From service encounters and social media interaction to revisit intention: dual pathways through tourist responses and value co-creation in culinary tourism

Abstract

Introduction:

This study examines how offline service experiences and online social media interaction are associated with revisit intention in platform-mediated culinary tourism. Drawing on the Stimulus–Organism–Response (S-O-R) framework and service-dominant logic, the study develops two complementary pathways in which tourist satisfaction and tourist engagement represent psychological responses, while value co-creation behavior functions as a behavioral mechanism linking these responses to revisit intention.

Methods:

A cross-sectional survey using convenience sampling was conducted among adult tourists who had participated in culinary tourism activities in Chongqing within the preceding 12 months. A total of 718 valid responses were obtained, including 457 online and 261 offline questionnaires. structural equation modeling was used to evaluate the measurement model and test the hypothesized relationships among service quality, social media interaction, tourist satisfaction, tourist engagement, value co-creation behavior, and revisit intention.

Results:

Service quality was positively associated with tourist satisfaction, while social media interaction was positively associated with tourist engagement. Both tourist satisfaction and tourist engagement were positively associated with value co-creation behavior. In turn, value co-creation behavior was positively associated with revisit intention. Tourist satisfaction and tourist engagement also showed positive direct associations with revisit intention. The findings further supported sequential indirect relationships linking offline service quality and online social media interaction to revisit intention through tourists' psychological responses and subsequent value co-creation behavior.

Discussion:

The findings demonstrate that revisit intention in platform-mediated culinary tourism is shaped by the interplay between offline service encounters and online social interaction rather than by either domain independently. By positioning value co-creation behavior as the behavioral link between tourists' psychological responses and future behavioral intentions, the study extends the application of the S-O-R framework and service-dominant logic to culinary tourism. The results also suggest that culinary tourism providers should simultaneously strengthen service quality, facilitate meaningful social media interaction, and create opportunities for tourists to participate actively in value creation to encourage future revisits.

1 Introduction

Culinary tourism has become an important form of experiential tourism in which food is no longer regarded merely as a supporting element of travel. Instead, local cuisine provides an important channel through which tourists encounter a destination's culture, identity, everyday life, and sense of place (Yang et al., 2024). Destinations increasingly use local food to enhance their attractiveness, communicate cultural meanings, and support the development of restaurants, markets, food festivals, and local supply chains (Gana and Hussain, 2024). Culinary experiences may also encourage tourists to interact with local enterprises, exchange destination-related information, and participate in value creation rather than passively consume standardized tourism products (Kovalenko et al., 2023). Culinary tourism therefore has implications not only for destination attractiveness but also for the formation of sustained relationships between tourists and destinations.

Chongqing provides a relevant context for examining these relationships. The city is widely recognized for hot pot, Chongqing Xiaomian, Jianghu cuisine, street food, night-time dining spaces, and visually distinctive urban foodscapes. These culinary resources function as cultural symbols embedded in Chongqing's mountainous urban environment, social traditions, and local identity. The city has also emerged as a prominent platform-mediated tourism destination in China. During the 2024 National Day holiday, the city received 22.68 million domestic tourists and increased by 14.1% year-on-year. In addition, the Chongqing online tourism market also continued to grow in the first half of 2024, and the number of online tourism trips and tourism consumption increased by 23.54% and 23.46%, respectively (Chongqing Municipal People's Government, 2024). These developments demonstrate the growing importance of recommendation systems, short videos, live-streaming, online reviews, and user-generated content in shaping the visibility of Chongqing's culinary tourism.

Nevertheless, increased online visibility does not necessarily result in sustained destination loyalty. Short videos, online reviews and platform recommendations can attract tourists to popular hotpot restaurants, food streets, night markets and check-in spots, but platform popularity alone may not be sufficient to generate revisit intention (Wang and Iahad, 2024). Some tourists may visit a destination because it is fashionable, visually appealing, or widely discussed online, while their subsequent intention to return may depend on whether the actual experience meets their expectations. Platform-generated attention may therefore produce short-term tourist flows without necessarily establishing a continuing relationship between tourists and the destination (Saini and Arasanmi, 2020). This challenge is particularly relevant to Chongqing, where the online popularity of culinary spaces may contribute to crowding, long waiting times, service delays, and elevated tourist expectations. A central practical question is therefore whether platform-generated attention can be converted into favorable experience evaluations, active tourist involvement, value co-creation behavior, and ultimately revisit intention.

Traditional tourism loyalty research has often explained revisit intention through service quality, satisfaction, destination image, perceived value or memorable tourism experiences (Wang, 2025). In culinary tourism, service quality extends beyond the food itself and includes staff responsiveness, queue management, information clarity, hygiene, payment convenience, environmental comfort, and problem-solving ability (Anton Martin et al., 2021). These service attributes may reduce uncertainty and provide tourists with a basis for evaluating whether the culinary experience has met or exceeded their expectations. Previous culinary tourism research have also shown that food authenticity, destination image, memorable culinary tourism experiences and satisfaction are all related to the revisit intention (Zhu et al., 2024). However, an explanation centered primarily on service evaluation and satisfaction may be insufficient in platform-mediated destinations because tourists increasingly develop destination relationships through digital interaction before, during, and after their visits.

Social media interaction represents a second component of the contemporary culinary tourism experience. Food-related short videos, online reviews and comments, rankings, live-streaming and interactive recommendation systems shape tourists' expectations before visiting and influence their interpretations of subsequent experiences (Abdul Latip et al., 2024). Tourists are not only recipients of destination information but also potential producers of culinary tourism content through browsing, liking, commenting, reviewing, recommending, and sharing. These activities may attract cognitive attention, generate emotional enthusiasm, facilitate interaction, and strengthen tourists' identification with a destination. Social media content and online interactions may affect perceived value, destination engagement, electronic word-of-mouth, and the revisit intention (Akbarina, 2026). Nevertheless, service quality and social media interaction have frequently been examined separately. Consequently, the distinct roles of offline service encounters and online digital interaction in forming tourists' internal responses and loyalty-oriented intentions remain insufficiently understood.

A further gap concerns the transition from internal psychological responses to proactive value co-creation behavior. Existing research on tourism co-creation has shown that tourist participation and co-created experiences are positively related to perceived value, satisfaction, memorability, and the wish to return (Carvalho et al., 2023). However, value co-creation should not be treated as an automatic consequence of exposure to favorable services or digital content. The Stimulus-Organism-Response framework explains how external stimuli are processed through internal evaluative and affective states, whereas Service-Dominant Logic conceptualizes value co-creation as a voluntary process through which actors integrate knowledge, time, emotions, feedback, skills, and social resources (Vargo and Lusch, 2004). Integrating these perspectives therefore requires an explanation of the psychological conditions under which tourists become willing to contribute their own resources to the culinary tourism experience.

This study addresses these gaps by proposing two theoretically distinct but complementary pathways. In the offline service-evaluation pathway, service quality represents an external stimulus associated with tourist satisfaction, which reflects tourists' evaluative response to the culinary experience. In the online interaction-engagement pathway, social media interaction represents a digital stimulus associated with tourist engagement, which reflects tourists' cognitive, emotional, and motivational involvement with Chongqing's culinary tourism. Tourist satisfaction and tourist engagement are conceptualized as distinct internal states rather than as observable participation behaviors. These states may create different forms of psychological readiness for value co-creation. Satisfaction may encourage resource contribution through reciprocity, whereas engagement may encourage it through sustained attention, emotional involvement, and destination identification.

Value co-creation behavior is consequently positioned as an enacted relational response through which tourists voluntarily contribute feedback, knowledge, recommendations, digital content, time, and social resources. Revisit intention is positioned as a subsequent loyalty-oriented response. This theoretical arrangement connects the psychological processing emphasized by the Stimulus-Organism-Response framework with the proactive resource integration emphasized by Service-Dominant Logic. It also avoids assuming that value co-creation is a deterministic result of service or digital stimuli. Instead, the study examines whether favorable evaluations and psychological involvement are associated with tourists' voluntary resource contribution and whether this behavior provides a relational bridge to revisit intention.

The novelty of this study lies in three related aspects. First, it distinguishes offline service quality from online social media interaction rather than treating destination stimuli as a single category. Second, it differentiates tourist satisfaction as an evaluative psychological state from tourist engagement as a participatory psychological state. Third, it positions value co-creation behavior as a behavioral bridge between tourists' internal responses and revisit intention. By integrating these elements, the study develops a theoretically parsimonious dual-pathway explanation of revisit intention in platform-mediated culinary tourism. The proposed pathways are regarded as theoretically primary rather than mutually exclusive, since service quality may also be related to engagement and social media interaction may also contribute to satisfaction.

