Associate Professor of Innovation and Data Science
Abstract of Research and Education
My main research theme is “looking at the flow of innovation”.
Innovation in this context refers to goods, organizations and services that can create new value for society. By combining analysis of data sets and interviews under the knowledge of the research fields of industrial organization and data science, finally we can understand how and when innovation is born. I am interested in how innovation is born, what factors drive it, and what factors accelerate it.
In undergraduate education, I am in charge of the “Foreign Literature Course” and the “Top Management Course”. In the former, I aim to teach methodologies for using data in real business, using English-based language literature with data analysis techniques. In the latter, we will discuss how companies are realizing and introducing their digital transformation (DX). I help students to hear first-hand from companies how they are realizing DX and data science.
In postgraduate education, I teach “Innovation Analysis (postgraduate)” and “Technology Operations and Management (MBA)”. In today’s management science, it is essential to combine qualitative and quantitative analysis in a way that is consistent with the research questions and research design. In my postgraduate courses, I will explain a comprehensive range of analytical methods, so that the student can learn to use them on their own research interests without being swayed by tools and techniques. In the MBA courses, I focus on innovation. In the MBA lectures, we will discuss with you the methodology for creating new values, goods and organizations, also known as innovation, with an emphasis on the links to business.
Details of Research Achievement
- Directory of Researchers Page of Kobe University：https://kuid-rm-web.ofc.kobe-u.ac.jp/profile/en.feec9d68989dd34d520e17560c007669.html