Perceived service quality was defined as customers’ overall evaluation of a service based on their past experiences and expectations by [55]. This notion has long been considered one of the key drivers of guest satisfaction, loyalty, and revisit intention in tourism and hospitality. The SERVQUAL scale developed by the same authors, comprises five dimensions: tangibility, reliability, responsiveness, assurance, and empathy. While this structure remains the most widely used framework to evaluate service experiences in every period studied, ongoing changes in service environments have reshaped how service quality is delivered and assessed.

In the current era, when the hospitality industry rapidly adopts digital transformation, the perception and delivery of service are being redefined. Digital innovations such as automated check-in systems, AI-enabled customer service, and smart room systems have significantly transformed guests’ perceptions of service quality, especially in the context of luxury hospitality ([72]). Recent perspectives also underline that AI-driven interfaces redefine service expectations and reshape the perceived quality of guest interactions ([20]). Despite these technological advances, traditional components of service quality, such as face-to-face interaction and personalized service, still maintain their importance ([18]). Maintaining high service standards remains a vital factor in gaining competitive advantage and sustaining loyalty ([8]).

Recent developments in digital service environments have led researchers to further study how traditional service quality frameworks keep up with technological change. Recent studies indicate that the framework requires adaptation due to increasing digitalization. Components such as digital convenience, AI-driven personalization, and data privacy have become increasingly relevant for evaluating modern service experiences ([24]).

[82] found that interactive digital interfaces and virtual hotel previews positively affect perceived service quality by increasing personalization and engagement. Similarly, [9] demonstrated that simulated empathy and responsiveness via metaverse platforms positively influence customer experience. [44] stated that gamification and immersive experiences used in virtual environments create memorable guest journeys. However, these technologies are not positive. [66] raised concerns about data security and user trust, while [58] emphasized technological inequalities and expressed that the digital divide can undermine perceived reliability and fairness in service delivery. As [46] mentioned, digital tools should be enhanced by integrating the emotional and human dimensions of hospitality services but not replaced.

Within this context, many hospitality businesses still aim at enhancing the guest experience by combining technology with human interaction ([44]). [6] found that hotels with high service standards are more successful in maintaining customer loyalty compared to hotels competing fundamentally on price. [5] reported that service gaps in luxury hotels often lead to brand switching and negative customer reviews, while [18] noted the value of personalized, face-to-face service among luxury guests. With the increasing integration of AI technologies, researchers such as [7] and [51] observed that hybrid service delivery and merging technology with authentic human engagement leads to higher guest satisfaction levels than fully automated solutions. Although service delivery continues to evolve, traditional quality frameworks such as SERVQUAL remain applicable ([9]), especially when adapted to include digital touchpoints, AI elements, and privacy concerns have been found effective in evaluating service quality in contemporary environments ([80]).

These technological and experiential shifts raise critical questions about how perceived service quality influences behavioral outcomes in contemporary hospitality settings, particularly revisit intention.

Perceived service quality is a foundational construct in hospitality marketing, widely recognized for shaping customer behavior and loyalty intentions. Rooted in the service quality models of [55] and customer loyalty frameworks by [83], service quality is theorized to influence guests’ future behavioral responses such as satisfaction, recommendation, and repeat visiting.

Empirical findings support this relationship robustly. For instance, [39] revealed that higher service quality at tourist destinations significantly increased visitors’ intentions to return, underlining its role in long-term customer retention. Similarly, [67] showed that restaurant service quality remained a key predictor of repeat visits even during pandemic conditions. In support of this link, [71] highlighted the positive role of technology-enhanced service quality in encouraging repeat visits within food and hospitality settings. However, despite the extensive literature on service quality, few studies have recently tested its influence on revisit intention using updated hospitality contexts ([15]; [20]).

Thus, based on insights from both theoretical frameworks and empirical studies, the following hypothesis is proposed:

H1: Perceived service quality has a positive and significant impact on revisit intention.

Brand equity is a critical factor shaping consumer behavior and particularly leading to loyalty, satisfaction, and revisit intention in hospitality ([1]). Brand equity reflects the value consumers give to a brand and comprises dimensions such as perceived quality, brand awareness, brand associations and brand loyalty ([52]; [27]; [74]). Aaker’s model also includes brand assets like patents, trademarks, and channel relationships ([2]), highlighting the role of consumer perception and loyalty in building sustainable brand value.