Accordingly, this study addresses the following research questions:

• RQ1: What are the relationships between service quality and tourist satisfaction and between social media interaction and tourist engagement in culinary tourism?

• RQ2: To what extent are tourist satisfaction and tourist engagement associated with value co-creation behavior and revisit intention?

• RQ3: Do tourist satisfaction and value co-creation behavior sequentially mediate the association between service quality and revisit intention, and do tourist engagement and value co-creation behavior sequentially mediate the association between social media interaction and revisit intention?

2 Literature review

2.1 Theoretical approach

The Stimulus-Organism-Response framework (S-O-R) originates from environmental psychology and proposes that external environmental conditions are associated with behavioral responses through individuals' internal cognitive and affective states. Stimuli refer to environmental cues encountered by individuals, the organism represents the internal processes through which these cues are evaluated and experienced, and the response refers to the behavioral outcome that follows this psychological processing (Hochreiter et al., 2023). Tourism studies have applied the framework to examine the relationships between destination environments, service encounters, digital information, experiential cues, tourists' psychological evaluations, and behavioral intentions (Bai and Lai, 2025).

The two types of stimuli in this study are service quality and social media interaction. Service quality refers to the offline service experience of Chongqing culinary tourism. Tourists' perceived standards for food-related services include the quality of food and drink, dining environment, attitude of dining staff, hygiene, convenience, clarity of information, assistance in solving problems. Although service quality has often been used as a general indicator of satisfaction in research on hospitality and tourism, it refers to different things in culinary tourism because food experiences are highly embodied, time-sensitive and service-dependent. Therefore, the service quality in this study does not refer only to the performance of restaurant services but to all service experiences for tourists in culinary tourism. Social Media Interaction is an online communication stimulus. Tourists' interactions with Chongqing culinary tourism content on digital platforms include browsing, liking, commenting, sharing, reviewing, discussing and watching food-related information (Asan and Zwiegelaar, 2025). Therefore, social media interactions are not considered engagement but are rather a type of digital stimulus that may induce engagement. Earlier studies on tourism have shown that social media is now a primary source for tourists' information and a place for experience that can influence their feelings, attitudes toward travel and willingness to travel.

The two parts of the organism are tourist satisfaction and tourist engagement. Tourist satisfaction refers to tourists' overall evaluative judgement concerning whether their culinary tourism experiences met or exceeded their prior expectations (Abdou et al., 2022). Tourist engagement represents an internal cognitive, emotional, and motivational state reflected in attention, enthusiasm, absorption, interaction, and identification with the destination experience (Parilla, 2023). In this study, tourist engagement is therefore positioned as an organism state, while value co-creation behavior represents an enacted response through which tourists voluntarily contribute their knowledge, time, emotions, feedback, and social resources.

Service-Dominant Logic (SDL) provides the theoretical explanation for this transition. Value is not embedded in an offering or produced unilaterally by an enterprise; it emerges when actors voluntarily integrate knowledge, time, emotion, skills, feedback, and social connections within a service ecosystem (Belaid et al., 2025). External stimuli may create an opportunity for co-creation. Satisfaction can generate reciprocity and willingness to support a satisfactory experience, while engagement supplies the attention, emotional energy, and relational motivation required for tourists to contribute their own resources. Tourists may then write reviews, share videos, recommend local restaurants, communicate with service providers, customize dining experiences, or assist other visitors. Accordingly, the integrated framework specifies a contingent sequence in which stimuli are appraised through organism states, these states motivate voluntary resource integration, and value co-creation behavior strengthens the continuing tourist destination relationship.

2.2 Research hypotheses and conceptual model development

Service quality is the tourists' perception of how reliable, prompt, safe, convenient and otherwise satisfactory the services in a tourism experience are (Gazi et al., 2024). Service quality in the context of Chongqing culinary tourism refers to the quality of food-related service experiences for tourists during local culinary activities. The components are staff response speed, service efficiency, hygiene and cleanliness, clarity of information, ease of payment, dining environment comfort, queue control, problem-solving assistance, etc., and do not include the general quality of the entire area. Tourist satisfaction refers to the all-around evaluation that tourists have formed of culinary tourism after their experience, compared with their previous expectations (Abdou et al., 2022). Service quality can be seen as the offline service stimulus in the Stimulus-Organism-Response framework, which affects a person's perception of that service. If the food and drink facilities for tourists are convenient, clean, safe, convenient to use and high-quality, they will likely give these places good ratings. One is satisfied when the actual performance meets or exceeds the earlier expectations for that person (Schiebler et al., 2026). Gastronomy and food tourism research has also shown in previous studies that service quality and the experience of receiving such services positively affect tourist satisfaction (Yang et al., 2024). Thus, this paper puts forward the following hypotheses.

• H1: Service quality is positively associated with tourist satisfaction.

Social media interaction refers to tourists' exposure to and communication with tourism-related content through digital platforms, including browsing, liking, commenting, sharing, reviewing, and discussing culinary tourism information (Hussain et al., 2024). Within the S-O-R framework, social media interaction functions as a digital stimulus that may be associated with tourists' cognitive attention, emotional enthusiasm, absorption, and identification with a destination. Interactive food-related content allows tourists to acquire destination knowledge, communicate with other users, express personal preferences, and develop a sense of connection with Chongqing's culinary culture. These processes correspond to tourist engagement rather than tourist participation because they primarily represent an internal state of psychological involvement. Previous tourism research has similarly found that interactive social media content is positively related to tourists' attention, emotional attachment, and engagement with destination experiences (Fajar and Erlangga, 2025; Moliner et al., 2023). Therefore, the following hypothesis is proposed.

• H2: Social media interaction is positively associated with tourist engagement.

Tourists' value co-creation behavior refers to tourists' voluntary contribution of knowledge, time, emotions, feedback, recommendations, and social resources to the development and extension of a tourism experience (Gu and Zhu, 2023). Value co-creation behavior is not the same as favorable communication. Tourists actively provide knowledge, emotions, time, suggestions and social resources to improve and spread the experience of culinary tourism. According to the concept of service-dominant logic, satisfied tourists are more likely to be active participants in resource integration rather than passive recipients (Xie et al., 2020). If a tourist has a good meal and is happy with their choice, they will be willing to spend more time or money at that restaurant. Therefore, satisfaction can be converted into value co-creation behavior when positive evaluations lead to a desire for reciprocation, support and participation in the destination experience. Positive experiences motivate tourists to act in a way that supports and participates in the construction of the destination (Ward and Berno, 2011), and both good tourist experiences and satisfaction are closely related to tourists' willingness to participate in and contribute to the value creation of the destination (Rueda-López et al., 2026). Recently, some studies have found that co-creation of tourism is associated with higher levels of consumer participation and the establishment of long-term consumer-tourism relationships (Zhang, 2023).

• H3: Tourist satisfaction is positively associated with tourists' value co-creation behavior.

Service-dominant logic is a mode of value creation that also involves the resources of various parties in the process. Therefore, it is expected that engaged tourists will be more likely to offer their knowledge, emotions, time and other social resources in the culinary experience. Engaging tourists in their daily lives at the destination can inspire them to make meaning through participation. Co-creation is also closely related to participation; highly involved tourists generally engage more actively in the construction of services with service providers, other tourists and the destination community (Seyfi et al., 2021). Co-creation of tourism value increasingly requires the active participation and collaboration of tourists, and thus has deviated from the traditional model of one-way service provision (Salem et al., 2026).

• H4: Tourist engagement is positively associated with tourists' value co-creation behavior.

Based on service-dominant logic, resources are generally the outcome of joint use and collaboration rather than the product of exclusive provision. Tourists who participate in value co-creation are not merely consuming a culinary tourism product (Fan et al., 2025). They are also using their own knowledge, emotions, time and other social resources to experience the place. Participation in the above activities will help visitors create new experiences of the place and feel more connected with it. Tourists post comments and communicate with staff and other visitors on social media about their travel experiences, local dining spots, etc., thus forming social ties in that place. Based on the theory of relational marketing, by making sustained investments in the relationship, one can build closeness and trust with the other side over a long period of time; as a result, these parties will be more willing to continue in this way (Morgan and Hunt, 1994). An increase in the level of participation and interaction for tourists is expected to increase their sense of belonging and intention to revisit. The above investments will likely make tourists feel more connected to the place and wish to return here again. Psychological ownership theory holds that people feel a sense of ownership over something they have contributed to through their own efforts, knowledge and participation (Pierce and Jussila, 2011). Research has shown that the sense of ownership people feel through their own participation in and co-creation of activities is likely to motivate them to remain loyal to the brand and purchase multiple times (Phan Tan, 2024). In a tourist area, tourists who create content and experiences about this place for themselves are more likely to feel a sense of belonging and want to protect the place, so they will be more likely to visit again. Research has shown that a high degree of destination attachment is positively correlated with both the intention to visit again and destination loyalty (Wei et al., 2024). Co-creation activities provide people with rich experience and emotion, thus fostering an attachment to the destination. As tourists feel closer to a place through active participation, they are more likely to visit again in the future. Earlier research by tourists and hospitality experts has found that a good travel experience and satisfaction are related to tourists' willingness to participate in, interact with, and help create the value of a destination (Rueda-López et al., 2026).

• H5: Tourists' value co-creation behavior is positively associated with revisit intention.

Satisfied tourists in culinary tourism are more likely to visit again because positive evaluations of food quality, service encounters, atmosphere, authenticity and cultural experiences have reduced their sense of risk and strengthened their emotional attachment to the destination. Satisfied tourists will be more likely to stay longer; therefore, positive evaluations of the post-consumption experience are required to foster long-term trust in people's minds (Nguyen-Viet et al., 2020).

Tourist engagement refers to the cognitive, emotional and behavioral participation of tourists in their experience of a place, such as attention, interest, immersion, participation and identity (Seyfi et al., 2021). Engagement is a higher form of satisfaction that involves active participation by tourists in their travel experience; thus, engaged tourists are not only satisfied but also actively pay attention to, participate in and feel a strong emotional attachment to the destination. Categories of interaction in culinary tourism activities include learning about local food culture, communicating with service staff and other tourists, sharing dining experiences, and building emotional connections with the food environment in Chongqing. Destination-oriented customer engagement can make people want to visit more often by forming an emotional connection between the tourist and the place, thus increasing their sense of place (Zheng and Khong-Khai, 2025). Therefore, the following hypotheses are put forward:

• H6: Tourist satisfaction is positively associated with revisit intention.

• H7: Tourist engagement is positively associated with revisit intention.

Service quality is an external factor in the S-O-R model that affects the tourists' internal assessment of the service, and thus inspires them to take the initiative in value co-creation. A good evaluation results from the actual service meeting and exceeds people's previous expectations (AlSokkar et al., 2024). If they are met with a good experience, the tourists will be more likely to behave reciprocally and participate actively in society, such as offering feedback, communicating with service providers, sharing their dining experiences and spreading the local food culture. Service-dominant logic further proposes that tourists are value co-creators by integrating their knowledge, emotions, experiences and social resources in the tourism process (Fan et al., 2025). Xie et al. (2020) have found that the value co-creation behavior of tourists can increase the sense of value and satisfaction in tourism. Monteiro et al. (2023) have found that customer co-creation is positively associated with the intention to revisit tourism services. Xu et al. (2021) have also shown that value co-creation behavior can increase destination loyalty and the wish to return. Fu (2025) has also listed some reasons why tourists want to visit the site again.

• H8a: Tourist satisfaction and value co-creation behavior sequentially mediate the association between service quality and revisit intention.

Social media interactions are digital stimulations in the S-O-R model that help tourists feel more connected to a place. Images and interactions on social media can stimulate consumer participation and spread electronic word-of-mouth for a place (Matusin et al., 2023). From the perspective of service-dominant logic, engaged tourists are more likely to combine their knowledge, emotions and social resources in the process of value co-creation. Digital communication technology has enabled more participation by tourists in value co-creation activities in tourism and hospitality, and sharing travel experiences on social media is now a way for destinations to foster value co-creation and attract tourists (Armutcu et al., 2023). Satar et al. (2023) have also discovered that destination-based customer engagement can be converted into a wish for a repeat visit through co-creation.

• H8b: Tourist engagement and value co-creation behavior sequentially mediate the association between social media interaction and revisit intention. Figure 1 is the conceptual model of this study.

Figure 1

3 Methods

3.1 Data collection

A cross-sectional quantitative survey was conducted to examine associations among service quality, social media interaction, tourist satisfaction, tourist engagement, tourists' value co-creation behavior, and revisit intention in Chongqing culinary tourism. This design is suitable for evaluating a theoretically specified covariance structure, but it does not establish temporal precedence or causal direction. Accordingly, all structural coefficients are interpreted as statistical associations. Quantitatively, many people have been studied in tourism and hospitality, and this kind of data is more standardized and suitable for applying multivariate statistics to test theoretical models (Huang et al., 2025).

The target population comprised adult tourists who had visited Chongqing and participated in local culinary tourism activities during the preceding 12 months. Chongqing was chosen as the study area because it is one of China's well-known culinary tourism cities, famous for hotpot, Chongqing xiaomian, Jianghu cuisine, street food, food streets and lively night-time dining (Cheshmehzangi, 2025). Therefore, tourists who have recently participated in culinary tourism in Chongqing were selected as the suitable subjects for this study on the proposed relationships among service quality, social media interaction, satisfaction, engagement, value co-creation behavior, and revisit intention.

Data were collected from May 10, 2026, to June 8, 2026, and ethical approval had been obtained. Given that culinary tourists are highly mobile and geographically dispersed, and it is difficult to construct an all-encompassing sample list, this study used convenience sampling (Golzar et al., 2022) have used convenience sampling in tourism research to study an inaccessible target group and aim to test theory rather than generalize to the whole population. To increase the convenience and applicability of samples in a particular environment, both online and offline sources were used. Wenjuanxing was used to create an online survey and distributed via WeChat, Douyin, Xiaohongshu, Weibo, QQ, tourism discussion groups, food-related online communities and university networks. The above platforms were considered suitable because, as shown in Kumar and Ramesh's (2025) research, they have become indispensable sources for tourism information queries and experience sharing on social media platforms. For the offline survey, QR-code questionnaires were distributed in the main culinary tourism clusters of Chongqing, such as Hongyadong, Ciqikou Ancient Town, Jiefangbei Pedestrian Street, Shancheng Alley, Nanbin Road Food Street, and other popular dining and tourist spots. The same questionnaire, screening criteria, informed consent statement and quality-control procedures were used for both online and offline participants. The first two questions of the questionnaire were added at the beginning to verify the accuracy of the data. A total of 850 questionnaires were distributed and 782 were collected. Excluding the 64 invalid answers, a total of 718 valid questionnaires were collected and analyzed, with an actual collection rate of 84.5%. Invalid responses include questionnaires that fail the screening questions, have an excessive number of missing values, show straight-line or patterned answers, are logically inconsistent, or are completed in an unreasonably short time. Among the final valid responses, 457 were collected online (63.6%) and 261 were collected offline (36.4%).

Some Quality Control Measures Have Been Taken to Improve Data Quality. Duplicate submissions in the online responses were excluded based on Wenjuanxing records, response time, device information (where available), and logical consistency checks. For the offline response, a trained research assistant provided the screening criteria, had respondents complete the questionnaire only once, and confirmed that all required items had been filled in before submitting.

The first list of observed items was 46. Based on the recommendations for structural equation modeling, a minimum sample size was determined by a subject-to-item ratio of 15:1, and thus, at least 690 responses were needed (Wolf et al., 2013). The final sample of 718 valid responses met the above condition. After item reduction, 39 observed items were kept for the final CFA and SEM analysis. Therefore, the sample size will be adequate for both testing the measurement model and the structural model.

3.2 Measurement tools and scale construction

All the indicators are based on scales from previous research in tourism, hospitality and consumer behavior. Since the research focused on Chongqing culinary tourism, the original measurement items were modified to reflect local food-related experiences, such as hotpot consumption, Chongqing xiaomian, street-food exploration, food-street visits, food service encounters, and social media interaction with Chongqing culinary content. The six latent constructs of the questionnaire are service quality, social media interaction, tourist satisfaction, tourist engagement, tourists' value co-creation behavior and revisit intention. All of the items were rated on a 5-point Likert scale, and the options for the rating were “strongly disagree” (1) and “strongly agree” (5). A five-point Likert scale is generally employed in research by tourists and other consumers because it has a certain degree of variation but is also relatively simple for respondents to understand and fill out.

Initially, the 15 items were used to measure service quality. In this paper, service quality refers to the tourists' perceptions of food-related service encounters during their culinary tourism experiences in Chongqing. The items are: response speed, information clarity, communication efficiency, service attitude, food safety, dining environment, convenience of payment, problem-solving ability and accessibility. After refining the items, 11 service quality items were finally selected.

