Hotel Management Behavior Model in eWOM Management

www.pasosonline.org Vol. 22 N. o 4. Págs. 705-723. octubre‑deciembre 2024 https://doi.org/10.25145/j.pasos.2024.22.046 Hotel Management Behavior Model in eWOM Management Manuel Gilabert* Universidad Argentina de la Empresa (Argentina) Maria del Carmen Berné Manero** Universidad de Zaragoza (España) Abstract: Electronic Word-of-Mouth (eWOM) is vital in various industries, particularly in the hospitality sector, where its effects on sales, prices, reputation and other business variables are evident. Understanding how eWOM is accepted and incorporated within organisations is essential for their development. The present study aims to explain managerial behaviour concerning the use of eWOM in hotels. To achieve this, a Partial Least Squares Structural Equation Modeling (PLS-SEM) model was validated using data from a questionnaire directed at hotels in a coastal region of Argentina, where year-round and seasonal hotels are located. It was found that the use of eWOM in management depends on the management's intention to use the same which is influenced by their attitude towards it. Additionally, attitude is influenced by the perceived usefulness and ease of management, and use is contingent upon the quality of the eWOM. Keywords: eWOM, hotel management, PLS-SEM, seasonal hotel, management behaviour . Modelo de comportamiento en la gestión del eWOM Resumen: El boca-oído electrónico (eWOM) es de vital importancia en diversas industrias, en particular la hotelera, donde se evidencian efectos en ventas, precios, reputación y otras variables. Comprender cómo se acepta e incorpora gerencialmente el eWOM en las organizaciones es fundamental para el desarrollo de las mismas. El presente estudio tiene como objetivo explicar el comportamiento gerencial en relación al uso de eWOM en hoteles. Para ello se validó un modelo de ecuaciones estructurales PLS-SEM con datos provenientes de un cuestionario dirigido a hoteles de un área costera de Argentina donde hay hoteles anuales y de temporada. Se encontró que el uso de eWOM en la gestión depende de la intención de la gerencia en gestionarlo, la cual a su vez se nutre de su actitud hacia el tema. Adicionalmente, la actitud depende de la utilidad y facilidad percibida, y la utilidad depende de la calidad del eWOM. Palabras clave: eWOM, gestión de hotel, PLS-SEM, hotel estacional, comportamiento gerencial. 1. Introduction One of the objectives of managerial research is to provide tools for current and future business leaders to make intelligent, evidence-based decisions. Furthermore, given the investment companies make to maintain a positive online image, it would be prudent to examine the potential benefits of such efforts (Torres, Singh & Robertson-Ring, 2015). Understanding managerial behavior regarding electronic Word-of-Mouth (eWOM) management is fundamental. Management is concerned about the online image of their organizations. Scholars have also been equally concerned about the emergence of consumer-generated comments and have studied various topics related to the phenomenon. Review sites must be closely monitored (Litvin & Hoffman, 2012). * INSOD Institute [Project D15A01]; E-mail: manuel_gila[email protected].ar ; https://orcid.org/0000-0002-9449-6902 ** Science, University and Knowledge Society Department of Aragon Government [S42_20R: CREVALOR]; IEDIS, Research institute; E-mail: [email protected]; https://orcid.org/0000-0003-3050-1634 Cite: Gilabert, M. & Berné Manero, M. C. (2024). Hotel Management Behavior Model in eWOM Management. PASOS. Revista de Turismo y Patrimonio Cultural , 22(4), 705-723. https://doi.org/10.25145/j.pasos.2024.22.046 © PASOS Revista de Turismo y Patrimonio Cultural. ISSN 1695-7121 706 Hotel Management Behavior Model in eWOM Management PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 While there has been a proliferation of research on the eWOM phenomenon in the last decade, a literature review reveals specific gaps. For instance, there are relatively few studies on eWOM from the perspective of decision-makers, as the vast majority have focused on its impact on consumers (Salvi et al., 2013). Studies that have sought to explain managerial behavior regarding the use of eWOM in hotels are limited and scarce motives (Berné-Manero, Ciobanu & Pedraja-Iglesias, 2020). Additionally, studies have not been found focusing on eWOM for seasonal hotels, even though these establishments have different staffing and operational schemes compared to year-round hotels (Arasli, Altinay & Arici, 2020; Belias et al., 2023), and their management could be driven by factors different from their year-round counterparts (Öztürk, Ergün, & Kutukiz, 