Developing a Framework for Evaluating and Predicting Management Innovation in Public Research Institutions
Sustainability (Switzerland), ISSN: 2071-1050, Vol: 15, Issue: 9
2023
- 15Captures
- 2Mentions
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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.
Metrics Details
- Captures15
- Readers15
- 15
- Mentions2
- Blog Mentions1
- Blog1
- News Mentions1
- News1
Most Recent News
Andong National University Researcher Adds New Findings in the Area of Information and Data Mining (Developing a Framework for Evaluating and Predicting Management Innovation in Public Research Institutions)
2023 MAY 16 (NewsRx) -- By a News Reporter-Staff News Editor at Information Technology Daily -- Investigators discuss new findings in information and data mining.
Article Description
As the external environment changes rapidly, organizations need management innovation to adapt to and exploit change as an opportunity. To innovate, it is necessary to evaluate management innovation, because if an organization can measure the degree of management innovation, it can also achieve it. Moreover, if management innovation is predictable, profits can be maximized, and costs can be minimized by allocating efficient resources and establishing appropriate strategies. Therefore, this study attempts to predict the management innovation in public research institutions. Basic data mining and ensemble data mining techniques were used for the prediction. This analysis targeted public research institutes in South Korea. The results showed that the predictive power of public research institutions with high innovation was high. This study suggests that management innovation can be predicted in highly innovative public research institutions. Furthermore, this study’s framework can be applied to other industries.
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