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https://hdl.handle.net/11000/40408Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Alos-Simo, Lirios | - |
| dc.contributor.author | Serna-Serna, Paula | - |
| dc.contributor.author | Verdu-Jover, Antonio José | - |
| dc.contributor.author | Gómez-Gras, José María | - |
| dc.contributor.other | Departamentos de la UMH::Estudios Económicos y Financieros | es_ES |
| dc.date.accessioned | 2026-09-07T10:35:18Z | - |
| dc.date.available | 2026-09-07T10:35:18Z | - |
| dc.date.created | 2026 | - |
| dc.identifier.citation | Current Issues in Tourism. | es_ES |
| dc.identifier.issn | 1368-3500 | - |
| dc.identifier.uri | https://hdl.handle.net/11000/40408 | - |
| dc.description.abstract | Grounded in the Natural Resource-Based View (NRBV), this study examines the influence of Artificial Intelligence (AI) and Big Data Analytics (BDA) on eco-innovation in tourism SMEs to address a critical gap in the sustainability literature. The analysis tests a sequential mediation model using Partial Least Squares Structural Equation Modeling (PLS-SEM) and survey data from 220 Spanish tourism firms. To ensure econometric robustness, the findings are validated through a Gaussian copula and two-stage least squares (2SLS) instrumental variable analysis. The results show that AI and BDA do not directly drive eco-innovation. Rather, their impact is channelled entirely through adoption of green digital technologies, which in turn stimulates process innovation. Thus, digital investment alone is insufficient; to leverage AI and BDA for sustainability, tourism SMEs must adopt an intensive approach that combines technological investments with subsequent process improvements. The study also highlights that successful eco-innovation depends on revising organisational routines to transform digital investment into innovative and sustainable outcomes. | es_ES |
| dc.format | application/pdf | es_ES |
| dc.format.extent | 22 | es_ES |
| dc.language.iso | eng | es_ES |
| dc.publisher | Taylor & Francis Group | es_ES |
| dc.relation.ispartofseries | Vol.30(17) | es_ES |
| dc.relation.ispartofseries | 1-22 | es_ES |
| dc.rights | info:eu-repo/semantics/closedAccess | es_ES |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
| dc.subject | artificial Intelligence | es_ES |
| dc.subject | big Data Analytics | es_ES |
| dc.subject | ecoinnovation | es_ES |
| dc.subject | green digital technologies | es_ES |
| dc.subject | process innovation | es_ES |
| dc.subject.other | CDU::3 - Ciencias sociales::33 - Economía::338 - Situación económica. Política económica. Gestión, control y planificación de la economía. Producción. Servicios. Turismo. Precios | es_ES |
| dc.subject.other | CDU::0 - Generalidades.::04 - Ciencia y tecnología de los ordenadores. Informática. | es_ES |
| dc.title | How do Artificial Intelligence (AI) and Big Data Analytics (BDA) drive eco-innovation in the tourism industry?. | es_ES |
| dc.title.alternative | ¿Cómo impulsan la Inteligencia Artificial (IA) y el Análisis de Big Data (BDA) la eco-innovación en la industria turística?. | es_ES |
| dc.type | info:eu-repo/semantics/article | es_ES |
| dc.relation.publisherversion | https://doi.org/10.1080/13683500.2026.2692462 | es_ES |
alos_simo, serrna_serna, verdu_jover, gomez_gras_CIIT 2026.pdf
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