2016). Considering eWOM management to be important is different from effectively implementing that management. Davis's (1989) Technology Acceptance Model (TAM) suggests that people's adoption decisions of technology are often determined by the extent to which they believe that using that technology would enhance their job performance (perceived usefulness) and that using the technology would be effortless (perceived ease of use). The literature indicates that those who manage eWOM perceive it as beneficial for the company. For instance, Perez-Aranda, Vallespín, & Molinillo (2019) found a correlation between effective management of information posted on review sites and perceived benefits for the company. However, it seems not to happen both ways. TAM reflects that perceived usefulness is an indirect cause of use, not vice versa, and the work of Aureli & Supino (2017) confirms that hotels' management interest in eWOM doesn't always lead to a proactive reputation management strategy. This study, based on Italian hotel managers, found very few hotel managers (five out of seventy-one) who stated that eWOM is not very important, indicating that they do not monitor or analyze their online reputation due to its misleading nature (two hotels) because these activities consume too much time (two hotels), or because they are not interested at all in knowing what people write on travel websites (one hotel). The others (almost 93% of respondents) declare that online reputation plays a vital role in the hotel industry. They monitor it for strategic reasons (in fact, hardly any hotel outsources monitoring) for a long time (most for more than three years) and frequently (80% reported analyzing it at least once a week). Thus, in today's dynamic business world, it's not enough to show concern or monitor such comments; hoteliers must have a strategy to process this information and reap the rewards of higher ratings and more reviews (Torres, Singh & Robertson-Ring, 2015). The present study aims to elucidate the process of acceptance and implementation of eWOM management by hotel decision-makers and its performance consequences. The selected study region for this research is the Atlantic Coast of the Buenos Aires province. Despite the numerous advantages highlighted in the literature for considering and managing eWOM, it has been observed that many hotels in the study region do not respond to the feedback left by guests on platforms. In response to the research challenge posed, the study will be conducted from the perspective of hotel decision-makers, considering primary information gathered through questionnaires administered to hoteliers. Following this introduction, the article is structured into different sections. First, a literature review on managerial behavior models is presented. Next, the hypotheses are stated, and the study methodology is outlined, using a Partial Least Squares Structural Equation Modeling (PLS-SEM) framework fed with survey data from managers. In the following section, the results of the employed techniques are displayed and described. Finally, in the last section, the findings are explained, related to other studies, and the main conclusions are established. It was found that the use of eWOM in management depends on management's intention to use it, which, in turn, is influenced by their attitude towards the topic. Additionally, attitude depends on perceived usefulness and ease of use, and the quality of eWOM affects perceived usefulness. 2. Literature review Generally speaking, organizations should respond to eWOM, mainly when it is negative, and should do so in a personalized, detailed, and timely manner (Lopes et al.,2023). Yet, motivations for management could vary depending on the destinations, hotel characteristics, and even the demographic features. Acerenza (2003, p. 53) addresses this issue, applying it to general management when analyzing destinations' competitiveness: " Around 70%, maybe more, of the hotel supply in many traditional tourist destinations consists of small and medium-sized hotels, mostly managed by their owners. However, given this reality, there are no programs aimed at renovating and re-equipping these establishments to adapt to the new requirements of current demand. Consequently, a high percentage of the accommodation offer becomes obsolete, affecting the quality of services and, therefore, the destination's competitiveness ". Specifically, regarding eWOM management, younger managers working in medium and large hotels Manuel Gilabert, Maria del Carmen Berné Manero 707 PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 seem to have more confidence in the effectiveness of their