The evolution of knowledge navigator model: The construction and application of KNM 2.0

Ping Jung Hsieh, Chinho Lin, Shofang Chang

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

The knowledge management (KM) maturity model provides a framework against which both old and new KM initiatives can be assessed to determine whether they are capable of generating new knowledge. Knowledge Navigator Model (KNM) proposed in 2009 (Hsieh et al., 2009) has been promoted in Taiwan to assist organizations to evaluate their KM status, and also aided to be a diffusion platform for government, academic and practice to exchange their KM experience. However, for the past 10 years, the industrial environment has been constantly changing that has brought the developing of KM practice. This study described the evolution of KNM to become KNM 2.0 in terms of construction and application. Qualitative and quantitative research methods were conducted to construct the proposed three modules of KNM 2.0. A 139 cases survey was employed and the results reveal the applicability of KNM 2.0. Our research contributes to the body of concepts on KM maturity models that could evaluate the readiness of service-oriented knowledge economy, big data and smart factory, and strategic KM performance. The proposed KNM 2.0, with these features which are novel and rapidly expanding fields, has been developed as an online Knowledge Management Evaluation (KM evaluation) website available for the practice to use to better understand their overall value brought by contemporary KM. Moving forward, by using KNM 2.0 to continually collect the data from the industries in Taiwan, it is expected to obtain more information about the practical KM that keeps developing with the trends, and also keep playing the role to distribute the contemporary concepts of KM. The KM experience could be referenced and the methodology could be applied to other countries.

Original languageEnglish
Article number113209
JournalExpert Systems With Applications
Volume148
DOIs
Publication statusPublished - 2020 Jun 15

All Science Journal Classification (ASJC) codes

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence

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