Entity-Relationship Mapping of 184 SME Internationalization Success Determinants for AI Feature Engineering: Integrating CSR, Deep Learning, and Stakeholder Insights

Corporate Social Responsibility (CSR) is increasingly shaping the pathways of Small Medium-sized Enterprises (SMEs). This study presents an entity-relationship diagram (ERD) approach to 184 determinants of SME internationalization success, in order to provide structured inputs for Deep Learning (DL) Recommenders that can support CSR-aligned internationalization strategies. Employing Visual Paradigm 17.2 Professional software for modeling, the research synthesizes state-of-the-art findings on foreign market entry, and export performance, into ERDs. Then the market adoption drivers for such a DL tool are explored through semi-structured interviews with twelve stakeholders. The results reveal a propensity to adopt the DL recommender, with experts highlighting essential features for engagement, pricing, and implementation. The discussion contextualizes these findings, while the conclusion addresses gaps and future directions. The study’s focus in Portugal/Germany may limit worldwide extrapolation, yet it advances knowledge by consolidating success determinants, validating platform requirements, exposing gaps, and suggesting research in both CSR, AI and SME internationalization.

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Publication Details

Journal
Sustainability
Published
2025-09-24
DOI
https://doi.org/10.3390/su17198587
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Entity-Relationship Mapping of 184 SME Internationalization Success Determinants for AI Feature Engineering: Integrating CSR, Deep Learning, and Stakeholder Insights

Manuel Au‐Yong‐Oliveira, José Vasconcelos Ferreira, Ana Moreira, Nuno Calheiros-Lobo
Sustainability
Big Data and Business Intelligence
article

Entity-Relationship Mapping of 184 SME Internationalization Success Determinants for AI Feature Engineering: Integrating CSR, Deep Learning, and Stakeholder Insights

Manuel Au‐Yong‐Oliveira, José Vasconcelos Ferreira, Ana Moreira, Nuno Calheiros-Lobo
article en

Abstract

Corporate Social Responsibility (CSR) is increasingly shaping the pathways of Small Medium-sized Enterprises (SMEs). This study presents an entity-relationship diagram (ERD) approach to 184 determinants of SME internationalization success, in order to provide structured inputs for Deep Learning (DL) Recommenders that can support CSR-aligned internationalization strategies. Employing Visual Paradigm 17.2 Professional software for modeling, the research synthesizes state-of-the-art findings on foreign market entry, and export performance, into ERDs. Then the market adoption drivers for such a DL tool are explored through semi-structured interviews with twelve stakeholders. The results reveal a propensity to adopt the DL recommender, with experts highlighting essential features for engagement, pricing, and implementation. The discussion contextualizes these findings, while the conclusion addresses gaps and future directions. The study’s focus in Portugal/Germany may limit worldwide extrapolation, yet it advances knowledge by consolidating success determinants, validating platform requirements, exposing gaps, and suggesting research in both CSR, AI and SME internationalization.

SustainabilityVol. 17(19)
Universidade Europeia (PT), INESC TEC (PT), University of Aveiro (PT)
Openalex Percentile: Top 57%
Big Data and Business Intelligence
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Entity-Relationship Mapping of 184 SME Internationalization Success Determinants for AI Feature Engineering: Integrating CSR, Deep Learning, and Stakeholder Insights — Manuel Au‐Yong‐Oliveira, José Vasconcelos Ferreira, et al. · Sustainability (2025) | TGRS Research Map | TGRS