online reputation, and the management of small hotels seems more interested than their counterparts in monitoring the physical and external characteristics of the hotel rather than guest experiences with hotel staff; the latter may be related to most small hotels being family-run businesses, where the family is generally part of the staff, making it easier for them to question external aspects than themselves (Aureli & Supino, 2017). Positive eWOM motivates management and staff to maintain good quality service, whereas negative eWOM helps hotels to identify problems and improve (Chen, Law & Yan, 2022). Managerial behavior has been studied from various perspectives and theories. A recent review of almost 1,000 publications from 2000 to 2017 on behavior theories identified 62 different approaches (Kwon & Silva, 2020). Particularly concerning the intention to adopt and use technologies, according to Momany and Jamous (2017), the development and application of the following models are highlighted: Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), Decomposed Theory of Planned Behavior (DTPB), Technology Acceptance Model (TAM and TAM2), the combination of TAM and TPB (CTAM-TPB), Model of PC Utilization (MPCU), Innovation Diffusion Theory (IDT), Motivational Model (MM), the Social Cognitive Theory (SCT), among others. Within the dozens of theories identified by Kwon & Silva (2020), a division suggested by Davis et al. (2015) can be made: those of individual behavior and sometimes interpersonal behavior and those of social or broad behavior. In this classification, the authors mention that theories from economics and psychology are likely to focus on individual behaviour. While the number of theories is significant, they often share several common elements, adding or removing some variables and interpretations of results. For example, the Technology Acceptance Model (TAM) indicates relationships between perceived usefulness, ease of use, attitude, intention, and actual system use. Graph 1 presents the relationships of the TAM model. Graph 1: Technology Acceptance Model TAM Source: Adapted from Davis (1989) The constructs can be defined in the literature as follows: - External variables or facilitating conditions: "Objective factors in the environment in which observers agree that they make an act easy to perform" (Venkatesh et al., 2003, p. 430). - Perceived ease of use: "The extent to which a person believes that using a particular system would be effortless" (Davis, 1989, p. 320). - Perceived usefulness: "The extent to which a person believes that using a particular system would enhance their job performance" (Davis, 1989, p. 320). - Attitude toward behavior: "Positive or negative feelings of an individual (evaluative affect) about the performance of the target behavior" (Fishbein & Ajzen, 1977, p. 216). - Intention to use: "The decision to perform or not perform a particular action" (Fishbein, Ajzen & Belief, 1975). - Actual system use: "The degree of technology use" (Compeau & Higgins, 1995). On the other hand, the Theory of Reasoned Action (TRA) model by Ajzen & Fishbein (1980) establishes the relationship between beliefs about behavior and beliefs about norms, which affect attitude and subjective criteria, respectively. The latter affects intention, which then impacts behavior. Graph 2 succinctly presents these relationships. Several years later, the same authors found that the perceived control variable was also relevant to explaining behavior and developed the Theory of Planned Behavior (TPB) model schematically depicted in Graph 3. 708 Hotel Management Behavior Model in eWOM Management PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 Graph 2: Theory of Reasoned Action TRA Source: Adapted from Ajzen & Fishbein (1980) Graph 3: Theory of Planned Behavior TPB Source: Adapted from Fishbein & Azjen (2011) Mendes Filho, Tan & Mills (2012) suggest that the Theory of Planned Behavior model could help explain guests' eWOM behavior in the tourism industry when planning their trips. Another theory used to understand technology adoption processes is the Behavioral Reasoning Theory (BRT) (Westaby, 2005; Westaby, Probst & Lee, 2010), which groups attitude, perceived norms, and perceived control from the Theory of Planned Behavior (TPB) model under the variable "global motives," and adds the variable "reasons," which relates to these motives and intention to explain behavior, as shown in Graph 4. Graph 4: Behavioral Reasoning Theory BRT Source: Westaby, Probst & Lee (2010) Claudy, García & O'Driscoll (2015) suggest that this theory provides a framework where user involvement is crucial for successful technology adoption. Users