While metaverse technologies offer new ways for hotels to engage with guests, brand equity remains central to how consumers utilize these innovations. Even in virtual spaces, guests lean on brand reputation, trust, and emotional ties to navigate new experiences. Brand equity acts as both a cognitive filter and emotional bridge in digitally enhanced hospitality. Recent studies emphasize that brand trust remains central even in virtual hospitality settings ([15]). A guest’s willingness to use services like virtual tours or AI assistants often depends on the trust they place in the brand ([52]; [33]).

Rather than being replaced by technology, brand equity evolves in parallel as it humanizes digital touchpoints and reinforces trust in hybrid or fully virtual interactions. For example, [64] found that strong brand equity fosters favorable post-stay evaluations and electronic customer advocacy, each of which positively influences revisit behavior, especially among digitally active generations. Within the scope of health tourism, [60] emphasized that destination brand equity is a key driver of repeat visits, while [63] demonstrated that sustainable brand identity enhances both brand perception and return intentions among eco-conscious travelers.

As in the past, in recent years, empirical research has further validated the strong correlation between brand equity and revisit intention in hospitality contexts. [3] found that brand equity notably contributes to customer satisfaction and loyalty, especially when reinforced by social media-driven brand engagement. [43] demonstrated that destination brand equity, which comprises awareness, authenticity, and emotional appeal, significantly enhances revisit intentions among international tourists. Likewise, [36] showed that food brand equity positively influences satisfaction and the likelihood of return visits in gastronomic tourism settings. Similarly, [12] confirmed that hotel brand equity, strengthened through value co-creation and relational innovation, plays an essential role in shaping revisit intention by enhancing emotional value and trust.

Therefore, combining theoretical models and empirical findings, it becomes evident that brand equity not only enhances perceived value but also fosters loyalty behaviors such as revisit intention.

Based on this strong conceptual and practical foundation, the subsequent hypothesis is presented:

H2: Brand equity has a positive and significant impact on revisit intention.

Furthermore, brand equity is often considered a result of the service quality perceived by consumers ([35]). A quality service strengthens the perceptions of brand equity, reinforcing trust, satisfaction and brand associations and it is supported long term loyalty ([30]; [68]). Previous studies also show that service quality, especially consistently delivered across integrated touchpoints, can significantly enhance brand equity ([69]). Similarly, both [22] and [32] empirically confirmed that service quality has a significant and positive effect on brand equity. In contrast, [73] did not find a direct relationship between these two variables in the hotel industry and suggested that this link may vary depending on the context or mediating factors.

Taken together, these perspectives highlight the relevance of re-examining the service quality and brand equity link within digitally transformed hospitality environments. Therefore, based on the existing literature, the following hypothesis is proposed:

H3: Perceived service quality has a positive and significant impact on brand equity.

Perceived service quality and brand equity independently influence revisit intention. However, studies addressing how these two variables interact in a causal framework are limited. In the literature, brand equity has been conceptualized as a potential mediating variable that carries the effect of perceived service quality on revisit intention ([47]). This study revealed that service quality indirectly affects revisit intention through brand equity and safety management system.

Accordingly, the following hypothesis is proposed:

H4: Brand equity mediates the relationship between perceived service quality and revisit intention.

To ensure statistical reliability and generalizability, the required minimum sample size was calculated based on the formula suggested by [42], with a 95% confidence interval, 5% margin of error, and a presumed population proportion of 0.5. Based on this calculation, the recommended minimum sample size was determined as 384 respondents. In total, 439 valid questionnaires were obtained by exceeding the required sample size.

The data were collected from guests of the Grand Mosta Hotel & Casino in Bulgaria between October 2024 and February 2025. The hotel, which is known for servicing to high-income and experience-oriented travelers, was purposefully selected to reflect the dynamics of luxury hospitality in a digitally enhanced service environment.

The data collection process employed a convenience sampling technique. Surveys were administered to guests who were available and willing to participate at the time of contact. The hotel’s Guest Relations Department approached guests during their stay, primarily in common areas (the lobby, spa, and restaurant) and invited them to complete the questionnaire by way of face-to-face interview if they had available time and expressed interest. The purpose of the study, anonymity, and data confidentiality were clearly communicated to all participants and informed consent was obtained prior to questionnaire administration.

No personally identifiable information was collected, and no incentives were offered to avoid bias. The study was formally approved by hotel management, though no institutional ethical board review was required due to the non-sensitive nature of the research and the independent status of one of the researchers. The anonymized dataset used in this study has been made openly available via Zenodo ([61]).

