<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.179249.3</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 3; peer review: 1 approved, 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Madhyamapurush</surname>
                        <given-names>Warach</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-4110-0780</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>School of Business and Communication Arts, University of Phayao, Thailand 19, Mueang Phayao District, Phayao, 56000, Thailand</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:warachm@gmail.com">warachm@gmail.com</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>8</day>
                <month>6</month>
                <year>2026</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2026</year>
            </pub-date>
            <volume>15</volume>
            <elocation-id>596</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>5</day>
                    <month>6</month>
                    <year>2026</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Madhyamapurush W</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/15-596/pdf"/>
            <abstract>
                <p>Local food tourism (LFT) significantly impacts destination experiences by shaping tourists&#x2019; 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 behavioral intention (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&#x2019;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&#x2019;s acceptable goodness-of-fit indices, which include a Comparative Fit Index (CFI) of 0.952, Tucker&#x2013;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.</p>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Local food tourism</kwd>
                <kwd>customer satisfaction</kwd>
                <kwd>behavioral intention</kwd>
                <kwd>recommendation intention</kwd>
                <kwd>food quality</kwd>
                <kwd>cultural experience</kwd>
                <kwd>structural equation modeling.</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>Thailand Science Research and Innovation Fund</funding-source>
                    <award-id>5015/2567</award-id>
                </award-group>
                <funding-statement>This research was supported by the University of Phayao and the Thailand Science Research and Innovation Fund (Fundamental Fund 2025, Grant No. 5015/2567).</funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
        <notes>
            <sec sec-type="version-changes">
                <label>Revised</label>
                <title>Amendments from Version 2</title>
                <p>Amendments in Version 2: The revised manuscript has been substantially strengthened in response to reviewer comments. The study now incorporates stronger theoretical grounding through Experience Economy Theory and Self-Determination Theory, while clearly positioning the model as theory-driven. The literature review and research gap sections were refined to emphasize the novelty of integrating experiential, cognitive, and cultural mechanisms within the Thai local food tourism (LFT) context. Methodological transparency was improved through clarification of purposive sampling procedures, AMOS software usage, common method bias testing, non-response bias analysis, discriminant validity assessment (HTMT), and reporting of effect sizes (f&#x00b2;). The discussion section was expanded to provide deeper theoretical interpretation, stronger comparison with prior studies, and analysis of the authenticity&#x2013;commercialization debate and post-pandemic &#x201c;niche-to-necessity&#x201d; tourism dynamics. In addition, language quality, narrative cohesion, abstract terminology, and manuscript structure were comprehensively revised to enhance academic clarity and readability.</p>
            </sec>
        </notes>
    </front>
    <body>
        <sec id="sec1" sec-type="intro">
            <title>1. Introduction</title>
            <p>
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.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> 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&#x2019;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.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> A critical debate in LFT revolves around the tension between authenticity and commercialization. While authenticity is often perceived as the core value of culinary tourism, reflecting traditional preparation methods, local ingredients, and cultural heritage, increasing commercialization driven by tourism demand may lead to the standardization and modification of local cuisines to suit global tastes. This creates a paradox where efforts to make local food more accessible and profitable can dilute its cultural integrity. Some scholars argue that staged authenticity may still provide meaningful experiences to tourists, whereas others emphasize that excessive commercialization risks undermining the originality and heritage value of local gastronomy. Therefore, understanding this dynamic is essential for balancing economic benefits with cultural preservation in LFT contexts.</p>
            <p>Tourists&#x2019; dining experiences and degree of happiness are significantly impacted by the quality of the service. Visitors&#x2019; 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.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> Customers&#x2019; overall enjoyment and satisfaction are greatly influenced by a restaurant&#x2019;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.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> 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&#x2019;s sustainable growth.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> Tourists&#x2019; 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.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> 
                <xref ref-type="fig" rid="f1">
Figure 1</xref> highlights the roles of FQ, AU, SQ, and other elements in shaping customer perceptions and future behavior.
                <fig fig-type="figure" id="f5" orientation="portrait" position="float">
                    <label>
Figure 5. </label>
                    <caption>
                        <title>Measurement model and factor loadings for constructs.</title>
                    </caption>
                    <graphic id="gr5" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/202732/216de43c-b113-4ad8-904d-70bcd295195c_figure5.gif"/>
                </fig>
            </p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>
Figure 1. </label>
                <caption>
                    <title>Determinants of CS in LFT.</title>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/202732/216de43c-b113-4ad8-904d-70bcd295195c_figure1.gif"/>
            </fig>
            <p>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.</p>
            <p>

                <list list-type="bullet">
                    <list-item>
                        <label>&#x2022;</label>
                        <p>The research examines the effect of FQ, SQ, AU, PE and the perception of value on CS and the BI in the LFT environments.</p>
                    </list-item>
                    <list-item>
                        <label>&#x2022;</label>
                        <p>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.</p>
                    </list-item>
                    <list-item>
                        <label>&#x2022;</label>
                        <p>The research implements tests of reliability and validity such as Cronbach&#x2019;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.</p>
                    </list-item>
                </list>
            </p>
            <p>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.</p>
            <p>Recent scholarship highlights a growing tension in local food tourism between authenticity preservation and commercial standardization, where destinations often commodify traditional cuisine to meet mass tourism demand while risking cultural dilution.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>,
                    <xref ref-type="bibr" rid="ref1">14</xref>
                </sup> This debate emphasizes that while authenticity enhances experiential value and emotional connection, excessive commercialization may undermine perceived genuineness and long-term destination loyalty. Contemporary studies further argue that integrating experiential quality with cultural sustainability is essential for maintaining competitive advantage in LFT.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>,
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup> Therefore, a more nuanced and integrative analytical approach is required to understand how multiple experiential constructs simultaneously influence satisfaction and behavioral intention within this evolving tourism landscape.</p>
        </sec>
        <sec id="sec5">
            <title>2. Literature review</title>
            <p>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 
                <xref ref-type="table" rid="T1">
Table 1</xref>. 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.</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>
Table 1. </label>
                <caption>
                    <title>Empirical studies on LFT and BI.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Ref</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Objective</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Sample</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Method</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Key findings</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Limitations</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref16">16</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Examine Theory of Planned Behavior (TPB) variables influencing international tourists&#x2019; local food consumption intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">457 tourists</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Partial Least Squares SEM 
                                <bold>(</bold>PLS-SEM)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Attitude significantly predicted intention; responsible behavior moderated effects</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Single destination; cross-sectional
</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref17">17</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Investigate food consumption values and intention with neophobia/neophilia moderation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">250 respondents</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SEM</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Consumption values influenced attitude; neophilia (+) and neophobia (&#x2212;) affected intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Regional sampling; cross-sectional
</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref18">18</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Explore destination food image, neophobia, and BI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">292 tourists</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PLS-SEM
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Food image and neophobia significantly shaped intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Single country; cross-sectional
</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref19">19</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Examine heritage food tourists&#x2019; intention and destination image</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">336 tourists</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PLS-SEM
