Distribution of Brand Love on Customers' Behavioral Intention: Cases of Five-star Hotels

Abstract

Purpose: The study focuses on the distribution of brand love on customers' behavioral intention at five-star hotels in Vietnam. Furthermore, the study also assesses the role of mediating variables and moderating variable involved in the research model. Research design, data and methodology This research surveys 458 customers using the services of five-star hotels in Vietnam through questionnaires on online platforms. Data cleaning and data analysis using SPSS 25.0 software combined with Smart-PLS 3.0 software were used in the research to evaluate the measurement model and structural model. Results: From the results of the structural model evaluation, it shows the positive distribution of brand love on customers' behavioral intentions towards five-star hotels in Vietnam. The mediating roles of brand engagement, brand equity, customer motivation, and the participation of the moderating variable, customer expectations, are determined by this research model. Conclusions: Based on the study results, the distribution of brand love positively affects customers' behavioral intention at five-star hotels in Vietnam, giving recommendations that have a positive impact on customer behavioral intention. In addition, the study shows the role of mediating variables as well as exploring the moderator's (customer expectations) in the distribution of relationships between customer motivation and customer behavioral intention.

1. Introduction

According to the United Nations World Tourism Organization (UNWTO), Vietnam is considered one of the countries with the fastest growth in tourism in the world, with an increasing rate of international tourist arrivals in the year 2019 compared to 2018 is16.2%. Currently, Vietnam has 15, 627 accommodation establishments, of which 178 accommodation establishments are rated five stars according to the Vietnam National Administration of Tourism. Vietnam has attracted many of the world's leading foreign investors in the accommodation business, with a series of luxury hotels and famous global brands. Typically, large corporations can be mentioned, such as: InterContinental Hotels Group-IHG;Accor Group Hotels, Hyatt Group, Starwood Hotels & Resorts, Marriott International, and some well-known domestic corporations also participate in the accommodation service business. The entry of many five-star hotel groups into Vietnam creates favorable conditions for the simultaneous development of this business, but it also creates numerous challenges, such as increasing industry competition. Therefore, increasing competitive advantage and increasing profitability by attracting and retaining customers is always the desire of businesses doing business in this field. To achieve the goal, businesses are constantly building their brands for customers to love. Fournier (1998) showed the importance of love for the brand in the long-term relationship of customers with the brand. And studies on customer behavioral intention help organizations realize that achieving satisfaction is sometimes no longer sufficient to maintain customer loyalty over time (Jones & Sasser, 1995). Instead, managers should implement integrated marketing activities to make the brand of the business loved by customers (Castaño & Eugenia Perez, 2014; Wallace, Buil, & Chernatony, 2014). Because brand love is related to desired organizational outcomes suchas positive customer word-of-mouth (Batra, Ahuvia, & Bagozzi, 2012), which increases brand loyalty (Carroll & Ahuvia, 2006), or willingness to pay a premium price (Thomson, Maclnnis, & Park, 2005; Bauer, Heinrich, & Albrecht, 2009).

Furthermore, Verma (2021) indicated that the relationship has a positive impact on brand love for overall brand equity as well as behavioral intention. Jiang, Li, Liu, andChang (2017) also argued that brand equity has an impact on customers' behavioral intention, with customer motivation as the mediator and customer expectation as the moderator role. Zhang, Li, Liu, Shen, and Li (2020)also contributed that customer motivation is the mediator in the relationship between the positive impact of brand equity and customer behavioral intention. Brand equity has been shown to have an impact on customer behavioral intention in the tourist and related industries (Liu, Wong, Tseng, Chang, & Phau, 2017; Phung, Ly, & Nguyen, 2019). On the other hand, brand love has also been shown to have a positive impact on customer brand engagement (Junaid, Hou, Hussain, & Kirmani, 2019).

