Developing a Framework for Evaluating and Predicting Management Innovation in Public Research Institutions

Kyungbo Park, Jeonghwa Cha and Jongyi Hong ()
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Kyungbo Park: Department of Business Administration, Andong National University, Andong 36729, Republic of Korea
Jeonghwa Cha: Department of Business Administration, Pusan National University, Pusan 46241, Republic of Korea
Jongyi Hong: Institute for Research & Industry Cooperation, Pusan National University, Pusan 46241, Republic of Korea

Sustainability, 2023, vol. 15, issue 9, 1-18

Abstract: 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.

Keywords: management innovation; data mining; ensemble data mining (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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