Towards Rigorous Eye-Tracking Methodology in Interdisciplinary Fields: Insights from and Recommendations for Tourism Research

TL;DR

This paper reviews eye-tracking methods in tourism research and highlights the need for more rigorous and transparent approaches to improve the validity of findings.

Contribution

The paper introduces a Checklist for Eye-Tracking Rigour (CETR) and a methodological decision tree to enhance methodological standards in tourism eye-tracking studies.

Findings

Most studies used basic fixation metrics to infer complex psychological states without sufficient validity.

Many studies failed to control for stimulus-level confounds and used inappropriate data-handling methods.

The proposed CETR and decision tree aim to guide researchers toward more confirmatory and neurobiologically grounded studies.

Abstract

Eye-tracking methodology represents a young but rapidly growing approach in tourism research, offering a direct window into the cognitive processes driving tourism stakeholders’ behaviour. However, a critical gap remains between the rapid adoption of this tool and the methodological rigour required to interpret its neurophysiological data. This critical review synthesizes 23 empirical studies (2020–2025) from the destination marketing and branding domain to diagnose eye-tracking’s state-of-the-art application. Adopting the SALSA framework (Search, Appraisal, Synthesis, Analysis) augmented by PRISMA 2020 guidelines, this study systematically searched Web of Science and Scopus databases. Studies were appraised using an eight-dimensional quality rubric, assessing from theoretical grounding to experimental design to statistical rigour. Findings revealed a “tool-first” exploratory phenomenon, where the majority of studies relied on basic fixation metrics to infer complex psychological states such as “interest”, when they could imply other cognitive states. Furthermore, most reviewed studies failed to control for stimulus-level confounds (e.g., luminance, AOI size) and utilized inappropriate data-handling procedures and methods, such as the absence of data cleaning and treating count and binary data as continuous data. These, coupled with transparency deficits, undermined the validity of their conclusions. Hence, a Checklist for Eye-Tracking Rigour (CETR) and a methodological decision tree were developed to guide researchers towards confirmatory and neurobiologically grounded research. Findings also provided a framework for managers/practitioners to more accurately interpret eye-tracking studies.

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