Knowledge-based strategy selection: a hybrid model and its implementation

Purpose – 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. Design/methodology/approach – 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. Findings – 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. Originality/value – 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.