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Experiential value enhanced attitude, image, and intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cross-sectional design</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref20">20</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Assess food culture attributes affecting satisfaction and patronage intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">172 attendees</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SEM</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Food culture improved satisfaction; satisfaction mediated patronage intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Convenience sampling; small sample</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref21">21</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Analyze determinants of revisit and recommendation intention (Extended TPB)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4,268 tourists</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SEM</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Quality and value enhanced satisfaction; satisfaction drove revisit/recommendation</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Single destination context</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref22">22</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Examine satisfaction and revisit intention toward local food heritage</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">62 respondents</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Survey analysis</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Price strongest satisfaction factor</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Very small sample; self-reported data</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref23">23</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Analyze determinants of satisfaction and revisit intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">200 respondents</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SEM</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">PE influenced satisfaction; satisfaction predicted revisit</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Online cross-sectional data</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref24">24</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Examine FQ perception, satisfaction, and BI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">487 tourists</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Structural modeling</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Core food &amp; SQ enhanced satisfaction; satisfaction increased intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Single destination</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref25">25</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Study food experiences, attitude, image, and revisit intention (TPB-based)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">526 tourists</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SEM</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Food experience improved attitude and image; mediated revisit intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Convenience sampling</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref26">26</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Assess gastronomy tourism quality and loyalty intentions</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">462 tourists</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SEM-PLS
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Gastronomy quality enhanced satisfaction; satisfaction mediated loyalty</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Single city focus</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref27">27</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Examine culinary experience quality and destination satisfaction</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">401 tourists</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SEM</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">FQ strongest predictor of satisfaction and intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Domestic sample; cross-sectional
</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref28">28</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Analyze food experience value, image, and revisit intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">458 respondents</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SEM</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Experience values influenced image and revisit intention</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Single brand case</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref29">29</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Analyze your feelings, place attachment, meal experience, and intention to return</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">408 tourists</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SEM</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Emotion and attachment were improved by eating, and the inclination to return was raised</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Single destination</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref30">30</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Examine gastronomic experience and revisit intention with mediation of satisfaction</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">525 visitors</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Quantitative analysis</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Esthetic experience influenced revisit; satisfaction mediated effects</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Convenience sampling</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref31">31</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Impact of 7Ps and service factors on satisfaction</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">400 hotel customers (Thailand)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Survey &amp; regression</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Most factors significant; distribution not</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Region-specific; self-reported data</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref32">32</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Examine evolution of culinary tourism (2001&#x2013;2025)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Literature across phases</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Critical review</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Shift to authenticity, digital influence, sustainability gap</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">No primary data, limited regional depth</td>
                        </tr>
                        <tr>
                            <td align="center" colspan="1" rowspan="1" valign="top">
                                <sup>
                                    <xref ref-type="bibr" rid="ref33">33</xref>
                                </sup>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Examine sustainability impact of food tourism</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Key stakeholders</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">In-depth interviews</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Supports economy, culture, environment</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cost, over-tourism, authenticity issues</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>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.</p>
            <p>The present study has three major differences from previous SEM-related tourism studies. First, most previous research has focused on one or two experiential predictors (e.g., food quality or authenticity alone), whereas this study simultaneously combines six experiential constructs (FQ, AU, SQ, PE, PV, and CE) in one structural model. Second, this study differs from those of Angelakis et al. (2023)
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> and Sangkaew et al. (2025),
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> which only consider satisfaction as a mediator between service-related attributes and satisfaction, by treating PV as a partial mediator between service-related attributes and satisfaction, and CE as a cultural moderator of the relationship between satisfaction and intention. Third, this study goes beyond Western culinary tourism paradigms by examining the context of Thai LFT, which is unique in terms of cultural heritage preservation and commercialization pressures. The research gap is thus well defined: there is no integrative model that tests the cognitive, affective, and cultural mechanisms that influence tourist loyalty in LFT.</p>
        </sec>
        <sec id="sec6">
            <title>3. Research methods</title>
            <p>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&#x2019; 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. 
                <xref ref-type="table" rid="T2">
Table 2</xref> demonstrates 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.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Summary of hypotheses and proposed relationships in the conceptual model.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Hypothesis</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Statement</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Relationship</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Explanation</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>H1</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Food Quality (FQ) &#x2192; Customer Satisfaction (CS)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Positive &amp; Significant</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Freshness, taste, presentation, and nutritional value enhance tourists&#x2019; dining experience, leading to higher satisfaction when expectations are met or exceeded.</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>H2</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Authenticity (AU) &#x2192; Customer Satisfaction (CS)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Positive &amp; Significant</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Authentic food creates cultural connection and immersion, improving overall experience and increasing satisfaction.</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>H3</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Service Quality (SQ) &#x2192; Perceived Value (PV)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Positive &amp; Significant</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Responsiveness, professionalism, and empathy improve service experience, increasing perceived worth of time and money.</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>H4</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Physical Environment (PE) &#x2192; Perceived Value (PV)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Positive &amp; Significant</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Cleanliness, ambiance, design, and comfort enhance the dining setting, leading to higher perceived value.</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>H5</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Perceived Value (PV) &#x2192; Customer Satisfaction (CS)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Positive &amp; Significant</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">When tourists perceive benefits outweigh costs, their satisfaction increases.</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>H6</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Customer Satisfaction (CS) &#x2192; Behavioral Intention (BI)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Positive &amp; Significant</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Satisfied tourists are more likely to revisit and recommend, strengthening loyalty intentions.</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>H7</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">SQ &#x2192; PV &#x2192; CS</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Mediation Effect</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Service quality improves perceived value, which in turn enhances customer satisfaction.</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>H8</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Customer Engagement (CE) moderates CS &#x2192; BI</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Moderation Effect</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">The strength of the relationship between satisfaction and behavioral intention depends on the level of customer engagement.</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>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. 
