How market-specific social capital leverages knowledge creation to improve dynamic capabilities: the moderating role of market turbulence

Yujuan Xi & Gongyi Zhang

Journal of Knowledge Management2026https://doi.org/10.1108/jkm-01-2025-0056article
AJG 2ABDC A
Weight
0.50

Abstract

Purpose Grounding in social network theory, this study aims to delineate the dimensions of market-specific social capital and develop a theoretical framework to investigate how these distinct dimensions influence dynamic capabilities. In addition, the mediating role of knowledge creation and the moderating role of market turbulence is examined in this process. Design/methodology/approach This study uses structural equation modelling and bootstrap methods to test the proposed model and hypotheses. Data were collected from 360 enterprises in China. Findings Results reveal that diverse dimensions of market-specific social capital influence dynamic capabilities through distinct pathways: consumer social capital and supplier social capital indirectly promote dynamic capabilities via knowledge creation, whereas competitor social capital directly accelerates dynamic capabilities. Moreover, the positive effect of knowledge creation on dynamic capabilities is notably more pronounced in highly turbulent markets. Originality/value This study provides unique insights into the pathway of market-specific social capital on dynamic capabilities from an integrated viewpoint of marketing and knowledge, thereby advancing ongoing research.

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https://doi.org/https://doi.org/10.1108/jkm-01-2025-0056

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@article{yujuan2026,
  title        = {{How market-specific social capital leverages knowledge creation to improve dynamic capabilities: the moderating role of market turbulence}},
  author       = {Yujuan Xi & Gongyi Zhang},
  journal      = {Journal of Knowledge Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/jkm-01-2025-0056},
}

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0.50

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F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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