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With the recent diversity of information technology and information devices and the large amount of meaningful and meaningless data being created, collected, processed and utilized exponentially, the analysis and utilization of data has expanded to more important areas, and data analysis using machine learning enables future predictions. Machine learning heralds many changes in the era of connectivity and convergence based on numerous data generated in various industries, including manufacturing, bio-industry, and robots.
In the era of the fourth industrial revolution, new technologies such as IoT, AI, and cloud computing are actively used in various industries such as IT, manufacturing, and services. Strategies are needed to respond to the overall economic situation and the rapidly evolving technology growth and business model in each industry sector. In particular, the proliferation of artificial intelligence and the Internet of Things has made it impossible for certain companies to monopolize technology standards, and the era of a shared economy through open source where all businesses and users share and collaborate with each other through code disclosure has arrived (Kim, B.S 2018). Open APIs, which are publicly available for free, are a prerequisite for companies seeking to develop, utilize and apply technologies.
Open Source is a concept that emerged under the Open Source Movement initiated by OSI, an international organization established in 1998 (Jang, H. H.& Choi, Y. H.& Gim, G. Y. 2019), and open source software is free software that provides source code and executable files publicly and allows anyone to freely distribute files of modified and modified software. When a company wants to develop and use software on its own, it is highly useful, but the cost of investing in development is enormous. However, the Open API is available free of charge and has significant advantages of reducing the cost and time required for self-development (Jang, H. H.& Choi, Y. H.& Gim, G. Y. 2019). To solve various problems such as cost and time when God is needed, Open API is expected to accelerate the increase in the use of Open API not only in companies but also by increasing the use of Open API. Software using the Open API is becoming more mature with a rapid increase in the number of participating companies and developers, and some technologies have gone beyond the performance of proprietary software (Jang, H. H.& Choi, Y. H.& Gim, G. Y. 2019).
Machine learning, a key technology in the era of the fourth industrial revolution, is able to predict the future of the future through analysis of big data in unstructured forms such as voice and images as well as structured data, and artificial intelligence technology based on it is gaining its importance in various industries. Among AI-related technologies, AI-based image recognition technology is continuously developing, but there is a lack of prior research on Vision API. Thus, the scope of this study is intended to focus on Vision API, which is based on AI, among various Open APIs. While prior research on software development and utilization using Open API has focused on the research on development and implementation or the factors affecting the intention of use, it is time for academic research on what factors should be considered first when utilizing software. Based on the existing open source and open API prior research, this study attempts to construct a hierarchy to derive factors that should be considered in the use of the AI-based Vision Open API through Delphi technique, which is an expert survey method, and to use AHP methodology to derive priorities for what factors should be considered first in the intention of utilizing the Open Vision API.