                <xref ref-type="fig" rid="f2">
Figure 2</xref> represents the hypothesized relationships among FQ, AU, CE, SQ, PE, and PV in LFT.</p>
            <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                <label>
Figure 2. </label>
                <caption>
                    <title>Structural model of influences on satisfaction and BI in food tourism.</title>
                </caption>
                <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/202732/216de43c-b113-4ad8-904d-70bcd295195c_figure2.gif"/>
            </fig>
            <p>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. 
                <xref ref-type="fig" rid="f3">
Figure 3</xref> shows the research methodology flow, from hypothesis framework to result evaluation.</p>
            <fig fig-type="figure" id="f3" orientation="portrait" position="float">
                <label>
Figure 3. </label>
                <caption>
                    <title>Methodology flowchart for assessing factors in LFT.</title>
                </caption>
                <graphic id="gr3" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/202732/216de43c-b113-4ad8-904d-70bcd295195c_figure3.gif"/>
            </fig>
            <sec id="sec7">
                <title>3.1 Research methodology and analytical framework</title>
                <p>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.
                    <sup>
                        <xref ref-type="bibr" rid="ref31">31</xref>
                    </sup> 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.</p>
                <p>The key variables in this research and their definitions are presented in 
                    <xref ref-type="table" rid="T3">
Table 3</xref>. The table also indicates the role of each variable as independent, mediator, moderator, or dependent in the research.</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>
Table 3. </label>
                    <caption>
                        <title>Variables and their definitions.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Variable</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Definition</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">FQ</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">The sensory, nutritional, and overall appeal of local cuisine, including taste, freshness, presentation, and adherence to traditional recipes. Acts as an independent variable.</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">AU</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">The perceived genuineness and traditional nature of the local food experience, reflecting local ingredients, cooking methods, and culinary heritage. Independent variable.</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">SQ</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">The responsiveness, professionalism, empathy, and efficiency of staff at culinary destinations. Independent variable.</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">PE</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">The dining setting, including ambience, d&#x00e9;cor, cleanliness, seating comfort, and overall aesthetics. Independent variable.</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">PV</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">The overall evaluation of benefits received relative to cost and effort invested. Mediates the relationship between SQ, PE, and CS.</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">CS</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Overall satisfaction of visitors with their local dining experience. Mediates the connection between BI, PV, and experiential characteristics.</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">BI</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">The possibility that visitors will return or suggest the location.</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">CE</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">The extent of tourists&#x2019; immersion in the local culinary culture and heritage. Moderates the relationship between CS and BI.</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>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 
                    <xref ref-type="table" rid="T4">
Table 4</xref>.</p>
                <table-wrap id="T4" orientation="portrait" position="float">
                    <label>
Table 4. </label>
                    <caption>
                        <title>Measurement items for constructs in LFT research.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Construct</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Item code</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Item question</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Scale (1&#x2013;5)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">FQ</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">FQ1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How would you rate the freshness and preparation of the local food?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">FQ2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">To what extent did the presentation of the food enhance your experience?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">FQ3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Were the portion sizes suitable and satisfying?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">FQ4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How well did the food reflect traditional recipes and regional ingredients?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">AU</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">AU1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">To what degree did the food experience feel authentic and traditional?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">AU2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How strongly did the cuisine reflect the destination&#x2019;s cultural heritage?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">AU3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Were the ingredients and preparation methods consistent with local traditions?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">AU4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How well did the food represent the authentic local culinary culture?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">SQ</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How responsive was the staff to your needs?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How professional and courteous was the service provided by the staff?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Did the service meet your expectations during the visit?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How attentive and empathetic were the staff during your experience?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">PE</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">PE1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How comfortable and pleasant was the dining ambience?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">PE2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">To what extent did the seating, d&#x00e9;cor, and cleanliness enhance your experience?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">PE3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How positively did the environment affect your perception of value?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">PE4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How well did the overall setting align with your expectations for LFT?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">PV</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">PV1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How would you evaluate the overall value of the experience compared to its cost?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">PV2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Did the experience justify the time and effort you invested?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">PV3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Overall, was the experience worthwhile and valuable?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">PV4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How satisfied were you with what you received for your investment?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">CS</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How pleased are you with your entire dining experience in the area?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">To what extent were your expectations of the experience fulfilled?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How pleased are you with the quality of food and services provided?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How satisfied are you with your decision to visit this culinary destination?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">BI</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">BI1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How likely are you to come back here to eat local cuisine?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">BI2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How likely are you to recommend this destination to others?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">BI3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How willing are you to try other culinary offerings at this destination?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">BI4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How likely are you to share your positive experience with friends and family?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">CE</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">CE1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">To what extent did the experience immerse you in the local culture?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">CE2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How much did the local food experience enhance your understanding of local traditions?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">CE3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">To what degree did you engage with cultural elements while enjoying the food?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">CE4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">How strongly did cultural exposure deepen your connection with the destination?</td>
                                <td align="char" char="&#x2013;" colspan="1" rowspan="1" valign="top">1&#x2013;5</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>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&#x2019;s alpha, CR), convergent (AVE) and discriminant (Fornell-Larcker criterion) validities. Direct, indirect, and moderated effects such as the mediating effect of PV and the moderating influence of CE were investigated using the structural model. CFI, TLI, RMSEA, and SRMR were also used to assess the model&#x2019;s fit.</p>
                <p>The sampling method used was purposive sampling, which focused on tourists who personally ate local food at the culinary destinations identified in Thailand during the data collection period (January-March 2024). The participants were screened for eligibility by data collectors at these sites. On-site (paper-based) and online (QR-linked) questionnaires were used to maximize reach and minimize coverage bias. A total of 412 questionnaires were sent out, of which 380 were usable, with a 92.2% response rate. Non-response bias: An independent samples t-test was used to compare early respondents (first 25%) with late respondents (last 25%) on the key constructs. No significant differences were found (p &gt; 0.05), indicating that non-response bias was not a problem. Software clarification: SEM and CFA analyses were conducted using IBM SPSS AMOS (Version 26), and not the base SPSS. In this manuscript, the term &#x201c;SPSS (Version 26)&#x201d; is used to indicate the AMOS module that is part of the IBM SPSS Statistics platform. This clarification is provided to address the reviewer&#x2019;s concern regarding technical accuracy. Common Method Bias (CMB): Harman&#x2019;s single factor test was performed to check for CMB. The single factor explained only 28.4% of the total variance (which is below the 50% threshold); hence, CMB is not a significant concern in this dataset. Furthermore, the factor loadings obtained from the CFA ranged from 0.76 to 0.88, indicating the discriminant validity of the constructs. Discriminant validity: In addition to the Fornell-Larcker criterion reported in 
                    <xref ref-type="table" rid="T5">
Table 5</xref>, the heterotrait-monotrait (HTMT) ratio was also computed. All HTMT values were lower than the conservative limit of 0.85, indicating discriminant validity among all pairs of constructs. Effect sizes (f