predisposed to change encounter less resistance to adopting new technology. A recent study adapted the BRT model and applied it to implementing and using eWOM as a business management tool. This is the eWIP model (Berné-Manero, Ciobanu & Pedraja-Iglesias, 2020). The proposed model (see Graph 5) includes the relationship between reasons (preconditions favoring or hindering the use of eWOM as a management tool), global motives (for developing the system), managerial behavior (performance gained from changes implemented through motivated actions), and intentions to continue using the tool. Additionally, a variable is added from the decision-maker's perspective: the characteristics of eWOM (Credibility, Authenticity, and Quality). Manuel Gilabert, Maria del Carmen Berné Manero 709 PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 Graph 5: eWIP Model Source: Berné-Manero, Ciobanu & Pedraja-Iglesias (2020). In this model, specific reasons for individuals engaging or not engaging in an observed behavior must be considered, and the decision-making context should be considered as a determinant of decisionmakers' behavior. Intentions are directly related to behavior and are strongly influenced by motives (Berné-Manero, Ciobanu & Pedraja-Iglesias, 2020). Most technology adoption studies use the traditional Technology Acceptance Model (TAM) as a theoretical foundation (Law, Leung & Chan, 2019). For instance, Wang & Li's (2019) research employs the TAM model applied to the eWOM field to explore the use of eWOM and eWOM generation behaviors. Wu's (2018) doctoral thesis uses TAM to analyze customers' acceptance of an online hotel reservation system, confirming the relationship between user system acceptance and usage intention, as Davis (1989) proposed in an online hotel direct sales scenario. In this case, it was found that the perceived ease of use of the hotel's online reservation system did not directly affect customers' intention to use the system for hotel reservations. The Nyoro et al. (2015) study reviews 25 articles that use TAM in the context of e-commerce adoption. The authors found that TAM is the most widely used model for predicting e-commerce adoption and that most studies are conducted in developing countries. They also found that TAM is suitable for providing statistically accurate results in e-commerce adoption. Some authors perform integrations or combinations of models, such as Tavera & Londoño (2014), who combine TAM and TBP to explain e-commerce acceptance in users. As the literature indicates, researchers have mostly sought to understand eWOM based on online material, not only about hotels but also whole destinations (Márquez-González & Herrero, 2017). However, hotel leaders and other stakeholders in hotel organizations remain relatively untapped data sources. This avenue can be explored through interviews, observations, and questionnaires sent to hoteliers (Bore et al., 2017), which could impact our understanding of how hoteliers manage eWOM responses (Chen, Law & Yan, 2022; Lopes et al., 2023). Finally, it is worth mentioning that some studies discuss hotels that close during the low season while others remain open year-round (Park et al., 2016; Öztürk, Ergün, & Kutukiz, 2016; SáezFernández, Jiménez-Hernández & Ostos-Rey, 2020; Arasli, Altinay & Arici, 2020; Belias et al., 2023). This differentiation may be relevant as a classification criterion and research support. However, the number of studies that have taken it as an analytical category so far is limited (e.g., Sáez-Fernández, JiménezHernández & Ostos-Rey, 2020). 3. Methods and Hypothesis To explain hoteliers' behavior regarding eWOM management, a model was defined based on the general Technology Acceptance Model TAM (Davis, 1989), as it is the most extensively used for studies in the field (Law, Leung & Chan, 2019), incorporating elements from eWIP (Berné-Manero, Ciobanu, & Pedraja-Iglesias, 2020), which takes into account eWOM characteristics and additionally includes the effect of hotel type (seasonal vs annual). The relevant hypotheses are developed below. The eWIP model shows a significant positive effect of eWOM characteristics on the global motives for hotel management to use eWOM. Therefore, this construct is expected to affect the perceived usefulness of eWOM significantly. Thus, the following hypotheses are established: H1: "eWOM characteristics (Credibility, Authenticity, and Quality) have a direct positive influence on the perceived usefulness of eWOM by hotel management." 