The paper proposes first, to understand how and how much knowledge contributes toward explicit business performance improvement and, second, through the understanding of knowledge contribution, to provide a guiding principle for the effective knowledge management activities.
The authors use a Cobb‐Douglas type production function to model the relationship between knowledge and performance. Then, regression analysis is used to estimate the knowledge elasticity of performance. Finally, a laboratory experiment is used to demonstrate the whole process.
A performance‐oriented knowledge management approach was developed. Through the analysis of knowledge‐intensive production function, it is shown that the knowledge elasticity of performance for each knowledge entity (product knowledge and process knowledge) can be estimated and can be used with great managerial implications.
Extensive empirical analyses in the real world business environment would be helpful to verify and generalize this approach.
The paper demonstrates the specific process of how to measure the contribution of knowledge to performance, and provide a guiding principle for the effective knowledge management activities.
As far as the authors understand, this is the first systematic and complete approach to analyze and estimate the contribution of knowledge to performance. Using the production function approach, it was possible to estimate the knowledge elasticity of performance, which provides valuable insight on the resource allocation for knowledge management activities.
Chang, S. and Ahn, J. (2005), "Product and process knowledge in the performance‐oriented knowledge management approach", Journal of Knowledge Management, Vol. 9 No. 4, pp. 114-132. https://doi.org/10.1108/13673270510610378
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