                    <sup>2</sup>): Effect sizes were calculated for each structural path in the study. FQ &#x2192; CS: f
                    <sup>2</sup> = 0.14 (medium); AU &#x2192; CS: f
                    <sup>2</sup> = 0.11 (small-medium); SQ &#x2192; PV: f
                    <sup>2</sup> = 0.16 (medium); PE &#x2192; PV: f
                    <sup>2</sup> = 0.12 (small-medium); PV &#x2192; CS: f
                    <sup>2</sup> = 0.19 (medium); CS &#x2192; BI: f
                    <sup>2</sup> = 0.29 (large); CE moderation: f
                    <sup>2</sup> = 0.06 (small). These values indicate that the path from CS to BI is the most practically relevant, and that the moderating effect of CE is statistically significant but practically relevant to the path from CS to BI.</p>
                <table-wrap id="T5" orientation="portrait" position="float">
                    <label>
Table 5. </label>
                    <caption>
                        <title>Reliability and validity of constructs.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Construct</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Cronbach&#x2019;s &#x03b1;</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">CR</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">AVE</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Discriminant validity (&#x221a;AVE&#x00a0;&gt;&#x00a0;correlations)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">FQ</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.87</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.90</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.65</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">AU</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.88</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.91</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.66</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">SQ</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.85</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.88</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.61</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">PE</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.84</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.87</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.60</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">PV</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.89</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.92</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.68</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">CS</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.90</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.93</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.70</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">BI</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.88</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.91</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.67</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            </tr>
                            <tr>
                                <td align="center" colspan="1" rowspan="1" valign="top">CE</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.86</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.89</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.63</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Yes</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>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.</p>
            </sec>
        </sec>
        <sec id="sec8" sec-type="results">
            <title>4. Research results</title>
            <p>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.</p>
            <sec id="sec9">
                <title>4.1 Demographics, reliability and validity, CFA, and structural equation modeling</title>
                <p>The sample is predominantly composed of young and middle-aged respondents, with 39.5% aged between 26&#x2013;35 years, followed by 23.7% in the 18&#x2013;25 category. Female respondents (52.6%) slightly outnumber males (47.4%), and the majorities are domestic tourists (78.9%). Cultural and food tourism represents the primary travel purpose (52.6%), followed by leisure travel (36.8%). Most respondents visit local food destinations occasionally (47.4%), typically traveling with family (36.8%) or friends (31.6%). These patterns indicate that local food tourism is especially popular among socially traveling domestic visitors seeking cultural experiences.</p>
                <p>The measurement model&#x2019;s validity and measurability were thoroughly examined before the structural model tests were conducted. Internal consistency dependability was assessed using Cronbach alpha and Cronbach&#x2019;s ratio (CR). All eight of the constructs in 
                    <xref ref-type="table" rid="T5">
Table 5</xref> had Cronbach&#x2019;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&#x2019;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.</p>
                <p>The discriminant validity was tested using the Fornell Larcker criterion, which also demonstrated the constructs&#x2019; empirical uniqueness. This indicates that, in comparison to other latent variables in the model, the measurement items have a stronger relationship with their constructs.</p>
                <p>These reliability and validity results provide compelling empirical support for the measurement model&#x2019;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.</p>
                <p>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&#x00a0;&lt;&#x00a0;0.001, all item t-values were statistically significant, indicating that the factor structure was resilient. As seen in 
                    <xref ref-type="table" rid="T6">
Table 6</xref> and 
                    <xref ref-type="fig" rid="f4">
Figure 4</xref>, the measurement items are robust and trustworthy markers of their corresponding latent constructs, as indicated by the high and significant factor loadings.</p>
                <table-wrap id="T6" orientation="portrait" position="float">
                    <label>
Table 6. </label>
                    <caption>
                        <title>CFA Factor loadings and significance.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Construct</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Item code</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Factor loading</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">t-value
</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
p-value
</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="4" valign="top">
                                    <bold>FQ</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">FQ1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.82</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.45</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">FQ2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.85</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">FQ3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.78</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.95</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">FQ4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.81</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.23</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="4" valign="top">
                                    <bold>AU</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">AU1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.83</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.67</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">AU2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.86</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.35</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">AU3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.80</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.01</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">AU4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.84</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.78</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="4" valign="top">
                                    <bold>SQ</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.79</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.88</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.82</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.44</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.81</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.22</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.80</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.10</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="4" valign="top">
                                    <bold>PE</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">PE1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.77</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.64</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PE2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.79</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.91</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PE3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.78</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.85</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PE4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.76</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.50</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="4" valign="top">
                                    <bold>PV</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">PV1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.83</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.59</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PV2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.81</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.27</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PV3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.84</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.71</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PV4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.82</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.36</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="4" valign="top">
                                    <bold>CS</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.87</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.85</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.63</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.86</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.92</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.84</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.54</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="4" valign="top">
                                    <bold>BI</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">BI1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.88</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.25</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">BI2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.87</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9.12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">BI3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.85</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.80</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">BI4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.86</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.90</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="4" valign="top">
                                    <bold>CE</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">CE1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.81</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.32</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">CE2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.84</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.70</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">CE3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.82</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.45</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">CE4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.83</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.58</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <fig fig-type="figure" id="f4" orientation="portrait" position="float">
                    <label>
Figure 4. </label>
                    <caption>
                        <title>Structural model of CS and BI in LFT.</title>
                    </caption>
                    <graphic id="gr4" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/202732/216de43c-b113-4ad8-904d-70bcd295195c_figure4.gif"/>
                </fig>
                <p>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. 
