Exploring Determinants and Theoretical Underpinnings of Revisit Intention in Tourism: A PRISMA-Based Systematic Literature Review

Abstract

This study aims to identify the variables that influence revisit intention and the theories most frequently employed in related research. This research adopts a systematic literature review (SLR) following the PRISMA 2020 guidelines, encompassing the identification, screening, and synthesis of articles from the Scopus, ScienceDirect, and Emerald databases. The results indicate that customer satisfaction, destination image, experience, and service quality emerge as the most dominant variables. At the same time, constructs such as electronic word-of-mouth (e-WOM), place identity, and accessibility receive comparatively little scholarly attention. Moreover, the Theory of Planned Behavior constitutes the most commonly applied theoretical framework, followed by the stimulus-organism-response (SOR) model, the Theory of Reasoned Action (TRA), and Cognitive Appraisal Theory. These findings reveal research gaps that provide a foundation for future conceptual model development. The study offers both theoretical and practical contributions toward strengthening strategies for fostering tourist loyalty.

1. Introduction

In the highly competitive hospitality industry, efforts to foster tourists’ revisit intention have become a crucial strategy for sustaining business viability and enhancing profitability. Revisit intention not only reflects the level of satisfaction with previous lodging experiences but also represents a post-consumption behavior that directly influences customer loyalty [1,2]. Moreover, Gregoriades et al. [3] emphasize that revisit intention serves as a key performance indicator for hotel businesses, particularly in navigating the economic uncertainties caused by the COVID-19 pandemic, which significantly reduced global tourist mobility. Prior studies also reveal that tourists with a strong intention to return tend to demonstrate higher consumption engagement, longer stays, and a greater likelihood of engaging in positive word-of-mouth communication, which can enhance the hotel’s reputation [1,4]. Therefore, promoting revisit intention is not only essential for improving customer retention rates but also constitutes a strategic foundation for sustainable growth in a dynamic hospitality landscape.

From a conceptual perspective, revisit intention is not a singular construct but a multidimensional one. It can be understood as motivational (the reasons that drive tourists to return, such as emotional attachment or cultural curiosity), intentional (the expressed willingness or plan to revisit), and behavioral (the actual decision or action to revisit) [5,6]. This differentiation highlights that revisit intention extends beyond mere loyalty, encompassing both cognitive evaluations and affective commitments.

The literature further shows nuanced definitions. For example, Braimah [7] frames revisit intention as a probability assessment of returning, emphasizing a rational-evaluative stance, whereas Ibrahim et al. [5] conceptualize it within a stimulus–organism–response framework, linking social media engagement to behavioral outcomes. Meanwhile, Khasawneh and Alfandi [6] view revisit intention as intertwined with risk perception and overall destination image, stressing contextual vulnerability. Nguyen et al. [1] highlight the role of post-visit experience evaluations and emotional attachment in predicting revisit decisions. Taken together, these perspectives suggest that revisit intention is not merely an “indicator of satisfaction and loyalty,” but a dynamic construct situated at the intersection of cognitive judgments, emotional responses, and contextual influences. This theoretical divergence provides the foundation for the present study, which seeks to synthesize fragmented insights and clarify how antecedent factors shape tourists’ revisit decisions.

Research on revisit intention holds significant importance, particularly in the context of developing marketing strategies and ensuring the sustainability of the hospitality and tourism industries. Revisit intention is regarded as a key indicator of a destination’s or hotel’s success in retaining tourists, as returning visitors typically exhibit longer stays, higher levels of consumption, and a greater propensity to provide positive recommendations through word-of-mouth [1,4]. In addition, strengthening revisit intention contributes to marketing cost efficiency, as retaining existing customers is generally more cost-effective than acquiring new ones [1,8]. Furthermore, Gregoriades et al. [3] underscore that in times of uncertainty, such as during the COVID-19 pandemic, the ability to retain tourists with a strong revisit intention becomes a critical factor for maintaining business continuity and stability. Therefore, understanding the determinants, mechanisms, and consequences of revisit intention is an essential academic and practical endeavor for optimizing the sustainable performance of destinations and accommodations.

The growing number of studies on revisit intention over the past decade highlights that this topic has become a central focus in tourism and hospitality research. Numerous studies have examined revisit intention from various perspectives, including antecedent factors [2,9,10], customer loyalty [11,12], and the role of social media in shaping return visit decisions [5,12]. However, the diversity of theoretical approaches, variations in operational definitions, differences in identified dimensions, and inconsistencies in determining antecedent factors have led to fragmentation in the academic understanding of this variable. Therefore, a comprehensive systematic literature review (SLR) is needed to identify, classify, and synthesize the various antecedent variables and theories used in revisit intention research. Through the SLR approach, this study aims to produce a more structured conceptual mapping that not only enriches academic discourse but also provides a clearer direction for future research.

Although research on revisit intention has evolved across various tourism contexts, existing studies reveal several limitations that need to be addressed. Alawneh et al. [13] focus solely on cultural and heritage tourism in Jordan, without comprehensively examining the definition, dimensions, antecedents, and theoretical foundations of revisit intention within the hospitality industry. However, the cultural-tourism focus of this study limits generalizability to broader hospitality contexts where factors such as service quality and destination branding play a greater role. Similarly, Dhewi et al. [14] limit their scope to heritage hotels, thus excluding revisit intention in more general hotel and tourism area contexts that encompass a wide range of modern accommodation types. The emphasis on heritage hotels highlights factors specific to historical and cultural experiences, which differ from determinants relevant in mainstream hotels. Meanwhile, Ramadan and Kasim [15] explore motivational factors using the push-pull theory within MICE destinations, but fail to provide a comprehensive analysis of the conceptual structure of revisit intention, including its definitions, dimensions, antecedents, and underlying consumer behavior theories. These studies focus on whether cultural tourism, heritage hotels, or MICE events offer valuable but narrow insights that cannot be directly generalized to broader hospitality and tourism contexts. For example, cultural or heritage settings often involve stronger identity-based motivations, while MICE destinations emphasize functional and event-related drivers. This contextual fragmentation underscores the lack of an integrated theoretical approach that explains revisit intention across diverse tourism environments. In response to these gaps, the present study offers a novel contribution by conducting a systematic literature review to identify, classify, and synthesize the antecedents and theoretical foundations of revisit intention within the broader context of the hotel industry and tourism areas. This approach aims to develop a comprehensive conceptual mapping of revisit intention, thereby enriching the academic literature and offering practical contributions to the development of marketing strategies in hotels and tourism destinations.

2. Literature Review

2.1. Revisit Intention

Revisit intention refers to a tourist’s behavioral intention to return to a specific destination in the future as part of their post-consumption experience [1]. Generally, this intention reflects a conscious decision by tourists regarding the likelihood of revisiting the same destination based on their previous travel experiences [6]. Additionally, revisit intention also encompasses the desire to recommend the destination to others, serving as a form of social endorsement for the place visited [16]. In the tourism industry, such behavior is particularly significant, as it is believed to strengthen business growth and enhance destination competitiveness [17]. However, it is important to note that revisit intention represents only an intention, not a guarantee of actual behavior. Manyangara et al. [2] show that although intention often predicts loyalty, external factors such as economic conditions, health concerns, or competing destinations can prevent it from turning into action. Thus, rather than assuming a direct causal chain, revisit intention should be viewed as a proximal indicator that may influence but does not automatically determine long-term loyalty and destination competitiveness.

