{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T19:11:56Z","timestamp":1770837116869,"version":"3.50.1"},"reference-count":103,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T00:00:00Z","timestamp":1753401600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Erasmus+ project","award":["2024-1-DE02-KA210-VET-000255761"],"award-info":[{"award-number":["2024-1-DE02-KA210-VET-000255761"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>This study introduces the concept of DEEPEIA, a novel deep learning (DL) platform designed to recommend the optimal export market, and its ideal foreign champion, for any product or service offered by a small and medium-sized enterprise (SME). Drawing on expertise in SME internationalization and leveraging recent advances in generative artificial intelligence (AI), this research addresses key challenges faced by SMEs in global expansion. A systematic review of existing platforms was conducted to identify current gaps and inform the conceptualization of an advanced generative DL recommender system. The Discussion section proposes the conceptual framework for such a decision optimizer within the context of contemporary technological advancements and actionable insights. The conclusion outlines future research directions, practical implementation strategies, and expected obstacles. By mapping the current landscape and presenting an original forecasting tool, this work advances the field of AI-enabled SME internationalization while still acknowledging that more empirical validation remains a necessary next step.<\/jats:p>","DOI":"10.3390\/info16080636","type":"journal-article","created":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T11:38:41Z","timestamp":1753443521000},"page":"636","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["DEEPEIA: Conceptualizing a Generative Deep Learning Foreign Market Recommender for SMEs"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4064-2342","authenticated-orcid":false,"given":"Nuno","family":"Calheiros-Lobo","sequence":"first","affiliation":[{"name":"Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2154-6171","authenticated-orcid":false,"given":"Manuel","family":"Au-Yong-Oliveira","sequence":"additional","affiliation":[{"name":"Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal"},{"name":"Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5577-8237","authenticated-orcid":false,"given":"Jos\u00e9","family":"Vasconcelos Ferreira","sequence":"additional","affiliation":[{"name":"Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1177\/09610006221142029","article-title":"Defining Artificial Intelligence for Librarians","volume":"56","author":"Cox","year":"2024","journal-title":"J. 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