                    <xref ref-type="table" rid="T7">
Table 7</xref> shows that the measurement model fit well, with RMSEA&#x00a0;=&#x00a0;0.056, CFI&#x00a0;=&#x00a0;0.952, TLI&#x00a0;=&#x00a0;0.945, and SRMR&#x00a0;=&#x00a0;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.</p>
                <table-wrap id="T7" orientation="portrait" position="float">
                    <label>
Table 7. </label>
                    <caption>
                        <title>CFA model fit and factor loadings.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Fit indices</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Value</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <inline-formula>

                                        <mml:math display="inline">
                                            <mml:mtext mathvariant="normal">RMSEA</mml:mtext>
                                        </mml:math>
</inline-formula>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.056</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <inline-formula>

                                        <mml:math display="inline">
                                            <mml:mi mathvariant="normal">CFI</mml:mi>
                                        </mml:math>
</inline-formula>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.952</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <inline-formula>

                                        <mml:math display="inline">
                                            <mml:mi mathvariant="normal">TLI</mml:mi>
                                        </mml:math>
</inline-formula>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.945</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <inline-formula>

                                        <mml:math display="inline">
                                            <mml:mtext mathvariant="normal">SRMR</mml:mtext>
                                        </mml:math>
</inline-formula>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.048</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>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. 
                    <xref ref-type="table" rid="T8">
Table 8</xref> illustrates the hypothesized relationships and their t-values, &#x03b2;, p-values and results. 
                    <xref ref-type="fig" rid="f5">
Figure 5</xref> presents the direct and the mediated association between the latent constructs.</p>
                <table-wrap id="T8" orientation="portrait" position="float">
                    <label>
Table 8. </label>
                    <caption>
                        <title>Structural model results.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Hypothesis</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Path</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">&#x03b2;</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">t-value
</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">p-value
</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Result</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">FQ&#x00a0;&#x2192;&#x00a0;CS</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.32</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.14</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Supported</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">AU&#x00a0;&#x2192;&#x00a0;CS</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.28</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4.63</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Supported</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ&#x00a0;&#x2192;&#x00a0;PV</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.34</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.47</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Supported</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">PE&#x00a0;&#x2192;&#x00a0;PV</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.29</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4.92</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Supported</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">PV&#x00a0;&#x2192;&#x00a0;CS</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.37</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6.12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Supported</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS&#x00a0;&#x2192;&#x00a0;BI</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.45</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.35</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Supported</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">SQ&#x00a0;&#x2192;&#x00a0;PV&#x00a0;&#x2192;&#x00a0;CS</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.13</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.91</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt;0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Supported (Mediation)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">CS&#x00a0;&#x00d7;&#x00a0;CE&#x00a0;&#x2192;&#x00a0;BI</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.10</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.87</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.004</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Supported (Moderation)</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
        </sec>
        <sec id="sec10" sec-type="results">
            <title>5. Conclusion and Discussion</title>
            <p>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.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>,
                    <xref ref-type="bibr" rid="ref18">18</xref>,
                    <xref ref-type="bibr" rid="ref19">19</xref>
                </sup> 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.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>,
                    <xref ref-type="bibr" rid="ref22">22</xref>,
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup> Besides, despite the popularity of cultural aspects, their moderating impact on the creation of loyalty has been demonstrated with scanty empirical support.
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>,
                    <xref ref-type="bibr" rid="ref29">29</xref>
                </sup> 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&#x2019;s LFT setting.</p>
            <p>The results show that the main factors influencing CS are FQ (&#x03b2; = 0.32) and AU (&#x03b2; = 0.28), which aligns with Hossain et al. (2024)
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> and Sangkaew et al. (2025),
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> indicating cross-contextual robustness. The strong CS &#x2192; BI path (&#x03b2; = 0.45) is higher than the effect sizes found in single-destination studies (Onat &amp; G&#x00fc;neren, 2024,
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> &#x03b2; = 0.38), indicating that Thai culinary culture has a greater impact on loyalty conversion than general hospitality settings. Authenticity vs. commercialization: The data indicate that Thai food tourists are very sensitive to authentic cues, even in commercialized settings. The high level of CE moderation (&#x03b2; = 0.10, p = 0.004) suggests that the more actively tourists interact with cultural aspects, such as engaging in traditional food rituals or interacting with local vendors, the more effectively they can translate their satisfaction into revisit and referral intentions. This means that  &#x201c;staged authenticity&#x201d; can still generate loyalty results, provided that it includes authentic cultural participation. However, when CE is low (i.e., tourists have purely commercialized meals without cultural involvement), the satisfaction&#x2013;intention pathway is weakened, indicating that perceived commercialization negatively affects loyalty when it lacks cultural meaning. The PV &#x2192; CS path (&#x03b2; = 0.37) was significantly stronger than in pre-pandemic studies, reflecting the post-pandemic  &#x201c;niche-to-necessity&#x201d; transition in LFT. In post-COVID travel behavior, travellers are now more focused on value-for-experience than value-for-money, indicating a shift in travel behavior towards experiential quality and cultural meaningfulness. Managerial implications: Destination managers must invest in cultural programming to create culturally immersive dining experiences. Specific strategies include live demonstrations of traditional Thai cooking methods, storytelling by local chefs about the origins of ingredients, and community-based food market experiences. The interventions directly address the CE moderating pathway, which means that satisfied tourists are more likely to return and promote their destination.</p>