2.2. SLR PRISMA

A Systematic Literature Review (SLR) is a methodological approach designed to identify, evaluate, and synthesize all relevant evidence related to a specific research question in a systematic, transparent, and replicable manner. SLR distinguishes itself from traditional literature reviews by employing predefined protocols for article search, selection, and analysis, thereby minimizing bias and enhancing the credibility of research outcomes [14,18,19]. In line with this approach, Górska-Warsewicz and Kulykovets [20] emphasize that SLR serves as a critical tool for integrating findings from multiple studies, allowing researchers to identify trends and research gaps and to build a stronger theoretical foundation. By adhering to the principles of systematicity and reproducibility, SLR requires the formulation of clear inclusion and exclusion criteria, the use of comprehensive database-driven search strategies, and explicit documentation of the selection and data extraction processes [21]. Therefore, SLR is not merely a summary of existing literature but a critical synthesis that contributes to the advancement of theory and practice in the studied field.

To ensure quality and transparency in the implementation of a Systematic Literature Review (SLR), the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method serves as the widely adopted primary guideline by Page et al. [22] and Page et al. [23]. PRISMA provides a structured framework consisting of four key stages, identification, screening, eligibility, and inclusion, each designed to minimize bias and enhance the validity of findings [18,21]. This rigor is particularly important in tourism revisit intention research, where prior studies are fragmented across diverse contexts (e.g., heritage hotels, cultural tourism, or MICE destinations) and often use varying definitions and measures of revisit intention [13,14,15]. By applying PRISMA, researchers can transparently document inclusion criteria and study selection, making it possible to compare heterogeneous findings and reveal conceptual gaps that are otherwise obscured. As such, using SLR combined with PRISMA is not only methodologically robust but also uniquely suited to synthesizing dispersed tourism research into a coherent framework.

3. Methodology

The study selection process in this systematic literature review follows the stages outlined by the PRISMA 2020 guidelines (Supplementary Materials), as developed by Page et al. [22] and Page et al. [23]. PRISMA 2020 ensures that the identification, selection, and inclusion of studies are carried out in a systematic, transparent, and replicable manner. To synthesize the findings from the selected articles, this study adopts a narrative synthesis approach. The synthesis involves a comprehensive reading of each article to identify antecedent variables that positively influence revisit intention. These findings are then systematically documented and summarized in tabular form to present a clear and organized overview of the relationships identified in previous research. In addition, this study also includes bibliometric outputs, namely the most relevant author and co-occurrence network, to provide a broader mapping of influential researchers and conceptual linkages in the field. Each stage of the process is described as follows:

3.1. Identification

Within the PRISMA 2020 framework, the identification stage seeks to collect all potentially relevant records from databases or other sources, representing the total number of documents retrieved prior to screening. In this study, the identification process relies exclusively on the Scopus, ScienceDirect, and Emerald databases, using the following keywords: “revisit intention” OR “re-visit intention” OR “intention to return” OR “intention to revisit” AND (Hospitality OR Hotel OR Tourist OR “tourist spot” OR “tourism sector” OR “tourist sites”). The search does not apply any restrictions on publication year; therefore, the results cover journal articles published between 2000 and 2025. The articles are filtered to include only those written in English and marked as fully published (final publication stage). The database search is conducted using Scopus, ScienceDirect, and Emerald. All searches are carried out until September 20, 2025, and include all articles indexed in each database up to that date. Altogether, the searches yield 5577 records. The complete list of reviewed articles, along with the PRISMA 2020 checklist, is available in the registration record published on Figshare. No data conversions or imputations are required, as all extracted data are fully reported in the included studies.

3.2. Records Removed Before Screening

In PRISMA 2020, prior to the screening stage, a record-cleaning process is conducted to remove duplicates and records that fail to meet administrative criteria. This step ensures that only eligible records proceed to content screening. In the present study, several records were excluded before the screening stage due to the following reasons:

(a)

The document was not a journal article (e.g., proceedings, book chapters).

(b)

The article was still in press.

(c)

The source was not a peer-reviewed journal.

(d)

The article was written in a language other than English.

3.3. Screening (Records Screened and Record Excluded)

The screening stage in PRISMA 2020 involves evaluating the titles and abstracts of records to determine whether they generally meet the inclusion criteria. Records deemed irrelevant to the research focus are excluded at this stage. In this study, the remaining records after the initial cleaning were screened based on their titles and abstracts. The primary screening criteria included:

(a)

The article focuses on the tourism or hospitality sector.

(b)

The main topic pertains to revisit intention or factors influencing revisit intention.

(c)

The article indicates the use of quantitative or mixed-methods approaches.

Records that did not meet these criteria were excluded and documented as records excluded. The screening process is conducted by four people, starting from this stage until the final selection. Each person screens the records independently and manually, without the assistance of automation tools. In cases where there are differences in judgment among reviewers, these are resolved through discussion until a consensus is reached.

3.4. Report Sought for Retrieval

PRISMA 2020 stipulates that following the screening stage, all potentially relevant records should undergo full-text retrieval to allow for a comprehensive evaluation of their eligibility. The purpose of this step is to assess the suitability of each study based on a full reading of its content. In this study, all articles that passed the title and abstract screening were recorded as reports sought for retrieval, and the full-text download process was conducted to proceed to the eligibility stage.

3.5. Report Not Retrieved

The reports not retrieved stage in PRISMA 2020 refers to records for which full-text retrieval was attempted but ultimately unsuccessful due to technical issues or access limitations. In this study, any articles whose full texts could not be accessed through Scopus, ScienceDirect, Emerald, or institutional sources were recorded as reports not retrieved and were not included in the eligibility assessment.

3.6. Eligibility (Records Assessed for Eligibility and Full-Text Excluded)

The eligibility stage in PRISMA 2020 involves a full-text evaluation to ensure that each article fully meets the established inclusion criteria. In this study, the full texts of all successfully retrieved articles were reviewed and assessed based on the following criteria:

(a)

The article is an empirical study (not a conceptual paper or review article).

(b)

It employs a quantitative or mixed-methods approach.

(c)

It investigates antecedents of revisit intention within the tourism or hospitality sector.

Articles that did not meet these criteria upon full-text review were excluded, and the reasons for exclusion were thoroughly documented as follows:

(a)

The article does not test the direct effect on the revisit intention variable. This means that studies only exploring indirect or mediating effects, without reporting a direct statistical test on revisit intention, were excluded.

(b)

The article does not examine the revisit intention variable at all. For example, papers that focus on related constructs such as loyalty or satisfaction but do not explicitly include revisit intention as a dependent variable were removed.

(c)

The article is incomplete. This refers to records such as conference abstracts, extended summaries, or non-final drafts that do not provide sufficient methodological or statistical information for data extraction.

To ensure consistency across different statistical approaches (e.g., multiple regression, path analysis, or SEM), only standardized coefficients (β) reported by the original authors are recorded. If a study reports several models, the coefficient from the main or final model specified by the authors is extracted, including both positive and negative effects, whether significant or not. All extracted data are then coded manually using a structured coding guideline, so that the extraction process remains systematic, transparent, and replicable.

