures of explanatory power. Advises for a shift in how researchers assess Structural Equation Models (SEM), emphasizing validity, reliability, and operational significance over traditional chi-square goodness-of-fit indices.

Hair et al. (2010)

Explores various statistical methods used to analyse data that involves multiple variables simultaneously.

Parasuraman et al. (1988)

Develops and validates the SERVQUAL scale, designed to capture consumer expectations and perceptions of service quality.

Podsakoff et al. (2003)

Examines the effect of method biases on behavioural research results, identifying potential sources of these biases and discussing strategies to control for them.

Anderson and Gerbing (1988)

Provides guidance for researchers on using SEM for theory testing and development within the social sciences.

Parasuraman et al. (1985)

Develops a theoretical framework for understanding service quality and identifies gaps affecting service quality from the provider's and the customer's perspectives. Proposes a model for assessing service quality.

Bitner (1992)

Examines how physical environments, in service industry, affect consumer behaviour and staff performance

Oliver (1980)

Develops a model to assess customer satisfaction. Suggests that customer satisfaction is affected by the relationship between expectancies, experiences and the resulting customer satisfaction level, which affect customer attitude change and purchase behaviour intentions.

Pine and Gilmore (1998)

Evaluates the economic process of how products and services transform in experiences.

Bitner (1990)

Evaluates how physical environment and staff behaviour affect customer evaluation of services and service failure.

Bagozzi and Yi (1988)

Evaluates methods and criteria to assess validity and fit in SEM.

Zeithaml et al. (1996)

Examines how high levels of perceived service quality influence customer positive behaviour like loyalty and willingness to pay higher prices, and diminish negative behaviours such as complaints and provider change.

Nunnally (1978)

Delves into principles and methods to develop and interpret psychological tests and measures. This document establishes a guide for researchers and practitioners in designing reliable and valid measures.

Walls et al. (2011)

Evaluates customer experiences perception in luxury hotels. Emphasizes how physical environment, human interactions, personal traits, and aspects related to trip affect customer experiences.

Cronin et al. (2000)

Assesses how service quality and value affect customer satisfaction and behaviour. Emphasizes how direct and indirect effects affect customer loyalty.

Baron and Kenny (1986)

Addresses the use of moderator and mediator variables in social sciences research.

Hosany and Witham (2010)

Addresses customer experiences in cruises and evaluates its impact on customer satisfaction and recommendation intentions.

Wu and Liang (2009)

Assesses the effect of customer experiential value on customer satisfaction on luxury restaurants and hotels. Evaluates how restaurant’s physical environment, staff interactions, and clients interactions affect perceived value and satisfaction.

Henseler et al. (2015)

Provides guidelines on how to assess discriminant validity when using variance-based SEM, such as Partial Least Squares (PLS). Proposes a new method to assess discriminant validity, the heterotrait-monotrait ratio of correlations (HTMT).

Brakus et al. (2009)

Delves into the measurement of brand experience concept, by developing a measurement model to assess brand experience and its impact on customer satisfaction and loyalty.

Mehrabian and Russel (1974)

Addresses how physical spaces affect human behaviour and sentiments. Assesses the effects of these environments on individuals.

Oh et al. (2007)

Evaluates customers search for unique and memorable experiences and its effect on goods and services purchasing.

Oliver (1999)

Analyses the relationship between customer satisfaction and loyalty. Proposes a model for the interrelation between customer satisfaction and loyalty, and customer behaviour.

Schmitt (1999)

Compares experiential marketing with traditional marketing approaches.

Chen and Chen (2010)

Evaluates the concept of visitor experience within heritage tourism context. Assesses the interrelationships between experience quality, perceived value, customer satisfaction and behavioural intentions.

Holbrook and Hirschman (1982)

Customer experiential dimensions in consumption. Establishes a set of common customer behaviour variables.

Chin (1998)

Evaluates statistical methods applied in research. Compares the Partial Least Squares (PLS) approach with a covariance-based approach for structural path estimation.

Zeithaml (1988)

Proposes a conceptual model for the interrelations between perceived quality, price and perceived value.

Cronin and Taylor (1992)

Assesses the concept and measurement of service quality and the interconnection between service quality, customer satisfaction and purchase intentions.

