Designing an Exploratory Sequential Meta-Synthesis–Structural Equation Modeling Approach for Validating Social Media Marketing Models: An Application in Food Tourism

Abstract

This study aimed to develop and validate an integrated social media marketing model for food tourism through an exploratory sequential meta-synthesis–PLS-SEM approach among Iranian Instagram users. An exploratory sequential mixed-methods design was employed. In the qualitative phase, a systematic meta-synthesis of studies published from 2016 to 2026 was conducted using Web of Science and Google Scholar, with study selection guided by PRISMA 2020, methodological appraisal based on qualitative quality criteria, and coding and synthesis performed in MAXQDA. The resulting conceptual model was transferred to the quantitative phase and operationalized through a 43-item researcher-developed questionnaire comprising 36 substantive items across ten constructs. The target population consisted of Iranian Instagram users who had interacted with food-tourism-related content. Using convenience and supplementary snowball sampling, 121 valid responses were obtained. The measurement and structural models were assessed using PLS-SEM, including reliability, convergent validity, discriminant validity, structural path coefficients, effect sizes, explanatory power, predictive relevance, indirect effects, and moderation analysis. All hypothesized structural relationships were supported. User-generated and foodstagramming content (β=.314, p<.001), influencer marketing and culinary celebrity influence (β=.357, p<.001), and platform/content-format characteristics (β=.221, p=.001) positively predicted destination and food brand image. Destination and food brand image positively affected social media engagement (β=.612, p<.001) and electronic word-of-mouth (β=.574, p<.001). Social media engagement significantly predicted food tourist experience and satisfaction (β=.628, p<.001), while electronic word-of-mouth predicted motivation and intention to share or consume (β=.661, p<.001). Food tourist experience and satisfaction strongly predicted loyalty and revisit intention (β=.693, p<.001). Contextual conditions significantly moderated the engagement–experience relationship (β=.174, p=.014). All examined indirect effects were significant, and the endogenous constructs showed satisfactory explanatory and predictive power. Social media marketing in food tourism operates through a sequential mechanism in which digital content and influencer-related antecedents shape destination and food brand image, which then activates engagement and eWOM pathways leading to satisfaction, loyalty, revisit intention, and sharing/consumption intentions; therefore, an integrated rather than fragmented approach is required for explaining and managing social media effects in food-tourism contexts.