摘要
This article investigates the relationship between intellectual capital, supply chain learning, and supply chain adaptability. Specifically, relying on organizational learning theory, a research model is proposed linking intellectual capital (consisting of the trichotomy of human, organizational, and social capital), supply chain learning (consisting of supplier learning and customer learning) and supply chain adaptability. We scrutinize these relationships in two culturally-diverse contexts, China and USA, and develop hypotheses concerning the differences in the relative strengths of these relationships. Data from 300 Chinese and 229 USA manufacturers in high-tech industries are used to test these hypotheses. While the relationships are generally supported, especially insightful are the results where they differ between the two countries. While human capital is more important in influencing organizational capital in USA, social capital is more important in China. Social capital also plays a more significant role in influencing customer learning in China, while no statistical differences are detected in social capital's influence on supplier learning across the two countries. The divergence observed can be explained by the cultural differences between the two countries. Implications are provided for managers in both countries to improve supply chain adaptability.
源语言 | 英语 |
---|---|
页(从-至) | 2738-2753 |
期刊 | IEEE Transactions on Engineering Management |
卷 | 69 |
期 | 6 |
DOI | |
出版状态 | 已出版 - 22 11月 2022 |
Corresponding author email
zhangshanshanscut@126.comProject sponsor
National Natural Science Foundation of China (NSFC)Project No.
7142010702471473087
关键词
- Cross-country comparison
- intellectual capital
- structural equation modeling
- supply chain adaptability
- supply chain learning
成果物的来源
- ABDC-A
- SCIE
- SSCI
指纹
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Wang, Z., Zhao, X., Schoenherr, T., & Zhang, S. (2022). Intellectual Capital, Supply Chain Learning, and Adaptability: A Comparative Investigation in China and the United States. IEEE Transactions on Engineering Management, 69(6), 2738-2753. https://doi.org/10.1109/TEM.2019.2956471