The studies reviewed highlight the distribution of brand love on customers’ behavior intention, particularly in the tourism and hospitality industries. However, there are limited studies on the distribution of brand love on customers’ behavioral intention and mediating factors including brand engagement, brand equity, and customer motivation. So, considering the distribution of brand love on behavioral intentions such as word-of-mouth, revisit, or willingness to pay/willingness to pay a premium price is especially important in the context of the research, which is a five-star accommodation service, a high-class service. The study focuses on the distributionof brand love on customers’ behavioral intention and mediations, such as brand engagement, brand equity, and customer motivation. The findings will be used to assess the role of mediating variables in the distribution of brand love and its impact on customers’ behavior intention.

The study also considersthe moderating effect of the moderator on customer expectations and how it affects the relationship between consumer motivation and customers’ behavioral intention. Based on the results of a study on the distribution of brand love on customers’ behavioral intention in a five-star hotel in Vietnam, recommendations were made to assist managers in building brands and increasing brand love and brand equity in the hospitality industry.

2. Literature Review

2.1. Brand Love and Brand Equity

The concept of brand love is based on Sternberg’s (1986) love triangle theory, which includes three main components: intimacy, passion, and decision or commitment. According to Carroll and Ahuvia (2006), the positive impact of brand love has on brand loyalty. Research by Sallam and Wahid (2015) in insurance services shows that brand love has a positive impact on brand loyalty and brand equity. According to Aaker (1996), brand loyalty is also a component of brand equity. According to research by Otero and Wilson (2018), brand love has a positive impact on brand equity and has a positive effect on consumers’ repurchase intention. Verma (2021) indicated that brand love also has a positive impact on overall brand equity. Hence, based on some previous studies that are suitable for the context of this study, the research hypothesis is proposed as follows:

H1: Brand love positively affects brand equity.

2.2. Brand Love and Brand Engagement

According to Hollebeek, Glynn, and Brodie (2014), the concept of brand engagement is defined by related elements such as cognitive, affection, and activation. Based on research by Junaid et al. (2019), brand lovehas a positive impact on brand engagement. Extensive study on the mediating effect of brand love on components of brand engagement De Oliveira Santini, Ladeira, Sampaio, and Pinto (2018); Maxian, Bradley, Wise, and Toulouse (2013) showed that brand love has a positive impact on brand engagement. Therefore, in this study, the following hypothesis is proposed:

H2: Brand love positively affects brand engagement.

2.3. Brand Engagement and Brand Equity

As stated by Dwivedi’s (2015) study on brand engagement and customer brand loyalty, the research results demonstrate that brand engagement affects brand loyalty, and according to the analysis considered from the management perspective of the above study, brand engagement has a positive impact on brand equity by improving customer loyalty to the brand. Verma (2021) contributes to demonstrating the positive impact of brand engagement on overall brand equity. Especially in the field of hospitality research, results from Rather, Sharma and Itoo (2018) suggested that brand engagement has a positive impact on brand equity. Based on the previous studies reviewed and the research context in hospitality, this study proposes the following hypothesis:

H3:Brand engagement positively affects brand equity.

2.4. Brand Equity and Customer Motivation

According to tourism and hospitality research, destination brands influence customer expectations, motivations, and travel intentions Sartori, Mottironi, and Corigliano (2012). Bianchi, Pike, and Lings (2014) also concluded that a positive brand increases brand equity and customer motivation in using services and products. According to Jiang et al. (2017), brand equity has a positive effect on customer motivation and behavioral intention. Therefore, based on the results of some previous studies and the relevance in the context of hotel service industry research, the research hypothesis is proposed as follows:

H4:Brand equity positively affects customer motivation.

2.5. Brand Love andBehavioral Intention

Based on Sternberg’s (1986) love triangle theory paradigm, research in hospitality was conducted. The intimacy and harmony between customers and brands, according to Alnawas and Altarifi (2016); Wang, Qu, and Yang (2019), “passion” indicated the enthusiasm and enthusiasm of the customer-brand relationship and was sometimes the driving force behind client acquisition. Decision/commitment come from an individual's perceived decision regarding interpersonal relationships. The decision is considered based on short-term preference and the commitment to maintain that love in the long term, which means in relation to some of the customer's behavioral intention towards the brand.

