Revealing performance heterogeneity through knowledge management maturity evaluation: A capability-based approach

Le Chen, Sik Wah Fong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

58 Citations (Scopus)

Abstract

The dynamic capabilities view (DCV) focuses on renewal of firms' strategic knowledge resources so as to sustain competitive advantage within turbulent markets. Within the context of the DCV, the focus of knowledge management (KM) is to develop the KMC through deploying knowledge governance mechanisms that are conducive to facilitating knowledge processes so as to produce superior business performance over time. The essence of KM performance evaluation is to assess how well the KMC is configured with knowledge governance mechanisms and processes that enable a firm to achieve superior performance through matching its knowledge base with market needs. However, little research has been undertaken to evaluate KM performance from the DCV perspective. This study employed a survey study design and adopted hypothesis-testing approaches to develop a capability-based KM evaluation framework (CKMEF) that upholds the basic assertions of the DCV. Under the governance of the framework, a KM index (KMI) and a KM maturity model (KMMM) were derived not only to indicate the extent to which a firm's KM implementations fulfill its strategic objectives, and to identify the evolutionary phase of its KMC, but also to bench-mark the KMC in the research population. The research design ensured that the evaluation framework and instruments have statistical significance and good generalizabilty to be applied in the research population, namely construction firms operating in the dynamic Hong Kong construction market. The study demonstrated the feasibility of quantitatively evaluating the development of the KMC and revealing the performance heterogeneity associated with the development.
Original languageEnglish
Pages (from-to)13523-13539
Number of pages17
JournalExpert Systems with Applications
Volume39
Issue number18
DOIs
Publication statusPublished - 15 Dec 2012

Keywords

  • Bench-marking
  • Dynamic capability
  • Knowledge management
  • Performance evaluation
  • Performance heterogeneity
  • Self-assessment

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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