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AUTHOR(S): Anjali Chanu Moirangthem, Asha Gupta
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ABSTRACT A natural attraction should ensure the delivery of positive experiences for tourists that match their interests, confirming their satisfaction. If tourists have had positive experiences at a place, they are also more likely to return to the same destination in the future. A study was conducted at Loktak Lake, Manipur, a Ramsar site and a wetland of international importance for understanding the tourist behavioural intention. Data was collected from a sample of 100 tourists visiting Loktak Lake and analysed using an instrument constituting a 5-point Likert sale comprised of 10 items. Statgraphics statistical software was used to capture the data and subsequent analysis. The Principal Component Analysis (PCA) was performed. Key statistical validations obtained using Kaiser-Meyer-Olkin test (KMO) and Barlett’s test. Together, the first two components account for 80% of total variance, which is quite strong. The elbow in the eigenvalue distribution in the scree plot occurs after PC2 that suggested a 2-factor structure may be meaningful for interpretation. The biplot (PC1 vs. PC2) reveals which variables drive tourist satisfaction and intention, and how they cluster. |
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KEYWORDS Tourists, Behavioural intention, Satisfaction, Likert Scale, Principal Component analysis, KMO, Barlett’s test |
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Cite this paper Anjali Chanu Moirangthem, Asha Gupta. (2025) Application of Principal Component Analysis in understanding Tourist Behavioural Intention-A case study from Manipur. International Journal of Tourism, 8, 1-13 |
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