The questionnaire consisted of three main scales. Perceived Service Quality was measured using the SERVPERF scale ([55]; [45]), including 22 items across five dimensions: tangibility, reliability, responsiveness, assurance, and empathy. Brand Equity was assessed using a 10-item scale developed by [81], which captures consumer-based brand equity dimensions such as brand loyalty, brand awareness, perceived quality and brand associations. Revisit intention was measured using a 3-item instrument modified from existing research ([83]; [16]), assessing behavioral intention to return, recommend, and prioritize the hotel in future stays.

All scale items were evaluated on a 5-point Likert scale ranging from 1 (“Strongly Disagree”) to 5 (“Strongly Agree”) ([34]). The scale items used in this study adapted from established instruments measuring perceived service quality, brand equity and revisit intention are grouped according to constructs and presented in Table 1.

Table 1. Questionnaire scale items.

*R: Reverse Code.

Figure 1. Conceptual model of the relationships among perceived service quality, brand equity and revisit intention.

This study adopts a conceptual model that examines the effects among perceived service quality, brand equity and revisit intention. Perceived service quality is conceptualized through five dimensions: tangibility, reliability, responsiveness, assurance, and empathy. Brand equity includes four key components: brand loyalty, awareness, associations, and perceived quality. The relationships among these constructs are illustrated in Figure 1.

The collected data was entered into IBM SPSS Statistics software for analysis by being coded. Descriptive statistics, reliability tests, exploratory factor analysis (EFA) and linear and mutual regression analyses were employed to assess the relationships between brand equity, perceived service quality, and revisit intention.

3.3.1. Profile Respondents

A total of 439 guests participated in the survey. The gender distribution was relatively balanced, with 53.5% male and 46.2% female respondents. The sample was predominantly middle-aged and older, with the largest age groups being 39 - 48 (28.2%) and 49 - 58 (25.3%). Educationally, most respondents were well-educated, with 38.5% held a bachelor’s degree and 16.2% having postgraduate degrees. Most participants were either business owners (35.8%) or managers (32.1%). Notably, 62.9% of participants visited the hotel six times or more, reflecting a high level of customer loyalty, as shown in Table 2.

Table 2. Demographic characteristics of respondents (n = 439).

3.3.2. EFA Results of Perceived Service Quality Scale

Given ongoing debates about the SERVQUAL model’s conceptual and sectoral limitations ([49]; [11]), EFA was performed to validate the five-dimensional SERVPERF structure. The Kaiser-Meyer-Olkin (KMO) value (0.970) and Bartlett’s test (χ² = 10129.913, p < 0.01) confirmed the sample adequacy and data suitability for factor analysis.

Although SERVPERF was originally developed as a five-dimensional scale comprising tangibility, reliability, responsiveness, assurance, and empathy, the exploratory factor analysis conducted in this study revealed a two-factor structure. This structure explained 72.129% of the total variance and reflected the specific perceptions of guests in the context of luxury hospitality.

The first factor was labeled “Perceived Reliability of the Hotel and its Staff,” including items from reliability, responsiveness, assurance, and empathy dimensions. The second factor retained “Tangibility” dimension as a separate construct, consistent with its distinct physical attributes (Table 3).

Table 3. Factor loadings of perceived service quality.

T: Tangibility, R: Reliability, RS: Responsiveness, A: Assurance, E: Empathy. *T3 and E2 < 0.70.

Upon reviewing the factor loadings, two items (T3 and E2) had loadings below 0.70 ([38]) and were excluded from further analysis. This decision is consistent with standard practices in EFA, where items with insufficient loadings are typically removed to strengthen construct validity and improve model interopretability ([25]).

3.3.3. EFA results of brand equity scale

EFA was conducted to assess the construct validity of the brand equity scale, which included 10 items across four theoretical subdimensions: brand loyalty, perceived quality, brand awareness, and brand associations ([81]). The Kaiser-Meyer-Olkin (KMO) value of 0.932 and Bartlett’s test of sphericity (χ² = 3081.10, p < 0.01) confirmed the adequacy of the sample and the data suitability for factor analysis.

Although the rotated solution initially suggested a four-factor structure, item loadings were inconsistent with the expected theoretical dimensions due to substantial cross-loadings. In contrast, the unrotated component matrix revealed a coherent unidimensional structure, with many items showing strong loadings above 0.70 on a single factor.

