Case-based reasoning for predicting multiperiod financial performances of technology-based SMEs

Tae Hee Moon; So Young Sohn

doi:10.1080/08839510701734285

Case-based reasoning for predicting multiperiod financial performances of technology-based SMEs

Tae Hee Moon, So Young Sohn

Department of Industrial Engineering

Research output: Contribution to journal › Review article › peer-review

10 Citations (Scopus)

Abstract

Recently, various types of technology funds became available to support the programs for technology development and commercialization of SMEs (Small and Medium Enterprise) in Korea. However, the potential financial performances have not been sufficiently considered at the selection stage of fund recipient SMEs whereas the default risk has been a major concern. This article proposes a Case Based Reasoning (CBR) system with Genetic Algorithm (GA) for predicting the Exponentially Weighted Moving Average (EWMA) of multiperiod financial performances of technology-oriented SMEs. It is expected that the proposed model can be applied to a wide range of technology investment-related decision-making procedures.

Original language	English
Pages (from-to)	602-615
Number of pages	14
Journal	Applied Artificial Intelligence
Volume	22
Issue number	6
DOIs	https://doi.org/10.1080/08839510701734285
Publication status	Published - 2008 Jul

Bibliographical note

Funding Information:
Address correspondence to S. Y. Sohn, Department of Information and Industrial Engineering, Yonsei University, 134 Shinchon-dong, Seoul 120-749, South Korea. E-mail: sohns@yonsei.ac.kr. This work was supported by the Korea Research Foundation Grant (no. KRF-2007-357-D00281) funded by the Korean Government (MOEHRD).

All Science Journal Classification (ASJC) codes

Artificial Intelligence

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1080/08839510701734285

Cite this

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abstract = "Recently, various types of technology funds became available to support the programs for technology development and commercialization of SMEs (Small and Medium Enterprise) in Korea. However, the potential financial performances have not been sufficiently considered at the selection stage of fund recipient SMEs whereas the default risk has been a major concern. This article proposes a Case Based Reasoning (CBR) system with Genetic Algorithm (GA) for predicting the Exponentially Weighted Moving Average (EWMA) of multiperiod financial performances of technology-oriented SMEs. It is expected that the proposed model can be applied to a wide range of technology investment-related decision-making procedures.",

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Case-based reasoning for predicting multiperiod financial performances of technology-based SMEs

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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