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

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  • Nuno Calheiros-Lobo

    (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)

  • Ana Palma-Moreira

    (Faculdade de Ciências Sociais e Tecnologia, Universidade Europeia, Quinta do Bom Nome, Estr. da Correia 53, 1500-210 Lisboa, Portugal)

  • Manuel Au-Yong-Oliveira

    (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
    Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), 4200-465 Porto, Portugal)

  • José Vasconcelos Ferreira

    (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)

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.

Suggested Citation

  • Nuno Calheiros-Lobo & Ana Palma-Moreira & Manuel Au-Yong-Oliveira & José Vasconcelos Ferreira, 2025. "Entity-Relationship Mapping of 184 SME Internationalization Success Determinants for AI Feature Engineering: Integrating CSR, Deep Learning, and Stakeholder Insights," Sustainability, MDPI, vol. 17(19), pages 1-33, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:19:p:8587-:d:1757403
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    References listed on IDEAS

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