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http://dx.doi.org/10.9717/kmms.2020.23.2.317

Analysis of Research and Development Efficiency of Artificial Intelligence Hardware of Global Companies using Patent Data and Financial data  

Park, Ji Min (Dept of Technology and Business Administration Yonsei University)
Lee, Bong Gyou (Graduate School of Information, Yonsei University)
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Abstract
R&D(Research and Development) efficiency analysis is a very important issue in academia and industry. Although many studies have been conducted to analyze R&D(Research and Development) efficiency since the past, studies that analyzed R&D(Research and Development) efficiency considering both patentability and patent quality efficiency according to the financial performance of a company do not seem to have been actively conducted. In this study, measuring the patent application and patent quality efficiency according to financial performance, patent quality efficiency according to patent application were applied to corporate groups related to artificial intelligence hardware technology defined as GPU(Graphics Processing Unit), FPGA(Field Programmable Gate Array), ASIC(Application Specific Integrated Circuit) and Neuromorphic. We analyze the efficiency empirically and use Data Envelopment Analysis as a measure of efficiency. This study examines which companies group has high R&D(Research and Development) efficiency about artificial intelligence hardware technology.
Keywords
R&D(Research and Development) Efficiency; Artificial Intelligence Hardware; DEA(Data Envelopment Analysis;
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