Development of a knowledge-based self-assessment system for measuring organisational performance

Kwai-Sang Chin, Kit-Fai Pun, Henry Lau

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    43 Citations (Scopus)

    Abstract

    Effective performance measurement is an important task in the discipline of engineering management. With the support of City University of Hong Kong, a research project was initiated to develop a knowledge-based expert self-assessment (KES) training toolkit on measuring and assessing organisational performance based on the evaluation criteria of a renowned Business Excellence Model - the Malcolm Baldrige National Quality Award (MBNQA). This paper explains the development of and elaborates the system framework, requirements, design and validation of the toolkit. The project results shows that the toolkit could facilitate the teaching of students of engineering management courses by providing a stimulating learning environment and practical experiences in measuring and assessing enterprise performance. Incorporating the KES model and toolkit into the engineering management curriculum can provide students and industrial users with hands-on experience and insights of organisational PM. © 2003 Elsevier Science Ltd. All rights reserved.
    Original languageEnglish
    Pages (from-to)443-455
    JournalExpert Systems with Applications
    Volume24
    Issue number4
    DOIs
    Publication statusPublished - May 2003

    Research Keywords

    • Knowledge-based system
    • Performance measurement
    • Self-assessment

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