earticle

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.