3.7. Included (Total Studies Included)

The final stage in PRISMA 2020 is included, which refers to the total number of studies ultimately incorporated into the systematic synthesis. In this study, all articles that passed the full-text eligibility assessment were compiled for further analysis, which included:

(a)

Analyzing the antecedents of revisit intention.

(b)

Examining the theoretical frameworks used in revisit intention research.

To minimize the risk of bias during the screening process, the risk of bias assessment is conducted by the research team independently, manually, and on a rotating basis among the team members. This approach is intended to ensure objectivity and consistency in the selection and evaluation of studies included in the synthesis. A clear and concise flow diagram, along with a description of the selection process following the PRISMA 2020 guidelines by Page et al. [22] and Page et al. [23], is presented in Figure 1.

Figure 1. PRISMA 2020 Flow Diagram for Systematic Reviews on the Revisit Intention Variable.

Following the PRISMA 2020 framework as outlined by Page et al. [22] and Page et al. [23], the study selection process in this research was carried out rigorously to ensure that only the most relevant, valid, and criterion-compliant articles were included for analysis. Each stage of the selection process is explained transparently to support the replication and traceability of this study. The data obtained from the selected studies are presented in three key formats: Figure 2, Annual Trends in Revisit Intention Research; Figure 3, Most Frequently Investigated Factors Influencing Revisit Intention; and a summary table. The table provides a comprehensive overview of the variables that influence revisit intention, highlights factors that are less frequently examined, and outlines the theoretical frameworks commonly applied in revisit intention research.

Figure 2. Trends in Revisit Intention Research.

Figure 3. Most Frequently Investigated Factors Influencing Revisit Intention.

4. Research Finding

4.1. Annual Trends in Revisit Intention Research

To provide a comprehensive overview of the dynamics in revisit intention research, this section first presents the annual development in the number of scholarly publications addressing the topic. The visualization of publication trends not only reflects the level of academic attention given to tourist loyalty issues but also highlights the topic’s relevance in addressing the evolving challenges and demands of the global tourism industry. Figure 1 illustrates the growth in the number of scientific articles examining revisit intention from 2000 to 2025, based on the data collected through the systematic review.

Based on the quantitative data presented in Figure 2, research on revisit intention began in the year 2000 and experienced fluctuations through 2008. Following this period, the number of revisit intention studies steadily increased, surpassing ten publications in 2014. A notable upward trend emerged beginning in 2015, with a sharp surge observed between 2020 and 2024, peaking in 2024 with a total of 159 documents. Rather than being interpreted solely as growing academic interest, this surge should also be understood in light of external factors, such as the COVID-19 pandemic and the proliferation of special issues in tourism journals, which created momentum for studies on tourist behavior and loyalty. However, the sharp decline in 2025 may be attributed to incomplete publication data for the current year and should not be interpreted as a substantive downward trend. Taken together, these findings indicate that while revisit intention remains a strategically relevant theme in tourism research, patterns of publication are shaped not only by theoretical and practical relevance but also by broader contextual drivers in the academic publishing landscape.

4.2. Leading Antecedents of Revisit Intention: A Frequency-Based Analysis

To enhance the understanding of key factors influencing revisit intention, this study performs a frequency analysis of antecedent variables identified across the selected articles. The findings are illustrated in Figure 3, titled “Most Frequently Investigated Factors Influencing Revisit Intention”. This visual representation emphasizes the five most frequently examined variables in prior research, offering valuable insights into the predominant areas of scholarly focus within the revisit intention discourse in tourism and hospitality contexts.

As shown in Figure 3, three antecedent variables, such as Satisfaction, Tourist Satisfaction, and Destination Image, appear most frequently, each cited in 17 articles. These results suggest that both general and tourism-specific satisfaction, along with perceptions of destination image, are consistently recognized as central drivers of tourists’ intention to revisit a destination. Perceived Value ranks next, identified in 6 studies, indicating that tourists’ assessment of received value relative to their expectations plays a meaningful, though less frequently explored, role. Finally, Customer Satisfaction is reported in 5 articles, pointing to a narrower yet significant dimension of how the fulfillment of customer expectations directly relates to revisit intention. Beyond these descriptive patterns, the dominance of satisfaction-related constructs and destination image reflects the strong alignment of revisit intention research with loyalty frameworks in consumer behavior theory. At the same time, the relatively limited attention to perceived value and customer satisfaction suggests that more nuanced aspects of tourist decision-making, such as cost–benefit evaluations and service-specific experiences, remain underexplored. Addressing these gaps may expand the theoretical landscape by integrating economic and experiential perspectives into models of revisit intention. Collectively, these findings underscore the critical influence of satisfaction and destination perception in shaping revisit behavior within tourism research.

4.3. Most Relevant Author

The bibliometric analysis of the most relevant authors is shown in Figure 4, which visualizes the researchers with the greatest contributions to studies on revisit intention. The figure presents the 20 most productive authors based on the number of publications and provides an overview of those who consistently contribute to this topic. This finding is important because it guides future researchers to refer to the key works that dominate the development of revisit intention research.

Figure 4. Most Relevant Author in Revisit Intention Research.

From Figure 4, Han H holds the top position with 26 publications, demonstrating strong consistency and significant influence in the academic discussion on revisit intention. Following this, three other notable authors are Carvache-Franco M, Carvache-Franco W, and Kim J, with 16, 16, and 15 publications, respectively. Their contributions highlight a group of productive scholars who focus on this topic from different perspectives, including destination management and tourist behavior. The dominance of these authors’ publications shows that the direction of revisit intention research is strongly shaped by their work, which future researchers can use as a key reference and foundation for developing richer and more contextual conceptual models.

4.4. Co-Occurrence Network

The next bibliometric analysis is shown in Figure 5, which presents the co-occurrence network of keywords used in studies related to revisit intention. This mapping shows the connections between concepts that frequently appear together in the articles, helping to illustrate the conceptual structure within tourism and tourist behavior research. The visualization makes it easier to identify dominant keywords, research clusters, and the direction of emerging topics.

Figure 5. Co-Occurrence Network in Revisit Intention Research.

From Figure 5, it is clear that the keyword “revisit intention” is central and closely connected to concepts such as tourist destination, tourist behavior, destination image, and satisfaction. The blue cluster highlights a focus on tourist behavior, destination image, and travel experience, while the red cluster is more related to service quality, loyalty, and customer satisfaction. This pattern indicates that research on revisit intention is not limited to the behavioral dimension of tourists but is also enriched by managerial factors such as service quality and destination marketing strategies. Thus, the keyword network confirms that revisit intention is a multidimensional topic that develops at the intersection of tourist behavior, destination experience, and service satisfaction.

4.5. Factor Affecting Revisit Intention

As part of this systematic analysis, a critical step was taken by categorizing various antecedent variables that influence revisit intention based on their conceptual similarities and the terminology used by previous researchers. This categorization approach serves to simplify the complexity of terminology while providing a more systematic structure for understanding both the consistent and divergent factors identified in the existing literature. Table 1 presents the synthesis of the reviewed studies, showing the original variables examined, the number of articles in which they appear, as well as the corresponding authors and years of publication. It should be noted that, unlike Figure 3 which presents the frequency of variables exactly as reported in the original articles, Table 1 groups variables with similar concepts (e.g., Satisfaction, Tourist Satisfaction, Customer Satisfaction) to highlight their conceptual coherence.