Five items for social media interaction were adapted from Asan and Zwiegelaar (2025). The constructed phenomenon shows how tourists have interacted with Chongqing culinary tourism content online. Based on previous studies of tourism, social media interaction is now generally divided into passive and active forms of participation in the study (Valkenburg et al., 2022). Passive interaction included browsing short videos, viewing food recommendations and reading online reviews; active interaction covered likes, comments, shares, discussions, posts and reviews of culinary tourism content (Bai and Lai, 2025).

Three items for measuring tourist satisfaction were adopted from Abdou et al. (2022). Tourist satisfaction is the general level of their experience of culinary tourism in Chongqing and how well that experience has met or exceeded their expectations. Satisfaction has been known to drive tourism's demand for repeat visits among visitors for a long time (Stylos and Bellou, 2019). Therefore, the construct will focus on satisfaction with Chongqing culinary tourism rather than overall satisfaction.

The first 15 items in Seyfi et al. (2021) were adapted to measure tourist engagement. The scale captured tourists‘ cognitive, emotional, and motivational involvement through enthusiasm, attention, absorption, interaction, and identification. Tourist engagement was conceptualized as an internal psychological state rather than as tourists' observable participation in value creation. Following the pilot-test refinement, TE13–TE15 were removed, and 12 items were retained for the formal analysis.

Four items for tourists' value co-creation behavior were adapted from Zhou et al. (2025). The items assessed tourists' observable contributions to the culinary tourism experience, including providing suggestions and feedback, communicating personal preferences, cooperating with service providers or other tourists, and sharing culinary experiences and recommendations. Unlike tourist engagement, which represents psychological involvement, value co-creation behavior captures the voluntary enactment of resource integration within the tourism experience.

The four items for measuring intention were adapted from Hurdawaty et al. (2025) and used. Measure how willing and likely tourists are to return to Chongqing for food and drink tourism and how often they will recommend Chongqing to others for this purpose.

Systematically modified to produce the final questionnaire. First, based on the demands of Chongqing culinary tourism, the original English-language scales were adapted. Secondly, the bilingual researchers were well-versed in tourism and hospitality research, and thus translated the items into Chinese. Third, back-translation was performed to ensure that the Chinese and English versions had the same meaning. Fourthly, a group of scholars evaluated the modified questionnaire to determine its content validity, fit with local conditions, etc. Finally, a trial run was conducted before the official data collection to identify any problems in the wording, translation or comprehension by the respondents. The complete English and Chinese versions of the questionnaire are provided as Supplementary Material for transparency and reproducibility.

3.3 Data analysis

Several steps of data analysis were carried out successively.

First, 30 people who had visited Chongqing and taken part in the local food tourism activities were selected as the pilot test subjects. A pilot sample of about 30 people is generally considered adequate to find unclear wording, translation issues, difficulty in understanding the items, and basic reliability problems in questionnaires (Kunselman, 2024). Cronbach's alpha, corrected item-total correlation, and Cronbach's alpha if an item was excluded were used for evaluation. Based on general psychometric norms, a Cronbach's α coefficient greater than 0.70 was considered acceptable, and items with corrected item-total correlations less than 0.30 were ruled out. Before the above-mentioned main analysis, some initial assessments of the reliability and appropriateness of the measurement items have been performed. All the indicators of the various subscales met the requirements for internal consistency and had a Cronbach's α > 0.70. Some of the items have poor item performance. SQ4 and SQ15 had corrected item-total correlations of less than 0.30 for service quality, and SQ10 and SQ11 also showed relatively low item-total correlations; thus, they were removed to improve the reliability of the construct. Therefore, SQ4, SQ10, SQ11 and SQ15 were deleted. TE6 had a low corrected item-total correlation for tourist engagement, and TE3 and TE13 showed weak item performance; thus, these three items were also removed. After item refinement, Cronbach's alpha increased to 0.920 for service quality and to 0.926 for tourist engagement. The remaining factors showed good reliability and were therefore kept. Therefore, the modified measurement instrument was found to be suitable for the following CFA and SEM analyses. The KMO values were 0.721 and 0.842, respectively, and thus met the criteria for the first validity test. Overall, the results of the pilot test show that the measurement items have good reliability and are contextually applicable; thus, they can be used in the official survey.

Then, the descriptive statistics of the respondents' demographics and the distribution of the main variables were presented. Reliability analysis was conducted using Cronbach's alpha and composite reliability. Values of 0.70 or higher were deemed acceptable, and thus had good internal consistency (Chan and Idris, 2017). Perform Confirmatory Factor Analysis (CFA) for model validation. Standardized factor loadings, average variance extracted and composite reliability were used to conduct convergent validity tests. Factor loadings > 0.60, AVE > 0.50 and CR > 0.70 were considered acceptable (Fornell and Larcker, 1981). Discriminant validity was examined by the Fornell-Larcker criterion and the heterotrait-monotrait ratio; values below 0.85 in the HTMT indicated that the constructs were well-separated (Hamid et al., 2017).

Because all constructs were measured using the same self-reported questionnaire at a single point in time, Harman's single-factor test was conducted to assess the potential influence of common method bias. All 39 retained measurement items were entered into an unrotated exploratory factor analysis using principal component extraction. Common method bias would be considered a serious concern if a single factor emerged or if the first unrotated factor accounted for more than 50% of the total variance (Fuller et al., 2016; Podsakoff et al., 2003). This diagnostic was used to determine whether a dominant common factor accounted for most of the covariance among the measurement items.

To assess whether the survey mode was associated with systematic differences in the responses, the 457 online responses and 261 offline responses were formally compared. Composite scores for service quality, social media interaction, tourist satisfaction, tourist engagement, value co-creation behavior, and revisit intention were calculated by averaging the retained items of each construct. Hotelling's T² test was first conducted to assess the overall multivariate difference between the two survey-mode groups. Welch's independent-samples t tests were then used to compare the individual construct means because the two groups had unequal sample sizes. Holm-adjusted p values were calculated to control the familywise error rate across the six comparisons. Hedges' g was reported as an effect-size measure, with absolute values of approximately 0.20, 0.50, and 0.80 indicating small, moderate, and large differences, respectively.

Finally, Structural equation models were used to test the above hypotheses and sequential mediation effects. SEM was selected to explore several latent variables and their direct and indirect connections at the same time (Wulandari, 2022).

4 Results

4.1 Descriptive statistical analysis

There were 718 validly answered questionnaires. The proportion of women was 56.7%, and the proportion of men was 43.3%; there were slightly more women than men. In terms of age, the majority of the respondents were in the 26–35 age group (42.3%), followed by those aged 18–25 (31.3%), indicating that young and young-middle-aged tourists are the main tourists of Chongqing culinary tourism. Educational background of the respondents is shown below: more than half of them have a bachelor's degree (54.6%), and 21.6% have a master's degree or higher; the sample has a relatively high level of education. The sample profile indicates that the respondents were relatively young, highly educated, and active on social media platforms. The three platforms were used to some extent: Douyin (80.4%), Xiaohongshu (59.7%), and Weibo (33.1%). Most of the respondents had looked up information about Chongqing cuisine before traveling (86.9%), and 91.8% were somewhat influenced by social media in their choice of restaurants or organization of a food tour during their trip. In addition, 80.8% of the respondents had participated in some form of food-related posting, sharing or commenting behavior. Among the culinary tourism activities, those with the highest participation were hotpot-related rituals and interaction with service staff (73.0%), followed by exploration of Jianghu Cai and specialty small shops (64.2%). Therefore, the sample is suitable for this study, and the respondents are both consumers of food and participants in the activities of Chongqing culinary tourism.

The demographic characteristics and culinary tourism participation profile of the respondents are presented in Table 1. Based on the above descriptive statistics, all the factors of Chongqing culinary tourism were rated positively by the respondents, with their means exceeding the midpoint of the five-point scale (Table 2).

4.2 Reliability analyses

Table 3 presents the internal-consistency results for the 39 items retained after formal measurement purification. The Cronbach's alpha values were between 0.767 and 0.926, and all exceeded the required threshold of 0.70, thus satisfying the conditions for good internal consistency of the constructs. Tourist engagement (α = 0.926) and service quality (α = 0.920) showed the highest reliability, and social media interaction (α = 0.865), tourists' value co-creation behavior (α = 0.859), and revisit intention (α = 0.857) were also reasonably reliable. Tourist satisfaction had the lowest alpha value (α = 0.767), but it was still in the acceptable range. Based on the above results, the measurement scales have demonstrated reliability and are thus suitable for the following validity tests and structural equation models.

As shown in Table 4, the KMO value is 0.956; it exceeds the standard threshold of 0.70 and is thus considered to be a good sample. Bartlett's test of sphericity was significant, χ² = 16,102.380, df = 741, p < 0.001; therefore, the correlation matrix was not an identity matrix and the retained items were sufficiently correlated for factor analysis. Thus, the data were suitable for the following confirmatory factor analysis.