Hair et al. (2011)

Conducts a review of PLS-SEM as a concurrent approach to covariance-based SEM.

Otto and Ritchie (1996)

Develops and validates a measurement model for the construct of service experience in tourism.

Ryu et al. (2012)

Develops and assesses conceptual model for the interrelationships between service quality foodservice, including physical environment, food, and service, on the one hand, and key outcomes in restaurant industry.

Mano and Oliver (1993)

Evaluates the dimensionality of post consumption variables like product evaluation, product affection and product satisfaction.

Vargo and Lusch (2004)

Explores the evolution from a traditional goods-based exchange model, inherited from economics, to a new paradigm centered around services and intangible resources in marketing research.

Han et al. (2011)

Addresses the process through which hotel customers develop loyalty to a firm.

Barsky and Nash (2002)

Assess the relationship between customer loyalty and emotions within the hotel industry.

Kandampully and Suhartanto (2000)

Identifies factors related to hotel image that produce a positive effect on customer satisfaction and customer loyalty.

Kline (2005)

Provides an introduction to SEM, covering both theoretical principles and practical applications.

Source: Own Elaboration

Based on documents included in cluster 2 (Table 6), several main interconnected ideas are highlighted: service quality and satisfaction measurement (Cronin et al., 2000; Cronin & Taylor, 1992; Parasuraman et al., 1988, 1985; Ryu et al., 2012); methodological approaches, including the use of SEM and statistical analysis in customer satisfaction, service quality, and customer hotel experience research (Anderson & Gerbing, 1988; Bagozzi & Yi, 1988; Chin, 1998; Fornell & Larker, 1981; Hair et al., 2011, 2010; Henseler et al., 2015; Kline, 2005), moderation and mediation effects (Baron & Kenny, 1986), and method bias (Podsakoff et al., 2003); physical environment’s impact on hotel customer experience (Bitner, 1990, 1992; Mehrabian & Russell, 1974; Wu & Liang, 2009); customer behaviour and behavioural intentions and their relationship with satisfaction, loyalty, and experiences on customer behaviour (Barsky & Nash, 2002; Brakus et al., 2009; Han et al., 2011; Holbrook & Hirschman, 1982; Kandampully & Suhartanto, 2000; Mano & Oliver, 1993; Oh et al., 2007; Oliver, 1980, 1999; Pine & Gilmore, 1998; Schmitt, 1999; Zeithaml et al., 1996); experiential marketing and experience economy (Andrew Walls Fevzi Okumus & Kwun, 2011; Chen & Chen, 2010; Hosany & Witham, 2010; Otto & Ritchie, 1996).

Concerning cluster 3, Figure 3 presents the results and shows a cluster including solely two documents.

FIGURE 3. CLUSTER 3 CO-CITATION NETWORK

Source: Own Elaboration

Table 7 identifies the documents references and the main subject included in the cluster 3 co-citation network.

TABLE 7. DOCUMENTS INCLUDED IN CLUSTER 3

Document

Subject

Choi and Choi (2001)

Assesses the relevance of hotel factor on overall travellers’ satisfaction and if hotel factors affect customers return intentions.

Ren et al. (2016)

Investigates consumer behaviour within the budget hotel sector.

Source: Own Elaboration

Cluster 3 (Table 7) is represented by studies involving determinants of guest satisfaction, how they relate to customers behaviour and are affected by hotel’s traits (Choi & Chu, 2001), including budget hotels (Ren et al., 2016).

4. DISCUSSION, RESEACH AGENDA AND CONCLUSIONS

4.1. Discussion

This study evaluates scientific literature delving into hotel customer experience and customer satisfaction. Data were collected, results were extracted, and a thematic analysis and a co-citation analysis were conducted. The thematic analysis sought to understand the evolution of themes over time. Hence, the scientific production output was split into three periods: 1999-2009; 2010-2019; and 2020-2023. The co-citation analysis sought to evaluate the intellectual structure of the research stream and to understand the background of the evolving themes relating to hotel customer experience and customer satisfaction.