Table 1. Determinant Variables of Revisit Intention.

No	Variable Related	Term Used	Number of Articles	Result	Conclusion	Author
1	Related to Customer Satisfaction	Customer Satisfaction	62	Positive/Significant	Inconsistent Results	Goh [24]; Khalil et al. [25]; Kim et al. [26]; Sun et al. [27]; Ardani et al. [28]; Khoo [29]
		Destination Satisfaction		Positive/Significant		Damayanti [30]; Shabankareh et al. [31]
		Foreign Tourist’s Satisfaction		Positive/Significant		Bandaru & Venkateshwarlu [32]
		Guest Satisfaction		Positive/Significant		Kerdpitak [33]; Yu [34]; Sharma & Bhat [35]; Ugwuanyi et al. [36]
		Overall Satisfaction		Positive/Significant		Cole & Scott [37]; Caber et al. [38]; Kim [39]
		Satisfaction		Positive/Significant		Back et al. [40]; Chitthanom [41]; Park et al. [42]; Ren et al. [43]; Allameh et al. [44]; Ariya et al. [45]; Bader et al. [46]; Cheung et al. [47]; Choo & Petrick [48]; Ćulić et al. [49]; Jeong & Shin [50]; Kim et al. [51]; Kim et al. [52]; Kou & Xue [53]; Lin et al. [54]; Liu et al. [55]; Viet & Van [56]; Sugiama et al. [57]; Wang et al. [58]
		Tourism Satisfaction		Positive/Significant		Su & Huang [59]; Zaitul et al. [60]; Yoopetch & Kongarchapatara [61]
		Tourist Satisfaction		Positive/Significant		Chan et al. [62]; Hasan et al. [63]; Kim & Oh [64]; Mohammed et al. [65]; Nguyen Huu et al. [66]; Pham et al. [67]; Rehman et al. [68]; Wilopo & Nuralam [69]; Zheng et al. [70]; Assaker & Hallak [71]; Kim et al. [72]; Long & Nguyen [73]; Nguyen Viet et al. [1]; Nguyen-Viet & Van Nguyen [74]; Nugraha [75]; Shatnawi et al. [76]; Shi et al. [77]
		Travel Experience Satisfaction		Positive/Significant		Pai et al. [78]
		Visitor Satisfaction		Positive/Significant		Juliana et al. [79]
		Tourist Overall Satisfaction		Positive/Significant		Bam & Kunwar [80]
		Recovery Satisfaction		Positive/Significant		Kim et al. [81]
		Satisfaction with Past Travel		Positive/Significant		Huang & Hsu [82]
		Satisfaction with Trip Experience		Positive/Significant		Kim et al. [83]
		Leisure Life Satisfaction		Positive/Significant		Kim et al. [83]
		Satisfaction with Attraction Revitalization		Positive/Significant		Nursyamsiah & Setiawan [84]
		Satisfaction with Amenities Revitalization		Positive/Not Significant		Nursyamsiah & Setiawan [84]
		Satisfaction with Accessibility Revitalization		Positive/Significant		Nursyamsiah & Setiawan [84]
		Satisfaction with Service Revitalization		Positive/Significant		Nursyamsiah & Setiawan [84]
2	Related to Destination Image	Destination Image	43	Positive/Significant Negative/Significant	Inconsistent Results	Adam et al. [85]; Allameh et al. [44]; Foster & Sidharta [86]; Kim [39]; Nam et al. [10]; Nasib et al. [87]; Viet & Van [56]; Pujiastuti et al. [88]; Supriono & Yulianto [89]; Ariesta et al. [90]; Fachmi et al. [91]; Hang et al. [92]; Kusumah et al. [93]; Liestiandre et al. [94]; Manyangara et al. [2]; Rasoolimanesh et al. [95]; Yuxin et al. [96]; Abbasi et al. [17]
		Airport Image		Positive/Significant		Hang et al. [92]
		Overall Image		Positive/Significant		Ko et al. [97]
		Cognitive Image		Positive/Significant Negative/Not Significant		Chew & Jahari [98]; Luvsandavaajav et al. [99]; Ren et al. [43]; Alfaisaly et al. [100]; Song et al. [101]; Duan & Wu [102]
		Affective Image		Positive/Significant Positive/Not Significant		Chew & Jahari [98]; Luvsandavaajav et al. [99]; Tosun et al. [103]; Alfaisaly et al. [100]; Song et al. [101]; Duan & Wu [102]
		Image of Infrastructure		Positive/Significant		Rahman et al. [104]
		Image of Value for Money		Positive/Significant		Rahman et al. [104]
		Perceived Image		Positive/Significant		Ren et al. [43]
		Hotel Image		Positive/Significant		Sornsaruht [105]; Dhewi et al. [106]
		Brand Image		Positive/Significant		Sukaatmadja et al. [107]
		Unique Image		Positive/Significant		Alfaisaly et al. [100]
		Perceived Destination Image		Positive/Significant		Hasan et al. [63]; Liu et al. [55]
		Green Image		Positive/Significant		Huyen et al. [108]
		Destination Brand Image		Positive/Significant		Shabankareh et al. [31]
3	Related to Experience	Cuisine Experience	26	Positive/Significant	Consistent Results	Lin [109]
		Customer Experience		Positive/Significant		Dhewi et al. [106]
		Experience		Positive/Significant		Seow et al. [110]
		Experience Marketing		Positive/Significant		Chen et al. [111]
		Experience Quality		Positive/Significant		Liu et al. [55]; Rahmawati et al. [112]
		Experiential Marketing		Positive/Significant		Nugraha [75]
		Hedonic Experience		Positive/Significant		Ugwuanyi et al. [36]
		Memorable Customer Experience		Positive/Significant		Fachmi et al. [91]
		Memorable Experience		Positive/Significant		Cheung et al. [47]; Jeong & Shin [50]
		Memorable Tourism Experience		Positive/Significant		Elfiondri et al. [113]; Kim [39]; Rasoolimanesh et al. [95]; Setiawan et al. [114]; Zhang et al. [115]
		Memorable Tourist Experience		Positive/Significant		Mel’on et al. [116]; Tiwari et al. [117]
		Perceived Experience		Positive/Significant		Sumhyai & Punyasiri [118]
		Relational Experience		Positive/Significant		Ugwuanyi et al. [36]
		Tourist Experience		Positive/Significant		Sukaatmadja et al. [107]; Luo et al. [119]
		Utilitarian Experience		Positive/Significant		Ugwuanyi et al. [36]
		Authentic Experience		Positive/Significant		Nguyen-Viet & Van Nguyen [74]
		Memorability of Pervious Travel Experience		Positive/Significant		Hu & Xu [120]
		Experiential Marketing		Positive/Significant		Lin [121]
4	Related to Service Quality	Service Quality	12	Positive/Significant	Consistent Results	Ardani et al. [28]; Manyangara et al. [2]; Polas et al. [122]
		Reliability		Positive/Significant		Bichler et al. [123]; Jadon & Kumar [124]
		Responsiveness		Positive/Significant		Bichler et al. [123]; Jadon & Kumar [124]; Jansri et al. [125]
		Assurance		Positive/Significant		Jadon & Kumar [124]; Jansri et al. [125]
		Empathy		Positive/Significant		Jadon & Kumar [124]
		Tangibililty		Positive/Significant		Jadon & Kumar [124]
		Tangible		Positive/Significant		Jansri et al. [125]
5	Related to Perceived Destination	Perceived Value	13	Positive/Significant	Consistent Results	Caber et al. [38]; Hasan et al. [126]; Pham et al. [67]; Allameh et al. [44]; Intuluck et al. [127]; Liu et al. [55]; Yuxin et al. [96]; Abbasi et al. [17]
		Perceived Coolness		Positive/Significant		Munawar et al. [128]
		Perceived Destination		Positive/Significant		Sumhyai & Punyasiri [118]
		Perceived Quality		Positive/Significant		Allameh et al. [44]
		Perceived Destination Image		Positive/Significant		Liu et al. [55]; Hasan et al. [63]
		Perceived Quality of Physical Attributes		Positive/Significant		Kim et al. [51]
		Perceived Quality of Service		Positive/Significant		Kim et al. [51]
		Perceived Behavioural		Positive/Significant		Abbasi et al. [17]
6	Related to Perceived Trust	Green Trust	11	Positive/Significant	Consistent Results	Chen et al. [129]; Huyen et al. [108]
		Brand Trust		Positive/Significant		Nasib et al. [87]
		Destination Trust		Positive/Significant		Yusof et al. [130]; Pujiastuti et al. [88]
		Customer Trust		Positive/Significant		Ardani et al. [28]
		Trust		Positive/Significant		Chitthanom [41]; Kusumawati et al. [131]; Torres-Moraga et al. [132]
		Perceived Trust		Positive/Significant		Hassan & Soliman [133]; Kim et al. [81]
7	Related to Cultural Intelligence	Cultural Contact	9	Positive/Significant	Consistent Results	Elfiondri et al. [134]; Lai et al. [135]; Nguyen Viet et al. [1]; Viet & Van [56]
		Cultural Memory		Positive/Significant		Lai et al. [135]
		Local Culture		Positive/Significant		Amir et al. [136]; Vu et al. [137]
		Cultural Value		Positive/Significant		Yao et al. [138]
		Overall Cultural Intelligence		Positive/Significant		Zhang et al. [139]
8	Related to Service	Hotel Services	3	Positive/Significant	Consistent Results	Cengizci et al. [140]
		Hospitality and Services		Positive/Significant		Ćulić et al. [49]
		Service Prices		Positive/Significant		Long & Nguyen [73]

