Earticle

초록

영어

As data markets sprout up all around the world, we, the researchers, propose a methodology to classify data markets hoping to be developed for the theory of them. In particular, we pay attention to the evolutionary nature of rapid market advancements and development. Although many data markets are vastly different in their characteristics as they serve different markets and customers, they share common attributes to determine the advancements, in their added values and automation. Therefore, to classify markets according to the relative status of evolution, two measurements to compare how advanced markets are defined: the degree of value added and the degree of automation. Given the measurements, we classify the markets into four different types: Tailor-Made, Do-It-Yourself, Grocery, and Financial-Exchange. As for the first three types of the four, a large number of instances can be found in the real world. Yet, the last one, Financial-Exchange type data market, which is theoretically the most advanced type, does not globally exist. Thus, we have investigated and a possible theoretical model of it for the sake of the completeness of the research. In this paper, we present the model for a possible implementation as a new business model. We find that the model offers many advantages over other types of data markets, especially in the area of data security and privacy information protection. Finally, we investigated how the theoretical model may be viable as a business model of its own kind.

목차

Ⅰ. 서론
 Ⅱ. 선행연구의 검토
 Ⅲ. 전통적 금융거래소와 데이터 거래소 이론적 모델
 Ⅳ. 데이터 장터의 진화 형태에 따른 비교
 Ⅴ. 금융거래소형 데이터 거래소의 장점 및 효과
 Ⅵ. 결론 및 시사점
 참고문헌
 

키워드

저자

• 이영환 [ Nick Lee | 건국대학교 기술경영학과 조교수 ]
• 전희주 [ Jun Hui-ju | 동덕여자대학교 정보통계학과 조교수 ] 교신저자
• 윤정연 [ Yoon Jeongyeon | 한국금융연수원 조교수 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국창업학회지 [Journal of the Korean Entrepreneurship Socieity]

• 간기

  격월간

• pISSN

  2092-8068

• 수록기간

  2006~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 325 DDC 658