Hierarchical Regression Analysis.

Gaining a deeper understanding of the mechanism through which social networks influence sustainable performance and exploring the role of resource bricolage in enhancing competitiveness are valuable. These insights can help small and medium-sized enterprises (SMEs) better adapt to market changes in the digital age and ultimately, this can enable SMEs to achieve sustainable development. In the context of accelerated technological change and resource scarcity, the question of how SMEs can leverage network resources to achieve sustainable growth has become a pressing issue. This study, grounded in social network theory and resource-based theory, develops a theoretical model exploring the relationships between social network characteristics, resource bricolage, and SME sustainable performance. Using survey data from 230 SMEs, the study empirically demonstrates that both social network scale and social network strength have significant positive impacts on sustainable performance. Additionally, resource bricolage mediates the effects of social network scale and strength on SME performance. Moreover, opportunity identification and opportunity exploitation-key dimensions of dynamic capabilities—moderate the relationship between resource bricolage and sustainable performance. This study highlights the mechanisms through which SMEs can leverage social networks to enhance their sustainable performance, offering theoretical guidance for effectively identifying and utilizing network resources in uncertain and dynamic environments.

深入解析社会网络影响可持续绩效的作用机制，并探究资源拼凑（resource bricolage）在提升竞争力中的角色，具有重要的学术与实践价值。此类研究认知有助于中小企业（SMEs）更好地适配数字时代的市场变革，最终助力其实现可持续发展。在技术变革加速、资源稀缺的时代背景下，中小企业如何借助网络资源实现可持续增长，已成为亟待解决的现实议题。本研究基于社会网络理论（social network theory）与资源基础观（resource-based theory），构建了探讨社会网络特征、资源拼凑与中小企业可持续绩效间关系的理论模型。本研究依托230家中小企业的调研数据开展实证检验，结果显示：社会网络规模与社会网络强度均对可持续绩效存在显著正向影响。此外，资源拼凑在社会网络规模、强度对中小企业绩效的影响路径中发挥中介效应。进一步而言，作为动态能力（dynamic capabilities）的核心维度，机会识别与机会开发在资源拼凑与可持续绩效的关系中起到显著调节作用。本研究阐明了中小企业借助社会网络提升可持续绩效的内在作用机制，为不确定性与动态性环境下有效识别与利用网络资源提供了理论指引。