According to research by Carroll and Ahuvia (2006); Albert et al. (2009); Batra et al. (2012), brand love has a strong impact on word-of-mouth intention for the brand that customers love. According to a study by Ismail and Spinelli (2012), by building an emotional relationship with customers such as the customer’s love for the brand, it will help stimulate positive word-of-mouth about the brand that customers love. According to Albert and Merunka (2013), Fetscherin and Mark (2014)showed that brand passion, a component of brand love, has a positive impact on customer word-of-mouth intentions. Sarkar (2011)has proven that when customers have love for brand, customers will say positive things about the brand to others, which helps to increase the spread of the brand in the market. Brand love can lead to positive brand interactions, increasing customer word-of-mouth intentions for the brand (Bergkvist & Bech- Larsen, 2010; Wallace et al., 2014). Based on some previous studies that were reviewed in accordance with the research context in the hotel service industry, the study hypothesis is proposed as follows:

H5a:Brand love positively affects customer word-of-mouth intention.

According to research by Thomson, Maclnnis, and Park (2005); Albert, Merunka, and Valette Florence (2009), brand loyalty is the result of brand love. Brand loyalty includes customers’ behavioral intention to repurchase products or services from the brand with their favorite customers. Thus, it can be seen that brand love positively affects the intention to repurchase products or services. Fetscherin and Mark (2014)also proved that brand love positively affects brand loyalty, which is associated with the intention to revisit services. Batra et al. (2012); Loureiro and Kaufmann (2012)suggested that the intention to repurchase a product/service was an expression of loyalty towards a favorite brand. Carroll andAhuvia (2006) has shown that brand love positively affects the intention to revisit products/services. Bıçakcıoğlu, İpek, and Bayraktaroğlu (2018); Turgut & Gultekin (2015)demonstrated that brand love affects customers’ revisit intention. Hence, this study proposes the following hypothesis:

H5b:Brand love positively affects customers' intention to revisit.

Brand love makes customers interested in maintaining their relationship with the brand (Batra et al., 2012). The relationship between customers and brands affects willingness to pay premium price because of the emotional commitment between customers and their favorite brands (Albert & Merunka, 2013). Thomson, MacInnis, and Park (2005); Kim, Kim, Jolly, and Fairhurst (2010)supposed that if brand love increases over time, then customers are willingness to pay premium prices for some brands that customers love. Han and Choi (2019) considered the intention to revisit products and services, as well as the willingness to pay at a higher price, to be important components of customer loyalty to the brand. Therefore, brand love affects the willingness to pay at premium prices, and this statement is also true with the research results of Albert and Merunka (2013). The studies reviewed in accordance with the research context of the hotel service industry form the basis for this study to propose the following hypothesis:

H5c:Brand love positively affects customers’ intention willingness to pay a premium price.

2.6.Customer Motivation and Behavioral Intention

The concept of customer motivation is based on the theoretical framework of “push”and “pull”by Dann (1977). Gunasekaran and Anandkumar (2012) suggested that customer motivation for different types of accommodation is a “pull” factor. According to an empirical study on tourism by Lee (2009), the relationship between motivation and future behavior of tourists indicates a conceptual framework in which future behavior is positively influenced by customer’s motivation. Baloglu (2000)demonstrated that motivation was the most important attribute included in the theoretical framework used to help predict the behavioral intentions of tourists. Thepositive impact of motivation on tourists' behavioral intentions was demonstrated by the studies of Yoon and Uysal (2005); Jang and Feng (2007)in the tourism field.

Besides, studies on tourism and hotel services also shown that customer motivation had a positive impact on customers’ behavioral intention (Gómez, Lopez, & Molina, 2015; Horng, Liu, Chou, & Tsai, 2012).In addition, Jiang et al. (2017) in the tourism field also showed that customer motivation had a positive effect on customer behavioral intention and this effect was moderated by customer expectations. Based on the Theory of Planned Behavior (TPB) of Ajzen (1991) and Zeithaml, Berry, and Parasuraman (1996), the behavioral intentions to be considered include: intention to revisit the service, word-of- mouth intention, willingness to pay premium price. Based on previous studies on customer motivation and customer behavioral intention in accordance with the research context, the proposed research hypothesises areas follows:

H6a:Customer motivation positively affects customers’ word-of-mouth intention.

H6b:Customer motivation positively affects customers’ intention to revisit.

H6c:Customer motivation positively affects customers’ intention willingness to pay premium price.

2.7.Moderator: Customer Expectation

The concepts of motivation, expectations, and behavioral intention are related in this study, which is based on two theoretical frameworks: Ajzen’s (1991) theory of planned behavior (TPB) and Gnoth’s (1997)research on motivation, expectations, and attitude. Gnoth (1997) showed that the three concepts of motivation, expectations, and attitude are related to each other and need to be considered holistically. Expectations modulate the relationship between travel motivation and behavioral intention. Gnoth (1997) suggested that expectations determine the perception of tourism products, services, and experiences and can help tourists classify the attitude, activities, and attractions of a destination. Hsu, Cai, and Li (2010)demonstrated that the related relationships between expectations and motivation facilitate the discussion of expectations, customer motivation, attitude and behaviroal intention. According to Huang and Hsu (2009)suggeted that expectation improve tourists’motivation to satisfy their psychological/biological needs, encouraging feelings, attitude, and behavioral intention.

According to Kincaid, Baloglu, Mao, and Busser(2010), argued that managers should understand and meet customer expectations effectively to improve competitive advantage and influence customers' intention to revisit. Harrington, Ottenbacher, and Kendall (2011) in the food service field showed that expectations were one of the most important factors affecting the frequency of revisit for food service by diners. Wong and Dioko (2013)indicated through the study that the level of customer expectations can regulate perceived performance and customer satisfaction. Ryan and Cliff (1997); Yi and La (2004); Kincaid et al. (2010) supposed expectations of customer behavior. In particular, Devlin, Gwynne, and Ennew (2002); Wong and Dioko (2013) proposed that customer expectations are one of the moderating variables affecting the customer decision making process. According to Jiang et al. (2017) in culinary tourism, confirmed that customer expectations are a moderating variable that affect the relationship between motivation and customer behavioral intention. Based on the research backgroundand the review of previous studies, the proposed research hypothesis is as follows:

H7a: Customer expectations moderate the relationship between customer motivation and word-of-mouth intention.

H7b: Customer expectations moderate the relationship between motivation and the intention to revisit.

H7c: Customer expectations moderate the relationship between customer motivation and willingness to pay premium price.

Figure 1: The proposed research model.

3. Methodology

3.1. Research Design

Research combines techniques in qualitative and quantitative research. In the first phase, the research is carried out based on a brief overview of some background studies and previous studies to serve as a theoretical framework for developing research hypotheses. Based on the theoretical framework and research context, the preliminary scale was given. In the second phase, qualitative research was carried out by conducting in-depth interviews with three experts in the hospitality industry. The observed variables of the scales are adjusted based on the results of experts' recommendations to match the model and research context of five-star hotels in Vietnam.After conducting in depth interviews with experts, the scales were converted into a questionnaire and sent to 10 customers to conduct a survey and group discussion. The customer survey was to check the reliability of the scales as well as the structure of the research model. Screening questions, statements of scales adopted from the literature, and demographic questions were all included in the questionnaire. Respondents used a 5-point Likert scale to rate their agreement or disagreement with the statements, with 1 being completely disagree and 5 being completely agree. The scale includes eight latent variables that are referenced from related previous studies. The brand love scale from Carroll and Ahuvia (2006); the brand engagement scale is a structural scale that is referenced from Hollebeek et al. (2014) and includes three components: cognitive, affection, and activation; theo overall brand equity scale is referenced from Yoo and Donthu (2001); the customer motivation and word-of-mouth scales form Hyun and Perdue (2017); the customer expectations scales from Li, Lai, Harill, Kline, and Wang (2011); the revisit and willingness to pay premium price scales from Lee, Hsu, Han, and Kim (2010).

After discussing scales with experts who work in five star hotels and have more than 7 years of experience at the level of chief or deputy manager, the scales were reinforced with some observable variables. Some of the statements are also related to the overall brand equity scale’s brand image and brand awareness elements. In particular, statements related to the customer policy and the hotel’s location are also included in the statements of the customer motivation scales. The customer expectation scales now include statements about the elements that grasp customer psychology. The scales built in the study are based on eight latent variables with 40 observable variables.

Collecting, processing data, and testing research hypotheses in the third phase based on the obtained research results combined with in-depth interviews with experts for the second time to make recommendations based on the research results.

3.2. Data Collection

The questionnaire was sent to customers who have been using five-star hotel services in Vietnam, including Vietnamese and foreign customers. Surveys are conducted through online platforms. After conducting the survey, having obtained 458 valid surveys that were included in the analysis for the study. With the above sample size suitable and reliable enough to perform multivariate analysis according to Hair, Black, Babin, Anderson, and Tatham (2006).

3.3.Data Analysis

Combined use of SPSS 25.0 and Smart PLS 3.0 software to perform data analysis in this study. After data collection, cleaned the data as well as performed sample description and description of observable variables through SPSS 25.0 software. PLS-SEM (Partial Least Square Structural Equation Model) was applied. Because PLS-SEM effectively applies to models with mediating variables and containing moderating variables, it helps to support estimates for structurally complex estimation models (Hair, Hult, Ringle, and Sarstedt, 2021). The PLS-SEM is consistent with the research model proposed in this study.

4. Results

The examination of descriptive statistics (Table 1) showed that in the research sample, there was a higher percentage of females (about 54.8%) than males (about 45%) and others (about 0.2%). Most of them have college/ university degree (about 66.6%) and postgraduate (about 24.7%). The samplecomposition is relatively young, with 56.2% under 35 years old and 25.5% between 35 and 46 years old. The income group with more than 200 million Vietnamese Dong has the highest proportion (about 38.9%), accounting for over one-third of the total sample size.

Table 1: Descriptive statistics

Note: 1 million VND ≈ USD 44 (as of February 2022)

4.1.Measurement Model Evaluation

In this study, the measurement models used include formative measurement model and reflective measurement models. The latent variable of brand engagement is measured by the formative measurement model. To evaluate the accuracy of convergence, it is necessary to apply the technique of “redundancy analysis” proposed by Chin (1998). According to this analysis technique, a single indicator measurement model is used as the dependent variable.

The regression value of the path in the model of “redundancy analysis”should have the regression value of the path ≥ 0.708 or R²≥ 0.5 (Hair et al., 2021). According to the analysis, the result R²= 0.512 achieves the exact level of convergence and evaluates the degree of multicollinearity through the VIF index (Outer VIF value). All indicators have a VIF < 5, indicating that the formative measurement model does not have multicollinearity. Using bootstrapping to evaluate the statistical significance of the variables other than P-value=0.00 (P-value<0.05). The formative measurement model for the latent variable of brand engagement has a high degree of convergence accuracy, no multicollinearity, and the external weight values are statistically significant and adequate for the next step of analysis.