4.3 Common method bias assessment

Harman's single-factor test was conducted using all 39 measurement items retained in the final model. The results of Harman's single-factor test are presented in Table 5. The unrotated principal component analysis extracted six factors with eigenvalues greater than 1, which jointly accounted for 61.810% of the total variance. The first factor had an eigenvalue of 13.939 and explained 35.742% of the total variance. This percentage was below the commonly applied threshold of 50%, and no dominant single factor emerged. These results suggest that common method bias was unlikely to constitute a serious threat to the interpretation of the relationships examined in this study. Nevertheless, Harman's single-factor test is a diagnostic procedure and does not completely exclude the possibility of residual common method variance.

4.4 Survey mode comparison

Table 6 presents the comparison of construct scores between the online and offline respondents. Hotelling's T² test indicated that the combined set of six construct scores did not differ significantly between the online and offline groups, T² = 6.881, F_{(6, 711)} = 1.139, p = 0.338. The individual comparisons were likewise non-significant. The unadjusted p values ranged from 0.065 to 0.967, and all Holm-adjusted p values exceeded 0.05. The largest difference was observed for tourist engagement, with online respondents reporting a slightly higher mean than offline respondents. However, the difference was not statistically significant, t_(555.67) = 1.847, p = 0.065, Holm-adjusted p = 0.392, Hedges' g = 0.142.

The internal consistency of all six scales was satisfactory in both groups. Cronbach's alpha coefficients ranged from 0.776 to 0.929 for the online sample and from 0.752 to 0.921 for the offline sample.

4.5 Confirmatory factor analysis

Table 7 is the fit indices of the measurement model. The results show that the model is a good fit for the data. The χ²/df value was 2.214; it is less than the upper bound of 3, and the RMSEA value was 0.041, so the model has a good fit. In addition, GFI (0.912), AGFI (0.901), NFI (0.925), TLI (0.956) and CFI (0.958) all exceeded the recommended value of 0.90. The above results indicate that the overall fit of the measurement model was good, and the retained items adequately represented their corresponding latent variables. Therefore, the model met the conditions for further verification and structural equation modeling.

Table 8 shows the results of convergent validity for the measurement model, such as composite reliability (CR) and average variance extracted (AVE). The CR values were between 0.769 and 0.928, all of which exceeded the required threshold of 0.70, and the constructs were deemed reliable. The AVE values were between 0.519 and 0.612, all exceeding the threshold of 0.50, and thus all constructs accounted for more than half of the variance in their retained indicators. Among the constructs, value co-creation behavior (AVE = 0.612) and revisit intention (AVE = 0.611) had relatively strong convergent validity. In short, the above results show that the measurement model has achieved sufficient convergent validity and is suitable for the subsequent discriminant validity and structural model tests.

Table 9 shows the discriminant validity results based on the Fornell-Larcker criterion, and the diagonal values are the square roots of AVE. The HTMT results are presented in Table 10. Based on the above results, the square root of AVE for each construct was between 0.720 and 0.782, and all these values exceeded their correlations with other constructs. Therefore, the quality of services, social media interactions, tourist satisfaction, tourist engagement, value co-creation behavior and a desire to return were not all the same. Although some of the correlations were relatively large, such as the relationship between value co-creation behavior and revisit intention (r = 0.678), they still did not meet the corresponding square roots of AVE. Thus, the measurement model met the requirement of discriminant validity and was appropriate for the following structural equation model.

Multicollinearity of the structural model was checked using the variance inflation factor (VIF) value based on construct scores before testing. The VIF values of the predictors for value co-creation behavior, tourist satisfaction and tourist engagement, were both 1.143. The VIF values of the predictors of revisit intention are 1.663 for value co-creation behavior, 1.402 for tourist satisfaction, and 1.373 for tourist engagement. All VIF values were significantly less than the typical upper limit of 5.0. Therefore, multicollinearity was not a serious problem in the structural model.

4.6 Structural equation modeling

Table 11 shows the general fit indices of the structural equation model after eliminating the weak measurement items. The structural model demonstrated acceptable fit on most reported indices, including χ²/df, RMSEA, IFI, TLI, and CFI. However, the SRMR value of 0.098 exceeded the conventional guideline of 0.08, indicating some residual model-data discrepancy. The overall fit should therefore be interpreted as mixed but generally adequate for hypothesis testing rather than uniformly strong. Specifically, the χ²/df value was 2.403; it met the upper bound of 3, and the RMSEA value was 0.044, well within the limit of 0.08. GFI (0.899) and AGFI (0.892) also exceeded the acceptable limit of 0.80, and IFI (0.938), TLI (0.934), and CFI (0.938) were all above 0.90. Based on the above results, the proposed structural model fits the cleaned data reasonably well and is suitable for the next step of hypothesis testing.

Table 12 presents the direct structural associations. All seven hypothesized coefficients were statistically significant at p < 0.001. Service quality was positively associated with tourist satisfaction (β = 0.447), while social media interaction was positively associated with tourist engagement (β = 0.480). Tourist satisfaction and tourist engagement were positively associated with value co-creation behavior, with standardized coefficients of 0.395 and 0.372, respectively. Value co-creation behavior was positively associated with revisit intention (β = 0.338). Tourist satisfaction (β = 0.207), and tourist engagement (β = 0.299) also retained significant direct associations with revisit intention. H1–H7 were therefore supported as hypothesized associations. These findings should not be interpreted as evidence of causality because the data were cross-sectional.

The structural model explained 31.1% of the variance in tourist satisfaction, 31.2% in tourist engagement, 47.3% in value co-creation behavior, and 52.7% in revisit intention. These values indicate moderate but incomplete explanatory power. The model accounted for nearly half of the variance in value co-creation behavior and more than half of the variance in revisit intention. However, substantial residual variance remained, particularly in tourist satisfaction and tourist engagement. This suggests that additional factors, such as perceived authenticity, food quality, destination image, crowding, price fairness, prior destination familiarity, cultural identification, novelty seeking, and intensity of social media use, may contribute to these constructs. Table 13 shows the bootstrap results of the sequential mediation effects. The indirect association between service quality and revisit intention through tourist satisfaction and value co-creation behavior was statistically significant, with an estimate of 0.060 and a 95% confidence interval ranging from 0.043 to 0.077. The indirect association between social media interaction and revisit intention through tourist engagement and value co-creation behavior was also statistically significant, with an estimate of 0.061 and a 95% confidence interval ranging from 0.044 to 0.079. Because neither confidence interval included zero, H8a and H8b were supported.

Table 14 shows the total effects of the main constructs in the structural model. Based on the above results, all bias-corrected 95% confidence intervals excluded zero, and thus the total effect was statistically significant. Among the preceding paths, social media interaction had the largest positive effect on tourists‘ engagement (0.480), followed by service quality in influencing tourists' satisfaction (0.447); thus, it can be seen that both online interaction and offline service experiences are relatively influential factors in affecting people's minds. The Total Effect of revisit intention was highest among all, with a coefficient of 0.425, followed by tourist satisfaction (0.341) and value co-creation behavior (0.338). The total effect of tourist satisfaction and tourist engagement on revisit intention was larger than the direct effects because they included both the direct path and the indirect path through value co-creation behavior. Service quality and social media interaction were also significantly associated with a larger degree of re-visit intention, and the effect sizes were 0.152 and 0.204, respectively. Based on the above results, revisit intention in Chongqing's culinary tourism is jointly driven by service evaluation, digital interaction, psychological response and value co-creation behavior.

Table 15 presents the comparison of the hypothesized model with the full cross-path model and the parallel value co-creation model. The hypothesized model was compared with a full cross-path model and a parallel value co-creation model. The full cross-path model produced better absolute and incremental fit on several indices, including SRMR, CFI, and TLI. In particular, its SRMR of 0.039 was below the conventional 0.08 guideline, whereas the SRMR of the hypothesized model was 0.098. By contrast, the hypothesized model produced lower AIC and BIC values, indicating greater parsimony. The hypothesized model was therefore retained primarily because it represented the a priori theoretical distinction between the offline service-evaluation pathway and the online interaction-engagement pathway using fewer structural relationships. However, it did not demonstrate superior performance on every fit criterion. The full cross-path model remains a plausible alternative, suggesting that service quality and social media interaction may each be associated with both tourist satisfaction and tourist engagement. Accordingly, the proposed model should be interpreted as a theoretically parsimonious explanation.

Figure 2 presents the final structural model for revisit intention in Chongqing culinary tourism.

