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Статья

Digital Capability for AI Readiness Among Tourism Micro and Small Enterprises in a Silk Road Heritage Destination

Nilufar Uktamovna AkhrorovaFaculty of Economics and Tourism, Bukhara State University, Bukhara 200100, UzbekistanDilrabo MardonovaDepartment of Tourism Management, Silk Road International University of Tourism and Cultural Heritage, Samarkand 140104, UzbekistanFeruza BekmurodovaDepartment of International Economics, University of World Economy and Diplomacy, Tashkent 100007, UzbekistanFarangiz YoriyevaDepartment of Economics, University of Science and Technologies, Tashkent 100208, UzbekistanBekmurod OllanazarovFaculty of Economics, Urgench RANCH University of Technology, Urgench 220100, UzbekistanШухрат КурбанбаевDepartment of Tourism, Urgench State University Named After Abu Rayhon Beruni, Urgench 220100, Uzbekistan
2026en
ABI

Аннотация

Tourism micro and small enterprises form the backbone of supply in most destinations, yet firm-level evidence on their readiness for artificial intelligence is thin, and emerging heritage destinations are almost absent from the record. This study asks what such firms use, how much AI-relevant digital capability they hold, and what differentiates the firms that hold more of it. Responses from 261 participating enterprises across five sub-sectors in Bukhara, Uzbekistan, fed a Digital Capability for AI Readiness Index of twelve survey-derived indicators covering the technology and organization domains of the technology–organization–environment framework. Market pressure, disposition and adoption intention were measured outside the index, and independent expert ratings corroborate it without contributing to it. Adoption falls from 79.7% for tools requiring nothing beyond an existing device to 22.6% for an AI assistant, an ordering consistent with what each tool requires the firm to supply. Capability averages 59.4% and differs sharply by sub-sector (ε2 = 0.215), a difference that survives removal of all realized tool use from the index and restriction to indicators applicable across every sub-sector, although roughly two fifths of its magnitude is carried by the tool-use indicators (ε2 = 0.131 without them). Firm size, customer orientation and disposition show no detectable association. A candidate explanation for the sub-sector difference, dependence on digital intermediation, was operationalized using the expert ratings and did not account for it. The study separates a technology-level ordering from a firm-level, sub-sector-associated one and releases a fully documented exploratory measure of the digital capability that plausibly precedes AI adoption rather than of AI readiness itself, for a data-scarce heritage destination. Whether the measure predicts subsequent AI adoption remains to be tested.

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