            <p>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.</p>
            <p>From a theoretical perspective, this study advances business behavioral science by positioning local food tourism within a multidimensional experiential framework that integrates cognitive evaluation (perceived value), affective response (satisfaction), and cultural immersion (cultural experience). Unlike earlier fragmented approaches, the present model captures the dynamic interplay between authenticity and market-driven service enhancements, thereby offering a more refined explanation of tourist decision-making processes. This aligns with emerging tourism behavior theories emphasizing hybrid consumption experiences that balance symbolic cultural meaning with functional service quality.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>,
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> The findings go beyond statistical validation by explaining how CE strengthens the link between customer satisfaction and behavioral intention. When tourists actively participate in local traditions, cuisine, and heritage, their experiences become emotionally meaningful and identity-driven rather than purely transactional. This deeper connection enhances loyalty and supports sustainable consumption. In the post-pandemic context, travelers increasingly prefer authentic and culturally rich experiences over mass tourism. The study shows that CE acts as a key moderating factor, amplifying the satisfaction&#x2013;loyalty relationship. Thus, satisfaction alone is not sufficient; it must be reinforced by immersive cultural experiences to drive long-term destination loyalty and sustainable tourism behavior.</p>
            <p>Local food tourism has evolved into a complex experiential domain where authenticity, service quality, and perceived value interact within increasingly commercialized environments. This study contributes to the academic discourse by empirically validating a comprehensive structural model that captures these multidimensional relationships using robust SEM techniques. By integrating contemporary perspectives on cultural sustainability and experiential consumption, the findings extend existing business behavioral science literature beyond traditional single-factor models. The results underscore that while authenticity and food quality remain foundational drivers of satisfaction, their effectiveness is significantly shaped by perceived value mechanisms and culturally immersive experiences, thereby offering a more nuanced and theoretically enriched understanding of tourist behavioral intentions. 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&#x00a0;=&#x00a0;0.056, CFI&#x00a0;=&#x00a0;0.952, TLI&#x00a0;=&#x00a0;0.945, SRMR&#x00a0;=&#x00a0;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 (&#x03b2;&#x00a0;=&#x00a0;0.28) and FQ (&#x03b2;&#x00a0;=&#x00a0;0.32), whereas PV is positively impacted by service quality (&#x03b2;&#x00a0;=&#x00a0;0.34) and PE (&#x03b2;&#x00a0;=&#x00a0;0.29). CS was a powerful predictor of behavioral intention (0.45), while PV reinforced satisfaction (0.37). The mediating effect of PV (&#x03b2;&#x00a0;=&#x00a0;0.13) and the moderating effect of CE (&#x03b2;&#x00a0;=&#x00a0;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. Research contributes theoretically by explaining the conditional role of cultural experience in shaping tourist behavior. The moderating effect of CE indicates that customer satisfaction translates more effectively into behavioral intention when supported by meaningful cultural immersion. This finding aligns with contemporary sustainable tourism frameworks that emphasize authenticity, local engagement, and experiential depth as drivers of resilience in the post-pandemic era. Thus, the study moves beyond traditional linear models by integrating cultural context as a critical enhancer of tourist loyalty and sustainable destination development.</p>
        </sec>
    </body>
    <back>
        <sec id="sec22" sec-type="data-availability">
            <title>Data availability statement</title>
            <sec id="sec23">
                <title>Underlying data</title>
                <p>Figshare: Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.31711435.v1">https://doi.org/10.6084/m9.figshare.31711435.v1</ext-link>.
                    <sup>
                        <xref ref-type="bibr" rid="ref31">31</xref>
                    </sup>
                </p>
                <p>The project contains the following underlying data:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Survey dataset.xlsx (Raw dataset of 380 respondents used for SEM analysis).</p>
                        </list-item>
                    </list>
                </p>
            </sec>
            <sec id="sec24">
                <title>Extended data</title>
                <p>Figshare: Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.31711435.v1">https://doi.org/10.6084/m9.figshare.31711435.v1</ext-link>.
                    <sup>
                        <xref ref-type="bibr" rid="ref31">31</xref>
                    </sup>
                </p>
                <p>This project contains the following extended data:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Questionnaire.pdf (Structured questionnaire used for data collection).</p>
                        </list-item>
                    </list>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgement</title>
            <p>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.</p>
        </ack>
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    <sub-article article-type="reviewer-report" id="report491862">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.202732.r491862</article-id>
            <title-group>
                <article-title>Reviewer response for version 3</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Rana</surname>
                        <given-names>Sohel</given-names>
                    </name>
                    <xref ref-type="aff" rid="r491862a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0009-0002-5326-9735</uri>
                </contrib>
                <aff id="r491862a1">
                    <label>1</label>University of Scholars, Dhaka, Bangladesh</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>12</day>
                <month>6</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Rana S</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport491862" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.179249.3"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>I appreciate the authors' efforts in revising the manuscript and responding comprehensively to the reviewers' comments. The authors have adequately addressed the concerns raised during the review process. The manuscript is now methodologically sound, theoretically grounded, and suitable for publication. I therefore recommend acceptance for indexing.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Tourism, Marketing, Consumer Behavior.</p>
            <p>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.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report491861">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.202732.r491861</article-id>
            <title-group>
                <article-title>Reviewer response for version 3</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Wongmahesak</surname>
                        <given-names>Kittisak</given-names>
                    </name>
                    <xref ref-type="aff" rid="r491861a1">1</xref>
                    <xref ref-type="aff" rid="r491861a2">2</xref>
                    <xref ref-type="aff" rid="r491861a3">3</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0009-0000-2129-4691</uri>
                </contrib>
                <aff id="r491861a1">
                    <label>1</label>Publication Research Institute and Community Service, Universitas Muhammadiyah Sidenreng Rappang (Ringgold ID: 605937), Sidenreng Rappang Regency, South Sulawesi, Indonesia</aff>
                <aff id="r491861a2">
                    <label>2</label>Post-Doctoral Fellowship Research Collaboration Program, Lincoln University College (Ringgold ID: 283706), Petaling Jaya, Selangor, Malaysia</aff>
                <aff id="r491861a3">
                    <label>3</label>Faculty of Political Science, North Bangkok University, Sai Mai, Bangkok, Thailand</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>10</day>
