• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.34-46
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• 2021

In the domestic data exchanging market, unreasonable pricing of purchase data is consistently mentioned as a major obstacle in data trading. This is a problem caused by the inability to properly evaluate the value of data products due to lack of product information and experience in using them. In order to activate trading, the data exchanges need to provide information that allows consumers to comprehensively judge the value of data products in addition to prices. The cost-based, income-based, and market-based methods, which are mainly applied to data valuation, are insufficient as data valuation methods to stimulate trading and distribution because only price information, a result of valuation from a supplier's point of view, can be shared with consumers. This study aims to develop a measurable valuation method that allows data trading stakeholders (exchanges, suppliers, and consumers) to judge and share the value of data products from a common perspective. To this end, we identified the value drivers of data products, which are considered important in overseas data exchanges and related research, and derived an evaluation method that can quantitatively measure each value driver. In addition, evaluation criteria in the form of a rating table were developed using data products for transactions, and a value evaluation index was developed through stratification analysis (AHP) to enable relative value comparison. As a result of applying the evaluation criteria to actual data products, it was found that the evaluation values were differentiated according to the characteristics of individual data products, so it could be used as a relative value comparison tool.

• The Journal of Bigdata
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• v.6 no.1
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• pp.153-160
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• 2021

This study examines previous studies on the income (profit) model, which is most used for valuation of data held by companies or institutions, and discusses key factors of the model and considerations in the data asset valuation process. Through this, it was confirmed that the shareability and utilization period of data assets are different from those of other companies. In addition, the value of data should be reviewed from various perspectives such as timeliness and accuracy. And for data asset value evaluation, it was derived that the user's use, ability to use, and value chain should be reviewed as a whole. As a future research direction, continuous research and development of models to be applied to actual business and revision of accounting law were proposed.

• Industry Promotion Research
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• v.8 no.3
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• pp.201-210
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• 2023

This study is based on data ecology theory and takes Chinese local governments' open public data as the research object. Data asset value assessment methods are compared from a new perspective of data business operations. The results show that the assessment model constructed using the hierarchical analysis method (AHP) can more objectively reflect the commercial value of government open data assets than the traditional cost, revenue and market methods, has the advantage of a comprehensive assessment of data value index, and better reflects the findings of a comprehensive index of regional data value. The data show that the local government data value assessment index is positively proportional to the region's digital economy development index, highlighting the driving effect on the digital economy. The results of the study provide a good help for the identification of local government data value rights. The research and practice of promoting the construction of data innovation and data business operation models, improving social well-being and promoting the rapid development of the digital economy to achieve data realisation provides a good reference.

• Information Systems Review
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• v.20 no.2
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• pp.1-19
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• 2018

In many countries, governments invest a substantial amount of budget in open government data (OGD) for governmental performance and transparency. To understand the actual performance of such policies, the governments should measure the realized value. Many organizations and researchers have attempted to assess the value of OGD. However, they have neglected a perspective of consumers who benefit from OGD. Moreover, little research has quantified the economic value. This research examines extant methods of intangible asset valuation to quantify the economic value of OGD in a citizen perspective. In consideration of the extant research methods and the characteristics of OGD, the contingent valuation method is the most appropriate because it effectively reflects various users and their purpose of use. We then conduct a survey of citizens living in Seoul, Korea and assess the economic value of OGD provided by the Seoul government. Findings show that citizens' willingness to pay (WTP) differs across respondents' prior experience, tax resistance, perceived benefit and perceived reality of virtual scenario, but it does not differ across their demographics. WTP also significantly varies across the question formats. We discuss the reliability of the results and implications for future research.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.1-17
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• 2010

Association rules among product items by association analysis suggest sales effect among products. These are useful for marketing strategies such as cross-selling and product display etc. However, if we evaluate more practical product values reflecting cross-selling effects, they will be also more useful for the decisions of companies such as product item selection for product assortment and profit maximization etc. This study proposes product value evaluation models with the concept of effective value based on single-item association chain and itemset association chain. In addition to that, we performed experiments with transaction data related to clothing of an online shopping mall in Korea to show the performances of our models. In result, we confirmed that some items increased in effective values compared with their pure values while the others decreased in effective values.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.367-369
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• 2014

Digital data are mostly comprised of unstructured data such as text file, office file, image file, video file, and drawing file. The recent digital data being generated and used within enterprise are sharply increasing in quantity. Those digital data are becoming significant as digital assets, but the value of digital assets is not properly evaluated. Accordingly, this study will present a model to evaluate the value of unstructured data as digital assets within enterprise and will also present a differentiated management plan for unstructured data as assets.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.108-110
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• 2020

