Strategic Readiness for AI and Smart Technology Adoption in Emerging Hospitality Markets: A Tri-Lens Assessment of Barriers, Benefits, and Segments in Albania

Majlinda Godolja (), Tea Tavanxhiu and Kozeta Sevrani
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Majlinda Godolja: Faculty of Economy, University of Tirana, 1010 Tirana, Albania
Tea Tavanxhiu: Faculty of Economy, University of Tirana, 1010 Tirana, Albania
Kozeta Sevrani: Faculty of Economy, University of Tirana, 1010 Tirana, Albania

Tourism and Hospitality, 2025, vol. 6, issue 4, 1-36

Abstract: The adoption of artificial intelligence (AI) and smart technologies is reshaping global hospitality. However, in emerging markets, uptake remains limited by financial, organizational, and infrastructural barriers. This study examines the digital readiness of 1821 licensed accommodation providers in Albania, a rapidly expanding tourism economy, using an integrated framework that combines the Technology Acceptance Model (TAM), technology–organization–environment (TOE) framework, and Diffusion of Innovations (DOI). Data were collected via a structured survey and analyzed using descriptive statistics, exploratory factor analysis, cluster analysis, and structural equation modeling. Exploratory factor analysis identified a single robust readiness dimension, covering smart automation, environmental controls, and AI-driven systems. K-means segmentation revealed three adopter profiles: Tech Leaders (17.7%), Selective Adopters (43.5%), and Skeptics (38.8%), with statistically distinct but modest mean differences in readiness, reflecting stronger adoption in central urban and coastal hubs compared to weaker uptake in cultural heritage and non-urban regions. Structural modeling showed that environmental competitive pressure strongly enhanced perceived usefulness, which, in turn, drove behavioral intention, whereas perceived ease of use (operationalized as implementation complexity) had negligible effects. Innovation readiness was consistently associated with broader adoption, although intention was translated into actual use only among Tech Leaders. The findings highlight a fragmented digital ecosystem in which enthusiasm for AI exceeds its feasibility, underscoring the need for differentiated policy support, modular vendor solutions, and targeted capacity building to foster inclusive digital transformation.

Keywords: AI adoption; smart technology; digital readiness; technology adoption frameworks; structural equation modeling (SEM); TOE model; TAM; DOI theory; hospitality SMEs; emerging markets; Albania; sustainability (search for similar items in EconPapers)
JEL-codes: Z3 Z30 Z31 Z32 Z33 Z38 (search for similar items in EconPapers)
Date: 2025
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