Last updated on August, 2016 by Fumiko Kano Glückstad
Cool Japan – Smart Denmark Initiative:
Integration of data sciences in the tourism research
Project period: 2018-2019
Grantee: Fumiko Kano Glückstad
This network initiative addresses the tourism research discipline in which the innovative and intelligent integration of data sciences is a key for future progress, but not yet fully implemented among the academic tourism research community. While the quantitative methods employed by tourism academicians have been heavily based on the theory-driven positivistic approach, the recent emergence of the Big Data trend has triggered data scientists to enter data-driven research on tourists’ behaviors and decision making predictions, which enables tourism academicians to conduct the quantitative research integrating the social constructivism perspective into their existing tourism research. What is urgently needed is the seamless integration of these two approaches. The ultimate scope of this initiative is that this integration makes possible a deeper understanding of tourists based on a formalized framework that investigates travel motivations, mental pictures and behavioral intentions that diverse subgroups of tourists have of a given destination. Specifically, an important aspect required in the contemporary society is to understand complex insights into culturally diverse subgroups of tourists and their behaviors across the global market place. As the name “Cool Japan” promotes Artificial Intelligence (AI) and IoT technologies applied to the tourism and hospitality management, the technology-driven tourism research is one of the strengths provided by Japanese researchers. This initiative seeks synergetic effects between two nations integrating these two opposing approaches.
UMAMI: Understanding Mindsets Across Markets Internationally
Funded by: Innovation Fund Denmark
Project period: 2017-2020
Project web-site: http://sf.cbs.dk/umami
JSAI new challenge session "5C: Comprehending Consumers - Computing Complexity of Cultures"
has been established under the overall framework of a five-years project "Challenge for Realizing Early Profits" under the Japanese Society of Artificial Intelligence from June 2016
Due to the world-wide media coverage facilitated by contemporary telecommunication, the value formation of Asian consumers is influenced by both local and global stimulus, which diversifies Asian consumers more than ever. Cleveland et al. (2001) emphasizes that: “a proportion of individuals worldwide develop bicultural identities: one based in local traditions combined with an identity connected to an emerging global culture (Arnett, 2002; Kurasawa, 2004)” and “as corporations globalize, the key challenge for managers is to institute an effective marketing orientation across a composite of cultures (Nakata and Sivakumar, 2001)”. Consumers increasingly expect to be addressed and met on their own terms. This can only be achieved if businesses can handle very complex insights into culturally diverse subgroups (“segments”) of consumers and their behavior across the global market place. With a view to penetrating international (in particular remote and emerging Asian) markets, the study of these contemporary consumer behaviors urgently requires a “method” that simultaneously captures mono-cultural (culturally specific), multicultural (regionally specific) and transcultural (universal) characteristics of consumer segments across a multiplicity of markets.
The key issue is how the value priorities of consumers are shaped in our globalized society. The new trend of so-called Big Data mining is in this respect meaningless without fully comprehending the core insights of interpersonal values connecting people around the globe. Thus innovative and intelligent use of Big Data is a key to the success of future international marketing activities. For this reason, this project aims at developing a tool to fully comprehend consumers across boundaries of international markets by computing the cultural complexity of consumer values and behavioral data. The tool will enable us to meaningfully filter Big Data by mining relations between subjective interpersonal values and objective consumer behavioral data across boundaries of societies.
Yasuro Tanida, R&D Director @ Synergy Marketing Inc. Japan
Fumiko Kano Glückstad @ Copenhagen Business School