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Empirical Study on Guanxi and Performance of the Agricultural Supply Chain Based on Knowledge Sharing Intermediary

Empirical Study on Guanxi and Performance of the Agricultural Supply Chain Based on Knowledge Sharing Intermediary

Jingshi He
Copyright: © 2022 |Volume: 18 |Issue: 1 |Pages: 18
ISSN: 1548-0666|EISSN: 1548-0658|EISBN13: 9781799893608|DOI: 10.4018/IJKM.305224
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MLA

He, Jingshi. "Empirical Study on Guanxi and Performance of the Agricultural Supply Chain Based on Knowledge Sharing Intermediary." IJKM vol.18, no.1 2022: pp.1-18. http://doi.org/10.4018/IJKM.305224

APA

He, J. (2022). Empirical Study on Guanxi and Performance of the Agricultural Supply Chain Based on Knowledge Sharing Intermediary. International Journal of Knowledge Management (IJKM), 18(1), 1-18. http://doi.org/10.4018/IJKM.305224

Chicago

He, Jingshi. "Empirical Study on Guanxi and Performance of the Agricultural Supply Chain Based on Knowledge Sharing Intermediary," International Journal of Knowledge Management (IJKM) 18, no.1: 1-18. http://doi.org/10.4018/IJKM.305224

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Abstract

“Guanxi” is a very special and important factor in Chinese traditional agricultural society and economic activities, and it has an important impact on all participants in the agricultural supply chain. Taking four dimensional attributes of guanxi—renqing (reciprocal favour exchange), mianzi (face), ganqing (emotional attachment), and xinren(trust) as the endogenous latent variables—this research established and empirically analyzed the structural equation model (SEM) of guanxi, knowledge sharing, and supply chain performance (SCP). Research found that renqing, mianzi, ganqing, and xinren have positive and significant effects on knowledge sharing, among which ganqing is the most significant factor, and renqing, mianzi, ganqing, and xinren have a positive impact on SCP through the mediating role of knowledge sharing. The influence mechanism of four dimension of guanxi on knowledge sharing and SCP and the influence of measurement variables on latent variable were analyzed. The results provide guidance for business decision making in the agricultural supply chain.