The purpose of this paper is to develop a novel hybrid multi-criteria decision-making (MCDM) model to help organizations select their knowledge-based strategy effectively. Knowledge management (KM) initiatives are often started with the selection of a strategy, which is a critical decision for a successful KM implementation.
KM initiatives are often started with the selection of a strategy, which is a critical decision for a successful KM implementation. Thus, the aim of this paper is to develop a novel hybrid MCDM model to help organizations select their knowledge-based strategy effectively.
Results illustrate that the proposed model is efficient to consider the complex interactions among criteria and provides a consistent decision with less pair-wise comparisons. Furthermore, a case study indicates that a “codification versus tacitness” strategy is preferred over other strategies considering nine main domain criteria.
The contribution of this paper is threefold: it addresses the gaps in KM literature on the effective and efficient assessment of KM strategy selection; it provides a comprehensive and systematic framework that combines analytic network process (ANP) and consistent fuzzy preference relations (CFPR) to assess KM implementation strategy; and it illustrates a real-world study to exhibit the applicability of the proposed approach and the efficacy of the framework.
Hesamamiri, R., Mahdavi Mazdeh, M. and Bourouni, A. (2016), "Knowledge-based strategy selection: a hybrid model and its implementation", VINE Journal of Information and Knowledge Management Systems, Vol. 46 No. 1, pp. 21-44. https://doi.org/10.1108/VJIKMS-03-2015-0020
Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited