Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach

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The limited empirical understanding of how experiential attributes influence satisfaction and behavioral intention (BI). This research uses a thorough Structural Equation Modeling (SEM) framework to examine the variables affecting customer satisfaction (CS) and business intelligence (BI) in LFT. 380 valid responses were obtained from a quantitative cross-sectional survey of visitors who sampled local cuisine at particular Thai culinary sites. A structured questionnaire measured six exogenous constructs: food quality (FQ), Authenticity (AU), service quality (SQ), physical environment (PE), cultural experience (CE), and perceived value (PV) along with CS as a mediator and BI (revisit intention and Consumer referral behavior) as the endogenous outcome. Cronbach’s alpha, composite reliability (CR), average variance extracted (AVE), and discriminant validity using the Fornell-Larcker criterion were used to evaluate reliability and validity. Utilizing confirmatory factor analysis (CFA), the measurement model was validated. The findings suggest that CS is strongly and favorably influenced by FQ, AU, CE, and PV. The association between experience qualities and loyalty outcomes is partially mediated by CS, which also strongly predicts BI. A well-fitting measurement model is indicated by the model’s acceptable goodness-of-fit indices, which include a Comparative Fit Index (CFI) of 0.952, Tucker–Lewis Index (TLI) of 0.945, Root Mean Square Error of Approximation (RMSEA) of 0.056, and Standardized Root Mean Square Residual (SRMR) of 0.058. SPSS findings provide practical insights for enhancing tourist loyalty through authentic and high-quality culinary experiences." } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/15-596/v1", "name": "Factors Influencing Customer Satisfaction and Behavioral Intention..." } } ] } Home Browse Factors Influencing Customer Satisfaction and Behavioral Intention... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Madhyamapurush W. Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :596 ( https://doi.org/10.12688/f1000research.179249.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach [version 1; peer review: 1 approved with reservations] Warach Madhyamapurush https://orcid.org/0000-0003-4110-0780 Warach Madhyamapurush https://orcid.org/0000-0003-4110-0780 PUBLISHED 19 Apr 2026 Author details Author details School of Business and Communication Arts, University of Phayao, Thailand 19, Mueang Phayao District, Phayao, 56000, Thailand Warach Madhyamapurush Roles: Conceptualization, Data Curation, Investigation, Methodology, Resources, Writing – Original Draft Preparation, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the QUVAE Research and Publications gateway. Abstract Local food tourism (LFT) significantly impacts destination experiences by shaping tourists’ perceptions, satisfaction, and post-visit behavior. The limited empirical understanding of how experiential attributes influence satisfaction and behavioral intention (BI). This research uses a thorough Structural Equation Modeling (SEM) framework to examine the variables affecting customer satisfaction (CS) and business intelligence (BI) in LFT. 380 valid responses were obtained from a quantitative cross-sectional survey of visitors who sampled local cuisine at particular Thai culinary sites. A structured questionnaire measured six exogenous constructs: food quality (FQ), Authenticity (AU), service quality (SQ), physical environment (PE), cultural experience (CE), and perceived value (PV) along with CS as a mediator and BI (revisit intention and Consumer referral behavior) as the endogenous outcome. Cronbach’s alpha, composite reliability (CR), average variance extracted (AVE), and discriminant validity using the Fornell-Larcker criterion were used to evaluate reliability and validity. Utilizing confirmatory factor analysis (CFA), the measurement model was validated. The findings suggest that CS is strongly and favorably influenced by FQ, AU, CE, and PV. The association between experience qualities and loyalty outcomes is partially mediated by CS, which also strongly predicts BI. A well-fitting measurement model is indicated by the model’s acceptable goodness-of-fit indices, which include a Comparative Fit Index (CFI) of 0.952, Tucker–Lewis Index (TLI) of 0.945, Root Mean Square Error of Approximation (RMSEA) of 0.056, and Standardized Root Mean Square Residual (SRMR) of 0.058. SPSS findings provide practical insights for enhancing tourist loyalty through authentic and high-quality culinary experiences. READ ALL READ LESS Keywords Local food tourism, customer satisfaction, behavioral intention, recommendation intention, food quality, cultural experience, structural equation modeling. Corresponding Author(s) Warach Madhyamapurush ( [email protected] ) Close Corresponding author: Warach Madhyamapurush Competing interests: No competing interests were disclosed. Grant information: This research was supported by the University of Phayao and the Thailand Science Research and Innovation Fund (Fundamental Fund 2025, Grant No. 5015/2567). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2026 Madhyamapurush W. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Madhyamapurush W. Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :596 ( https://doi.org/10.12688/f1000research.179249.1 ) First published: 19 Apr 2026, 15 :596 ( https://doi.org/10.12688/f1000research.179249.1 ) Latest published: 19 Apr 2026, 15 :596 ( https://doi.org/10.12688/f1000research.179249.1 ) 1. Introduction Tourism is taking a new shape as travelers are demanding more than sightseeing activities since tourists are demanding to be immersed in the local culture. Food has taken center stage and is giving sensory, emotional and cultural satisfaction. Food experiences enable the visitors to visit destinations through meaningful ways. 1 LFT is a tourism where one goes to a particular place to have an experience of its gastronomy culture and traditional cuisine. It is a combination of food and culture that can be remembered. To the tourists, local food is a part of the identity and heritage of a destination, it is important in determining the entire travel experience. 2 The quality of the cuisine is a major factor in determining how satisfied tourists are with their gastronomic experiences. The freshness, flavor, presentation, and AU of a destination’s cuisine all influence how people perceive it; delicious food elevates enjoyment and positive sentiments about a place. For this reason, FQ is among the first things that local businesses and tourism managers are interested in. 3 A very important factor in making food tourism experiences memorable is AU. Tourists are interested in foods that contain some of the traditional ways of cooking and local cuisines. True food experiences enhance cultural affiliations and offer the feeling of distinctiveness. AU is another aspect that is usually looked at by tourists as a representation of heritage and uniqueness of a destination. 4 Tourists’ dining experiences and degree of happiness are significantly impacted by the quality of the service. Visitors’ perceptions of a destination are enhanced by thoughtful, polite, and efficient treatment. Poor service is a major component of the entire culinary experience and can negatively affect satisfaction even with good FQ. 5 Customers’ overall enjoyment and satisfaction are greatly influenced by a restaurant’s physical environment, which includes its ambiance, seating arrangements, cleanliness, and location. A pleasant and attractive setting adds PV to the meal and improves the whole dining experience. 6 LFT plays a role in terms of CE as it helps visitors to connect local cultural practices, festivals and food. Some of the ways through which the tourists can interact with the culture are cooking demonstrations, local markets, and traditional events. These experiences make the interactions memorable and not exactly to taste food. 7 PV influences consumer attitudes that tourists develop towards culinary experiences in relation to cost and effort. Tourists ask themselves whether the experience is worth the money, time, and effort spent. Perceived high value reinforces satisfaction and increases the chances of positive behavior intentions. It connects the physical and the spiritual side of the experience. 8 CS is a key variable in tourism, which determines visitor behavior. To a larger extent, satisfied tourists revisit the destinations and idolize the experiences to other people. There are various factors which influence satisfaction and these factors are FQ, AU, service, environment, CE and PV. Knowledge of it assists managers to improve the overall tourism experiences. 9 BI is the likelihood that travelers will return to or recommend a place. In tourist research, it is a typical indicator of loyalty, and positive experiences and high levels of satisfaction increase the likelihood that a person will return or actively advocate a place. These actions are essential for the tourism industry’s sustainable growth. 10 The relationship between satisfaction and BI is quite strong in tourism literature. Content customers increase their repeat visits, make referrals. The occurrence of genuine food, attentive services and involvement in interesting cultural activities raises the chances of such an action, and it underlines the significance of a holistic concept about culinary tourism. 11 Tourists’ perceptions of local dining experiences are influenced by a variety of factors, including sensory quality, service, CEs, and the whole environment. Positive experiences in these areas increase satisfaction and advance business intelligence. When determining the overall tourism experience, all of the factors work in tandem with one another. 12 Enhancing visitor happiness and encouraging return visits are the practical implications of this research for tourism stakeholders. Managers and local businesses can devise measures to enhance experiences, deliver expectations of the visitors, and enhance destination attractiveness. Offering cultural immersion, good quality, and delightful food experiences contribute to the long-term loyalty. 13 LFT provides a different approach of involving the visitors and advertising destination identity. Satisfaction and loyalty behaviors are influenced by the different elements of FQ and AU, service, environment, CEs, and PV. These aspects are important to understand to enhance tourist experiences. Culinary tourism is one of the crucial fields of developing memorable and sustainable tourism products. 14 Experience-based features like FQ, destination image, and experiential value have become the focus of the LFT research in explaining the behavior of tourists. These dimensions are significant to the CS and behavioral outcomes. An extensive model that incorporates several experiential features give more in-depth understanding of the overall tourism experience. 15 Figure 1 highlights the roles of FQ, AU, SQ, and other elements in shaping customer perceptions and future behavior. Figure 1. Determinants of CS in LFT. 1.1 Research aim The increasing significance of LFT makes it clear that there is a necessity to investigate the role of numerous experiential determinants in the CS level and the BI. Nevertheless, the two factors are normally analyzed separately, restricting the understanding of the overall impact of the two. Research seeks to bring about various experiential qualities, which include SQ, PE, FQ, AU, and CE, into one model with the aim of increasing tourist satisfaction, loyalty, and sustainable development in the LFT. 1.2 Research contributions • The research examines the effect of FQ, SQ, AU, PE and the perception of value on CS and the BI in the LFT environments. • To gather primary data on the key constructs, FQ, AU, quality of service, PE, PV, CS, and BI, a quantitative survey of 380 tourists who tried local cuisine in the chosen culinary destinations was provided. • The research implements tests of reliability and validity such as Cronbach’s alpha, CR, AVE, and discriminant validity, and subsequently CFA and SEM are used to test direct, mediated and moderated relationships leading to a validated model of drivers of tourist satisfaction and loyalty outcomes in LFT. 1.3 Research organization The research structured into seven parts. The introduction to the importance of LFT and its effects on customer satisfaction and BI is presented in Section 1. Section 2 is a literature review of pertinent literature on FQ, AU, SQ and other aspects of experience in LFT. Section 3 gives the framework of the hypotheses, which outlines the relationships between the major constructs. Section 4 describes the methodology, such as the data collection and measurement instruments. In section 5, results of the SEM analysis presented. The discussion is examined in section 6 and provide practical implications to the tourism managers. Section 7 is the last section, which ends with future research recommendation on LFT. 2. Literature review Earlier empirical research on LFT and its satisfaction, and BI have discussed numerous variables such as the quality of food, SQ, AU, and CE. Nevertheless, some of the studies are constrained by small sample sizes, being destination specific, and cross-sectional thus limiting the generalizability and temporal applicability. The objectives of the research, the characteristics of the sample, the methodologies, the main findings, and the limitations of these researches are summarized in Table 1 . It presents uniform results that FQ and AU have a positive effect on satisfaction and BI. Nevertheless, no exhaustive models that incorporate all these factors have been developed and thus the gap that this research seeks to fill in is to provide a more holistic understanding. Table 1. Empirical studies on LFT and BI. Ref Objective Sample Method Key findings Limitations 16 Examine Theory of Planned Behavior (TPB) variables influencing international tourists’ local food consumption intention 457 tourists Partial Least Squares SEM ( PLS-SEM) Attitude significantly predicted intention; responsible behavior moderated effects Single destination; cross-sectional 17 Investigate food consumption values and intention with neophobia/neophilia moderation 250 respondents SEM Consumption values influenced attitude; neophilia (+) and neophobia (−) affected intention Regional sampling; cross-sectional 18 Explore destination food image, neophobia, and BI 292 tourists PLS-SEM Food image and neophobia significantly shaped intention Single country; cross-sectional 19 Examine heritage food tourists’ intention and destination image 336 tourists PLS-SEM Experiential value enhanced attitude, image, and intention Cross-sectional design 20 Assess food culture attributes affecting satisfaction and patronage intention 172 attendees SEM Food culture improved satisfaction; satisfaction mediated patronage intention Convenience sampling; small sample 21 Analyze determinants of revisit and recommendation intention (Extended TPB) 4,268 tourists SEM Quality and value enhanced satisfaction; satisfaction drove revisit/recommendation Single destination context 22 Examine satisfaction and revisit intention toward local food heritage 62 respondents Survey analysis Price strongest satisfaction factor Very small sample; self-reported data 23 Analyze determinants of satisfaction and revisit intention 200 respondents SEM PE influenced satisfaction; satisfaction predicted revisit Online cross-sectional data 24 Examine FQ perception, satisfaction, and BI 487 tourists Structural modeling Core food & SQ enhanced satisfaction; satisfaction increased intention Single destination 25 Study food experiences, attitude, image, and revisit intention (TPB-based) 526 tourists SEM Food experience improved attitude and image; mediated revisit intention Convenience sampling 26 Assess gastronomy tourism quality and loyalty intentions 462 tourists SEM-PLS Gastronomy quality enhanced satisfaction; satisfaction mediated loyalty Single city focus 27 Examine culinary experience quality and destination satisfaction 401 tourists SEM FQ strongest predictor of satisfaction and intention Domestic sample; cross-sectional 28 Analyze food experience value, image, and revisit intention 458 respondents SEM Experience values influenced image and revisit intention Single brand case 29 Analyze your feelings, place attachment, meal experience, and intention to return 408 tourists SEM Emotion and attachment were improved by eating, and the inclination to return was raised. Single destination 30 Examine gastronomic experience and revisit intention with mediation of satisfaction 525 visitors Quantitative analysis Esthetic experience influenced revisit; satisfaction mediated effects Convenience sampling Existing research on LFT that integrate various experiential factors influencing CS and BI are limited. Although FQ, AU, SQ, and CE have all been studied separately, little study has been done to integrate these dimensions into a single model. By combining FQ, CE, AU, SQ PE, and PV into a thorough model to investigate their combined effects on visitor satisfaction and BI, this research closes this gap. The suggested model offers insightful information for improving visitor experiences and encouraging loyalty in LFT. 3. Hypotheses framework The theoretical foundation of the hypotheses proposes that FQ, AU, SQ, and PE serve as key experiential drivers that influence CS and PV, which in turn determine tourists’ BI in local food tourism. PV is proposed as a mediating variable between SQ and PE and CS, meaning that SQ and PE influence satisfaction indirectly through their impact on perceived value. Furthermore, CE is suggested as a moderating variable that enhances the association between CS and BI, meaning that a high level of cultural immersion increases the impact of satisfaction on behavioral intention. H1. FQ has a positive and significant effect on CS. FQ, including freshness, taste, presentation, and nutritional value, directly influences tourists’ dining experiences. When the food meets or exceeds expectations, tourists experience greater enjoyment, which increases the satisfaction of the customer. Therefore, higher FQ leads to higher satisfaction. H2. AU has a positive and significant effect on CS. AU reflects the extent to which the food experience is traditional and culturally genuine. When tourists perceive the cuisine as authentic, they feel a stronger connection to the destination. This cultural immersion enhances their overall experience and increases CS. H3. SQ has a positive and significant effect on PV. SQ, including responsiveness, professionalism, and empathy, improves the overall dining experience. High-quality service increases tourists’ perception that the experience is worth their time and money, thereby enhancing PV. H4. PE has a positive and significant effect on PV. The PE include the dining atmosphere, cleanliness, design, seating comfort, and overall setting of the restaurant. A well-maintained and aesthetically pleasing environment enhances tourists’ overall experience. When the environment is comfortable and attractive, tourists perceive the experience as more worthwhile, which increases their PV. H5. PV has a positive and significant effect on CS. PV reflects tourists’ evaluation of the benefits received relative to the price, time, and effort invested. When tourists believe the experience is worth what they paid, they feel more satisfied. Therefore, higher perceived value leads to higher CS. H6. CS has a positive and significant effect on BI. Satisfied customers have more chances to visit the destination again and refer others to visit the destination. Satisfaction is an important predictor of BI and it helps in relating positive experiences with the result of loyalty. H7. PV mediates the relationship between SQ and CS. SQ enhance the value perception by the tourists, thereby increasing their satisfaction. Therefore, PV is a very important process by which SQ influences the general CS. H8. CE moderates the relationship between CS and BI. The more a tourist has a high cultural immersion, the greater the level is likely to translate their satisfaction into BIs like returning or referring the destination. CE strengthens BI effect of satisfaction. Figure 2 represents the hypothesized relationships among FQ, AU, CE, SQ, PE, and PV in LFT. Figure 2. Structural model of influences on satisfaction and BI in food tourism. 5. Methodology Research adopted quantitative research design and the surveyed data (real experiences of 380 tourists who have taste local food in the identified culinary destinations in Thailand) was modeled using statistical modeling tools. Experience features that the research analyzed FQ, AU, SQ, PE, and PV and their impacts on CS and BI. Measurement of all constructs was done through validated Likert-scale items and testing of structural models was through SEM. The suitability of the framework was evaluated based on reliability, validity and multicollinearity tests. Figure 3 shows the research methodology flow, from hypothesis framework to result evaluation. Figure 3. Methodology flowchart for assessing factors in LFT. 4.1 Data collection Research gathered 380 valid answers of tourists in Thailand who tested the local food in the chosen food outlets. The measurement of eight latent constructs was conducted by using a structured questionnaire according to the validated scales; FQ, AU, SQ, PE, PV, CS, BI, and CE. 31 The questionnaire underwent pre-test to ensure the questionnaire was understandable, reliable, and content valid. The data were obtained both online and offline to have accuracy and representativeness. The obtained dataset was a good empirical foundation to test the hypothesized connections and perform structural model analysis. 4.2 Variable explanation The key variables in this research and their definitions are presented in Table 2 . The table also indicates the role of each variable as independent, mediator, moderator, or dependent in the research. Table 2. Variables and their definitions. Variable Definition FQ The sensory, nutritional, and overall appeal of local cuisine, including taste, freshness, presentation, and adherence to traditional recipes. Acts as an independent variable. AU The perceived genuineness and traditional nature of the local food experience, reflecting local ingredients, cooking methods, and culinary heritage. Independent variable. SQ The responsiveness, professionalism, empathy, and efficiency of staff at culinary destinations. Independent variable. PE The dining setting, including ambience, décor, cleanliness, seating comfort, and overall aesthetics. Independent variable. PV The overall evaluation of benefits received relative to cost and effort invested. Mediates the relationship between SQ, PE, and CS. CS Overall satisfaction of visitors with their local dining experience. Mediates the connection between BI, PV, and experiential characteristics. BI The possibility that visitors will return or suggest the location. CE The extent of tourists’ immersion in the local culinary culture and heritage. Moderates the relationship between CS and BI. 4.3 Constructs and measurement items The research adopted the available constructs and measurement items to test the relationships of experiential attributes, PV, CS, CE and behavioral intent. All variables were operationalized using various indicators in other research which had been previously conducted and measured in a five-point Likert scale. This research uses the following constructs, measurement items and the questionnaire questions presented in Table 3 . Table 3. Measurement items for constructs in LFT research. Construct Item code Item question Scale (1–5) FQ FQ1 How would you rate the freshness and preparation of the local food? 1–5 FQ2 To what extent did the presentation of the food enhance your experience? 1–5 FQ3 Were the portion sizes suitable and satisfying? 1–5 FQ4 How well did the food reflect traditional recipes and regional ingredients? 1–5 AU AU1 To what degree did the food experience feel authentic and traditional? 1–5 AU2 How strongly did the cuisine reflect the destination’s cultural heritage? 1–5 AU3 Were the ingredients and preparation methods consistent with local traditions? 1–5 AU4 How well did the food represent the authentic local culinary culture? 1–5 SQ SQ1 How responsive was the staff to your needs? 1–5 SQ2 How professional and courteous was the service provided by the staff? 1–5 SQ3 Did the service meet your expectations during the visit? 1–5 SQ4 How attentive and empathetic were the staff during your experience? 1–5 PE PE1 How comfortable and pleasant was the dining ambience? 1–5 PE2 To what extent did the seating, décor, and cleanliness enhance your experience? 1–5 PE3 How positively did the environment affect your perception of value? 1–5 PE4 How well did the overall setting align with your expectations for LFT? 1–5 PV PV1 How would you evaluate the overall value of the experience compared to its cost? 1–5 PV2 Did the experience justify the time and effort you invested? 1–5 PV3 Overall, was the experience worthwhile and valuable? 1–5 PV4 How satisfied were you with what you received for your investment? 1–5 CS CS1 How pleased are you with your entire dining experience in the area? 1–5 CS2 To what extent were your expectations of the experience fulfilled? 1–5 CS3 How pleased are you with the quality of food and services provided? 1–5 CS4 How satisfied are you with your decision to visit this culinary destination? 1–5 BI BI1 How likely are you to come back here to eat local cuisine? 1–5 BI2 How likely are you to recommend this destination to others? 1–5 BI3 How willing are you to try other culinary offerings at this destination? 1–5 BI4 How likely are you to share your positive experience with friends and family? 1–5 CE CE1 To what extent did the experience immerse you in the local culture? 1–5 CE2 How much did the local food experience enhance your understanding of local traditions? 1–5 CE3 To what degree did you engage with cultural elements while enjoying the food? 1–5 CE4 How strongly did cultural exposure deepen your connection with the destination? 1–5 4.4 Quantitative analysis SEM was employed using SPSS (Version 26) to examine the relationship between FQ, AU, SQ, PE, PV, CS, BI and CE. CFA assessed to validate the measurement model, which measures reliability (Cronbach’s alpha, CR), convergent (AVE) and discriminant (Fornell-Larcker criterion) validities. Direct, indirect, and moderated effectssuch as the mediating effect of PV and the moderating influence of CEwere investigated using the structural model. CFI, TLI, RMSEA, and SRMR were also used to assess the model’s fit. 4.5 Ethical considerations The research described in this article was reviewed and approved by the University of Phayao Human Ethics Committee, Thailand. The approval reference number is HREC-UP-HSS 2.2/175/89. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. Written informed consent was obtained from all participants prior to their participation in the survey. Participation was voluntary, and respondents were informed about the purpose of the study, confidentiality of responses, and their right to withdraw at any time without any consequences. 5. Result The results confirm that the measurements and structure models are adequate. High internal consistency, convergent, and discriminant validity were demonstrated by the validity and reliability tests, and CFA indicated that the model suited well. It has been discovered through structural analysis that experimental characteristics have a significant direct and indirect influence on PV customer satisfaction. Furthermore, CS is an excellent predictor of BI, and CE supports the relationship between the two, supporting all of the assumptions. 5.1 Demographic analysis Table 4 displays the demographic breakdown of the 380 respondents in Thailand, including gender, age, nationality, reason for visiting local food sites, frequency of visits, makeup of travel groups, and average local food expenditure per visit. The distribution of respondents in Thailand according to (a) the frequency of visiting local culinary destinations and (b) the makeup of the travel group is depicted in Figure 4 . Table 4. Demographic profile of respondents. Demographic Variable Category Frequency (n) Percentage (%) Age 18–25 90 23.7 26–35 150 39.5 36–45 80 21.1 46 and above 60 15.8 Gender Male 180 47.4 Female 200 52.6 Nationality Domestic Tourist 300 78.9 International Tourist 80 21.1 Travel Purpose Leisure 140 36.8 Cultural/Food Tourism 200 52.6 Business 40 10.5 Frequency of Visiting Local Food Destinations First-time visitor 110 28.9 Occasionally (1–3 times/year) 180 47.4 Frequently (4+ times/year) 90 23.7 Travel Group Alone 50 13.2 Family 140 36.8 Friends 120 31.6 Tour group 70 18.4 Figure 4. Demographic distribution of tourists based on (a) frequency of visits and (b) travel group. 5.2 Reliability and validity The measurement model’s validity and measurability were thoroughly examined before the structural model tests were conducted. Internal consistency dependability was assessed using Cronbach alpha and Cronbach’s ratio (CR). All eight of the constructs (in Table 5 and Figure 5 ) had Cronbach’s alpha values between 0.84 and 0.90, which is higher than the suggested value of 0.70. These results demonstrate that each construct’s items consistently measure the intended latent variable. To test for convergent validity, AVE was employed. Every construct had AVE values between 0.60 and 0.70, which is higher than the suggested minimum of 0.50. Acceptable convergent validity is demonstrated by Figure 6 , which confirms that the constructs account for more than 50% of the variance in the corresponding indicators. Table 5. Reliability and validity of constructs. Construct Cronbach’s α CR AVE Discriminant validity (√AVE > correlations) FQ 0.87 0.90 0.65 Yes AU 0.88 0.91 0.66 Yes SQ 0.85 0.88 0.61 Yes PE 0.84 0.87 0.60 Yes PV 0.89 0.92 0.68 Yes CS 0.90 0.93 0.70 Yes BI 0.88 0.91 0.67 Yes CE 0.86 0.89 0.63 Yes Figure 5. Visualization of cronbach’s α and cr for constructs. Figure 6. AVE for constructs in LFT research. The discriminant validity was tested using the Fornell Larcker criterion, which also demonstrated the constructs’ empirical uniqueness. This indicates that, in comparison to other latent variables in the model, the measurement items have a stronger relationship with their constructs. These reliability and validity results provide compelling empirical support for the measurement model’s adequacy. In order to ensure the correct operationalization and conceptual uniqueness of FQ, AU, SQ, PE, PV, CS, CE, and BI, internal consistency and construct validity will be established. This validation enhances the validity of the model and give it sufficient ground concerning the testing of the hypothesized relationships among experiential attributes, satisfaction, and behavioral intention in LFT. 5.3 CFA for assessing measurement model adequacy and relationships CFA was used to assess the suitability of the measurement model and the relationship between the latent components and the observed indicators. With standardized factor loadings ranging from 0.76 to 0.88, the CFA results show that every measurement item loaded heavily onto its corresponding constructs. Strong indicator reliability was demonstrated by all loadings exceeding the suggested criterion of 0.60, suggesting that each item accurately reflects its underlying construct. At p < 0.001, all item t-values were statistically significant, indicating that the factor structure was resilient. As seen in Table 6 and Figure 7 , the measurement items are robust and trustworthy markers of their corresponding latent constructs, as indicated by the high and significant factor loadings. Table 6. CFA Factor loadings and significance. Construct Item code Factor loading t-value p-value FQ FQ1 0.82 8.45 <0.001 FQ2 0.85 9.12 <0.001 FQ3 0.78 7.95 <0.001 FQ4 0.81 8.23 <0.001 AU AU1 0.83 8.67 <0.001 AU2 0.86 9.35 <0.001 AU3 0.80 8.01 <0.001 AU4 0.84 8.78 <0.001 SQ SQ1 0.79 7.88 <0.001 SQ2 0.82 8.44 <0.001 SQ3 0.81 8.22 <0.001 SQ4 0.80 8.10 <0.001 PE PE1 0.77 7.64 <0.001 PE2 0.79 7.91 <0.001 PE3 0.78 7.85 <0.001 PE4 0.76 7.50 <0.001 PV PV1 0.83 8.59 <0.001 PV2 0.81 8.27 <0.001 PV3 0.84 8.71 <0.001 PV4 0.82 8.36 <0.001 CS CS1 0.87 9.00 <0.001 CS2 0.85 8.63 <0.001 CS3 0.86 8.92 <0.001 CS4 0.84 8.54 <0.001 BI BI1 0.88 9.25 <0.001 BI2 0.87 9.12 <0.001 BI3 0.85 8.80 <0.001 BI4 0.86 8.90 <0.001 CE CE1 0.81 8.32 <0.001 CE2 0.84 8.70 <0.001 CE3 0.82 8.45 <0.001 CE4 0.83 8.58 <0.001 Figure 7. Structural model of CS and BI in LFT. In addition, a number of goodness-of-fit indices were used to evaluate the overall model fit in relation to the dependability of individual items. Table 7 shows that the measurement model fit well, with RMSEA = 0.056, CFI = 0.952, TLI = 0.945, and SRMR = 0.048. These values fall within the suggested ranges, indicating that the model provides the suggested factor structure and can be regarded as a reasonable description of the observed data. The measuring model is well-specified and statistically valid, as demonstrated by the CFA findings. The constructs have satisfactory model fit and significant factor loading, which makes them valid to be used in the testing of the structure model in the future. This affirmation consolidates the faith in exploring the associations amid experiential attributes, PV, CS, CE and BI in LFT. Table 7. CFA model fit and factor loadings. Fit indices Value RMSEA 0.056 CFI 0.952 TLI 0.945 SRMR 0.048 5.4 Path analysis of structural model and hypothesis testing SEM was conducted to examine the proposed direct, indirect, and moderating relationships among FQ, AU, SQ, PE, PV, CS, CE, and BI constructs. The results indicate that FQ and AU have significant positive effects on CS, supporting H1 and H2. SQ and PE significantly influence PV, supporting H3 and H4. PV also shows a significant positive effect on CS, supporting H5. Furthermore, CS significantly affects BI, confirming H6. The mediation analysis confirms that PV mediates the relationship between SQ and CS, supporting H7. The moderation analysis indicates that CE strengthens the relationship between CS and BI, supporting H8. Table 8 illustrates the hypothesized relationships and their t-values, β, p-values and results. Figure 8 presents the direct and the mediated association between the latent constructs. Table 8. Structural model results. Hypothesis Path β t-value p-value Result H1 FQ → CS 0.32 5.14 <0.001 Supported H2 AU → CS 0.28 4.63 <0.001 Supported H3 SQ → PV 0.34 5.47 <0.001 Supported H4 PE → PV 0.29 4.92 <0.001 Supported H5 PV → CS 0.37 6.12 <0.001 Supported H6 CS → BI 0.45 7.35 <0.001 Supported H7 SQ → PV → CS 0.13 3.91 <0.001 Supported (Mediation) H8 CS × CE → BI 0.10 2.87 0.004 Supported (Moderation) Figure 8. Measurement model and factor loadings for constructs. The experiential attributes that have been studied in LFT research have continued to include FQ, AU, and quality of service though a considerable number of studies have investigated each of the attributes individually, which restricts a comprehensive interpretation of the combined effect on customer satisfaction and behavioral intention. Also, little focus has been placed on mediating factors of PV and moderating factor of CE operating within a behavioral system. This disconnect prevents the further understanding of the processes, which relate the experiential characteristics with the results of the loyalty. The research has been relevant since it has incorporated FQ, SQ, PE, PV, CS, AU, and CE into a single SEM model. Earlier researches usually narrowed down to a single predictor including attitude, food image or experiential value without considering several dimensions of this experience at once. 16 , 18 , 19 Certain of the studies examined satisfaction as a mediating variable but used small samples or one destination at a time, making them difficult to generalize. 20 , 22 , 23 Besides, despite the popularity of cultural aspects, their moderating impact on the creation of loyalty has been demonstrated with scanty empirical support. 26 , 29 This research enhances these limitations by conducting a simultaneous analysis of direct, mediating and moderating effects by using a complex structural model. The combined system provides greater empirical clarity as to the channels connecting experiential characteristics to the outcomes in terms of loyalty. It develops knowledge on cognitive and cultural processes through which tourists respond. This methodology gives a more comprehensive account of BI within LFT. The empirical analysis was conducted using data collected from 380 tourists who experienced local culinary destinations in Thailand. Although the sample was limited to 380 respondents, it meets recommended thresholds for SEM and provides adequate statistical power to test complex direct, mediating, and moderating relationships. The focused sample enhances the reliability and contextual relevance of the findings within Thailand’s LFT setting. 5.5 Practical implications The results highlight the significance of food quality and AU for local food businesses and destination managers. To enhance CS, stakeholders should prioritize fresh ingredients, traditional preparation methods, and culturally reflective menus. Maintaining culinary culture while ensuring high sensory quality positively impacts the visitor experience. Employee professionalism, attentiveness, and an appealing ambiance are key to PV. Investing in staff training, hospitality standards, cleanliness, and atmosphere design can boost PV and satisfaction. Strong ties between CS and BI highlight the need for consistent, memorable dining experiences. Combining cultural immersion events with quality-value approaches can enhance competitiveness and promote sustainable development in LFT. 6. Conclusion LFT has turned out to be a significant aspect of destination experiences that determine the level of satisfaction and loyalty behavior in tourists. Although there has been increasing pressure on the use of experiential attributes, a detailed model where quality, PV, and cultural immersion are integrated has been minimal. Research has constructed and proved a combined structural model of SQ, AU, PE, FQ, PV, CS, CE, and BI. Since all of the factor loadings were over 0.60 and the model fit indices were good (RMSEA = 0.056, CFI = 0.952, TLI = 0.945, SRMR = 0.048), the measurement model exhibited high levels of validity and reliability. Based on 380 respondents, the structural results showed that customer satisfaction is significantly positively impacted by AU (β = 0.28) and FQ (β = 0.32), whereas PV is positively impacted by service quality (β = 0.34) and PE (β = 0.29). CS was a powerful predictor of behavioral intention (0.45), while PV reinforced satisfaction (0.37). The mediating effect of PV (β = 0.13) and the moderating effect of CE (β = 0.10) were also justified. The findings can guide empirically the enhancement of culturally immersive and value-oriented culinary tourism approaches. However, this is cross-sectional research based on self-reported data from the selected destinations. It is possible that future research may use longitudinal designs, cover different regions, and use other psychological or emotional variables to improve explanatory validity and applicability. Data availability statement Underlying data Figshare: Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach. https://doi.org/10.6084/m9.figshare.31711435.v1 . 31 The project contains the following underlying data: • Survey dataset.xlsx (Raw dataset of 380 respondents used for SEM analysis). Extended data Figshare: Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach. https://doi.org/10.6084/m9.figshare.31711435.v1 . 31 This project contains the following extended data: • Questionnaire.pdf (Structured questionnaire used for data collection). Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Acknowledgement This manuscript has been submitted through QUVAE Research and Publications Gateway. The researcher wishes to express gratitude to QUVAE Research and Publications for their invaluable assistance in depositing the raw data into the Figshare repository. References 1. Thio S, Jokom R, Widjaja DC: The contribution of perceived food consumption value on destination attractiveness and revisit intention. J. Culin. Sci. Technol. 2024; 22 (4): 727–743. Publisher Full Text 2. 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Soonsan N, Sukhabot S, Phakdee-Auksorn P: Understanding the relationship between gastronomic experience, satisfaction, and revisit intention. Kasetsart J Soc Sci. 2023; 44 (2): 585–592. Publisher Full Text 31. Madhyamapurush W: Factors influencing customer satisfaction and behavioral intention in local food tourism: A structural equation modeling approach. [Data set]. figshare. 2026. Publisher Full Text Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 19 Apr 2026 ADD YOUR COMMENT Comment Author details Author details School of Business and Communication Arts, University of Phayao, Thailand 19, Mueang Phayao District, Phayao, 56000, Thailand Warach Madhyamapurush Roles: Conceptualization, Data Curation, Investigation, Methodology, Resources, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information This research was supported by the University of Phayao and the Thailand Science Research and Innovation Fund (Fundamental Fund 2025, Grant No. 5015/2567). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Article Versions (1) version 1 Published: 19 Apr 2026, 15:596 https://doi.org/10.12688/f1000research.179249.1 Copyright © 2026 Madhyamapurush W. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Madhyamapurush W. Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :596 ( https://doi.org/10.12688/f1000research.179249.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 19 Apr 2026 Views 0 Cite How to cite this report: Wongmahesak K. Reviewer Report For: Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :596 ( https://doi.org/10.5256/f1000research.197745.r476970 ) The direct URL for this report is: https://f1000research.com/articles/15-596/v1#referee-response-476970 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 23 Apr 2026 Kittisak Wongmahesak , Faculty of Political Science, North Bangkok University, Sai Mai, Bangkok, Thailand; Post-Doctoral Fellowship Research Collaboration Program, Lincoln University College (Ringgold ID: 283706), Petaling Jaya, Selangor, Malaysia; Publication Research Institute and Community Service, Universitas Muhammadiyah Sidenreng Rappang (Ringgold ID: 605937), Sidenreng Rappang Regency, South Sulawesi, Indonesia Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.197745.r476970 This article explores the determinants of customer satisfaction (CS) and behavioral intention (BI) within the local food tourism (LFT) sector in Thailand using Structural Equation Modeling (SEM). While the technical execution of the research is sound and the data analysis ... Continue reading READ ALL This article explores the determinants of customer satisfaction (CS) and behavioral intention (BI) within the local food tourism (LFT) sector in Thailand using Structural Equation Modeling (SEM). While the technical execution of the research is sound and the data analysis is rigorous, the manuscript requires significant refinement in its narrative structure and integration of the literature to meet the high academic standards of F1000Research. 1) Narrative Structure and Presentation: The current manuscript is heavily segmented with numerous subheadings and a high volume of figures and tables. To improve readability and academic flow, the authors should transition toward a more cohesive "prose" style. Specifically, the content should be streamlined into five core sections: Introduction, Literature Review, Research Methods, Research Results, and Conclusion and Discussion. Paragraphs should be balanced to ensure a smooth transition of arguments rather than relying on bullet points or excessive subdivisions. 2) Literature Review and Argumentation: The theoretical foundation needs more "sharpness" regarding the contemporary evolution of culinary tourism. The authors must demonstrate a deeper understanding of post-pandemic shifts and service quality dynamics. To achieve high-quality literature synthesis, the following recent works must be integrated into the discussion: - The discussion on service quality and the marketing mix should be bolstered by citing Walailak et al. (2025), specifically regarding how service quality factors drive satisfaction in the Thai hospitality context. - To address the resilience of the tourism sector and the shift from "niche" to "necessity," the authors must incorporate the multidimensional evolution of culinary tourism as discussed by Phanpanya et al. (2025). - The argument regarding the impact and opportunities of food tourism in the modern era should be strengthened using the insights on sustainability provided by Worrachananun (2025). 3) Integration of Results and Discussion: While the SEM results are clearly presented in Table 8 and Figure 8, the "Conclusion and Discussion" section should do more than restate the statistical findings. It must explain why specific variables, such as Cultural Experience (CE), serve as moderators and how these findings contrast with or support the newly suggested literature on sustainable food tourism and post-pandemic resilience. 4) Specific Points to Address: - Consolidation: Reduce the number of figures and tables. For instance, some of the demographic data in Table 4 could be summarized in the text to maintain the "essay" flow. - Critical Debate: Enhance the "Introduction" by presenting a sharper debate on the conflict between "authenticity" and "commercialization" in LFT. - Formatting: Ensure all citations follow a consistent academic style and that the five-section structure is strictly followed without unnecessary subheadings. In conclusion, the article is technically robust and provides valuable empirical data for the field of business behavioral science. By adopting a more sophisticated narrative style and integrating the requested contemporary literature, the authors will significantly enhance the manuscript's academic contribution and originality. Addressing these points is essential for the article to be considered scientifically sound for final approval. References: Phanpanya, K., Chanchaipitiphat, N., Jaepho, S., & Darmawijaya, I. G. (2025). From Niche to Necessity: A Multidimensional Evolution of Culinary Tourism and Post-Pandemic Resilience (2001-2025). Thai Arts and Culture Review, 1(2), Article 1. https://doi.org/10.14456/tacr.2025.6 Walailak, P., Kajornatthapol, P., & Veerapong, S. (2025). Drivers of Customer Satisfaction in Northern Thailand’s Hotel Industry: The Marketing Mix and Service Quality Factors. Asian Administration and Management Review, 8(2), Article 10. https://doi.org/10.14456/aamr.2025.35 Worrachananun, M. (2025). Sustainable Food Tourism: Impacts, Opportunity, and Challenges in The Modern Era. Asian Administration and Management Review, 8(1), Article 3. https://doi.org/10.14456/aamr.2025.3 Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Political Science, Public & Private Management, International Political Economy, Social Research I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Wongmahesak K. Reviewer Report For: Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :596 ( https://doi.org/10.5256/f1000research.197745.r476970 ) The direct URL for this report is: https://f1000research.com/articles/15-596/v1#referee-response-476970 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 19 Apr 2026 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 Version 1 19 Apr 26 read Kittisak Wongmahesak , North Bangkok University, Sai Mai, Thailand; Lincoln University College (Ringgold ID: 283706), Petaling Jaya, Malaysia; Universitas Muhammadiyah Sidenreng Rappang (Ringgold ID: 605937), Sidenreng Rappang Regency, Indonesia Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Wongmahesak K. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 23 Apr 2026 | for Version 1 Kittisak Wongmahesak , Faculty of Political Science, North Bangkok University, Sai Mai, Bangkok, Thailand; Post-Doctoral Fellowship Research Collaboration Program, Lincoln University College (Ringgold ID: 283706), Petaling Jaya, Selangor, Malaysia; Publication Research Institute and Community Service, Universitas Muhammadiyah Sidenreng Rappang (Ringgold ID: 605937), Sidenreng Rappang Regency, South Sulawesi, Indonesia 0 Views copyright © 2026 Wongmahesak K. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This article explores the determinants of customer satisfaction (CS) and behavioral intention (BI) within the local food tourism (LFT) sector in Thailand using Structural Equation Modeling (SEM). While the technical execution of the research is sound and the data analysis is rigorous, the manuscript requires significant refinement in its narrative structure and integration of the literature to meet the high academic standards of F1000Research. 1) Narrative Structure and Presentation: The current manuscript is heavily segmented with numerous subheadings and a high volume of figures and tables. To improve readability and academic flow, the authors should transition toward a more cohesive "prose" style. Specifically, the content should be streamlined into five core sections: Introduction, Literature Review, Research Methods, Research Results, and Conclusion and Discussion. Paragraphs should be balanced to ensure a smooth transition of arguments rather than relying on bullet points or excessive subdivisions. 2) Literature Review and Argumentation: The theoretical foundation needs more "sharpness" regarding the contemporary evolution of culinary tourism. The authors must demonstrate a deeper understanding of post-pandemic shifts and service quality dynamics. To achieve high-quality literature synthesis, the following recent works must be integrated into the discussion: - The discussion on service quality and the marketing mix should be bolstered by citing Walailak et al. (2025), specifically regarding how service quality factors drive satisfaction in the Thai hospitality context. - To address the resilience of the tourism sector and the shift from "niche" to "necessity," the authors must incorporate the multidimensional evolution of culinary tourism as discussed by Phanpanya et al. (2025). - The argument regarding the impact and opportunities of food tourism in the modern era should be strengthened using the insights on sustainability provided by Worrachananun (2025). 3) Integration of Results and Discussion: While the SEM results are clearly presented in Table 8 and Figure 8, the "Conclusion and Discussion" section should do more than restate the statistical findings. It must explain why specific variables, such as Cultural Experience (CE), serve as moderators and how these findings contrast with or support the newly suggested literature on sustainable food tourism and post-pandemic resilience. 4) Specific Points to Address: - Consolidation: Reduce the number of figures and tables. For instance, some of the demographic data in Table 4 could be summarized in the text to maintain the "essay" flow. - Critical Debate: Enhance the "Introduction" by presenting a sharper debate on the conflict between "authenticity" and "commercialization" in LFT. - Formatting: Ensure all citations follow a consistent academic style and that the five-section structure is strictly followed without unnecessary subheadings. In conclusion, the article is technically robust and provides valuable empirical data for the field of business behavioral science. By adopting a more sophisticated narrative style and integrating the requested contemporary literature, the authors will significantly enhance the manuscript's academic contribution and originality. Addressing these points is essential for the article to be considered scientifically sound for final approval. References: Phanpanya, K., Chanchaipitiphat, N., Jaepho, S., & Darmawijaya, I. G. (2025). From Niche to Necessity: A Multidimensional Evolution of Culinary Tourism and Post-Pandemic Resilience (2001-2025). Thai Arts and Culture Review, 1(2), Article 1. https://doi.org/10.14456/tacr.2025.6 Walailak, P., Kajornatthapol, P., & Veerapong, S. (2025). Drivers of Customer Satisfaction in Northern Thailand’s Hotel Industry: The Marketing Mix and Service Quality Factors. Asian Administration and Management Review, 8(2), Article 10. https://doi.org/10.14456/aamr.2025.35 Worrachananun, M. (2025). Sustainable Food Tourism: Impacts, Opportunity, and Challenges in The Modern Era. Asian Administration and Management Review, 8(1), Article 3. https://doi.org/10.14456/aamr.2025.3 Is the work clearly and accurately presented and does it cite the current literature? Partly Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Political Science, Public & Private Management, International Political Economy, Social Research I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Wongmahesak K. Peer Review Report For: Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach [version 1; peer review: 1 approved with reservations] . F1000Research 2026, 15 :596 ( https://doi.org/10.5256/f1000research.197745.r476970) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/15-596/v1#referee-response-476970 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. 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