I would categorize myself as a highly interdisciplinary researcher bridging technical and social/humanities research disciplines. Based on my educational background as psychologist, I have been engaged in consumer behavior research, marketing management and business development of home appliances and electronics products in both Japanese and Danish high-tech industries in the past two decades. During my PhD at CBS, my experience and knowledge was further extended to the academic research on language technology (semantic networks and knowledge engineering), cognitive modeling and the application of artificial intelligence technologies to social sciences in close collaboration with machine learning experts from Technical University of Denmark (DTU).

Utilizing my strong interdisciplinary experience and network, I am co-heading an externally funded interdisciplinary innovation project, and have obtained a diploma from Harvard Business School on: “Innovation Management Leadership: From Project to Competitive Advantage - Pasteur Program 2017” both supported by Innovation Fund Denmark (IFD). In this project, the DTU colleagues and I have developed a sophisticated consumer data analysis method to classify consumers based on personal values. My current interest is to use this consumer classification method to analyze consumers’ motivation, attitudes and actual behaviors based on various sources such as surveys, experiments, social media and customer databases. This might be highly useful for practical business applications such as the development of STP (Segmentation, Targeting and Positioning) strategies and for new product designs.

Our early stage ideas were evaluated and selected for the Best Excellent Paper at the 2018 Global Marketing Conference held in Tokyo.

Primary research interests:

• Social & Cross-Cultural Psychology
• Consumer Psychology (Consumer Segmentation & Segment-specific Consumer Analysis)
• Cross-cultural cognition (mental representations and semantic analysis)
• Intercultural Data Analysis Methods
• Business Intelligence (the application of Machine Learning technologies to Social Sciences in particular with focus on Consumers and Tourists Big Data)