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Article summary:

1. The article proposes a framework for assessing the success of knowledge management systems (KMS).

2. The framework evaluates KMS success models based on their fit with actual KMS success factors, theoretical foundation, and applicability to different types of KMS.

3. The article analyzes four KMS success models using the framework and concludes that it is a useful tool for assessing KMS success models.

Article analysis:

The article "Assessing Knowledge Management Success" proposes a framework for evaluating knowledge management system (KMS) success models. The authors aim to assess the usefulness of existing KMS success models by comparing them to KMS success factors, examining their theoretical foundation, and determining if they can be applied to different types of KMSs.

The article begins by providing an overview of KMSs and their goals, including knowledge creation, storage/retrieval, transfer, application, and support for organizational memory. The authors then classify KMSs into two approaches: process/task approach and infrastructure/generic approach. They argue that both approaches are necessary for a complete KMS.

Next, the authors discuss the importance of measuring KMS success or effectiveness. They list three reasons for doing so: company valuation, management focus, and justification of investments in KM activities. They highlight the need for effective evaluation models to guide the design and implementation of KMSs.

The proposed assessment framework consists of three main criteria: how well the model fits KMS success factors, the degree of its theoretical foundation, and its applicability to both types of KMSs. The authors argue that a model with a strong fit to success factors, solid theoretical foundation, and broad applicability is more likely to be useful.

To establish the set of KMS success factors, the authors review relevant literature on KM/KMS success and organizational memory success. They identify several strategy issues affecting KMS design as well as technical and management issues. These factors are combined into composite success factors based on their frequency in the literature.

The article then evaluates four existing KM/KMS success models using the proposed framework. It analyzes how well each model aligns with the identified success factors, examines their theoretical foundations, and determines if they can be applied to both types of KMSs.

Overall, this article provides a comprehensive framework for assessing KM/KMS success models. It highlights the importance of considering success factors, theoretical foundations, and applicability to different types of KMSs. However, it does not provide a critical analysis of the biases or limitations of the existing models it evaluates. It also does not explore potential risks or counterarguments related to KMS success. Additionally, the article lacks empirical evidence or case studies to support its claims.