社会企业家精神和可持续技术:对社区的影响、社会创新和包容性发展

Raghu Raman , T.A. Alka , M. Suresh , Prema Nedungadi
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引用次数: 0

摘要

社会企业家精神正在成为可持续发展的变革力量,特别是在不平等、非正式和制度差距突出的背景下。本研究采用综合和批判性的方法来研究SE如何与可持续发展目标(sdg)保持一致,并为包容性、弹性和创新驱动的变革做出贡献。通过综合六个基础理论:行为决策理论、计划行为理论、社会认知理论、制度理论、社会资本理论和扎根理论,它解决了关键的研究缺口——理论应用的碎片化、部门分析的有限性和方法论的弱概括性。采用PRISMA方案进行了系统的文献综述,以确保2015年至2024年研究选择的严谨性和透明度。该审查确定了现有文献中的主题差距,包括未充分探索的领域,如特定部门融资、数字创新、新兴部门创业、可持续技术采用,以及可持续发展目标相关成果中SE的上下文嵌入。利用理论-情境-特征-方法(TCCM)框架和基于机器学习的BERTopic建模,本研究对SE研究进行了分析,以提供概念深度和经验映射。它的独创性在于将理论与先进的文本分析相结合,以发现可操作的、理论驱动的SE-SDG一致性见解。调查结果显示,中小企业通过包容性模型和人工智能、区块链等数字工具,对可持续发展目标4、8和9做出了贡献。SE还在机构(可持续发展目标16)和伙伴关系(可持续发展目标17)的支持下推进可持续发展目标10、11和12。该研究要求跨认知、关系和制度领域的多层次理论集成,以及混合模型设计、利益相关者协作和数字能力建设的管理含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social entrepreneurship and sustainable technologies: Impact on communities, social innovation, and inclusive development
Social entrepreneurship (SE) is emerging as a transformative force for sustainable development, particularly in contexts marked by inequality, informality, and institutional gaps. This study adopts an integrative and critical approach to examine how SE aligns with Sustainable Development Goals (SDGs) and contributes to inclusive, resilient, and innovation-driven change. It addresses key research gaps—fragmented theoretical applications, limited sectoral analysis, and weak methodological generalizability—by synthesizing six foundational theories: behavioral decision theory, theory of planned behavior, social cognitive theory, institutional theory, social capital theory, and grounded theory. A systematic literature review was conducted using the PRISMA protocol to ensure rigor and transparency in selecting studies from 2015 to 2024. The review identifies thematic gaps in existing literature, including underexplored areas such as sector-specific financing, digital innovation, entrepreneurship in emerging sectors, sustainable technology adoption, and the contextual embedding of SE within SDG-linked outcomes. Using the theory-context-characteristics-methods (TCCM) framework and machine learning-based BERTopic modeling, this study analyzes SE research to offer both conceptual depth and empirical mapping. Its originality lies in the interdisciplinary integration of theory with advanced text analytics to uncover actionable, theory-driven insights into SE–SDG alignment. Findings reveal SEs’ contributions to SDGs 4, 8, and 9 through inclusive models and digital tools such as AI and blockchain. SE also advances SDGs 10, 11, and 12 while being enabled by institutions (SDG 16) and partnerships (SDG 17). The study calls for multilevel theoretical integration across cognitive, relational, and institutional domains, with managerial implications for hybrid model design, stakeholder collaboration, and digital capability building.
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