Abstract
As the amount of data increases enormously, business analytics such as descriptive, predictive, and prescriptive analytics is one of the most important topics for better decision making especially for CTO or CIO in corporate. Prescriptive analytics shows fundamental difference with descriptive analytics and predictive analytics in that it requires high-value alternative actions or decisions to achieve a given goal. However, only a few studies have been introduced since it is a emerging technology. Thus, this study aims to trigger research on this technical area by implementing a prescriptive analytics system and by verifying it in the point of usability and usefulness. The system, InSciTe Advisory, is focused on improving research performance and is based on 5W1H questions to build actionable strategies to achieve a given goal. The comparison evaluation of the system with Elsevier SciVal showed a rate of 118.8% in usefulness and reliability.
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© 2014 Springer-Verlag Berlin Heidelberg
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Song, Sk., Jeong, DH., Kim, J., Hwang, M., Gim, J., Jung, H. (2014). Research Advising System Based on Prescriptive Analytics. In: Park, J., Pan, Y., Kim, CS., Yang, Y. (eds) Future Information Technology. Lecture Notes in Electrical Engineering, vol 309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55038-6_89
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DOI: https://doi.org/10.1007/978-3-642-55038-6_89
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-55037-9
Online ISBN: 978-3-642-55038-6
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