710 Hotel Management Behavior Model in eWOM Management PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 The following hypotheses emerge from the general TAM model (Davis, 1989) but are applied to eWOM management by hotels: H2: "Perceived usefulness of eWOM by hotel management has a direct and positive influence on the intention to use eWOM." H3: "Perceived usefulness of eWOM by hotel management has a direct and positive influence on the attitude towards using eWOM." H4: "Ease of use of eWOM by hotel management has a direct and positive influence on the attitude towards using eWOM." H5: "Ease of use of eWOM by hotel management has a direct and positive influence on the perceived usefulness of eWOM." H6: "Attitude towards eWOM by hotel management has a direct and positive influence on the intention to use eWOM." H7: "Intention to use eWOM by hotel management has a direct and positive influence on the use or performance in eWOM management." Graph 6 schematically presents the different constructs and the proposed relationships. Graph 6: Proposed model for acceptance and use of eWOM Source: own elaboration On the other hand, it is expected that the ease of managing eWOM may depend on the characteristics of the hotels. Higher-category (star-rated) hotels are likely to have higher levels of investment that enable them to have more straightforward management compared to smaller-scale ones; similarly, those hotels that operate year-round and consequently have staff working throughout the year are likely to be more efficient and have an easier time managing eWOM compared to those that close for part of the year (Park et al., 2016; Sáez-Fernández, Jiménez-Hernández & Ostos-Rey, 2020; Arasli, Altinay & Arici, 2020). Likewise, there could be differences based on the city where the hotels are located and differences in the perceived ease of managing eWOM based on managerial characteristics (age and gender). Therefore, it is established that: H8: "Hotel characteristics (star rating, location, and type of operation) and managerial characteristics (age and gender) influence the perceived ease of managing eWOM." The source of information to work on these hypotheses was questionnaires (designed in Google Forms) distributed from November 2021 to February 2022 via email, WhatsApp, and Facebook to the hotels in the region. The instrument used begins by requesting general information about the hotel and management (Hotel Name, City, Gender, Age, Type of operation - annual or seasonal) and a question to verify whether they consider eWOM at any stage of the decision-making process. If the response was "YES," they were directed to questions 1 to 34 of Table 1, and if the response was "NO," they were required to the respective questions 35 to 40. Each item is answered using an 11-point Likert scale, from 0 (strongly disagree) to 10 (strongly agree). Before distribution, a database was created by manually extracting information published on the websites of the tourism departments of the Atlantic Coast region’s districts. The constructed database included 721 accommodations with email and phone numbers (in most cases), which reasonably Manuel Gilabert, Maria del Carmen Berné Manero 711 PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 approximates the population of hotels, lodges, and apart-hotels in the region. The respective hotel website URL and Facebook page were also obtained in some cases. In managerial behavior studies, the response rate is expected to be low, as the target population consists of individuals with a high level of responsibility and commitment. A brief explanatory video was recorded to increase confidence and the response rate. The questionnaire was distributed via email, WhatsApp, and through regional hotel associations (FEHGRA and AHT) from November 2021 to February 2022. The response collection period was extended as establishments took time to respond, likely due to the high tourist season. Approximately 10% of the emails resulted in outdated addresses, as evidenced by error messages received from servers (inactive domain, mailbox full, or simply incorrect address). It was also observed that some lessons belonged to non-specific hotel domains (e.g., yahoo.com / Hotmail.com / Gmail.com), and some hotels had automated responses configured for their email addresses. One hotel had configured an automatic response listing room rates for the summer of 2019, which was three years outdated. After the collection process, 120 responses were obtained, representing 16.6% of the available database, a rate higher than that reported in other similar studies: 11% (Brettel et al., 2012), 13.4% (Berné-Manero, Ciobanu, & Pedraja-Iglesias, 2020), and 14% (Torres, 2012). Next, the demographic characteristics of the sample are detailed. Regarding gender, the distribution of responses was balanced, with half of the