RT Journal Article
T1 Evaluating tourism destination images: integrating survey, neural responses and artificial intelligence
A1 Jarzus, Kathrin
A1 Erdmann, Anett
A1 Ramos-Henríquez, José Manuel
A1 Mas Iglesias, José Manuel
AB This study introduces a triple-method approach to evaluate tourism destination attractiveness by integrating consumer surveys, neurophysiological measurements, and large language models (LLMs). Drawing on dual-process theory as a conceptual and interpretive framework, we examine how different measurement methods, individually and in combination, can help explain tourists' preferences for destination images. The study involved 96 participants from two countries who were shown in an experiment ten images representing various tourism types while collecting self-reported data, neurophysiological measurements, and LLM-based image assessments. To analyze image rankings and relative preferences, we adopted a multi-stage analytical approach. Our findings suggest that each measurement method captures distinct aspects of tourist decision-making: Survey measurements primarily correlate with fast-affective responses. Neurophysiological data reveal affective and cognitive responses not detected in self-reports. LLMs offer complementary evaluations. However, the incremental explanatory value of LLM-based assessment varies by image-type. Combined measurements also differ in effectiveness across tourism types, underscoring the need for tailored evaluation approaches.
PB Elsevier
SN 2212-571X
YR 2026
FD 2026-06-01
LK https://hdl.handle.net/20.500.14352/132312
UL https://hdl.handle.net/20.500.14352/132312
LA eng
NO Jaszus, K., Erdmann, A., Ramos-Henríquez, J. M., & Mas-Iglesias, J. M. (2026). Evaluating tourism destination images: Integrating survey, neural responses and artificial intelligence. Journal of Destination Marketing & Management, 40, 101089. https://doi.org/10.1016/j.jdmm.2026.101089
DS Docta Complutense
RD 20 mar 2026