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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Using Neuroscience To Decode Tourist Behaviour And Intentions For Sustainable Choices

Authors: Baldocchi, Marco; Lusby, Carolin;

Using Neuroscience To Decode Tourist Behaviour And Intentions For Sustainable Choices

Abstract

Tourism is an inherently emotional experience. Yet, for decades, research has relied predominantly on rational-choice models and self-report surveys, assuming that tourists make deliberate and conscious decisions. Recent advances in neuroscience and consumer behavior studies challenge this assumption, revealing that up to 95% of our decisions are driven by unconscious processes and emotional responses. This paper introduces a neuroscientific framework for decoding tourist behavior. It is based on dual-system theory (System 1 and 2), predictive brain models, and physiological measurement techniques such as EEG, eye-tracking, GSR, facial coding, and implicit association testing. Through real-world case studies in food tourism, hospitality, and cultural heritage, we show how these tools uncover unspoken emotional responses that shape memory, satisfaction, and behavior. A dedicated section addresses sustainable tourism, illustrating how neuroscience-informed nudges can help align tourist behavior with ecological values without compromising enjoyment. Finally, we explore implications for tourism operators, marketers, and policymakers, emphasizing how emotion-driven design and communication can foster more engaging and sustainable tourism experiences.

Keywords

Predictive Processing, Unconscious Decision-making, Tourist Behavior, Consumer Neuroscience, Emotion Measurement, Sustainable Tourism

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green