respondents being male and the other half female. Regarding age, the most frequent segment was 31 to 45 (38%), followed by 46 to 60 (28%). Regarding categorization, the most frequent components were 3-star (32%) and 2-star (28%). There were no responses from 5-star hotels, which aligns with the limited presence of such hotels in the region. It is essential to clarify that the sample is likely biased towards smaller hotels. Regarding the opening scheme, 68 hotels (56%) indicated a systematic closure during the low tourist season. The responses indicate the presence of hotels distributed throughout the region, as shown in Table 2. Approximately one out of every four respondents indicated that they do not consider eWOM in the decision-making process. The main reasons provided to justify this decision were lack of time to read all reviews (42%), followed by the difficulty of pleasing all customers (39%), and the belief that such management will not yield profits (32%). A structural equation modelling (SEM) approach was employed using the partial least squares technique (PLS-SEM). " PLS-SEM has emerged as a technique to analyze the complex relationships between latent variables, allowing for an explanation of observed data and predictive analysis as a relevant element in scientific research. The PLS approach was developed to reflect social and behavioural sciences' theoretical and empirical conditions. The mathematical and statistical procedures are rigorous and robust. Still, the mathematical model is flexible because it does not impose strict assumptions on data distribution, measurement scale, or sample size " (Martínez-Ávila & Fierro-Moreno, 2018, p. 5). According to the mentioned authors, if the key objective is the prediction of constructs, it is advisable to use this technique. Building upon the literature review, a model based on the general Technology Acceptance Model (TAM) (Davis, 1989) was defined, as it is one of the most widely used models to explain the adoption of new technologies and has been tested in various domains. Elements from the eWIP model (BernéManero, Ciobanu, & Pedraja-Iglesias, 2020) were also incorporated, considering the characteristics of eWOM. Additionally, the contextual external variable of the hotel type effect (seasonal vs. annual) was included, which is specific and relevant to this study. Regarding the recommended number of cases for statistically consistent implementation of Partial Least Squares (PLS), Martínez-Ávila & Fierro-Moreno (2018) cite Marcoulides & Saunders (2006), who determine this number based on the relationships within the structural model, as depicted in Table 3. Given that the proposed model has seven relationships between constructs, the recommended minimum number of cases would be 80, a threshold exceeded in the obtained sample. Regardless of those above, it is advisable to interpret the results cautiously due to the sample size. The raw questionnaire data was exported from Google Forms in a format compatible with MS Excel to organize the information for data processing. The SmartPLS 3.3 software was used for statistical calculations related to PLS. The validity and reliability of the measurement model include several steps (Martínez-Ávila & FierroMoreno, 2018). First, the internal consistency reliability of the constructs was reviewed using Cronbach's Alpha (>0.7) and composite reliability (>0.7). Additionally, convergent validity was assessed through Average Variance Extracted (AVE) (>0.5) according to recommended standards (Nunnally, 1994). Indicators with factor loadings less than 0.707 were discarded, as Carmines & Zeller (1979) suggested. To detect potential collinearity issues, it was verified that the Variance Inflation Factor (VIF) was less than 10 (Myers & Myers, 1990) for different items. 712 Hotel Management Behavior Model in eWOM Management PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 Table 1: Elements of the questionnaire Source: Own elaboration. After a purification process (λ<0.7), items marked in italics were excluded from the model. Manuel Gilabert, Maria del Carmen Berné Manero 713 PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 Table 2: Geographical distribution (region) of the responses Region Responses % of total COSTA 21 18% PINAMAR 32 27% VILLA GESELL 29 24% MAR CHIQUITA 2 2% GRAL. PUEYRREDON 32 27% NECOCHEA 4 3% TOTAL 120 100% Source: own elaboration Table 3: Minimum observations in PLS-SEM Número mínimo de observaciones de la muestra Número de relaciones en el modelo estructural 59 3 65 4 70 5 75 6 80 7 84 8 88 9 91 10 Source: Marcoulides & Saunders (2006) Cronbach's Alpha " is an index used to measure the reliability of internal