Author
Listed:
- 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)
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.
Suggested Citation
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jtourh:v:6:y:2025:i:4:p:187-:d:1753876. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.