Based on the categorization of antecedent variables presented in Table 1, customer satisfaction emerges as the most dominant determinant, appearing in the highest number of articles and encompassing a wide range of terminology such as tourist satisfaction, destination satisfaction, and overall satisfaction. In addition, variables such as destination image, experience, perceived value, and service quality also consistently appear as key determinants. This reflects the strong influence of positive perceptions, emotional experiences, and service quality on tourists’ decisions to revisit a destination. The articles synthesized and incorporated into the research findings are limited to those that employ a quantitative approach, conduct hypothesis testing, report a positive effect on revisit intention, and use samples consisting of tourists, hotel guests, or individuals associated with tourism sites or hospitality services.

On the other hand, variables such as trust, culture, and service remain underexplored, offering potential opportunities for future research to deepen the understanding of factors that may enhance tourist loyalty toward specific destinations. Beyond trust, culture, and service, several other antecedent variables related to revisit intention have been rarely examined. These lesser-used variables are summarized in Table 2.

Table 2. Less Frequently Studied Antecedent Variables of Revisit Intention.

No	Variable Related	Number of Articles	Authors
1	E-WOM	5	Pujiastuti et al. [88]; Seow et al. [110]; Sharipudin et al. [141]; Shatnawi et al. [76]; Adam et al. [85]
2	Attitude	6	Goh [24]; Lai et al. [142]; Yang et al. [143]; Yoopetch & Kongarchapatara [61]; Hasan et al. [63]; Hasan et al. [126]
3	Accessibility	4	Ariesta et al. [90]; Çetin et al. [144]; Nasib et al. [87]; Sugiama et al. [57]
4	Subjective Norm	4	Goh [24]; Hasan et al. [126]; Lai et al. [142]; Yoopetch & Kongarchapatara [61]
5	Place Identity	3	Isa et al. [145]; Nguyen-Viet & Van Nguyen [74]; Yao et al. [138]
6	Place Attachment	3	Wang et al. [146]; Zhou et al. [147]; Zhou et al. [148]
7	Destination Quality	3	Kusumawati et al. [131]; Liestiandre et al. [94]; Sukaatmadja et al. [107]
8	Attraction	2	Ariesta et al. [90]; Sugiama et al. [57]
9	Perceived Risk	2	Nguyen Viet et al. [1]; Alfaisaly et al. [100]
10	Physical Environment	2	Lin et al. [54]; Polas et al. [122]
11	Destination Brand Awareness	2	Damayanti [30]; Intuluck et al. [127]
12	Cultural Identity	1	Liu et al. [55]
13	Social Return	1	Mittal et al. [149]
14	Friendly Environmental Behavior	1	Lee et al. [150]

The classification of rarely studied variables in revisit intention research, as shown in Table 2, reveals that although variables such as electronic word of mouth (e-WOM), attitude, and accessibility possess strong theoretical potential in explaining revisit intentions, their frequency in the literature remains limited. For example, e-WOM and attitude were each identified in only six studies, while other variables such as accessibility, subjective norm, place identity, place attachment, and destination quality appeared in merely three or four publications. Some variables, such as cultural identity, social return, and friendly environmental behavior, were found in only a single study. These findings indicate that psychosocial factors, spatial identity, and aspects of sustainability and destination accessibility have yet to receive significant attention in revisit intention research. One possible reason for this limited exploration is that many of these variables are context-specific and require interdisciplinary approaches, making them less frequently adopted in mainstream tourism research. However, their theoretical potential is considerable: e-WOM can capture the growing influence of digital interactions on travel decisions, attitude and subjective norm can strengthen the application of behavioral theories such as TRA and TPB, and variables like cultural identity or friendly environmental behavior can enrich the integration of cultural and sustainability perspectives into revisit intention models.

4.6. Theoretical Foundations Frequently Used in Revisit Intention Research

To provide a more comprehensive understanding of the conceptual foundation underlying revisit intention studies, it is essential to identify the theories most commonly employed by researchers in analyzing this phenomenon. The choice of theoretical framework not only reflects the analytical lens used to explain tourist behavior but also indicates the prevailing theoretical paradigms within the literature. Accordingly, Table 3 presents the most frequently adopted theories in revisit intention research, based on the systematically reviewed studies.

Table 3. Theoretical Foundations in Revisit Intention Research.

