Journal of Applied Data Sciences
Vol 7, No 4: December 2026

Modeling Gastronomy Tourists' Behavioural Intention Using eWOM, Food Authenticity, Customer Perceived Value, and Destination Image

Imas Gandasari (Universitas Negeri Jakarta)
Mohamad Rizan (Unknown)
Setyo Ferry Wibowo (Unknown)



Article Info

Publish Date
29 Oct 2026

Abstract

Understanding tourists' behavioural intention is essential for developing competitive and sustainable gastronomy tourism destinations. This study develops and validates an integrated Structural Equation Modeling (SEM) framework to examine the effects of electronic word-of-mouth (eWOM), food authenticity, customer perceived value, and destination image on gastronomy tourists' behavioural intention. A quantitative cross-sectional survey was conducted among 424 domestic gastronomy tourists in Bandung, Indonesia, and the data were analyzed using SEM. The results show that eWOM significantly influences customer perceived value and destination image but has no direct effect on behavioural intention. In contrast, food authenticity significantly enhances customer perceived value, destination image, and behavioral intention, while customer perceived value and destination image significantly mediate the effects of eWOM and food authenticity. The proposed model explains 47.5% of the variance in behavioural intention, demonstrating moderate explanatory capability. These findings extend Customer Behavior Theory, Customer Perceived Value Theory, Destination Image Formation Theory, and Food Tourism Theory by demonstrating that tourists' behavioural intention is primarily shaped through sequential cognitive evaluations rather than direct exposure to digital information. From an applied data science perspective, the study demonstrates the usefulness of SEM as a predictive modeling framework for transforming behavioural data into evidence-based decision support for sustainable gastronomy tourism management.

Copyrights © 2026






Journal Info

Abbrev

JADS

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Description

One of the current hot topics in science is data: how can datasets be used in scientific and scholarly research in a more reliable, citable and accountable way? Data is of paramount importance to scientific progress, yet most research data remains private. Enhancing the transparency of the processes ...