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공공부문 데이터의 경제적 가치평가 연구: 소상공인 신용보증 데이터 사례open accessEconomic Valuation of Public Sector Data: A Case Study on Small Business Credit Guarantee Data

Other Titles
Economic Valuation of Public Sector Data: A Case Study on Small Business Credit Guarantee Data
Authors
김동성김종우이홍주강만수
Issue Date
Mar-2017
Publisher
한국지식경영학회
Keywords
Data Valuation; Public Sector Data; Business Credit Guarantee
Citation
지식경영연구, v.18, no.1, pp.67 - 81
Indexed
KCI
Journal Title
지식경영연구
Volume
18
Number
1
Start Page
67
End Page
81
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/20505
DOI
10.15813/kmr.2017.18.1.004
ISSN
1229-9553
Abstract
As the important breakthrough continues in the field of machine learning and artificial intelligence recently, there has been a growing interest in the analysis and the utilization of the big data which constitutes a foundation for the field. In this background, while the economic value of the data held by the corporates and public institutions is well recognized, the research on the evaluation of its economic value is still insufficient. Therefore, in this study, as a part of the economic value evaluation of the data, we have conducted the economic value measurement of the data generated through the small business guarantee program of Korean Federation of Credit Guarantee Foundations (KOREG). To this end, by examining the previous research related to the economic value measurement of the data and intangible assets at home and abroad, we established the evaluation methods and conducted the empirical analysis. For the data value measurements in this paper, we used ‘cost-based approach’, ‘revenue-based approach’, and ‘market-based approach’. In order to secure the reliability of the measured result of economic values generated through each approach, we conducted expert verification with the employees. Also, we derived the major considerations and issues in regards to the economic value measurement of the data. These will be able to contribute to the empirical methods for economic value measurement of the data in the future.
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