Figure 2

5 Discussion

5.1 Key findings

5.1.1 Dual pathways associated with revisit intention

The findings support two theoretically distinct but complementary pathways associated with revisit intention in platform-mediated culinary tourism. The first is an offline service-evaluation pathway in which service quality is associated with tourist satisfaction. The second is an online interaction-engagement pathway in which social media interaction is associated with tourist engagement. Tourist satisfaction and tourist engagement are subsequently associated with value co-creation behavior and revisit intention. These results suggest that tourists' loyalty-oriented intentions are related not only to their evaluations of food and service performance but also to their continuing cognitive, emotional, and relational involvement with the destination.

The two pathways represent different psychological processes. The offline pathway is primarily evaluative because tourists use service-related information to determine whether their culinary experience met or exceeded prior expectations. The online pathway is primarily participatory because social media interaction may attract attention, stimulate emotional involvement, support communication, and strengthen identification with Chongqing's culinary culture. Satisfaction and engagement may therefore create different forms of psychological readiness for tourists to contribute their own resources to the destination experience.

The findings extend satisfaction-centered explanations of culinary destination loyalty by indicating that favorable evaluation alone may not fully explain revisit intention in a platform-mediated environment. Tourists may also maintain a relationship with a destination through online attention, cultural identification, communication, and content sharing. Nevertheless, the results should not be interpreted as evidence that the two pathways are causally independent or mutually exclusive. Service quality may also be associated with tourist engagement, while social media interaction may contribute to satisfaction by shaping information quality and prior expectations. The cross-sectional data support the proposed associations but do not establish their temporal or causal order.

5.1.2 Service quality as the foundation of tourist satisfaction

The positive association between service quality and tourist satisfaction indicates that food alone does not determine tourists' evaluations of culinary tourism. Tourists also assess staff responsiveness, hygiene, food safety, service reliability, information clarity, payment convenience, environmental comfort, queue management, and problem-solving support. These attributes are particularly relevant in Chongqing, where popular hot pot restaurants, food streets, night markets, and highly visible online check-in locations may experience crowding, long waiting times, and service delays. Under these conditions, reliable service delivery may reduce uncertainty and narrow the gap between platform-generated expectations and the experience encountered at the destination.

This finding is consistent with previous tourism and hospitality research showing that service quality is closely associated with satisfaction and post-visit behavioral intentions (Singh and Bhuyan, 2026). It also supports the argument that tourists evaluate an integrated destination experience rather than assessing individual service encounters in isolation (Yacoub et al., 2025).

Although tasting local food is central to culinary tourism, tourists' evaluations may also depend on whether they can access culinary spaces conveniently, obtain accurate information, wait for services within a reasonable period, complete payments efficiently, and consume food in a safe and comfortable environment. Service quality in culinary tourism should therefore be understood as a destination-level experience extending beyond food quality or restaurant service alone.

Evidence from European culinary destinations provides a useful comparison. Research involving international visitors to a Spanish culinary destination found that perceived value and sensory experience were associated with intentions to repeat the culinary experience, while iconic food strengthened some of these relationships (Anton Martin et al., 2021). The Chongqing findings are broadly consistent with this evidence because they indicate that distinctive cuisine may attract tourists, but the wider experiential and service context remains important to post-visit evaluation. However, Chongqing differs from many European culinary destinations because tourists' expectations may be intensified by the rapid circulation of short videos, rankings, and user-generated recommendations. The service-quality and satisfaction relationship may therefore be especially sensitive to discrepancies between highly curated online representations and crowded offline experiences.

The finding does not imply that service quality necessarily causes satisfaction. Instead, it indicates that tourists who reported more favorable service experiences also tended to report higher satisfaction. Longitudinal or experimental research would be required to establish whether improvements in particular service attributes produce subsequent changes in satisfaction.

5.1.3 Social media interaction as a driver of tourist engagement

The association between social media interaction and tourist engagement indicates that digital platforms are not merely promotional channels. They also provide informational, emotional, and relational environments through which tourists may become psychologically involved with a culinary destination. Short videos, live-streaming, online reviews, travel blogs, rankings, and user-generated content can introduce tourists to Chongqing‘s food culture before a visit and maintain their attention after the physical experience has ended (Lin et al., 2025). Chongqing's iconic culinary elements, including hot pot culture, Chongqing Xiaomian, Jianghu cuisine, food streets, and night markets, are continuously represented and reinterpreted through digital platforms. These representations may provide destination knowledge, generate anticipation, stimulate emotional responses, and enable communication with content creators, local residents, and other travelers. In this sense, social media interaction is associated with tourist engagement because it may strengthen attention, enthusiasm, absorption, interaction, and identification with the destination. It should not be interpreted as tourist participation itself, since engagement represents an internal psychological state rather than the observable contribution of resources.

The finding is consistent with previous research indicating that social media information and interaction are associated with destination perceptions, travel intentions, and electronic word-of-mouth (Wang and Yan, 2022). Digital platforms may also allow tourists to participate in the interpretation of culinary symbols by connecting food experiences with narratives of local culture and identity (Del Moral, 2025).

Rather than simply receiving official destination messages, tourists may compare reviews, communicate with other users, reinterpret food traditions, and incorporate culinary experiences into their own online identities. These processes may deepen their psychological involvement with the destination.

Evidence from Malaysia provides a relevant Southeast Asian comparison. Research on culinary heritage destinations found that travelers use social media both to consume and produce culinary information. Authenticity, curiosity, nostalgia, and visually compelling content were important to their information-search and travel behavior, while travelers frequently used their own experiences to generate content for subsequent visitors (Abdul Latip et al., 2025). This pattern is consistent with the Chongqing findings because social media interaction appears to connect destination information, emotional involvement, and continued content circulation. However, the Chinese digital environment is characterized by highly integrated platforms such as Douyin, Xiaohongshu, and WeChat, through which discovery, discussion, recommendation, and sharing may occur within a relatively concentrated platform ecosystem. The strength and form of the interaction-engagement association may therefore vary across national and technological contexts.

5.1.4 Value co-creation behavior as an enacted relational response

A central finding of the study is that value co-creation behavior is associated with both tourists' internal psychological responses and revisit intention. Value co-creation behavior represents the behavioral stage at which tourists may express favorable evaluations and psychological involvement through observable resource contributions. In Chongqing culinary tourism, these contributions may include communicating taste preferences, providing service feedback, cooperating with restaurant employees, posting reviews, sharing dining experiences, recommending local businesses, participating in food-related discussions, and helping other tourists understand local food culture. From the perspective of Service-Dominant Logic, tourists engaging in these activities function as resource integrators because they contribute time, knowledge, emotions, experience, social relationships, and digital influence to the destination ecosystem (Susanto et al., 2024).

The finding helps explain the theoretical transition from the reactive psychological process described by the S-O-R framework to the proactive resource integration emphasized by Service-Dominant Logic. Service quality and social media interaction provide experiential and digital stimuli, while satisfaction and engagement represent internal responses. Value co-creation behavior is the stage at which tourists may voluntarily enact those internal responses through resource contribution.

This transition is not automatic. A tourist may be satisfied without providing feedback or sharing an experience, and an engaged tourist may remain psychologically interested without actively contributing resources. Satisfaction and engagement should therefore be viewed as conditions associated with readiness for value co-creation rather than deterministic causes of co-creation. Tourists retain agency in deciding whether, when, and how to contribute. This distinction addresses the conceptual tension between S-O-R, which is frequently interpreted as a reactive framework, and Service-Dominant Logic, which emphasizes proactive and voluntary resource integration.

Research in Yogyakarta, Indonesia, similarly found that tourists and tourism providers co-create food experiences through interaction, customization, and co-production and that these activities contribute to changes in the wider destination foodscape (Park and Widyanta, 2022). The Chongqing results extend this perspective to a highly platform-mediated context in which value co-creation may occur through both physical service encounters and online content production. Whereas co-creation in an emerging Indonesian food destination may depend strongly on direct interactions between tourists and suppliers, Chongqing tourists can continue contributing destination value through reviews, recommendations, videos, and discussions after the physical visit has ended.

Value co-creation behavior may also represent a relational investment. By contributing personal resources, tourists may develop stronger psychological ownership, attachment, and commitment to the destination. Revisit intention can consequently be interpreted not only as a future travel choice but also as an intention to maintain an existing tourist-destination relationship. However, the cross-sectional results do not establish that co-creation necessarily produces stable loyalty. It is also possible that tourists who already possess strong revisit intentions are more willing to participate in value co-creation. Longitudinal evidence is required to clarify this temporal direction.