                <month>6</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Wongmahesak K</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport491861" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.179249.3"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The current iteration demonstrates a significantly higher level of technical transparency and methodological rigor. Specifically, the explicit mention of IBM SPSS AMOS for structural modeling, the reporting of effect sizes (f^2), and the inclusion of Common Method Bias (CMB) testing through Harman&#x2019;s single-factor test provide the necessary scientific integrity for a high-impact platform like F1000Research. The study effectively bridges the gap between technical competence and psychological precursors in the context of Thai local food tourism, which is particularly relevant in the post-pandemic "niche-to-necessity" evolution of the industry.</p>
            <p> </p>
            <p> From a critical academic perspective, the manuscript still needs final sharpening to move beyond technical accuracy to&#x00a0;a leading theoretical contribution. While the integration of Experience Economy Theory and Self-Determination Theory is a step forward, the connection between the empirical results and these frameworks remains somewhat descriptive. The author confirms that Cultural Experience (CE) acts as a moderator, but the discussion needs to be more analytical regarding the "why." In the context of Thailand, the author should explain how cultural immersion turns a standard commercial meal into a behavioral trigger for revisit and referral. Furthermore, the narrative cohesion between the "Critical Debate" on authenticity introduced in the Introduction and the final Discussion needs a stronger bridge to explain if tourists are willing to overlook "staged authenticity" when sensory quality is high.</p>
            <p> </p>
            <p> The manuscript still has persistent linguistic issues and grammatical inaccuracies that affect its academic professionalism. There are significant instances of sentence fragments, most notably in the Abstract, where a crucial statement regarding research gaps lacks a main verb, leaving the reader to infer the intended meaning. Additionally, the text is marred by frequent comma splices and repetitive phrasing, such as the redundant use of "demanding" at the opening of the Introduction, which disrupts the prose's rhythmic flow. A critical technical oversight is the inconsistent use of the acronym "BI," which the author uses interchangeably with "Behavioral Intention" and "Business Intelligence." These inconsistencies are unacceptable for indexing and indicate a need for careful proofreading. The manuscript requires a comprehensive linguistic overhaul by a professional academic editor to ensure that the "Academic Flow" and "Sophisticated Prose" meet the standards of top-tier international publishing.</p>
            <p> </p>
            <p> In conclusion, the paper is technically sound, and the data are rich. Final approval will depend on deepening the theoretical dialogue and achieving linguistic excellence. Please move beyond restating statistical tables and instead offer a sharp, cohesive argument that highlights the study's specific Thai nuances. Consolidating the visuals and resolving the acronym overlap will make the academic narrative clearer and ensure the work is accessible to the global tourism research community. Addressing these analytical and linguistic points is essential for the article to be considered scientifically robust and ready for final indexing.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Political Science,&#x00a0;Public &amp; Private Management, International Political Economy,&#x00a0;Social Research</p>
            <p>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.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report482388">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.200745.r482388</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Rana</surname>
                        <given-names>Sohel</given-names>
                    </name>
                    <xref ref-type="aff" rid="r482388a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0009-0002-5326-9735</uri>
                </contrib>
                <aff id="r482388a1">
                    <label>1</label>University of Scholars, Dhaka, Bangladesh</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>22</day>
                <month>5</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Rana S</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport482388" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.179249.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>1.&#x00a0;The manuscript lacks a strong theoretical underpinning. Although hypotheses are presented, the study does not sufficiently anchor the model within an established theory.&#x00a0;Currently, the framework appears largely descriptive and variable-driven rather than theory-driven.</p>
            <p> 2. The literature review mainly summarizes prior studies but lacks critical synthesis. Explain how this study differs from earlier SEM-based tourism studies. And develop a stronger research gap statement.</p>
            <p> 3. Several methodological details are missing or underdeveloped: Sampling Procedure, CMB, Non-response Bias, and discriminant validity.</p>
            <p> 4. Strengthen the discussion by interpreting findings theoretically, comparing findings with previous studies, and explaining managerial significance more analytically.</p>
            <p> 5. The manuscript contains numerous grammatical and stylistic problems. Improve academic writing and language quality.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Tourism, Marketing, Consumer Behavior.</p>
            <p>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.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report486400">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.200745.r486400</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Wongmahesak</surname>
                        <given-names>Kittisak</given-names>
                    </name>
                    <xref ref-type="aff" rid="r486400a1">1</xref>
                    <xref ref-type="aff" rid="r486400a2">2</xref>
                    <xref ref-type="aff" rid="r486400a3">3</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0009-0000-2129-4691</uri>
                </contrib>
                <aff id="r486400a1">
                    <label>1</label>Publication Research Institute and Community Service, Universitas Muhammadiyah Sidenreng Rappang (Ringgold ID: 605937), Sidenreng Rappang Regency, South Sulawesi, Indonesia</aff>
                <aff id="r486400a2">
                    <label>2</label>Post-Doctoral Fellowship Research Collaboration Program, Lincoln University College (Ringgold ID: 283706), Petaling Jaya, Selangor, Malaysia</aff>
                <aff id="r486400a3">
                    <label>3</label>Faculty of Political Science, North Bangkok University, Sai Mai, Bangkok, Thailand</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>21</day>
                <month>5</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Wongmahesak K</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport486400" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.179249.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The revised manuscript (Version 2) demonstrates a commendable effort by the author to address initial concerns about the integration of contemporary literature and the narrative's structural flow. The inclusion of recent scholarship from 2025 (e.g., Phanpanya et al.; Walailak et al.; Worrachananun) significantly bolsters the study&#x2019;s relevance, positioning it within the post-pandemic paradigm of "niche-to-necessity" culinary tourism. However, from the perspective of an advanced quantitative researcher and a professor of tourism, I find that while the technical execution is robust, the manuscript requires further "sharpening" to achieve the level of novelty and theoretical contribution expected by a top-tier international outlet like 
                <italic>F1000Research</italic>.</p>
            <p> </p>
            <p> 
                <bold>1. Theoretical Refinement and Novelty (The "So What?" Factor):</bold>&#x00a0;The primary challenge of this paper remains its incremental novelty. The paths between Food Quality (FQ), Service Quality (SQ), and Customer Satisfaction (CS) are well-trodden in tourism literature. To strengthen the contribution, the author should more strongly highlight the Moderating Role of cultural experience (CE). While H8 is supported, the Discussion section still treats CE as just another variable. The author should elaborate on 
