Fuzzy-Set Qualitative Comparative Analysis (fsQCA) and Necessary Condition Analysis (NCA) in Tourism and Hospitality Studies: A Review for Bridging Bi-Polar Methodological Divides

Tourism and hospitality studies struggle with a methodological divide, forcing scholars to choose between generalizability and contextual understanding while often failing to capture complex causal relationships like equifinality and conjunctural causation. This reliance on conventional approaches can obscure the critical insights needed for strategic decision-making and development within the industry. Thus, this review aims to demonstrate how fsQCA elucidates diverse configurations of conditions that lead to specific outcomes, while NCA identifies critical bottleneck conditions essential for achieving those outcomes, thereby enriching understanding of complex causality and effectively bridging bipolar methodological and analytical frameworks. To support this exploration, the authors conducted a systematic review of 89 articles. The results reveal that these set-theoretic methods effectively bridge long-standing methodological divides, integrating qualitative depth with quantitative rigour, moving beyond variable-oriented analyses to embrace case-oriented insights, explicitly modelling asymmetrical relation-ships, encouraging configurational thinking, enhancing causal inference, addressing data characteristics and limitations of traditional methods. It also enhances theoretical development by fostering more nuanced, context-sensitive causal models that align with the principles of complexity theory. Practically, the findings empower managers and policymakers with strategic flexibility by highlighting diverse pathways to success and enabling prioritised resource allocation by identifying non-negotiable necessary conditions. While acknowledging limitations such as a focus primarily on methodological application and the exclusion of grey literature, the study proposes future research directions, including integrated fsQCA-NCA frameworks, longitudinal studies, multi-level analyses, and exploring emerging phenomena and niche markets, to further advance scholarly understanding and practical applications in the field.