Title :
The theoretical analysis and empirical study on the structure modeling of knowledge work
Author_Institution :
Politics & Public Adm. Sch., East China Univ. of Political Sci. & Law, Shanghai, China
Abstract :
This paper examines the structure characteristic and the measurement of knowledge work. This approach aims at measuring the knowledge works quantitatively and optimizing its productivity. Current knowledge on the issue is summarized based on the existing literature on the characteristic identification and measurement of knowledge work. Identification and definition for the concept of knowledge work are developed. Meanwhile, In order to give a structural measurement for knowledge work, this paper introduces the concept of entropy and builds a tree structure model for the quantitative expression of the uncertainty degrees of knowledge work. This tree structure model is applied empirically in a case of knowledge work measurement. Empirical data was collected by interviewing 3 knowledge workers in a digital technology company. The findings show that mastery of knowledge work´s structural rules is a challenging phenomenon in practice. This study also shows that the tree structure model can be applied as an analytical tool. The findings of the study may help managers to achieve knowledge work´s standardized management and excavate the innovation activities among knowledge work. This can be used as a starting point for developing novel productivity measures for knowledge work.
Keywords :
entropy; innovation management; knowledge management; productivity; standardisation; characteristic identification; digital technology company; entropy concept; innovation activities; knowledge work measurement; knowledge work standardized management; knowledge work structural rules; knowledge work structure modeling; knowledge work uncertainty degrees; knowledge workers; productivity; structural measurement; tree structure model; Companies; Entropy; Manuals; Productivity; Rendering (computer graphics); Technological innovation; Uncertainty; entropy; knowledge work; procedure; standardization; structural model;
Conference_Titel :
Management Science & Engineering (ICMSE), 2014 International Conference on
Conference_Location :
Helsinki
Print_ISBN :
978-1-4799-5375-2
DOI :
10.1109/ICMSE.2014.6930347