DEEPEIA: Conceptualizing a Generative Deep Learning Foreign Market Recommender for SMEs

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.

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Published
2025-07-25
DOI
https://doi.org/10.3390/info16080636
Citations
1
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.52

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article

DEEPEIA: Conceptualizing a Generative Deep Learning Foreign Market Recommender for SMEs

Manuel Au‐Yong‐Oliveira, José Vasconcelos Ferreira, Nuno Calheiros-Lobo
1 citations
Information
Machine Learning in Materials Science
0.52
article

DEEPEIA: Conceptualizing a Generative Deep Learning Foreign Market Recommender for SMEs

Manuel Au‐Yong‐Oliveira, José Vasconcelos Ferreira, Nuno Calheiros-Lobo
article en
1 citations

Abstract

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.

InformationVol. 16(8)
INESC TEC (PT), University of Aveiro (PT)
Erasmus+
Openalex Percentile: Top 35%
Machine Learning in Materials Science
0.52
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