Sociotechnical AI Adoption and Adaptive Resilience in Hospitality and Tourism SMEs: A Qualitative Meta-Synthesis

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Abstract Artificial intelligence (AI) is transforming hospitality, yet tourism and hospitality small and medium-sized enterprises (SMEs) remain on the disadvantaged side of an AI-enabled digital divide. Moving beyond cost-centric explanations, this study synthesizes post-pandemic (2020–2026) qualitative evidence to explain the sociotechnical mechanisms that constrain or enable adoption. Using PRISMA-informed procedures, we meta-synthesized nine high-quality empirical studies and conducted a thematic synthesis through an integrated Technology–Organization–Environment (TOE) and Sociotechnical Systems (STS) lens. The findings show that resistance is often existential and identity-protective, driven by dehumanization concerns and structural inertia arising from fragmented data and limited IT capacity. Adoption becomes more feasible when SMEs pursue hybridization, allocating AI primarily to back-of-house and routine tasks while preserving human frontstage interactions that sustain authenticity and trust. Platform-mediated partnerships can scaffold digital infrastructure and reduce implementation risk for resource-poor firms, while the green–digital twin transition strengthens adoption legitimacy by linking AI to measurable sustainability and efficiency gains. We propose the SME–AI Adaptive Resilience Framework, positioning adoption as a negotiation between efficiency, authenticity, and ethical trust, and highlighting the role of governance/assurance practices in sustained adoption, with implications for managers, technology providers, and policymakers.
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Sociotechnical AI Adoption and Adaptive Resilience in Hospitality and Tourism SMEs: A Qualitative Meta-Synthesis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sociotechnical AI Adoption and Adaptive Resilience in Hospitality and Tourism SMEs: A Qualitative Meta-Synthesis Mohammadreza Parsanejad, Ali Zokaei Kuhbanani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8874905/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Artificial intelligence (AI) is transforming hospitality, yet tourism and hospitality small and medium-sized enterprises (SMEs) remain on the disadvantaged side of an AI-enabled digital divide. Moving beyond cost-centric explanations, this study synthesizes post-pandemic (2020–2026) qualitative evidence to explain the sociotechnical mechanisms that constrain or enable adoption. Using PRISMA-informed procedures, we meta-synthesized nine high-quality empirical studies and conducted a thematic synthesis through an integrated Technology–Organization–Environment (TOE) and Sociotechnical Systems (STS) lens. The findings show that resistance is often existential and identity-protective, driven by dehumanization concerns and structural inertia arising from fragmented data and limited IT capacity. Adoption becomes more feasible when SMEs pursue hybridization, allocating AI primarily to back-of-house and routine tasks while preserving human frontstage interactions that sustain authenticity and trust. Platform-mediated partnerships can scaffold digital infrastructure and reduce implementation risk for resource-poor firms, while the green–digital twin transition strengthens adoption legitimacy by linking AI to measurable sustainability and efficiency gains. We propose the SME–AI Adaptive Resilience Framework, positioning adoption as a negotiation between efficiency, authenticity, and ethical trust, and highlighting the role of governance/assurance practices in sustained adoption, with implications for managers, technology providers, and policymakers. Artificial Intelligence Tourism and Hospitality SMEs Meta-synthesis Sociotechnical Systems Adaptive Resilience Twin Transition Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 29 Mar, 2026 Reviews received at journal 26 Mar, 2026 Reviews received at journal 11 Mar, 2026 Reviews received at journal 09 Mar, 2026 Reviewers agreed at journal 09 Mar, 2026 Reviewers agreed at journal 04 Mar, 2026 Reviewers agreed at journal 26 Feb, 2026 Reviewers invited by journal 26 Feb, 2026 Editor assigned by journal 26 Feb, 2026 Submission checks completed at journal 17 Feb, 2026 First submitted to journal 13 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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