Why do you want to work in Hokkaido? Hokkaido University students uncover the "true causes" of employment intentions using causal AI in a PBL project

Hootfolio Inc., in collaboration with NEC Corporation, conducted an educational program at Hokkaido University utilizing causal AI "causal analysis®." This initiative was carried out as a Project-Based Learning (PBL) program aimed at fostering data utilization and decision-making skills. Students, acting as co-creation project members involving regional companies, local governments, and students, took on the challenge of deriving measures to promote local employment for young people from actual survey data.

■ Background: Data-driven decision-making required for regional problem-solving

In response to challenges facing regional societies, such as population decline and the outflow of young people to urban areas, the importance of data-driven decision-making (EBPM: Evidence-Based Policy Making) is increasing, moving beyond reliance on experience or impressions. In particular, causally understanding "what produces results" is considered a crucial perspective for enhancing the effectiveness of policies and measures.

Causal AI "causal analysis®" provided by Hootfolio Inc. is a no-code solution that can visualize cause-and-effect relationships hidden in data without specialized knowledge. In this program, students utilized this technology to analyze actual survey data, deepening their understanding of regional issues and engaging in policy formulation.

Photo: Students earnestly learning about causal analysis

■ Program Overview: PBL focused on Hokkaido's appeal and employment intentions

Format: In-class PBL (group work, final presentation)
Target: Students of the Center for Mathematical and Data Science Education and Research, Hokkaido University
Theme: Analyze factors influencing Hokkaido's appeal and employment intentions for companies within Hokkaido, and propose regional policies

Program content:

1. Basic understanding of causal analysis

   Learning the difference between correlation and causation, and how to apply it to social issue analysis

2. Causal analysis of student survey data

   Exploring factors influencing Hokkaido's appeal and employment intentions

3. Policy formulation and presentation

   Considering specific measures for local governments and companies based on analysis results

Students directly engaged with data, exploring the causal relationships of "why that element leads to appeal." They experienced learning that scientifically demonstrates the factors leading to results, rather than merely grasping numerical values.

■ Student Analysis Results: Factors increasing the intention to work in Hokkaido

Student analysis revealed that the factor most strongly influencing the intention to work in Hokkaido was "no job transfers." On the other hand, "good access to urban areas" and "being a large company" did not necessarily increase the intention to work in Hokkaido.

Furthermore, analyzing by place of origin showed differences in important points. Students from rural areas within Hokkaido tended to prioritize "commuting convenience," while students from Sapporo City tended to prioritize "work-life balance."

These results suggest that students wishing to work in Hokkaido may prioritize "an environment where they can work long-term, rooted in the region, without job transfers" over salary or company size.

Figure 1: Key points of student analysis and consideration

■ Policies proposed by students

Based on the analysis results, students proposed the following measures to local governments and regional companies:

① Certification system to visualize no job transfers and work-life balance

Proposed the creation of a "Hokkaido Settlement Excellent Company System" to certify companies that meet criteria such as no job transfers, overtime hours, and paid leave acquisition rates. This aims to create an environment where students can choose companies with peace of mind.

Figure 2: Policy proposal ① derived through causal analysis

② Promoting regional appeal based on place of origin
Proposed measures to change information dissemination by companies and local governments according to different values based on place of origin. It was considered effective to appeal to those from within Hokkaido with convenience of living, to those from Sapporo with urban functions and QOL, and to those from outside Hokkaido with natural environment and SDGs initiatives.

Figure 3: Policy proposal ② derived through causal analysis

■ Educational Effects: Insights born from stakeholder data

A characteristic of this program is that "Hokkaido students' data" was analyzed by "Hokkaido students themselves." Because the theme concerned their own future and region, students approached the analysis with a strong sense of ownership.

Furthermore, by consistently experiencing the process from hypothesizing based on data, verifying results through causal analysis, and designing specific measures based on that knowledge, it became an opportunity to cultivate practical problem-solving skills beyond mere analytical skills.

Moreover, the fact that students themselves interpreted the data led to perspectives and insights that are often overlooked by adult preconceptions, which is another characteristic of this program. Through discussions and policy considerations based on analysis results, students developed the ability to think, explain, and make decisions based on data.

■ About causal AI causal analysis®

Causal AI solution for intuitively grasping the "true causes" that influence outcomes

Utilizing proprietary AI technology developed at NEC Corporation's research laboratories, it extracts and visualizes "cause and effect" relationships hidden in data that were difficult to see with conventional analysis. With an intuitive interface, even without specialized statistical knowledge, it answers the question of "what produces results" and enables scientifically guided next actions in business.

In addition to marketing, its application is expanding to HR areas such as factor analysis to enhance employee engagement, and to policy formulation and community development.

■ About hootfolio

Hootfolio Inc. is a startup spun out from NEC Corporation in January 2025. With the mission of "scientific decision-making for everyone," it provides the SaaS-based analysis service "causal analysis®" utilizing causal AI. Based on the technological capabilities cultivated as an NEC-born startup, we will accelerate the social implementation of scientific decision-making in collaboration with companies, governments, and research institutions.

Hootfolio Inc.

Company Name: Hootfolio Inc.
Location: 5-32-12 Shiba, Minato-ku, Tokyo, Charmezon Stage Tamachi
Established: August 2024
Representative: Kenta Kasahara
Company Website: https://hootfolio.com/
Business Activities: Provision of causal analysis solution "causal analysis"