5.1.5 Satisfaction and engagement as complementary psychological mechanisms

Tourist satisfaction and tourist engagement were associated with revisit intention through related but conceptually distinct mechanisms. Satisfaction represents an evaluative judgment concerning whether the culinary experience met or exceeded expectations. Tourist engagement represents sustained cognitive attention, emotional enthusiasm, absorption, interaction, and identification with the destination. Engagement should not be characterized as a higher form of satisfaction because it does not represent a more intense point on the same psychological continuum. Instead, the two constructs capture different aspects of the tourist-destination relationship. A tourist may be satisfied with food quality and service delivery but have little continuing interest in the destination after the visit. Conversely, a tourist may remain highly interested in Chongqing's culinary culture, follow destination-related content, and interact with other users even when some elements of the physical experience were imperfect. Satisfaction therefore reflects whether tourists evaluated their experience favorably, whereas engagement reflects whether the destination continued to attract their attention and emotional involvement. Both mechanisms may be relevant to revisit intention, particularly in a destination where culinary experiences are continuously circulated and reinterpreted through digital platforms.

This interpretation is consistent with research showing that tourist satisfaction is associated with destination loyalty and revisit intention (Shi et al., 2022). However, the present findings extend a satisfaction-centered explanation by identifying engagement as an additional psychological mechanism. A recent systematic review of memorable gastronomic tourism experiences similarly found that culinary tourism outcomes are shaped by heterogeneous sensory, authentic, social, cultural, cognitive, and service-related dimensions (García-Pérez and Castillo-Ortiz, 2024). The coexistence of satisfaction and engagement in the present model reflects this multidimensional character of culinary tourism.

The results do not demonstrate that one psychological mechanism is inherently stronger or more important than the other. Although their standardized coefficients differ, no formal statistical test was conducted to compare the magnitude of the satisfaction and engagement paths. The two constructs should therefore be interpreted as complementary rather than hierarchically ordered mechanisms. Destination managers may need to support both reliable and satisfying service experiences and sustained cognitive, emotional, and relational engagement with local culinary culture.

5.1.6 Explanatory scope and alternative model structure

The explanatory power of the model should be interpreted with appropriate caution. The model accounted for 31.1% of the variance in tourist satisfaction, 31.2% in tourist engagement, 47.3% in value co-creation behavior, and 52.7% in revisit intention. These values indicate moderate but incomplete explanatory power rather than uniformly weak performance. The model explained nearly half of the variance in value co-creation behavior and more than half of the variance in revisit intention, but substantial unexplained variance remained, particularly in tourist satisfaction and tourist engagement.

The remaining variance may reflect factors not included in the proposed model, such as perceived food authenticity, destination image, price fairness, crowding, food quality, prior familiarity with Chongqing, novelty seeking, cultural identification, memorable culinary experiences, and the intensity of social media use. Future research should examine whether these factors provide additional explanatory value or operate as boundary conditions of the proposed relationships.

The competing-model results also qualify the interpretation of the dual-pathway structure. The full cross-path model demonstrated better SRMR, CFI, and TLI values than the hypothesized model, suggesting that service quality may also be associated with engagement and that social media interaction may also be associated with satisfaction. In contrast, the hypothesized model produced lower AIC and BIC values, indicating greater parsimony. The proposed model should therefore be understood as a theoretically economical representation of the primary offline evaluative and online participatory pathways rather than as a uniquely superior structure.

The SRMR value of 0.098 for the hypothesized model exceeded the conventional guideline of 0.08, indicating some remaining discrepancy between the model and the observed data. Consequently, the findings provide qualified support for the proposed dual-pathway explanation. Replication with independent samples, longitudinal designs, and cross-cultural settings is required to determine whether the same pathway structure remains stable across culinary destinations and digital-platform environments.

5.2 Theoretical contributions

This study makes three theoretical contributions to culinary tourism research, destination loyalty research, and the integration of the Stimulus-Organism-Response framework with Service-Dominant Logic.

First, this study extends the S-O-R framework by distinguishing between an offline service-evaluation pathway and an online interaction-engagement pathway. Previous tourism studies have frequently used the S-O-R framework to explain the relationships between destination stimuli, tourists' internal states, and behavioral intentions (Zhu et al., 2025). However, different types of tourism stimuli have often been grouped together as general environmental or experiential cues. This study differentiates service quality as an offline stimulus from social media interaction as an online stimulus. It also distinguishes tourist satisfaction as an evaluative organism state from tourist engagement as a participatory organism state. This distinction provides a more specific explanation of the psychological processes associated with revisit intention in platform-mediated culinary tourism.

Second, this study strengthens the theoretical connection between the S-O-R framework and Service-Dominant Logic by positioning value co-creation behavior as an enacted relational response. Previous research has shown that tourists participate in value creation through interaction, feedback, cooperation, and experience sharing (Hien and Luu, 2026). However, value co-creation has often been treated as a general experiential outcome or an additional mediator without clearly explaining the transition from tourists' internal psychological states to proactive resource contribution. In the present study, tourist satisfaction and tourist engagement represent internal organism states, whereas value co-creation behavior represents the voluntary enactment of those states through the contribution of knowledge, time, emotions, feedback, recommendations, and digital content. The S-O-R framework therefore explains the formation of psychological readiness, while Service-Dominant Logic explains how tourists act as resource integrators within the culinary tourism experience.

Third, this study extends satisfaction-centered explanations of destination loyalty by incorporating tourist engagement and value co-creation behavior into the formation of revisit intention. Previous research has frequently treated satisfaction as the principal psychological mechanism associated with destination loyalty (Herrero-Crespo et al., 2022). The present study shows that satisfaction and engagement represent complementary psychological mechanisms. Satisfaction reflects tourists' evaluation of whether the culinary experience met their expectations, whereas engagement reflects continuing attention, enthusiasm, absorption, interaction, and identification with the destination. Value co-creation behavior further explains how these internal responses may be expressed through feedback, cooperation, recommendation, knowledge sharing, and digital content production. This provides a more process-oriented explanation of revisit intention that extends beyond post-consumption satisfaction alone.

Overall, this study contributes an integrated explanation of revisit intention in platform-mediated culinary tourism by connecting offline service encounters, online social media interaction, tourists' internal psychological responses, voluntary resource integration, and loyalty-oriented intention within a unified S-O-R and Service-Dominant Logic framework.

5.3 Practical implications

First, Chongqing's tourism authorities and destination marketing organizations should strengthen the public service system for culinary tourism. The positive association between service quality and tourist satisfaction indicates that destination evaluation depends not only on food attractiveness but also on the reliability, hygiene, convenience, and transparency of the wider service environment. In high-traffic culinary areas such as Hongyadong, Jiefangbei, Ciqikou Ancient Town, Shancheng Alley, Nanbin Road, night markets, and popular hot pot districts, tourism authorities should establish unified standards for food-service information, price disclosure, hygiene inspection, visitor-flow management, and complaint handling. Official tourism platforms could provide real-time information on restaurant locations, waiting times, transport connections, food-safety records, price ranges, and complaint procedures. Clear multilingual signs, queue guidance, public sanitation facilities, and accessible visitor-assistance points would further reduce uncertainty and support more favorable evaluations of the culinary experience.

Second, restaurants, food streets, and culinary tourism enterprises should improve operational service quality while creating more interactive dining experiences. Enterprises should strengthen reservation and queue-management systems, disclose expected waiting times, provide clear menu and ingredient information, simplify ordering and payment procedures, maintain visible hygiene standards, and establish rapid complaint-response mechanisms. Digital queue numbers, online reservations, electronic menus, transparent pricing, and service-recovery procedures would be particularly useful in crowded culinary districts. At the same time, enterprises could provide hot pot sauce customization, taste-preference consultation, introductions to local ingredients, chef and employee storytelling, small culinary-culture exhibitions, and opportunities for tourists to provide suggestions. These activities can make tourists feel that their preferences and feedback are incorporated into the dining experience, thereby encouraging more active contribution and recommendation.

Third, destination managers should diversify the content and spatial coverage of Chongqing‘s culinary tourism rather than concentrating promotion on a small number of internet-famous restaurants and check-in locations. Official culinary tourism content should also include traditional restaurants, family-owned businesses, neighborhood food spaces, local markets, Xiaomian shops, Jianghu cuisine, night-market experiences, and intangible cultural heritage food practices. Destination marketing organizations could develop themed neighborhood food routes, community culinary maps, traditional hot pot culture programmes, and local food heritage stories. Expanding the range of promoted culinary spaces would provide tourists with new reasons to return while supporting small local businesses and strengthening the cultural richness of Chongqing's culinary tourism.