No	Theoretical Framework	Author
1	Theory of Planned Behavior (TPB)	Ardani et al. [28]; Elfiondri et al. [113]; Goh [24]; Hasan et al. [126]; Juliana et al. [79]; Lai et al. [142]; Lee et al. [150]; Liestiandre et al. [94]; Zaitul et al. [60]; Zheng et al. [70]
2	SOR Theory	Yang et al. [143]; Isa et al. [145]; Pham et al. [67]; Shi et al. [77]; Torres-Moraga et al. [132]; Yuxin et al. [96]; Zheng et al. [151]
3	Theory of Reasoned Action (TRA)	Yoopetch & Kongarchapatara [61]; Kusumawati et al. [131]; Kusumawati et al. [152]
4	Cognitive Appraisal Theory	Tiwari et al. [117]; Zhou et al. [148]

Based on Table 3, the Theory of Planned Behavior (TPB) emerges as the most widely utilized framework in revisit intention research. Its broad adoption across various contexts and publication years underscores the theory’s relevance and flexibility in explaining tourists’ behavioral intentions to return to a destination. Following TPB, the Stimulus-Organism-Response (SOR) Theory has also gained considerable traction, particularly in studies examining how external stimuli—such as experiences or services—influence tourists’ internal responses, which subsequently shape revisit intention. Although the Theory of Reasoned Action (TRA) and Cognitive Appraisal Theory are not as prevalent as TPB and SOR, they continue to make valuable contributions to understanding the psychological and cognitive mechanisms underpinning revisit intention. This diversity of theoretical frameworks indicates that revisit intention research is grounded not only in robust behavioral theories but is also increasingly incorporating cognitive and affective perspectives to capture the complexities of modern tourist decision-making.

4.7. Studies Excluded After Full-Text Assessment

Although many articles make valuable contributions in identifying variables that influence revisit intention, some initially appear to meet the inclusion criteria and are considered for further analysis. However, after a rigorous final selection process, several are excluded due to methodological or substantive reasons that do not align with the focus of this study. This subsection presents examples of articles excluded from the final synthesis, along with brief explanations for their exclusion. The list of excluded articles and the reasons for their exclusion are summarized in Table 4.

Table 4. List of Excluded Articles with Justifications.

No	Author	Research Objective	Reason for Exclusion
1	Nazir et al. [153]	This study examines the influence of destination image, perceived risk, and perceived barriers on international tourists’ behavioral intention to revisit Pakistan. It also aims to evaluate the mediating role of destination image in the relationship between perceived risk, perceived barriers, and behavioral intention.	This article is excluded because it does not explicitly examine revisit intention as a main variable. Revisit intention only appears as part of the questionnaire items, but it is not independently analyzed or used as a central focus in testing the relationships between variables.
2	Raggiotto & Scarpi [154]	This paper examines a moderated sequential mediation model based on hypothesized relationships in the context of an extreme sports event, aiming to understand the factors that influence participants’ loyalty to the destination.	This article is excluded because revisit intention is not explicitly examined as a main variable. It is only included as part of the destination loyalty construct and is not independently analyzed in testing the relationships between variables.

Based on Table 4, although both articles mention revisit intention, they do not explicitly treat it as a primary variable that is thoroughly analyzed within the research model. In the article by Nazir et al. [153], revisit intention appears only implicitly within the broader construct of destination loyalty, which is measured as a composite of several behavioral dimensions, without being the main focus in testing variable relationships. Similarly, in the article by Raggiotto and Scarpi [154], revisit intention is included as part of the definition of destination loyalty; however, the study specifically tests the mediating effects of self-enhancement and place attachment on overall loyalty, not on revisit intention as a separate outcome.

Therefore, although both articles offer relevant theoretical insights into revisit behavior, they do not meet the inclusion criteria for further analysis in this study because revisit intention is not examined independently as a standalone variable. Instead, it is used as part of survey items or as a secondary element within another construct, rather than as a central focus of the conceptual framework or hypothesis testing. As a result, both articles are excluded from the final synthesis.

5. Discussion

The analysis of publication trends shows that research on revisit intention has increased over the last decade, with a more notable rise during the period from 2020 to 2024. The number of publications reached its peak in 2024, with a total of 159 articles. This growth should be understood not only as evidence of greater conceptual interest but also as a response to external factors, such as the dynamics of the COVID-19 pandemic and the emergence of special issues that encourage tourism-related publications. This phenomenon illustrates the link between publication trends and the rapidly evolving social and tourism industry context. At the same time, the decline in publications in 2025 needs to be interpreted with caution, since the available data do not yet cover the entire year. Overall, these findings confirm that revisit intention remains a relevant and strategic field of study, even though publication patterns are shaped by external dynamics and the practical needs of the tourism industry.

Not all variables show consistent positive and significant effects on revisit intention. Factors such as experience, service quality, perceived destination, trust, cultural intelligence, and service are consistently significant, while customer satisfaction and destination image show mixed results. The most consistently cited variables in the literature on revisit intention are customer satisfaction and destination image. Customer satisfaction refers to tourists’ affective evaluations of their overall experience during a visit, which strongly influences their intention to return [40]. Studies by Park et al. [42] and Ren et al. [43] indicate that high levels of satisfaction with historical or ecotourism experiences not only reinforce the desire to revisit but also foster lasting emotional connections. However, after adding newly identified studies to the SLR, the satisfaction–revisit link is no longer uniformly positive and significant. For example, while several satisfaction reports show positive direct effects, “satisfaction with amenities revitalization” does not yield a significant direct path to revisit intention and instead operates via place attachment [84]. When place attachment acts as a mediating variable, the relationship between satisfaction with amenities revitalization and revisit intention becomes positive and significant, suggesting that this satisfaction enhances revisit intention only when visitors feel emotionally connected to the place [84]. In this context, improved amenities contribute not merely to functional satisfaction but also to emotional attachment, fostering a stronger sense of comfort and belonging. Hence, amenities revitalization is most effective when combined with efforts that build place attachment, such as creating social interaction spaces and preserving cultural elements that make the environment personally meaningful. This divergence suggests that the impact of satisfaction depends on how it is operationalized (global vs. attribute-specific) and on model specification (direct vs. mediated paths), rather than functioning as a universal predictor across contexts [42,43,83].

Meanwhile, destination image, shaped by cognitive, affective, and conative attributes, significantly influences tourist perceptions [85,86]. This is supported by Hasan et al. [63] and Nam et al. [10], who found that a positive destination image directly enhances revisit intention, especially when supported by place attachment and brand trust [87,88]. Thus, the combination of customer satisfaction and destination image emerges as a key strategy for maintaining tourist loyalty. Yet the evidence is not fully consistent.

Rasoolimanesh et al. [95] report that destination image exerts a negative and insignificant direct effect on revisit intention, but the relationship becomes positive and significant when mediated by memorable tourism experiences (MTE). This suggests that destination image strongly motivates revisit intention only when tourists’ perceptions are translated into meaningful, emotionally rich memories that deepen personal engagement with the destination. Similarly, Song et al. [101] find that both cognitive and affective images show insignificant direct effects on revisit intention; however, when mediated by place dependence, these relationships become positive and significant. In other words, cognitive and affective images influence revisit intention most strongly when tourists perceive the destination as functionally irreplaceable and personally valuable, reflecting a high level of dependence on the place for specific leisure experiences. These mixed findings indicate that the role of destination image depends on how it is measured and the context in which it is studied, suggesting it is a conditional rather than universal predictor of revisit intention.

