Knowledge Management as a Discipline in Hong Kong Higher Education

In this Article

1. Abstract
2. Why Knowledge Management Required Academic Structure
3. Methodology: Document-Based Curriculum Synthesis
4. Institutional and Programme Context
5. Disciplinary Architecture: From Tacit Knowledge to Intellectual Capital
6. Blended Learning Design and Threaded Online Discussions
7. Key Findings
8. Limitations and Scope Conditions
9. Implications for Postgraduate Design
10. References

Abstract

A postgraduate module record can reveal how a field becomes academically institutionalized.

This review examines Knowledge Management in Hong Kong higher education through a document-based curriculum synthesis. The focal case is module code 12-7-926-1, associated with MSc/PgD/PgC Business Intelligence and related IT and Management postgraduate provision. Rather than treating Knowledge Management as a loose management slogan, I read the module and subject sequence as evidence of how a university-level curriculum turns tacit knowledge, organizational learning, intellectual capital, business intelligence, and e-learning into assessable postgraduate study.

The synthesis is intentionally curriculum-centred. It follows the supplied module facts, subject titles, approval dates, planned offering dates, and staff-context signals, then asks what kind of academic structure they imply for professional learners in Hong Kong.

Why Knowledge Management Required Academic Structure

Knowledge Management, or KM, sits in an awkward position. In companies, it often appears as a practice: capture lessons learned, improve search, map expertise, build communities, or install a knowledge repository. In postgraduate education, that same activity needs a more disciplined form. Learners need definitions, models, assessment criteria, implementation logic, and technology awareness.

That tension matters in Hong Kong higher education because many postgraduate learners are already working professionals. They do not need a purely abstract account of knowledge. They need to move between boardroom vocabulary, system design, project governance, and organizational behaviour without flattening one into the other.

The organizing asset in this curriculum is intellectual capital, not conventional information management. Information management asks how records, data, and content are stored, retrieved, and governed. Intellectual capital asks how knowledge assets contribute to organizational interpretation and performance. That shift changes the learning problem: the learner must evaluate knowledge as a strategic asset, not only as content in a database.

Note: A KM curriculum becomes weak when it treats knowledge capture as the whole discipline. The stronger version links knowledge creation, transfer, measurement, and technology-mediated practice.

Methodology: Document-Based Curriculum Synthesis

I used a qualitative document-based curriculum synthesis because the available evidence is strongest at the level of programme design, not student outcome measurement. A quantitative survey would be the wrong tool here; the supplied facts do not include enrolment, grades, graduate destinations, teaching evaluations, or rankings.

The primary curriculum evidence spans module code 12-7-926-1 and the following subjects: ISE542 Managing Knowledge, ISE543 KM Systems, ISE5600 Organisational Learning, ISE5601 Managing and Measuring Intellectual Capital, ISE5606 Business Intelligence and Data Mining, and ISE5607 E-Learning Technologies and Practices. I also use ISE553 where the supplied facts connect Six Sigma methods, including DMAIC, DFSS, FMECA, and QFD, with teaching led by WS Yeung and Albert HC Tsang.

The temporal anchors are important. The original approval is dated November 2002. Planned offerings run from September 2004 to January 2006. A scheduled review appears in 2008. I treat the 2008 date strictly as a quality-assurance checkpoint, not as proof of programme success.

Within the limits of the curriculum record, this method allows a focused reconstruction of design intent. It cannot establish labour-market outcomes or institutional effectiveness.

Institutional and Programme Context

The subject sits within postgraduate provision connected to MSc/PgD/PgC Business Intelligence and MSc/PgD/PgC IT and Management. That pairing is significant because it places KM near analytics, information systems, and management rather than inside a purely library, computing, or human resources frame.

The supplied facts locate the offering department context at the Department of Industrial and Systems Engineering at The Hong Kong Polytechnic University. This is a useful institutional signal. Industrial and systems engineering gives KM a process, systems, and organizational improvement vocabulary; it does not leave the field as a general management elective.

Staff-context facts also identify Eric Tsui as appointed Professor of KM at PolyU in August 2002, during the programme formation period. That appointment is relevant because it shows a named academic focus around KM close to the original approval date. The supplied facts also mention CMS as the module leader school; I use that only as an administrative context marker, not as a basis for reconstructing an organizational chart.

For comparison, labels such as MSc in E-Commerce or MSc/PgD in Software Technology should not be casually merged with this case unless curriculum documents connect them directly. Similar professional audiences do not automatically mean the same disciplinary architecture.

Disciplinary Architecture: From Tacit Knowledge to Intellectual Capital

The architecture of the curriculum can be read as a sequence. ISE542 establishes the management of knowledge. ISE543 moves toward KM systems. ISE5600 extends the discussion into organizational learning. ISE5601 then makes intellectual capital measurement a central subject, while ISE5606 links business intelligence and data mining to knowledge discovery.

That sequence matters because tacit knowledge, information dynamics, and knowledge transfer are connected but distinct. Tacit knowledge concerns what people know through experience and may struggle to articulate. Information dynamics concern how structured and semi-structured content moves through systems and decisions. Knowledge transfer concerns the social, technical, and organizational conditions that allow knowledge to move without losing meaning.

