Heuristic Algorithms in Digital Transformation: Tourism-Healthcare Integration

Authors

  • Shengyu Gu School of Geography and Tourism, Huizhou University, Huizhou, China Author

DOI:

https://doi.org/10.63313/AJET.9064

Keywords:

Digital Transformation, Heuristic Algorithms, Cross-Industry Innovation, Tourism Management, Healthcare Systems, Intelligent Decision-Making, Smart Industries

Abstract

This study develops a cross-industry framework for understanding how heuristic algorithms function as engines of digital transformation across tourism and healthcare systems. Rather than treating artificial intelligence as a domain-specific optimization tool, the paper conceptualizes heuristic algorithms as adaptive intelligence mechanisms that reshape organizational decision logic, institutional coordination, and innovation pathways under conditions of uncertainty and bounded rationality. Through a comparative analysis, the study demonstrates that tourism and healthcare share common transformation dynamics, including datafication, automation, platformization, and heuristic reasoning, despite differences in data content and professional practices. Tourism is identified as an innovation origin where heuristic applications in flow management and experience design first emerged, while healthcare represents a high-stakes transformation case that validates the robustness and scalability of these methods. The core contribution lies in reframing heuristic algorithms as cognitive infrastructures that support cross-sector integration, governance modernization, and organizational adaptation. By shifting attention from algorithmic performance to transformation outcomes such as resilience, coordination, and institutional learning, this research advances management science toward a systemic understanding of digital transformation driven by adaptive intelligence across industries.

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Published

2026-07-29

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Articles

How to Cite

Heuristic Algorithms in Digital Transformation: Tourism-Healthcare Integration. (2026). Academic Journal of Emerging Technologies, 3(2), 31–45. https://doi.org/10.63313/AJET.9064