consistency of a scale, that is, to assess the extent to which the items of an instrument are correlated. In other words, Cronbach's Alpha is the average of the correlations between the items that make up an instrument. This coefficient can also be understood as the extent to which some construct, concept, or factor being measured is present in each item. Generally, a group of items that explore a common factor will show a high value of Cronbach's Alpha " (Oviedo & Campo-Arias, 2005, p. 575). Composite Reliability (CR) is recommended to evaluate reliability through internal consistency. It was designed for generic measurement models to overcome the limitation of Cronbach's Alpha, which requires tau-equivalent items. Values between .70 and .79 in CR reflect acceptable levels of internal consistency reliability, indicating that at least 70% of the variance of the measurements or empirical scores in the test is error-free. Similarly, values between .80 and .89 are considered good, and those greater than or equal to .90 are excellent (Cho & Kim, 2015). Next, discriminant validity was reviewed, where the validity of constructs was verified using the Fornell-Larcker criterion. Additional tests were conducted using cross-loadings analysis and the Heterotrait-Monotrait Ratio (HTMT) (Martínez-Ávila & Fierro-Moreno, 2018). The Average Variance Extracted (AVE) indicates the extent to which the construct's variance is explained through the selected indicators (Fornell & Larcker, 1981). The AVE " should be greater than or equal to 0.50 and provides the amount of variance that a construct obtains from its indicators concerning the amount of variance due to measurement error; this means that each construct or variable explains at least 50% of the variance of the indicators " (Martínez-Ávila & Fierro-Moreno, 2018, p. 18). The HTMT ratio is the average of the correlations between indicators measuring different constructs (Heterotrait-Heteromethod correlation, HT) about the average of correlations of indicators within the same construct (Monotrait-Heteromethod correlations, MT). There is discriminant validity if the MonotraitHeteromethod correlations (correlations between indicators measuring the same construct) are more significant than the Heterotrait-Heteromethod correlations (correlations between indicators measuring different constructs). Thus, it is recommended that the HTMT ratio is below one (Martínez-Ávila & Fierro-Moreno, 2018) or below .90 (Henseler, Ringle & Sarstedt, 2015) to demonstrate adequate discriminant validity. 720 Hotel Management Behavior Model in eWOM Management PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 (timeliness, relevance, and excellence) is a relevant aspect that subsequently affects perceived utility. Credibility and authenticity, highlighted in the literature, did not consistently emerge as aspects reflected in eWOM characteristics (items 15 to 21 of the questionnaire with λ<0.7) from a managerial standpoint. In other words, hoteliers associate eWOM with quality information, but not all pay attention to the credibility and authentic source of eWOM. They focus on the importance of the timeliness, relevance, and excellence of eWOM communication, which are more objective factors. At the same time, secondary attention is given to more subjective aspects, such as the credibility of the message and the source. This could indicate a somewhat limited understanding of the potential scope of eWOM and suggests room for future refinement. Additionally, the association between the type of hotel opening and the perceived ease of eWOM management stands out. Annual hotels find eWOM management easier compared to seasonal hotels. Just as it has been found that organizations with year-round operations achieve greater efficiency (Park et al., 2016; Sáez-Fernández, Jiménez-Hernández & Ostos-Rey, 2020), the study's results suggest that differences in eWOM communication management ease exist based on the opening scheme, from a managerial perspective. This could be attributed to year-round hotels having permanent staff for eWOM communication monitoring and more time for response strategy planning. Moreover, they may be more inclined to invest in eWOM management systems (Oliveira, Renda & Correia, 2020), given their yearround operations compared to being open only a few months a year. This circumstance constrains the performance of seasonal hotels and should be considered in their planning. The TAM-EWOM model presents several similarities with the general TAM model (Davis, 1989), particularly concerning the fact that perceived ease and perceived utility affect attitude, which affects intention that subsequently impacts behavior. However, a