This empirical outcome indicates that respondents may perceive brand equity more holistically, rather than distinguishing between its conceptual dimensions. The decision to operationalize brand equity as a unidimensional construct is supported by research showing that consumers in high-involvement and symbolic service contexts often rely on a holistic brand evaluation rather than assessing individual dimensions separately ([19]). This perspective is particularly relevant in luxury hospitality settings, where experiential, emotional, and symbolic cues converge into a unified brand judgment, thereby justifying the adoption of a single-factor structure in the present study.

Table 4. Component matrix for brand equity.

BL: Brand Loyalty, PQ: Perceived Quality, AW: Brand Awareness, AS: Brand Association. *AS3 < 0.70.

Following established EFA guidelines, items with insufficient loadings or interpretive inconsistency are commonly excluded to enhance structural validity ([48]). Only AS3, a reverse-coded item, showed a weak loading (0.304) and was removed from subsequent analyses due to its low contribution and the impact of respondent fatigue ([57]; [65]). The final unidimensional factor structure demonstrated strong internal consistency (Cronbach’s α = 0.936 seen in Table 5), supporting the scale’s reliability in the context of luxury hospitality settings. The complete factor structure is presented in Table 4.

3.3.4. Reliability Analysis

Cronbach’s alpha coefficients were calculated to assess the internal consistency of the scales. According to the reliability threshold of 0.70 recommended by Cronbach ([50]), all constructs were considered statistically acceptable. The overall Perceived Service Quality scale showed very high reliability (α = 0.974), followed by Brand Equity (α = 0.936) and Revisit Intention (α = 0.904). These results confirm the statistical consistency of the measurement instruments used in this study (see Table 5).

Table 5. Reliability analysis results (cronbach’s alpha).

T3, E2, AS3 excluded due to low factor loadings.

3.3.5. Relationships among Perceived Service Quality, Brand Equity and Revisit Intention

Perceived service quality was strongly correlated with brand equity (r = 0.722, p < 0.01) and moderately correlated with revisit intention (r = 0.492, p < 0.01). In addition, brand equity exhibited a strong positive correlation with revisit intention (r = 721, p < 0.01) shown in Table 6.

Table 6. Pearson correlation matrix.

All correlations are significant at the 0.01 level (2-tailed). N = 439.

3.3.6. Hypotheses Testing

Linear regression analysis was conducted to examine the effect of perceived service quality on revisit intention. The model was found to be statistically significant (F = 139.346, p < 0.001) and explained approximately 24.2% of the variance in revisit intention. Service quality significantly predicted revisit intention (β = 0.492, p < 0.001) (Table 7). Therefore, H1 hypothesis, which proposed a positive and significant effect of perceived service quality on revisit intention, was supported.

Table 7. Results of the effect of perceived service quality on revisit intention.

Dependent Variable: Revisit Intention, PSQ: Perceived Service Quality.

A multiple regression analysis was conducted to evaluate the individual effects of the perceived service quality dimensions “perceived reliability of the hotel and its staff” and “tangibility” separately on revisit intention. The model was statistically significant (F = 80.244, p < 0.001) and explained 26.6% of the variance in revisit intention. Both dimensions had positive and significant effects: reliability (β = 0.281, p < 0.001) and tangibility (β = 0.289, p < 0.001). No multicollinearity issues were detected (VIF = 1.769). These findings confirm that both reliability of the hotel and its staff and tangibility are important predictors of guests’ intention to revisit the hotel (see Table 8).

Table 8. Results of combined effects of PSQ dimensions on revisit intention.

Dependent Variable: Revisit Intention.

Table 9. Results of the effect of brand equity on revisit intention.

Dependent Variable: Revisit Intention, BE: Brand Equity.

A linear regression analysis was performed to assess the effect of brand equity on revisit intention. The model was highly significant (F = 473.234, p < 0.001) and explained 52% of the variance, indicating strong explanatory power. The analysis confirmed that brand equity positively and significantly predicts revisit intention (β = 0.721, p < 0.001). Therefore, Hypothesis H2 was supported (see Table 9).

A linear regression analysis was performed to examine the effect of perceived service quality on brand equity. The model was statistically significant (F = 477.142, p < 0.001) and explained 52.2% of the variance in brand equity. Perceived service quality was found to be a strong and significant predictor (β = 0.722, p < 0.001), indicating that higher service quality is associated with greater brand equity (see Table 10). So, Hypothesis H3, suggesting that perceived service quality positively and significantly affects brand equity, was supported.

