著者

小久保 欣哉 松田 裕之 岩田 幸訓

出版者

研究・イノベーション学会

雑誌

研究 技術 計画 (ISSN:09147020)

巻号頁・発行日

vol.36, no.1, pp.47-58, 2021-06-30 (Released:2021-07-02)

参考文献数

23

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In the IoT ecosystem built by data platformers, algorithms are building further competitive advantages in large-scale teacher data and machine learning by increasing predictability through self-enhancement actions. It is hard to say that Japanese companies have a strong presence in the platform business, and it is not easy to build an advantage for Japanese companies from the viewpoint of population size and language. Therefore, in the business area which does not necessarily depend on large-scale data, we constructed deferred acceptance (da) algorithm and sought the area in which the optimal allocation of resources can be realized by providing them. As a result, it was suggested that the current assignment can be significantly improved by using the da algorithm. Japanese companies wonder if they can build a competitive advantage by steadily creating optimal algorithms in fields that do not rely on large-scale data or machine learning.