notable difference is that, particularly in eWOM management, perceived ease does not significantly influence perceived utility. This implies that the management views eWOM as applicable based on its quality, regardless of the ease or resources available for its management. A direct relationship between perceived utility and intention to manage is also absent, instead operating indirectly through attitude. This implies that perceived utility alone does not have a decisive impact on intention. Moreover, in line with the TAM model, external variables affect perceived utility and ease. In this particular case, eWOM quality is a crucial variable influencing perceived utility for management. This finding aligns with the eWIP model (Berné-Manero, Ciobanu, & Pedraja-Iglesias, 2020), where eWOM characteristics impact overall motives for eWOM management. It's worth noting that the eWIP model includes attitude towards eWOM within these motives, while in the TAM-EWOM model, the effect on attitude is first mediated by perceived utility. Finally, concerning the explanatory capacity of performance, the TAM-EWOM model offers a substantial contribution, explaining 64.3% of the construct, a higher ratio compared to the reported 28% in the eWIP model. In other words, the TAM-EWOM model serves as a tool with a high level of explanatory power regarding the acceptance and adoption of eWOM in hotel decision-making and its components, presented in a cause-and-effect sequence. To begin with, it highlights how factors such as experience with the tool and its management, the availability of support resources, and the ever-essential resource of time can determine the level of achieved performance. On the other hand, the emphasis of management on the more objective factors of eWOM (quality) while downplaying the more subjective aspects (credibility and authenticity) is a behavior that warrants attention. As the specialized literature suggests, these are essential characteristics of eWOM communications and are highly relevant from the consumer's perspective. The results also indicate that the hotels in the sample need to be more widely considering the relationship between eWOM management and fundamental customer acquisition and retention marketing strategies. This situation reveals a potential orientation of the industry toward products and sales rather than customer-centricity, a perspective that the industry should reconsider. Lastly, it is noteworthy that annual hotels perceived eWOM management as simpler than seasonal hotels. This circumstance could further reinforce operational and management differences resulting from the distinction between seasonal and year-round accommodations. A limitation in terms of categorizing a hotel as seasonal from this study's standpoint is that the variable's measurement model was dichotomous (annual opening / non-annual opening). While this approach has been adopted in previous research and is reasonable, considering different types of closures during low seasons, spanning various lengths of time, could potentially enhance the models, particularly those involving eWOM volume. Another aspect to consider is that, although the response rate achieved was higher than in other studies, having more extensive and diverse samples from different regions would strengthen the models. Given that the hotel industry holds significant importance for the local economy, both in terms of revenue and employment, it is central to highlight that this work contributes to reflecting on Manuel Gilabert, Maria del Carmen Berné Manero 721 PASOS Revista de Turismo y Patrimonio Cultural. 22(4). Octubre-diciembre 2024 ISSN 1695-7121 opportunities for improvement in a region marked by seasonality. Enhancing the management of organizations within this industry impacts not only the accommodations and their owners but also the employees and their families, the tourist destination where the accommodations are situated, and the regional and national economy. Looking ahead to future research, it would be valuable to explore the specificities of seasonal hotels and their management and the variables that may influence the perceived ease of eWOM management. These could include factors such as the use of integrated management systems, the proportion of customers acquired via booking platforms, or employee characteristics, among other variables. References Acerenza, M. Á. (2003). Gestión de marketing de destinos turísticos en el ambiente competitivo actual. Aportes y transferencias , 7 (2), 43-56. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50 (2), 179-211. Ajzen, I., & Fishbein, M. (1980). 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