Brian King, Texas A&M University

Babak Taheri, Texas A&M University

Danae Manika, Brunel University of London

Kyoung Jun Lee, Kyung Hee University

The aim of this special issue is to advance scholarly understanding of Responsible and Trustworthy Artificial Intelligence in tourism and hospitality, by assembling cutting-edge research, innovative methodologies, and critical reflections. As AI technologies become embedded in service delivery, marketing, operations, and consumer experience, transformative opportunities are accompanied by potential ethical challenges. Issues of fairness, accountability, transparency, and trust are particularly pressing as the sector adopts AI in pursuit of personalization, efficiency, and engagement. Responsible AI is linked with the concept of trustworthy AI, which reflects a stronger technological view and focuses on systems that are lawful, ethical, and robust throughout their lifecycle. Earlier research in tourism and hospitality has shown the need for interdisciplinary inquiry regarding the technical, managerial, legal, and societal dimensions of responsible AI adoption.

This special issue aims to provide a dedicated forum for interdisciplinary inquiry into the tensions and synergies that are evident between innovation, ethical responsibility, and human experience. It particularly encourages submissions that highlight the design, adoption, and governance of AI-enabled digital platforms, data-sharing ecosystems, and information infrastructures shaping tourism and hospitality. Papers may investigate the broader societal impacts of AI and topics such as bias and fairness in algorithmic decision-making, consumer trust in AI systems, sustainable and frugal AI applications, digital twins for experience innovation, and governance and regulatory frameworks and human-centered design. This builds on prior Electronic Markets contributions on responsible and trustworthy AI and extends them into the domain of tourism and hospitality. This special issue will foster dialogue across disciplines to highlight best practices as well as challenges in the design, deployment, and governance of responsible AI systems. Ultimately, it seeks to open up pathways that will ensure enhanced customer experiences through AI-driven innovation in tourism and hospitality, while upholding ethical, social, and environmental responsibility.

Electronic Markets is a Social Science Citation Index (SSCI)-listed journal in the area of information management and information systems. All papers should fit the journal scope. This special issue invites submissions that investigate the critical dynamics, challenges, and transformative potential of responsible and trustworthy AI in tourism and hospitality. We welcome studies that deploy quantitative, qualitative, or mixed methods approaches, providing that they demonstrate methodological rigor and scholarly relevance. Suitable contributions may include conceptual and theoretical papers, empirical investigations, case-based analyses, position papers, and integrative reviews.

Potential topics

• Ethical AI frameworks in tourism and hospitality: fairness, accountability, transparency, and inclusivity.
• AI-driven consumer experiences: balancing personalization, convenience, and privacy.
• AI robustness and risk: testing booking, pricing, and chatbot vulnerabilities, modeling threats, and strengthening resilience.
• Trust, reliability and safety: building consumer trust, ensuring reliable performance, and managing risks.
• Auditing AI systems: ongoing evaluations in pursuit of fairness, accuracy, and compliance.
• Generative AI in marketing: pursuing responsibility in branding, engagement, and consumer journeys.
• Sociotechnical and cultural dimensions: cross-cultural and historical perspectives on AI adoption.
• AI, sustainability, and CSR: supporting or hindering responsible and sustainable practices in tourism and hospitality.
• Future directions: conceptual frameworks and policy challenges for responsible and trustworthy AI in service innovation and resilience.
• Social and labor impacts: the effects of adopting AI on employment, equity, and workforce well-being.
• Frugal AI and digital twins: cost-effective and resource-conscious applications for operations and guest experiences.
• Algorithmic transparency and rights: making AI decisions understandable and offering recourse for affected consumers.
• Dark side of AI: risks of manipulation, surveillance, over-automation, and addictive design.
• Corporate digital responsibility (CDR) in the age of AI within tourism and hospitality.
• AI on digital platforms: exploring recommender systems, marketplaces, and platform governance.
• Data ecosystems: sharing and leveraging user/usage data across digital travel and hospitality platforms.
• Trustworthy AI principles: ensuring AI systems in tourism and hospitality are lawful, ethical, and technically robust.
• Verification, validation, and explainability: designing AI that is interpretable and auditable for multiple stakeholders.
• Trustworthy AI and consumer journeys: balancing automation with transparency and user empowerment.

Timeline

• September 15, 2026: Submission deadline

This special issue focuses on the mathematical and computational foundations necessary for developing trustworthy artificial intelligence applications in transportation systems. As AI increasingly influences critical transportation decisions affecting safety, efficiency, and equity, there is an urgent need for rigorous mathematical frameworks that ensure these systems are reliable, interpretable, and accountable.

The special issue welcomes contributions that advance the theoretical understanding and practical implementation of trustworthy AI in transportation. This includes work on mathematical models that enhance transparency, ensure robustness against adversarial attacks, quantify uncertainties, and address fairness concerns in transportation algorithms and systems.

Submissions should demonstrate how mathematical and computational approaches contribute to building trustworthy AI systems that stakeholders can understand, verify, and depend upon for critical transportation applications.

Potential topics

• Mathematical frameworks for explainability and interpretability in transportation AI
• Formal verification and validation methods for autonomous vehicles
• Trustworthy machine learning algorithms for traffic prediction and management
• Robustness and adversarial resilience in transportation systems
• Uncertainty quantification in AI-based transportation applications
• Fairness and bias mitigation in transportation decision-making systems
• Privacy-preserving techniques in transportation data analytics
• Game-theoretic approaches to multi-agent transportation systems
• Causal inference methods for transportation research
• Probabilistic and Bayesian methods in transportation AI

Timeline

• December 1, 2026: Full paper submission deadline