Beyond regression: an ANN approach for exploring social entrepreneurship’s impact on sustainability in Korean organizations

Won-Seok Bang, Ko Hee Yoon, Kuk Hoan Wee, Binitha Chowdary Bandi, Sun Hwa Kim, Jung-Yoon Kim, Dong-Hwan Cho () and N. S. Reddy ()
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Won-Seok Bang: Entrepreneurship Research Institute, Gyeongsang National University
Ko Hee Yoon: Pusan National University
Kuk Hoan Wee: Pusan National University
Binitha Chowdary Bandi: The University of Warwick
Sun Hwa Kim: Korea Maritime and Ocean University
Jung-Yoon Kim: Cumberland University
Dong-Hwan Cho: Gyeongsang National University
N. S. Reddy: Gyeongsang National University

Journal of Global Entrepreneurship Research, 2025, vol. 15, issue 1, 1-15

Abstract: Abstract Purpose This study explores the complex dynamics within Korean public organizations, specifically focusing on the interplay between social entrepreneurship, marketing innovation, and sustainability. The study aims to provide a fresh perspective by utilizing artificial neural networks (ANN) and structural equation modeling (SEM). Design/methodology/approach The research methodology involves collecting data from a survey of 230 employees across various government-affiliated institutions in Korea. Four critical sub-dimensions of social entrepreneurship—Proactiveness, Innovativeness, Risk-taking, and Social orientation—are considered independent variables. Marketing innovation and sustainability are treated as dependent variables. The study compares the flexibility and adaptability of ANN models with SEM. Findings Proactiveness and risk-taking showed no significant influence, while innovativeness and social orientation had strong positive effects, with social orientation as the most decisive antecedent. Marketing innovation enhanced sustainability, and ANN revealed nonlinear threshold effects, where moderate proactiveness and innovativeness optimized outcomes but excessive levels reduced them. Originality This study integrates Triple Bottom Line, Stakeholder, Institutional, and Schumpeter’s theories to explain entrepreneurship–sustainability dynamics, highlights the decisive role of social orientation and the need for balance in entrepreneurial behaviors, and demonstrates the methodological value of ANN in uncovering hidden nonlinearities beyond SEM.

Keywords: Artificial neural networks; Marketing innovation; Social entrepreneurship; Social orientation; Sustainability (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s40497-025-00444-5

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