Fourth, social media communication should move beyond one-way visual promotion and provide opportunities for sustained tourist engagement. The positive association between social media interaction and tourist engagement indicates that platforms such as Douyin, Xiaohongshu, Weibo, and WeChat should combine visually attractive content with opportunities for communication, cultural interpretation, and user participation. Destination accounts could organize question-and-answer sessions, live culinary demonstrations, co-created food routes, tourist storytelling activities, user-generated travel guides, and discussions with chefs, local residents, and cultural practitioners. Online content should include practical information about waiting times, transport, prices, food preferences, and service conditions as well as explanations of Chongqing hot pot rituals, Jianghu cuisine, neighborhood food history, and night-time dining culture. Transparent review systems and accurate service information would help align online expectations with the actual destination experience.

Fifth, Chongqing should establish destination-level value co-creation mechanisms that connect tourism authorities, culinary enterprises, digital platforms, local communities, and tourists. Value co-creation behavior was associated with tourist satisfaction, tourist engagement, and revisit intention, indicating that tourists should be given clear channels through which they can contribute knowledge, preferences, feedback, and digital content. Possible mechanisms include official tourist-feedback systems, menu and route suggestion programmes, voting on neighborhood food routes, user-generated content campaigns, short-video storytelling activities, culinary culture workshops, and guided learning activities related to Chongqing cuisine. Tourism authorities and enterprises should also respond visibly to useful tourist suggestions by publishing service improvements, revised food routes, or updated visitor information. Demonstrating that tourist contributions produce practical outcomes can strengthen tourists' sense of involvement in the destination.

Finally, the performance evaluation of Chongqing culinary tourism should extend beyond online exposure, visitor numbers, and short-term platform popularity. Tourism authorities and destination marketing organizations could monitor repeat visits, the depth and continuity of online interaction, the quality of tourist feedback, participation in value co-creation programmes, review credibility, and the inclusion of local small businesses in user-generated content. Platforms and destination managers could also track whether tourists participate in food-route development, submit service suggestions, return to culinary districts, or produce content covering a wider range of neighborhood food spaces. These indicators would provide a more comprehensive assessment of whether platform visibility is being converted into sustained tourist relationships, local business participation, and cultural communication.

5.4 Limitations and future research

Although this study provides empirical evidence concerning revisit intention in Chongqing culinary tourism, several limitations should be acknowledged.

First, the cross-sectional design does not establish temporal precedence or causal relationships among service quality, social media interaction, tourist satisfaction, tourist engagement, value co-creation behavior, and revisit intention. Although the proposed structural relationships were theoretically specified, the data were collected during a single period. Consequently, reverse or reciprocal relationships cannot be ruled out. For example, tourists with stronger revisit intentions may be more willing to engage with destination-related social media content or participate in value co-creation activities. Future research should employ longitudinal, time-lagged, panel, or experimental designs to examine whether changes in service quality and social media interaction precede changes in satisfaction, engagement, value co-creation behavior, and revisit intention.

Second, the use of convenience sampling limits the representativeness and external validity of the findings. The combined online and offline recruitment strategy facilitated access to eligible culinary tourists but may have overrepresented younger, more highly educated, and digitally active respondents. Tourists who do not frequently use social media, avoid highly popular culinary districts, or have limited digital access may be underrepresented. Future studies should use probability-based, stratified, quota, or systematic sampling procedures based on official visitor profiles. Greater representation of different age groups, educational levels, places of residence, travel frequencies, and levels of digital participation would provide a more comprehensive understanding of Chongqing culinary tourists.

Third, the use of online and offline data-collection procedures may have introduced survey-mode effects. The present study compared the 457 online responses with the 261 offline responses and found no statistically significant or substantively meaningful differences in the six construct scores. However, the comparison was based on composite means and did not constitute a complete multigroup measurement-invariance assessment. Similar mean scores do not necessarily demonstrate that respondents in the two groups interpreted all measurement items in the same manner. Future studies should apply multigroup confirmatory factor analysis to test configural, metric, scalar, and structural invariance across online and offline samples before making detailed comparisons between data-collection modes.

Fourth, all constructs were measured using the same self-reported questionnaire during a single data-collection period. The responses may therefore be affected by memory error, social-desirability bias, consistency motives, or other forms of common method variance. Harman' s single-factor test indicated that the first unrotated factor accounted for 35.742% of the total variance, suggesting that common method bias was unlikely to constitute a serious threat. Nevertheless, this diagnostic cannot completely eliminate the possibility of residual common method variance. Future research should separate the measurement of predictors and outcomes over time, use a theoretically unrelated marker variable or common latent factor, and combine questionnaire data with multiple behavioral sources. These sources may include online reviews, platform-interaction records, restaurant reservations, booking information, user-generated content, and verified revisit records.

Fifth, the exclusive focus on Chongqing limits the geographical and cultural generalisability of the findings. Chongqing has a distinctive culinary identity, high-density urban food spaces, a predominantly domestic tourism market, and a digital environment shaped by platforms such as Douyin, Xiaohongshu, WeChat, and Weibo. The proposed relationships may operate differently in destinations with less integrated digital platforms, different food cultures, lower levels of online visibility, or a larger proportion of international tourists. Future research should replicate the model in other Chinese culinary destinations and in European and Southeast Asian settings. Cross-cultural comparisons could determine whether the offline service-evaluation and online interaction-engagement pathways remain stable across different culinary traditions, platform environments, and cultural norms.

Sixth, the model explained 31.1% of the variance in tourist satisfaction, 31.2% in tourist engagement, 47.3% in value co-creation behavior, and 52.7% in revisit intention. Although these values indicate meaningful explanatory power, substantial variance remained unexplained, particularly in tourist satisfaction and tourist engagement. Future studies could incorporate additional antecedents and contextual conditions, such as food authenticity, food quality, destination image, memorable culinary experiences, crowding, price fairness, novelty seeking, destination familiarity, cultural identification, and intensity of social media use. These variables may operate as additional predictors, mediators, or moderators of the proposed relationships.

Seventh, value co-creation behavior was modeled as a single construct, although tourists may contribute resources through different types of activity. Offline cooperation with service personnel, online experience sharing, feedback provision, customization, recommendation, and cultural learning may have different antecedents and consequences. Treating these behaviors as a single construct may conceal meaningful differences between physical and digital forms of resource integration. Future research should develop and validate a multidimensional value co-creation behavior scale and compare the respective roles of participation, feedback, cooperation, helping, advocacy, customization, and digital content creation.

Finally, the study examined revisit intention rather than verified revisit behavior. Intention represents an important predictor of future action, but tourists may be unable to revisit because of travel costs, distance, time constraints, competing destinations, or other situational factors. In addition, RI1–RI3 directly measured revisit intention, whereas RI4 assessed willingness to recommend Chongqing as a culinary tourism destination. Recommendation intention is related to destination loyalty but is conceptually distinct from revisit intention. Future research should measure revisit intention, recommendation intention, destination loyalty, and actual repeat visitation as separate outcomes. Linking survey responses with longitudinal booking data, platform records, or verified travel histories would provide stronger evidence concerning whether the proposed psychological and relational mechanisms are associated with tourists' subsequent behavior.

6 Conclusion

Drawing on the Stimulus-Organism-Response framework and service-dominant logic, this study identifies two complementary pathways associated with revisit intention in platform-mediated culinary tourism. The offline service-evaluation pathway links service quality with tourist satisfaction, which is subsequently associated with value co-creation behavior and revisit intention. The online interaction-engagement pathway links social media interaction with tourist engagement, which is likewise associated with value co-creation behavior and revisit intention. The findings position tourist satisfaction and tourist engagement as distinct but complementary psychological mechanisms. Satisfaction reflects tourists' evaluations of their culinary tourism experiences, whereas engagement captures their cognitive, emotional, and motivational involvement with the destination. Value co-creation behavior serves as an enacted behavioral bridge through which these psychological responses are translated into resource contributions, such as sharing experiences, providing feedback, recommending local food businesses, and interacting with other actors in the destination ecosystem. This conceptualization connects the reactive psychological process described by the S-O-R framework with the proactive resource-integration process emphasized by service-dominant logic. Overall, revisit intention in platform-mediated culinary tourism is associated not only with food and service experiences but also with digital interaction, tourist engagement, and active participation in value co-creation. The results therefore suggest that destination managers should improve the reliability and convenience of culinary tourism services, facilitate meaningful social media interaction, and provide accessible opportunities for tourists to share knowledge, offer feedback, and participate in the interpretation and improvement of destination experiences. These coordinated measures may help transform short-term platform visibility into more enduring tourist-destination relationships. Nevertheless, because the study employed a cross-sectional, self-reported survey, the observed relationships should not be interpreted as causal, and stated revisit intention may not necessarily translate into actual revisit behavior.

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