In addition, experience and service quality have also been identified as critical determinants of revisit intention. Experience refers to tourists’ personal interactions that generate emotional, cognitive, and behavioral impressions, elements that play a significant role in fostering loyalty [106]. Studies by Seow et al. [110], Liu et al. [55], and Hu and Xu [120] consistently demonstrate that unique, authentic, and memorable tourism experiences have a positive and statistically significant effect on revisit intention. These findings highlight the importance of emotional resonance, local culture, and lasting memories in shaping tourists’ behavioral intentions. Rahmawati et al. [112] further reinforce this view, showing that positive experiences can even offset shortcomings such as limited infrastructure. Collectively, these results confirm that experience is a consistently strong predictor of revisit intention, particularly when it evokes meaningful emotional engagement and aligns with the contextual and structural characteristics of the destination.

Alongside experience, service quality plays a vital role in enhancing revisit intention through tourists’ evaluations of destination services, including hospitality, professionalism, and efficiency [28,46]. Findings from Manyangara et al. [2] and Polas et al. [122] reinforce that high service quality independently boosts tourist trust, which in turn strengthens revisit intention. Therefore, tourism destinations must prioritize the improvement of both experience and service quality as strategic investments to ensure long-term tourist loyalty.

Perceived destination and trust also play crucial roles in shaping tourists’ revisit intention. Perceived destination refers to tourists’ subjective evaluations of the functional, emotional, and experiential value of a destination. Hasan et al. [126] found that a high perceived value of a destination significantly enhances tourists’ positive attitudes, thereby strengthening their intention to return. Interestingly, studies by Pham et al. [67] and Sumhyai & Punyasiri [118] highlight that perceived value and perceived destination image, formed through electronic word-of-mouth (e-WOM), have a direct impact on revisit intention. Similarly, Liu et al. [55] demonstrate that perceived destination image acts as a mediator in the relationship between tourist experience and revisit intention, underscoring the vital role of destination perception in fostering tourist loyalty. Moreover, trust, defined as tourists’ belief in the integrity and safety of a destination, significantly enhances the tourist–destination relationship. Chen et al. [129] and Nasib et al. [87] identify that high levels of trust not only increase revisit intention but also reduce the likelihood of tourists spreading negative information. Findings by Yusof et al. [130] and Ardani et al. [28] further reveal that trust strengthens tourists’ willingness to recommend the destination to others. Therefore, destinations must manage trust as a strategic foundation for sustaining long-term tourist loyalty.

Cultural intelligence has also been identified as a factor influencing revisit intention, particularly in the context of cultural tourism. Cultural intelligence refers to a tourist’s ability to understand, adapt to, and effectively interact with the local culture of a destination. According to Zhang et al. [139], tourists with high cultural intelligence tend to be more open to cultural differences, which strengthens their desire to revisit the destination. Findings by Elfiondri et al. [134] reveal that cultural contact, through direct interaction with local traditions and the use of locally based tourism language, significantly enhances revisit intention. Similarly, Lai et al. [135] and Yao et al. [138] found that deep cultural experiences create strong tourism memories and high levels of place attachment, which ultimately reinforce tourists’ intentions to return. These findings underscore the importance of developing culturally intelligent destination strategies by offering authentic and interactive cultural experiences to sustain long-term tourist loyalty.

Finally, supplementary service-related variables also significantly influence tourists’ revisit intention. These variables include additional amenities, staff friendliness, food and beverage service, and fair pricing. According to Bam and Kunwar [80], the quality of hospitality services is a critical factor in enhancing tourist satisfaction and indirectly encouraging revisit intention—particularly in unique destinations such as Nepal. Studies by Cengizci et al. [140] and Ćulić et al. [49] further affirm that superior hotel services contribute to the creation of a favorable destination image, which positively impacts tourists’ intentions to return. Interestingly, Long and Nguyen [73] found that fair service pricing in rural tourism destinations enhances tourists’ perceived value, thereby strengthening their desire to revisit. These findings emphasize the importance of destinations to continuously improve the quality of supplementary services in order to create a holistic tourism experience and secure long-term tourist loyalty through consistently strengthened revisit intention.

A review of the less frequently studied variables in revisit intention research reveals significant opportunities to broaden our understanding of tourists’ return intentions. While variables such as electronic word-of-mouth (e-WOM), attitude, and accessibility have been examined more often than others, exploration of variables like place identity, place attachment, destination quality, attraction, perceived risk, physical environment, destination brand awareness, cultural identity, social return, and friendly environmental behavior remains limited. Yet, these underexplored variables have shown positive and significant effects on revisit intention. For instance, the study by Alfaisaly et al. [100] demonstrated that e-WOM has a significant impact on shaping positive destination image and enhancing revisit intention. However, such findings have yet to be widely replicated across diverse tourism contexts. Similarly, attitude, which closely relates to tourists’ personal evaluations of marketing communication—particularly post-visit emails—has been shown to significantly increase revisit intention [143]. Additionally, accessibility, as explored by Ariesta et al. [90], was found to have a positive and significant effect on revisit intention, although it has so far been studied primarily in marine tourism contexts. Future research can operationalize e-WOM not only as tourists’ online reviews but also as measurable constructs of post-stay evaluations, interactivity on digital platforms, and cross-cultural differences in sharing behavior [76,141]. This approach would allow researchers to test how e-WOM functions as both a mediator and moderator in shaping revisit intention. Therefore, these relatively underexplored variables offer valuable avenues for further research, potentially enriching the theoretical and practical understanding of revisit intention dynamics across different types of tourism destinations.

In studies on revisit intention, a range of behavioral theories has been employed to comprehensively understand how tourists form the intention to return to a destination. One of the most dominant frameworks is the Theory of Planned Behavior (TPB), which posits that attitude, subjective norms, and perceived behavioral control collectively shape behavioral intention, including the decision to revisit [60,150]. TPB’s strength lies in its flexibility to incorporate cognitive and contextual variables, such as local cultural values and perceptions of safety [70,94]. TPB is widely applied in various tourism contexts, such as cultural tourism [28], ecotourism [113], culinary tourism [126], community-based tourism [60], as well as educational and medical tourism [79,94]. These contexts show that TPB is most relevant when tourist behavior is rational and planned, meaning that the decision to revisit is z of revisit intention because it captures the cognitive and social dynamics that shape tourists’ decision-making processes.

In addition to TPB, the Stimulus-Organism-Response (SOR) model plays a key role in explaining how external stimuli, such as destination atmosphere, service quality, and digital marketing communication shape tourists’ affective and cognitive states, which in turn influence revisit behavior [67,143,145]. The advantage of SOR lies in its ability to highlight the mediating role of emotional and psychological states, as shown in place-attachment studies where environmental attributes such as infrastructure and atmosphere trigger stronger revisit intentions [145]. SOR is most relevant for explaining tourist behavior that is emotional and reactive to destination experiences, such as perceptions of atmosphere (tourscape), brand authenticity, or memorable experiences. Research by Shi et al. [77] shows that brand authenticity and destination brand equity influence revisit intention through the mediation of satisfaction, while Torres-Moraga et al. [132] find that sustainable tourscape elements build trust and destination identification as key mediators. Therefore, SOR is more appropriate in contexts where revisit intention is driven by emotional resonance, sensory experiences, and social interactions at the destination rather than by purely rational tourist considerations.