Frameworks Used as Curriculum Scaffolding

The supplied curriculum frameworks include CKFs, the SAP-LAP model, the CARMA cycle, the Skandia Navigator, and the Intangible Asset Monitor. These are not decorative references. They give learners operational language for diagnosing knowledge leadership, interpreting organizational learning, and discussing intellectual capital without relying only on broad concepts.

• CKFs help structure critical knowledge-related factors in an organizational setting.
• SAP-LAP supports a situation, actor, process, learning, action, and performance logic for analysis.
• CARMA gives a cycle-based way to examine knowledge actions and review.
• Skandia Navigator and Intangible Asset Monitor connect intangible assets to corporate performance interpretation.

The edge case is adoption. Assuming curriculum frameworks like the Skandia Navigator translate directly into organizational adoption without contextual adaptation would overstate what a module can do. A postgraduate curriculum can teach interpretive discipline; implementation still depends on the organization.

Blended Learning Design and Threaded Online Discussions

Threaded online discussions are the primary student-led interaction method in the supplied pedagogical design. That choice fits KM unusually well.

A threaded discussion externalizes reasoning. A learner has to state assumptions, cite a case feature, respond to a peer, and refine a position. In a face-to-face seminar, some of that thinking disappears once the conversation ends. In an asynchronous thread, the knowledge exchange leaves a visible record that can be reviewed, challenged, and extended.

This is especially useful for working professionals. They can engage with cases, frameworks, and implementation problems around employment schedules, while still participating in peer knowledge transfer. The connection with ISE5607 E-Learning Technologies and Practices is therefore not incidental; the learning design itself becomes a small-scale KM environment.

Quick Tip: When assessing threaded discussion in KM, look beyond participation volume. The stronger evidence is whether learners convert experience into explicit reasoning that others can reuse.

The unresolved question is assessment granularity. A thread can show knowledge articulation, but the curriculum record alone does not tell us how instructors judged quality, originality, or practical transfer.

Key Findings

Finding 1: KM is framed as interdisciplinary

The curriculum presents KM as an interdisciplinary discipline combining organizational learning, technology management, intellectual capital, and business intelligence. It does not isolate KM as a software deployment problem. It also does not reduce the field to leadership culture.

Patrick Lambe’s January 2001 move to Knowledge Platform appears in the supplied staff-context facts as part of the wider professional KM environment of the period. I read that as context for the field’s development, not as evidence about this programme’s outcomes.

Finding 2: Implementation frameworks carry the curriculum

The curriculum emphasizes implementation frameworks, not theory alone. CKFs, SAP-LAP, and CARMA provide operational language for knowledge leadership and organizational learning. This is where postgraduate teaching becomes practical: the learner is asked to diagnose, structure, and explain an intervention rather than simply define KM.

ISE553 strengthens the implementation orientation through Six Sigma methods such as DMAIC, DFSS, FMECA, and QFD. Those tools do not belong only to quality management. In this curriculum context, they sit near KM as disciplined ways to analyse process knowledge, failure modes, design requirements, and improvement cycles.

Finding 3: Intellectual capital measurement is central

Intellectual capital measurement is not treated as an optional add-on. Skandia Navigator and Intangible Asset Monitor connect knowledge assets to corporate performance interpretation. This gives learners a bridge between intangible knowledge claims and managerial evaluation.

Benchmarks demonstrate their value only when the learner understands the assumptions behind the benchmark. In KM education, the measurement tool is less important than the judgement used to apply it.

Limitations and Scope Conditions

This article is a research-summary reconstruction from supplied curriculum and programme facts. It is not a full institutional history of The Hong Kong Polytechnic University, the Department of Industrial and Systems Engineering, CMS, HKCyberU, Hong Kong I-Education Limited, or any related postgraduate provision.

I do not infer enrolment numbers, graduate outcomes, teaching evaluations, employer satisfaction, or programme rankings. The source material does not support those claims. I also avoid treating scheduled academic review dates as proof of programme success rather than administrative compliance checkpoints.

References to KM implementation research over the last decade are treated qualitatively because no named dataset, study count, or verifiable statistical source is provided. The authority signals and framework inclusions documented here reflect curriculum design intent and do not inherently guarantee specific graduate employment outcomes or institutional effectiveness.

Implications for Postgraduate Design

The curriculum suggests a three-layer design recommendation for academic partners developing postgraduate KM modules.

1. Conceptual foundations: define tacit knowledge, knowledge creation, organizational learning, and intellectual capital before introducing tools.
2. Implementation frameworks: map each subject to a practical diagnostic model, such as CKFs, SAP-LAP, CARMA, or Six Sigma-linked analysis.
3. Technology-mediated practice: use threaded discussion, KM systems, business intelligence, data mining, and e-learning design to make knowledge activity visible.

The practical next step is mapping each KM subject to a specific knowledge function, assessment artifact, and organizational use case. For example, ISE5601 can produce an intellectual capital interpretation artifact, while ISE5607 can produce an online interaction design that demonstrates knowledge transfer.

Summary: The strongest curriculum pattern is not the presence of KM terminology. It is the alignment between theory, implementation frameworks, measurement models, and asynchronous professional learning.