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The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Measuring intellectual capital: a new model and empirical study

Chen, Jin, Zhu, Zhaohui, Yuan Xie, Hong·2004·Journal of Intellectual Capital

Abstract

The groundwork of intellectual capital (IC) management, measuring IC, attracts much attention from academics and practitioners. The purpose of this paper is to design a measurement model and a qualitative index system of IC, so as to provide a good tool for enterprises to manage their IC. Based on a review of several IC measurement models proposed by western researchers, IC is classified into human capital, structural capital, innovation capital and customer capital, and thereupon a qualitative index system for the above four IC elements is designed through an analysis of their contents. Through an empirical study, it is found that there is a significant relationship between the scores of the four IC elements of a company and its business performance, which proves the validity and rationality of the IC measurement model and the qualitative index system. In the meantime, the empirical study further proves that there is a remarkable relationship between the four IC elements. Therefore enterprises must manage and improve their IC from an integrative perspective.

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Metadata

Authors
Chen, J., Zhu, Z., & Yuan Xie, H.
Venue
Journal of Intellectual Capital
Publisher
Emerald
Published
2004-03-01
Volume
5
Issue
1
Pages
195-212
ISSN
1469-1930 (ISSN-L)
OpenAlex
W1964546750
Cited by
755
References
15
FWCI
34.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Measuring intellectual capital: a new model and empirical study. https://app.cochat.ai/papers/10.1108/14691930410513003
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Chen, J., Zhu, Z., & Yuan Xie, H. (2004). Measuring intellectual capital: a new model and empirical study. Journal of Intellectual Capital. https://doi.org/10.1108/14691930410513003

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.