Furthermore, the Theory of Reasoned Action (TRA) offers a rational perspective by explaining behavioral intention based on attitude and subjective norms. It emphasizes that positive attitudes and trust in a destination’s quality and sustainability are crucial in forming revisit intentions [61,131,152]. TRA is most relevant in the context of rational and planned tourist behavior, where the decision to revisit is based on a logical evaluation of the destination’s benefits and social support from the environment. Research by Yoopetch and Kongarchapatara [61] shows that attitude, subjective norms, and satisfaction have a positive effect on revisit intention in tea tourism, while Kusumawati et al. [131] find similar results in island tourism. Therefore, TRA provides a strong understanding of how cognitive beliefs and social influence shape tourists’ commitment to revisiting a destination.

Lastly, the Cognitive Appraisal Theory (CAT) contributes by highlighting the role of emotional and cognitive evaluations of memorable tourism experiences, which act as mediators between destination stimuli and revisit intention [117,148]. Empirical evidence confirms that human emotions such as joy, love, surprise, or even fear significantly influence the formation of memorable tourism experiences, which subsequently drive revisit intention [117,148]. CAT is most relevant for explaining tourist behavior that is emotional and experience-centered, such as authentic experiences, place attachment, and memorable tourism experiences. The study by Zhou et al. [148] shows that authentic experiences trigger cognitive evaluations (memorable experiences) and positive emotions (place attachment), which enhance revisit intention. Similarly, Tiwari et al. [117] emphasize that human emotions play an important role in shaping memorable experiences that drive revisit intention. Therefore, compared with theories that focus on rational aspects (such as TRA and TPB), CAT is more suitable for experience-based and affective tourism contexts, where the interaction between cognition and emotion becomes the key to shaping tourist behavior.

Building on this integration, the four theories, TPB, SOR, TRA, and CAT, form a comprehensive framework that connects cognitive, emotional, and behavioral factors in explaining revisit intention. TPB and TRA focus on the rational side of decision-making, where tourists’ attitudes, perceived control, and social norms shape their revisit plans. In contrast, SOR and CAT emphasize emotional and experiential aspects, showing how environmental cues and personal appraisals trigger behavioral responses. When combined, these theories show that revisit intention results from the interaction between thinking, feeling, and context. This integration highlights the need for future research to connect rational planning with emotional experience to better capture the complexity of tourist behavior and improve understanding of revisit intention in various tourism contexts.

6. Conclusions and Further Study

This study presents a systematic synthesis of the literature on revisit intention, revealing that the topic has experienced significant growth, particularly since 2020. The increase in publications during this period reflects a heightened strategic focus on tourist loyalty, represented by revisit intention, within contemporary tourism research. The synthesis identified several key variables most frequently used to explain revisit intention: customer satisfaction, destination image, experience, service quality, perceived destination, trust, cultural intelligence, and service. These variables play a crucial role in shaping tourists’ revisit intentions, as they bridge tourists’ perceptions, emotions, and evaluations of destinations. Each of these variables has been tested across diverse contexts and methodologies, demonstrating consistent empirical relevance and providing a robust foundation for understanding tourist behavior.

Nevertheless, this study also identifies several variables that remain underexplored in revisit intention research, such as attitude, electronic word-of-mouth (e-WOM), accessibility, and place identity. The limited exploration of these variables highlights conceptual gaps that offer promising opportunities for future investigation. From a theoretical standpoint, the Theory of Planned Behavior (TPB) emerges as the most widely adopted framework due to its ability to explain the relationship between attitudes, subjective norms, and perceived behavioral control in shaping tourists’ intentions. In addition to TPB, other frameworks such as the Stimulus, Organism, Response (SOR) model, the Theory of Reasoned Action (TRA), and the Cognitive Appraisal Theory (CAT) also play important roles, as they accommodate the psychological, affective, and evaluative dimensions of revisit behavior. However, the application of these theories remains largely limited to specific types of destinations and has yet to sufficiently address the diversity of modern tourism contexts, such as ecotourism, digital tourism, and community-based tourism. Accordingly, future research should consider developing an integrated model that combines TPB, SOR, and emotional-based theories such as Affective Events Theory to capture both rational decision-making and affective processes in shaping revisit intention.

However, this study has several limitations. First, the evidence synthesized is constrained by the scope and methodological quality of the included articles. Many studies rely on cross-sectional survey designs and self-reported data, which can introduce bias such as social desirability or common method variance. Additionally, most reviewed studies are concentrated in Asia and Europe, creating a geographical imbalance that limits the global applicability of the findings. Regions such as Africa, Latin America, and other underexplored destinations remain largely absent from current research. Furthermore, this review does not provide a critical comparison of regional or contextual differences in interpreting revisit intention. The analysis is limited to identifying key authors, theories, and antecedent factors, without examining how cultural, social, or destination-specific contexts may shape these relationships. Future research is therefore encouraged to address this gap by investigating how regional and contextual variations influence revisit behavior. Third, limitations exist in the review process itself. Although the PRISMA 2020 guidelines were followed and clear inclusion criteria were applied, this review relied solely on the Scopus, ScienceDirect, and Emerald databases. As a result, potentially relevant studies indexed in other databases such as Web of Science or EBSCOhost may have been overlooked. Moreover, no formal quality appraisal tools (e.g., risk of bias assessments) were employed due to the narrative nature of the synthesis, which limits the ability to evaluate the strength of evidence across studies.

Based on the gaps identified, future research should aim to develop more integrative conceptual frameworks that incorporate underexplored variables such as place identity, e-WOM, accessibility, and attitude. These variables hold promise for offering deeper insights into tourist behavior but remain insufficiently examined in the current literature. Scholars are also encouraged to test these models across a wider range of destinations—especially in emerging, post-pandemic, and non-traditional tourism settings to improve the generalizability of findings. Interdisciplinary approaches, such as combining behavioral theories with emotional or digital communication frameworks, should be adopted to reflect the growing complexity of tourism behavior in the digital age. Moreover, future research should broaden its geographical scope by including underrepresented regions to examine whether existing theoretical models and causal relationships remain valid across diverse cultural, economic, and social contexts. Such expansion will enhance the global relevance and external validity of revisit intention studies.

From a managerial perspective, this review provides several actionable insights for hotel managers, destination marketers, and policymakers. First, satisfaction-driven loyalty programs should move beyond general service improvement toward experience personalization. Hotels and destinations can enhance repeat visits by designing tailored post-stay engagement, such as personalized communication, exclusive member events, or loyalty rewards based on previous preferences to strengthen affective attachment. Second, destination image can be strategically leveraged for branding through storytelling and authentic content marketing that evokes emotional resonance. For example, highlighting cultural authenticity or environmental sustainability in campaigns can create memorable associations that foster revisit intentions. Third, managers should treat service quality as both a trust-building and experience-shaping mechanism. Regular staff training in intercultural communication and empathy can translate into consistent service delivery that strengthens tourists’ perceived safety and comfort. Fourth, policymakers can play a complementary role by investing in public amenities, accessibility, and digital infrastructure that improve destination convenience and inclusivity, factors empirically linked to stronger revisit intentions. Finally, initiatives that foster cultural intelligence, such as community-based tourism programs and local interaction platforms, can enhance tourists’ sense of belonging, further encouraging return visits.