                <italic>why</italic> cultural immersion serves as a catalyst, transforming a standard meal into a behavioral trigger (revisit/referral). The "novelty" lies not in the fact that these variables interact, but in the specific cultural nuances of the Thai LFT context that make this interaction unique compared to Western or purely commercial dining contexts.</p>
            <p> </p>
            <p> 
                <bold>2. Advanced Quantitative Rigor and Methodological Transparency:</bold> While the SEM indices (CFI, TLI, RMSEA) are excellent, two technical omissions need to be immediately flagged:</p>
            <p> -&#x00a0;Software Clarification:&#x00a0;The author mentions using "SPSS (Version 26)" for SEM and CFA. Strictly speaking, base SPSS does not perform SEM; this is typically done via&#x00a0;IBM SPSS AMOS, LISREL, or R (lavaan). The author should clarify whether AMOS was used, as this is a matter of technical accuracy.</p>
            <p> - Common Method Bias (CMB):&#x00a0;Given that the data is cross-sectional and self-reported from a single source, the risk of CMB is high. The author must report the results of&#x00a0;Harman&#x2019;s Single Factor Test&#x00a0;or, ideally, a&#x00a0;Common Method Latent Factor&#x00a0;test. Without addressing CMB, the validity of the structural paths&#x2014;particularly the high correlation between satisfaction and behavioral intention&#x2014;remains scientifically vulnerable.</p>
            <p> - Effect Size (f^2):&#x00a0;While p-values indicate significance, the author should report effect sizes (f^2) to demonstrate the practical significance of each path. This would provide a more nuanced interpretation of which "experiential quality" is the most potent driver of loyalty.</p>
            <p> </p>
            <p> 
                <bold>3. Narrative Cohesion and the "Essay" Style:</bold>&#x00a0;The manuscript has improved, but still retains a "report-like" structure in the Results and Methodology sections. The transition between the Literature Review and the Hypotheses Development should be more fluid. Specifically, the "Critical Debate" regarding authenticity versus commercialization introduced in the Introduction should be revisited in the Discussion. Does the data suggest that tourists in Thailand are willing to overlook "staged authenticity" if the service quality is high? Or does the moderation of CE imply that once authenticity is lost, satisfaction no longer leads to behavioral intention? Answering these questions in cohesive prose will satisfy the previously requested "Academic Flow" requirement.</p>
            <p> </p>
            <p> 
                <bold>4. Strategic Recommendations for Final Polish:</bold>
            </p>
            <p> - Deepen the Discussion:&#x00a0;Move beyond restating Table 8. Contrast your findings with the "niche-to-necessity" evolution. If LFT is now a necessity, how does the role of "Perceived Value" (H5) shift compared to pre-pandemic studies?</p>
            <p> - Consolidate Visuals:&#x00a0;Table 4 (Measurement Items) is quite long. Consider moving it to an Appendix or a supplementary file to allow the "Literature Review" and "Methods" sections to breathe as a continuous academic narrative.</p>
            <p> - Refine the Abstract:&#x00a0;The abstract mentions "Business Intelligence (BI)" as a variable, but the paper uses "Behavioral Intention (BI)." Please correct the acronym overlap to avoid confusion for indexing services.</p>
            <p> </p>
            <p> In conclusion,&#x00a0;the manuscript is technically sound, and the data are rich. However, to transition from a "technically correct" paper to indexing, the author must emphasize the theoretical contribution of the moderation effects and ensure methodological transparency regarding CMB and software usage. Addressing these points will sharpen the manuscript&#x2019;s contribution to the global discourse on sustainable and cultural gastronomy.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Political Science,&#x00a0;Public &amp; Private Management, International Political Economy,&#x00a0;Social Research</p>
            <p>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.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report476970">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.197745.r476970</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Wongmahesak</surname>
                        <given-names>Kittisak</given-names>
                    </name>
                    <xref ref-type="aff" rid="r476970a1">1</xref>
                    <xref ref-type="aff" rid="r476970a2">2</xref>
                    <xref ref-type="aff" rid="r476970a3">3</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0009-0000-2129-4691</uri>
                </contrib>
                <aff id="r476970a1">
                    <label>1</label>Publication Research Institute and Community Service, Universitas Muhammadiyah Sidenreng Rappang (Ringgold ID: 605937), Sidenreng Rappang Regency, South Sulawesi, Indonesia</aff>
                <aff id="r476970a2">
                    <label>2</label>Post-Doctoral Fellowship Research Collaboration Program, Lincoln University College (Ringgold ID: 283706), Petaling Jaya, Selangor, Malaysia</aff>
                <aff id="r476970a3">
                    <label>3</label>Faculty of Political Science, North Bangkok University, Sai Mai, Bangkok, Thailand</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>23</day>
                <month>4</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Wongmahesak K</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport476970" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.179249.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>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.</p>
            <p> </p>
            <p> 
                <bold>1) Narrative Structure and Presentation:</bold>&#x00a0;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.</p>
            <p> </p>
            <p> 
                <bold>2) Literature Review and Argumentation:</bold> 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:</p>
            <p> -&#x00a0;The discussion on service quality and the marketing mix should be bolstered by citing&#x00a0;Walailak et al. (2025), specifically regarding how service quality factors drive satisfaction in the Thai hospitality context.</p>
            <p> -&#x00a0;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&#x00a0;Phanpanya et al. (2025).</p>
            <p> -&#x00a0;The argument regarding the impact and opportunities of food tourism in the modern era should be strengthened using the insights on sustainability provided by&#x00a0;Worrachananun (2025).</p>
            <p> </p>
            <p> 
                <bold>3) Integration of Results and Discussion:</bold> 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.</p>
            <p> </p>
            <p> 
                <bold>4) Specific Points to Address:</bold>
            </p>
            <p> -&#x00a0;Consolidation:&#x00a0;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.</p>
            <p> -&#x00a0;Critical Debate:&#x00a0;Enhance the "Introduction" by presenting a sharper debate on the conflict between "authenticity" and "commercialization" in LFT.</p>
            <p> -&#x00a0;Formatting:&#x00a0;Ensure all citations follow a consistent academic style and that the five-section structure is strictly followed without unnecessary subheadings.</p>
            <p> </p>
            <p> 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.</p>
            <p> </p>
            <p> 
                <bold>References:</bold>
            </p>
            <p> Phanpanya, K., Chanchaipitiphat, N., Jaepho, S., &amp; 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</p>
            <p> </p>
            <p> Walailak, P., Kajornatthapol, P., &amp; Veerapong, S. (2025). Drivers of Customer Satisfaction in Northern Thailand&#x2019;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</p>
            <p> </p>
            <p> 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</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Political Science,&#x00a0;Public &amp; Private Management, International Political Economy,&#x00a0;Social Research</p>
            <p>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.</p>
        </body>
    </sub-article>
</article>
