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Journal Article

Modeling Organizational Knowledge Dynamics: Using Analytic Hierarchy Process (AHP)  pp236-247

Constantin Bratianu, Adriana Agapie, Ivona Orzea

© Sep 2011 Volume 9 Issue 3, ECIC 2011, Editor: Geoff Turner and Clemente Minonne, pp181 - 295

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: Modelling Organizational Knowledge Dynamics (OKD) is important in developing knowledge strategies within the framework of strategic management. We present in this paper a new perspective on modelling OKD based on the dynamic equilibrium equation of the organizational knowledge, and on using the Analytic Hierarchy Process (AHP). The dynamic equilibrium equation is considered for a time interval ∆T, and contains the following terms: the level of total organizational knowledge variation ∆K, the knowledge creation variation ∆C, the knowledge acquisition variation ∆A, and the knowledge loss variation ∆L. Since each of these terms has a different relative importance in the organizational knowledge balance, it is necessary to find a way of evaluating their weighting factors. For this purpose we use the AHP mathematical model developed by Saaty for the managerial decision making. AHP requires a structuring of the field of knowledge, and we considered a structure composed of three levels: (1) the goal level – increasing the level of organizational knowledge; (2) the strategies level – the strategy for increasing knowledge creation (S1), the strategy for increasing acquisition of new knowledge (S2), and the strategy for reducing knowledge loss (S3); (3) the activities level – hiring new valuable human resources (A1), developing training programs (A2), creating a performing motivation of employees (A3), and purchasing books, journals, software programs, and other information materials (A4). This structured model of AHP has been applied as an empirical research within a large company. We sent questionnaire to a number of 500 employees, and received valid answers from 173 respondents. The AHP method is based on paired comparisons of strategies with respect to the goal of increasing the level organizational knowledge, and then on paired comparisons of activities with respect to each strategy we defined. These paired comparisons yield matrices that lead to systems of eigenvalue equations whose solutions compose the vector of priorities for strategies, and for activities with respect to each strategy. Values of the vector of priorities for strategies are the weighting factors for the equilibrium equation components.


Keywords: analytic hierarchy process, knowledge acquisition, knowledge creation, knowledge dynamics, knowledge loss


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