Mapping Knowledge Networks in Organizations: Creating a Knowledge Mapping Instrument
2000
- 431Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage431
- Downloads274
- Abstract Views157
Article Description
The ability to leverage organizational expertise is a critical success factor in most forms of knowledge work. However, expertise is an exceedingly difficult resource to manage. The design of computer-based support for knowledge management requires extensive, costly and inefficient cycles of knowledge elicitation to generate a reasonable knowledge map. We propose an alternative approximation technique which reduces these costs, while providing functionally equivalent data. In this methodological case study we chronicle the development of the key instrument in this approximation technique.
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