According to Hair et al. (2021), latent variables are measured by the reflective measurement model after assessing the reliability of each indicator using the Factor Loading coefficient λ ≥ 0.7. Because the factor loading was less than 0.7, BE4 and BE5 were removed from the measurement model in this study. According to Fornell and Larcker (1981), internal consistency is assessed by the Composite Reliability index (CR)> 0.7. In this study, the CR indexes are all higher than 0.8, indicating that the measurement model achieves internally consistent reliability. Assessing the accuracy of convergence by Average Variance Extracted (AVE) ≥ 0.5, in this study, the AVE index is higher than 0.6, showing that the measurement model achieves the convergence accuracy. The results are shown in Table 2.

To evaluate the discriminant validity of each construct in the proposed measurement model by Henseler, Ringle, and Sarstedt (2015), the HTMTij values were < 0.9 (Table 3). After conductingthe measurement model evaluation steps BE4, BE5, WOM3, and RV1, the indicators have been removed from the measurement model. The observed variables were suitable to proceed to the next step of structural model evaluation.

Table 2: Validity and Reliability Analysis

Note: Std. Dev.: Standard deviation; X Hotel is a five-star hotel those customers have used or are using.

Table 3. Discriminant validity- Heterotraint-Monotraint Ratio (HTMT)

4.2.Construct Model Evaluation

When evaluating the structural model, consider evaluating the VIF coefficient (Inner VIF) to assess whether multicollinearity occurs. In this research, the VIF coefficients from 1.00 to 2.06 are all less than 3. Therefore, there is no multicollinearity in the structural model.

Bootstrapping was performed with 5, 000 samples to examine the significance of path regression coefficients this study considers the P-value ≤ 0.05, the impact level is statistically significant (Hair et al., 2021). According to the analysis results of Table 4.

Table 4.Path Analysis Results

Note: Reg. Coeff.: Regression coefficients; Std. Dev.: Standard deviation; * <.05, ** <.01, *** <.001

The analysis results show that hypotheses H1, H2, H3, H4, H5a, H5b, H5c, H6a, H6b, H6c, and H7a were supported. Hypotheses H7b and H7c were rejected.

When considering the distribution of brand love on customers’behavioral intention, in addition to the direct distribution of brand love on customer behavioral intention, there are also indirect distributions of brand love on customer intention through mediating variables such as brand engagement, brand equity, and customer motivation. The level of indirect contribution of partial mediation variables is expressed through the VAF (Variance Accountedfor Value) index. The VAF index is calculated based on the original sample recommended by Hair et al. (2021). From the calculated VAF, the role of mediation variables is partly: contributing 33.3%to the distribution of brand love on the word-of-mouth intention; contributing an indirecteffectof 21.5% to the distribution of brand love on customers’intention to revisit hotel services; contributing a 22.9% indirecteffect to the distribution of brand love on willingness to pay a premium price. According to the analysis results of Table 5.

Table 5.VAF Index Analysis

Note: * <.05, ** <.01, *** <.001

Customer motivation has an effect on customer word-of- mouth intention. The effect of customer motivation on customer word-of-mouth intention is influenced by the moderating variable, which is customer expectations. Customer expectation negatively moderates the effect of customer motivation on the customers’ word-of-mouth intention (β = -0.08, p = 0.05). According to Cohen (2013), the moderator variable customer expectation moderates the relationship between customer motivation and word-of- mouth intention with f2 = 0.02, which is assessed to have a small explanatory contribution.