Results demonstrated the evolution of themes over time and how they interconnect with literature. Over the first analysed period (1999-2009), results showed that customer experience seems integrated with dimensions and nature of service provided, physical environments and customers attitudes. These themes are relevant aspects to assess customer satisfaction and emphasize some determinants of service quality like functionality, cleanliness, integrity, and aesthetics (Johnston, 1995) as well as the role of hotels’ physical environment’s impact on customers’ experiences (Bitner, 1990, 1992; Mehrabian & Russell, 1974; Wu & Liang, 2009). The emergence of the theme model and the emphasis on methodological approaches, including SEM and statistical analysis, moderation and mediation effects, and method bias (Anderson & Gerbing, 1988; Bagozzi & Yi, 1988; Baron & Kenny, 1986; Chin, 1998; Fornell & Larker, 1981; Hair et al., 2011, 2010; Henseler et al., 2015; Kline, 2005; Podsakoff et al., 2003), resulting from the co-citation analysis, signals a generalized use of SEM analysis in hotel customer experience and customer satisfaction research, and the analysis of mediation and moderation of variables including determinants of customer satisfaction.

The second analysed period (2010-2019) highlights a wider range of themes. Similarly to the previous period, statistical and methodological approaches were emphasized and the theme mediating effect suggests the relevance of this type of analysis among scientific research published over this period. However, themes like WOM and eWOM emerged and became relevant, linked to customer behaviour, customers intentions, and purchasing decisions (Litvin et al., 2008; Serra Cantallops & Salvi, 2014; Sparks & Browning, 2011; Vermeulen & Seegers, 2009; Xu & Li, 2016; Zhou et al., 2014), to shape potential customers’ decisions, trust, and intentions. Additionally, the emergence of themes related to job satisfaction recognizes the role of employees within the hotel industry and the approaches to be adopted by companies in a sector highly dependent on coordination and skilled staff (Mullins, 1993).

Results from the thematic analysis of the period 2020-2023 highlighted three main ideas: hotel performance; job-satisfaction; and the role of eWOM in customers purchasing behaviour. The emphasis on hotel performance, its antecedents and consequences, as well as mediating effects, was also relevant themes. These themes and the references to statistics and methodological approaches observed in cluster 2 of the co-citation analysis (Anderson & Gerbing, 1988; Bagozzi & Yi, 1988; Baron & Kenny, 1986; Chin, 1998; Fornell & Larker, 1981; Hair et al., 2011, 2010; Henseler et al., 2015; Kline, 2005; Podsakoff et al., 2003) suggest that the use of SEM analysis, the assessment of antecedents and consequences, as well as the mediating effects were widely used to elucidate how the interrelations between hotel customer experience, determinants of customer satisfaction, loyalty, customer behaviour, and decision making occur. A second theme involving job satisfaction emphasizes the role of skilled employees and high coordination in hotels, for providing unique and memorable experiences, customer satisfaction and business performance. Similarly to the previous periods, eWOM was emphasized within literature and confirmed by the cluster 1 co-citation map (Litvin et al., 2008; Serra Cantallops & Salvi, 2014; Sparks & Browning, 2011; Vermeulen & Seegers, 2009; Xu & Li, 2016; Zhou et al., 2014), specifically with regard to online reviews and social media.

The obtained results provide relevant theoretical and practical implications. From a theoretical perspective, the results show that scientific literature on hotel customer experience and customer satisfaction has primarily focused on how experiences affect the satisfaction of current and potential clients, the role of online reviews, WOM and eWOM, employees, physical environments, and their impact on hotel performance. Furthermore, the results indicate that the use of SEM analysis and the assessment of mediating and moderating effects are prevalent in scientific research, highlighting opportunities for employing different methodological approaches to assess the interrelationship between hotel customer experience and customer satisfaction. Additionally, the continuous emphasis on the determinants of service quality in hotel customer experience and customer satisfaction research suggests that despite technological changes, innovation and development in services, changes in the physical environment, and shifts in customer preferences, the way customers assess service quality and satisfaction remains comparable over time.