본 연구의 목적은 딥러닝 기법의 하나인 인공신경망 모델을 활용하여 선박의 가치평가 모델을 개발하는 것이다. 선박의 가치는 해운시장 변화와 밀접한 관계가 있으며, 경기 변동성이 크고 시장 민감성이 높은 해운시장의 특성상 가치의 불확실성 역시 높게 나타나고 있다. 이러한 선박가치의 중요성에도 불구하고 국내외적으로 선박가치평가의 체계 개선 및 평가모델의 객관성과 신뢰성을 제고시키기 위한 연구는 부족한 실정이다. 따라서 본 연구에서는 딥러닝 방법을 통해 선박의 가치를 산출하는 새로운 평가모델을 제시하고자 한다. 가치평가의 대상은 중고 VLCC선이며, 선행연구를 통해 선박의 가치 변화를 유발하는 주요 요인들을 선별하여 변수를 설정하고 2010년 1월부터 현재까지의 해당 데이터를 확보하였다. 교차검증을 통해 파라미터들을 추정하여 인공신경망의 최적 구조를 식별하고 이에 대한 객관성과 신뢰성을 검증한 결과 인공신경망 모델의 가치평가 정확성이 우수함을 확인하였다. 본 연구는 선박가치평가의 전통적 방법론에서 탈피하여 기계학습 기반의 딥러닝 모델을 활용한 측면에서 독창적인 의미가 있다.

• 한국벤처창업학회:학술대회논문집
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• 2023.11a
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• pp.79-84
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• 2023

플랫폼은 산업 전반에 걸쳐 막강한 영향력을 행사하며 비즈니스 생태계를 변화시키고 있다, 이러한 변화의 흐름에 따라서 플랫폼 기업의 가치가 빠르게 상승하고 있으며 좋은 플랫폼 기업을 발굴하여 육성하는 것이 곧 국가경쟁력 향상으로 이어지고 있다. 플랫폼 비즈니스 기반의 기업은 플랫폼 특성인 네트워크 효과와 수확체증 현상이 영향력을 발휘하기 전인 사업 초기에는 충분한 수익 발생이 어렵고 승자독식의 산업구조로 인해 치열한 선두 경쟁을 강요받고 있기에 기업 성장을 위해서는 투자유치를 통한 자금을 확보할 필요성이 있다. 본 연구는 플랫폼 비즈니스 기반의 기업에 대한 투자자의 투자결정요인을 도출하고 각 요인 간의 중요도 차이를 분석하여 투자를 준비하는 플랫폼 기업에게 투자자의 관점을 이해하고 사업을 검토하는 데 참고할 수 있는 시사점을 제시하여 플랫폼 기업의 투자유치 성공률을 제고 및 플랫폼 생태계 활성화를 목적으로 하고 있다. 투자자의 투자결정요인과 플랫폼 가치평가에 관한 선행연구를 바탕으로 플랫폼 기업에 적합한 14가지의 투자결정요인을 도출한 뒤 계층화를 통해 플랫폼, 시장, 창업자/팀, 재무, 제품/서비스의 5가지 주요 요인을 선정했으며 투자자를 대상으로 AHP 분석기법을 활용한 1:1 쌍대비교 설문을 진행하였다. 연구 결과 가장 높은 중요도를 나타내는 요인은 플랫폼 특성으로 확인되었으며, 이는 본 연구에서 선정한 플랫폼 특성인 플랫폼 규모, 핵심 참여집단 확보 여부, 가치 고착 용이성, 확보한 데이터 가치가 플랫폼 기업의 가치평가에 적절하다는 것을 시사한다. 추가로 플랫폼 기업에 대한 투자경험 유무로 그룹을 나누어 중요도를 비교한 결과 플랫폼에 투자한 투자자가 그렇지 않은 투자자에 비하여 플랫폼 기업이 확보한 데이터 가치에 대해 높은 중요도를 두고 있다는 것을 확인했다.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.131-143
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• 2023

In the future knowledge society, the importance of business data is expected to increase, and it is recognized as a raw material for companies to manufacture product or develop service. As the importance of data increases, methods to calculate the economic value of database assets is being studied. There are many studies to evaluate the value of database assets, but the characteristics of database assets are not fully reflected. In this study, we classified database assets into revenue-type, non-revenue-type, and public-type database assets by considering the characteristics of database assets. In addition, focusing on the fact that revenue-type database assets can be valued similarly to existing technology valuation, we developed a method for calculating the life of database assets that includes risk-adjusted discount rate.

• Journal of the KSME
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• v.57 no.8
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• pp.49-53
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• 2017

이 글에서는 스마트 팩토리 구현을 위해 고려되어야 하는 다양한 속성들 중에서 '데이터'에 대해서 논하고자 한다. 특히, 제조업의 관점에서 데이터의 가치를 평가하는 방법과 도메인 지식의 중요성에 대해 설명하였고, 중소기업에서 데이터를 활용하기 위한 방안을 함께 고민해보았다.