Table 6. Moderator Analysis

Note: * <.05, ** <.01, *** <.001

Figure 2: The moderator's Simple Slope Analysis

5. Discussion

The results of this study showed that brand love had distribution on customers’ behavioral intention, such as word-of-mouth intention (β=0.30, p=0.00), revisit intention (β=0.40, p=0.00), and willingness to paypremium price (β=0.37, p=0.00). This study's result is also supported by some previous studies Carroll and Ahuvia (2006); Kim, Kim, Jolly, and Fairhurst (2010); Batra et al. (2012); Ismail and Spinelli (2012); Albert and Merunka (2013); Fetscherin and Heinrich (2014); Kwon and Mattila (2015); Turgut and Gultekin (2015); Bıçakcıoğlu et al. (2016); Liu, Wang, Chiu, and Chen (2018); Han and Choi (2019); Shen, Huang, Choi, and Morrison (2021). Furthermore, through mediation variables such as brand equity, brand engagement, and customer motivation, brand love had a distribution on customers’ behavioral intention. This mediating role is estimated to contribute 33.3% of the brand love distribution on customers’ word of mouth intention, 21.5% of the brand love distribution on customers’ revisit intention, and 22.9% ofthe brand love distribution on willingness to pay premium price.

The study’s results also show the moderator role of the customer expectation in the impact relationship between customer motivation and word-of-mouth intention. This is also supported by Jiang et al. (2017). However, Jiang et al. (2017) suggested that customer expectation positive moderation impactedon the relationship between customer motivation and customers’ behavioral intention, specifically word-of-mouth. However, in this study, the moderator of customer expectations had a negative impact on the relationship between customer motivation and customer word-of-mouth intention (β= -0.08, p=0.05). This can be explained because the services of 5-star hotels have their own characteristics of high-class services. “Star rating”is also a component that affects customer perception as well as customers’ behavioral intention. Because, according to Israel’s (2002) research, “star rating”has an influence on customer expectations; the higher the star rating, the higher the customer expectations. Moreover, the level of customer expectation affects customer perception, and the level of customer satisfaction affects customers’ behavioral intention Wong and Dioko (2013). From previous studies and the results of this study, it is shown that the higher the customer expectation for the service of a five-star hotel, the impact of customer motivation on word-of-mouth intention tends to decrease.

6. Conclusions

Some recommendations were offered to develop positively affect customers’behavioral intention at five-star hotels in Vietnam based on the results of the distribution of brand love on customers' behavioral intention. Hotels should build a good service process that brings customer satisfaction by developing a set of service process standards for each hotel brand. In addition, hotels should consider training staff in the service process to adapt to the changing environment and current trends, especially during the period when the COVID-19 epidemic has seriously affected Vietnam from 2019 to 2022. So, it shows that there is a need for a change in the service process to ensure the health and safety of customers during the epidemic season and satisfy customer needs when using services at the hotel. Five-star hotels also consider building a separate index to assess the customer's love for the brand, so that from this index, it will form the basis to evaluate a part of the customer’s brand love. Hotels could pay more attention to bringing joy to customers when using services at the hotel by training staffs on customer psychology based on psychological insights to create joy for customers when using services at the hotel and applying more technology to a number of steps in the customer service and customer support process.

Aside from that, the study contributes some recommendations to help positively affect customers’ behavioral intentions at five-star hotels in Vietnam, which are indirectly affected by brand engagement, brand equity, and customermotivationas a result of the distribution of brand love on behavioral intention. Hotels should consider creating links to help support the connection of customers with the hotel brand through websites and applications with beautiful interfaces and easy customer interaction. Five-star hotels need to meet customers’ expectations in terms of facilities, meet the requirements of hygiene and safety standards, and have a convenient location while ensuring good security, meeting good service quality, staff grasping customer psychology well, and having a good price policy for loyalty customers. Service quality must meet five-star standards, and customer service should be deserving of the value of the customer’s payment. Brand promotion activities must be closely linked to the establishment, image, and quality of the hotel honestly to avoid creating too high expectations from customers for the five-star hotel’s services.

Like any other study, this one has limitations. Because the survey was conducted during the COVID-19 pandemic, the number of international customers using five-star hotel services was not as equitably distributed as it hadbeen before the pandemic. So, futures can be done with other methods, such as time series data, so that the results are more generalizable. In addition, future research on customer expectations needs to include multi-group analysis of domestic and international customer groups to see how cultural differences affect customers’behavioral intentions.