From a managerial perspective, results emphasize the relevance of WOM in customers assessment of hotel experience and how online reviews affect potential guest decisions about where to stay, their behaviour, and purchasing decisions. Furthermore, despite the evolving nature of the industry, service quality, customer experience and customer satisfaction are dependent on the high coordination of employees and skilled staff. From this perspective, results show that managers should focus their efforts on building and maintaining skilled staff, which requires the development of management policies targeting job-satisfaction. Given the recurrent emphasis on job satisfaction in the thematic analysis and its closeness to the theme performance, results suggest that job satisfaction and skilled staff are critical to attaining superior business performance.

4.2. Research agenda and conclusions

Several main ideas emerged from this study. However, according to the results, an emphasis on the determinants of customer satisfaction, hotels’ physical environment, employees and job satisfaction, and the replacement of WOM by eWOM as a driving force in customers’ decisions about accommodation seem critical to the relationship between customer experience and customer satisfaction and to the research stream.

Moreover, relevant topics emerged for future research. The rapid evolution of technology underscores opportunities to understand how technological innovations can be leveraged to improve service delivery and customer satisfaction (Ivanov & Webster, 2020; Tussyadiah & Park, 2018). Therefore, the effect of emerging technologies such as artificial intelligence (AI), machine learning and the Internet of things (IoT) represent opportunities for companies to enhance customer experience and satisfaction. This process can be achieved through the hotels’ technological and physical changes, as well as, through the instant analysis of customer´s eWOM. Moreover, given the global nature of the hotel industry, it seems critical to understand how cultural factors affect customer satisfaction. Therefore, comparative studies across different cultural contexts can provide insights on how hotels can adapt their services to meet diverse needs.

Previous crises such as the COVID-19 pandemic showed how the hotel industry is dependent on tourism demand and how demand can be disrupted by external factors that threaten entire economic sectors such as the tourism industry and the hotel industry. This issue demonstrates that the hotel industry is highly vulnerable to global crises. Therefore, longitudinal studies are required, assessing how events like pandemics, economic recession, and natural disasters impact customer perceptions and behaviours over time, and how hotels can build resilience (Gössling et al., 2021; Sigala, 2020). Similarly, as sustainability and sustainable environments become increasingly important to customers, hotels need to enhance their knowledge of how the impact of their green practices affects customer experience and customer satisfaction. Research can focus on customer perceptions of sustainability efforts and their willingness to pay a premium for environmentally friendly services (Han et al., 2010).

Hotel industry relies on a motivated workforce to provide superior value to customers. The link between employee satisfaction and customer experience is critical in the service industry. Consequently, future research should also examine how factors such as job satisfaction, employee engagement, and workplace environment affect service quality (Chi & Gursoy, 2009), and particularly how technology innovations like AI and IoT affect employees motivation and satisfaction and how the emergence of these tools affects customer experience and customer satisfaction through employees satisfaction and productivity.

Despite providing relevant insights into the relationship between hotel customer experience and customer satisfaction, this study has several limitations. First, the conclusions are based on evidence from quantitative methods such as thematic analysis and co-citation analysis of previous literature. Additionally, although a qualitative analysis of the documents within the co-citation map was conducted, some relevant documents were absent. Furthermore, since the data was retrieved solely from the WoS database, there is a risk of omitting pertinent information. Nevertheless, given the volume of documents within the dataset and the methodology employed, there is a high degree of confidence in the reliability of the results. The WoS database is significant to the scientific community, reliable as a data source, and contains higher-quality papers, making it a valuable source of standardized data (Donthu et al., 2021).

FUNDING

NECE and this work are supported by FCT - Fundação para a Ciência e Tecnologia, I.P. by project reference UIDB/04630/2020 and DOI identifier 10.54499/UIDP/04630/2020.

AUTHOR'S CONTRIBUTIONS

Conceptualization, Carlos Sampaio and Mónica Régio; Methodology, Carlos Sampaio; Data Collection, Carlos Sampaio; Data Analysis, Carlos Sampaio and Mónica Régio; Writing - Original Draft Preparation, Carlos Sampaio and Mónica Régio; Writing - Review and Editing, Carlos Sampaio and Mónica Régio; Supervision, Carlos Sampaio and Mónica Régio.

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* Autor de correspondencia: cfsampaio@ipcb.pt

1 ORCID: https://orcid.org/0000-0002-5249-7798

2 ORCID: https://orcid.org/0000-0001-7918-9691