Big Data Driven Strategic Management in Tourism Governance: A Systematic Literature Review and Future Research Agenda

Abstract

The digital transformation of tourism has generated massive data from platforms, social media, and sensors, creating opportunities for big data-driven strategic management in governance. However, academic literature on how big data supports strategic decision-making in tourism policy remains fragmented. This study systematically reviews the integration of big data analytics into strategic management processes within tourism governance. Using a Systematic Literature Review (SLR) approach, it synthesizes peer-reviewed articles focusing on big data, tourism governance, and policy analytics through structured identification, screening, and eligibility stages. Findings reveal three main thematic clusters: (i) big data for demand forecasting and visitor behavior analytics, (ii) data-driven insights for evidence-based policy and destination governance, and (iii) the emergence of smart tourism ecosystems supported by real-time data and digital tools. Despite growing interest, gaps remain regarding institutional capacity, stakeholder data integration, governance frameworks, and ethical issues like privacy. This study proposes a conceptual framework linking big data analytics, strategic management capabilities, and tourism governance outcomes. It outlines a future research agenda focusing on governance models, data interoperability, and AI integration. The results provide theoretical contributions to tourism research and practical insights for policymakers seeking to strengthen data-driven governance in the digital transformation era.