Comparing fsQCA with PLS-SEM: predicting intended car use by national park tourists

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Abstract
Multivariate analysis techniques are always evolving in social sciences. We compared a new alternative approach called fuzzy-set qualitative comparative analysis (fsQCA) with the conventional regression-based approach called partial least squares structural equation modeling (PLS-SEM) by testing the models to predict the national park tourists’ car use and car less-use intentions. PLS-SEM results were conditionally supported by fsQCA for car use intention, namely, pro-driving norm and neutralization techniques have significant positive effects on tourists’ car use intention. For car less-use intention, fsQCA provided more nuanced information to predict high and low car less-use intention. Considering their respective advantages and limitations, these two approaches could be used complementarily in pro-environmental behavior research.
Funding Information
  • National Natural Science Foundation of China (41371161)

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