Big Data Analytics and Blockchain for Personalized Ecotourism: Toward a Digital Governance Framework for Sustainable Destinations

Abstract

Purpose of the study — This study develops a conceptual framework explaining how Big Data Analytics and blockchain-enabled trust governance can support personalized ecotourism and sustainable destination management.

Research Methodology— This study applies an integrative conceptual review. Literature was collected from Scopus, Web of Science, ScienceDirect, SpringerLink, Taylor & Francis Online, Emerald Insight, SAGE Journals, and Google Scholar for DOI verification. The review used keyword-based searching, inclusion and exclusion criteria, concept-centric coding, thematic synthesis, and conceptual proposition development. No survey instrument, statistical software, or empirical dataset was used.

Result— The synthesis identifies four main constructs: Big Data Analytics Capability, Blockchain-Enabled Trust Governance, Personalized Ecotourism Experience, and Sustainable Destination Management. The framework shows that Big Data Analytics functions as an intelligence capability for visitor insight, prediction, monitoring, and decision support. Blockchain strengthens trust, transparency, consent, traceability, and stakeholder accountability. Personalized Ecotourism Experience serves as a linking mechanism between digital capability and sustainability-oriented destination outcomes.

Conclusion— This study proposes Digital Ecotourism Governance Capability as an integrative concept combining analytical intelligence, trusted coordination, ethical data governance, visitor impact control, and community value creation. The framework contributes to tourism management, smart tourism, ecotourism, sustainable destination management, and digital governance literature.

Limitations: This study is conceptual and literature-based; therefore, the proposed framework and propositions require empirical validation in real ecotourism destinations.

Contribution: The study provides a theoretical basis for future empirical research and a managerial guide for destinations seeking to personalize visitor experiences while protecting ecological limits and community interests.