Table 10. Results of the effect of perceived service quality on brand equity.

Dependent Variable: Brand Equity, PSQ: Perceived Service Quality.

Given the significant contribution of both brand equity and perceived service quality to revisit intention, as well as the significant impact of perceived service quality on brand equity, brand equity may function as a mediator in this relationship. The mediating role of brand equity was tested using Hayes’s PROCESS macro (Model 4). As demonstrated in Table 11, the indirect effect of brand equity was statistically significant, as the 95% bootstrap confidence interval didn’t include zero. Therefore, it is concluded that brand equity has a full mediating role in the relationship between perceived service quality and revisit intention, and thus, Hypothesis H4 is supported.

Table 11. Hayes PROCESS model 4 results: the mediating effect of brand equity.

Y (Dependent Variable): Revisit Intention, X (Independent Variable): PSQ (Perceived Service Quality), M (Mediator): BE (Brand Equity).

This study makes two important contributions to the theoretical literature. First, the factor analysis of brand equity and service quality scales revealed simplified, empirically validated structures that differ from their classical theoretical dimensions ([55]; [45]). Specifically, brand equity emerged as a unidimensional construct ([81]), while service quality condensed into two core factors: “Perceived Reliability of Hotel and its Staff” and “Tangibility.” This situation points to simpler and more applicable scale structures, especially in the luxury hotel context.

Second, rather than questioning the broader applicability of brand equity as a mediating variable, this study clarifies the specific nature of this mediation in luxury hospitality by demonstrating a full, rather than partial, mediating effect. Contrary to earlier models suggesting partial mediation (e.g., [47]), this research identifies a full mediation that perceived service quality impacts revisit intention only through brand equity. This highlights an underexplored mechanism in high-end service contexts and expands theoretical understanding of brand-driven loyalty formation.

Although there is extensive academic interest in service quality, brand equity, and behavioral outcomes, empirical studies that examine all three constructs simultaneously, especially those treating brand equity as a mediating variable remain limited. This study addresses that gap by presenting a tested mediation model within the context of digitally supported luxury hospitality.

The research demonstrates that while technological transformation continues to reshape service channels, fundamental psychological constructs such as trust, attentiveness, and brand attachment still play a decisive role in consumer decision-making within hybrid service environments. Accordingly, the study not only contributes to the development of empirical theory but also confirms the continued relevance of classical theoretical frameworks in contemporary service contexts.

This study provides important insights for managers into luxury hospitality. First, findings show that brand equity has a stronger impact on guest loyalty than service quality alone. Maintaining high service standards is necessary, but it is not sufficient. Managers should also invest in building emotional brand connections through consistent communication, symbolic brand identity, and personalized guest engagement.

Second, the results highlight two key service quality areas: staff reliability and physical environment. Training staff to be responsive, empathetic, and dependable should be a top priority. As well, maintaining clean, elegant, and functional spaces helps reinforce the guest’s overall impression.

Third, the findings highlight that technology should support, but should not substitute, human interaction in service delivery. Tools like AI assistants, mobile check-ins, or digital concierge services can improve convenience. However, trust, warmth, and personalized service still shape how guests feel about their stay. Technology should enhance these human elements, not overshadow them.

Finally, since brand equity fully mediates the impact of service quality on revisit intention, improving service alone is not enough. Service efforts should be tied to brand strategy. Every positive service experience must also strengthen how guests see and feel about the brand. Coordination between marketing, operations, and guest relations is essential for long-term loyalty.

This study has some limitations. It is constrained by focusing on a single location and having a relatively homogeneous sample. Because the data were collected from a single luxury hotel using convenience sampling, caution should be exercised when generalizing the findings to other hospitality settings or guest segments. Furthermore, since subjective data is used, it is recommended that behavioral tracking methods should be preferred in future studies.

In particular, the existing literature is quite limited in studies examining perceived service quality, brand equity and revisit intention variables within unified model. This gap necessitates a more in-depth investigation of the combined and mediating relationships among these variables. Future studies could also compare traditional, automated, and hybrid service models across different cultural contexts and examine the effects of emotional branding and digital tools on loyalty without undermining human-centered service values.

Besides, future research can also build on these findings by examining novel notions “hybrid service quality” and “hybrid brand equity”, which reflect the integration of human and digital value creation in hospitality experiences. Such models could offer a more realistic understanding of how guests evaluate service and brand relationships in AI-augmented or metaverse-based environments.