Environmental Risk Perception and Tourist Behavioral Intentions Under PM2.5 Pollution: A Mixed-Methods Investigation in Coastal Thailand - Ittiphong, Kasemsri; Pookkaman, Nuchjaree; Theerasak, Waraporn (Arts of Management Journal, 2026)
This study examines how fine particulate matter (PM2.5) air pollution shapes environmental risk perception (ERP) and tourist behavioral intentions at Bangsaen, a popular coastal destination in Chonburi Province, Thailand. Utilizing Protection Motivation Theory (PMT) as a guiding framework, a convergent mixed-methods design integrated qualitative semi-structured interviews with 36 tourists and a quantitative structured questionnaire administered to 123 visitors during January–February 2026. The study focused primarily on the threat-appraisal pathway, conceptualizing ERP as an intervening cognitive appraisal proxy rather than direct protection motivation, while coping appraisal was examined qualitatively and via exploratory single-item correlation. The study yielded three principal findings: (1) tourists exhibited moderate-to-high overall ERP (M = 3.89, SD = 0.77), which was positively associated with all seven behavioral dimensions, showing the strongest association with destination selection sensitivity (r = .676, p < .001); (2) adaptive coping responses dominated (78%), driven by high qualitative self-efficacy and the availability of indoor substitution activities, while trip cancellation intentions were less prevalent (22%); and (3) ERP levels differed significantly across subgroups, with older, female, and non-Asian international visitors exhibiting greater risk sensitivity, suggesting that threat appraisals are influenced by experiential familiarity. Critically, while the findings offer valuable segmented communication strategies for coastal destination managers, the study’s academic value is bounded by a youth-skewed convenience sample, a cross-sectional design that prevents causal inference, and a single-item quantitative measure of response efficacy. These methodological constraints highlight the necessity for future longitudinal research with representative probability sampling.