Evidence-Based Innovation Policy and Strategy
Designing more effective national science, technology, and innovation strategies using data
Research
Research Frontiers
The Shichijo Lab has established four research frontiers that address critical societal challenges using data science methodologies. All these research areas are based on a mission-driven approach, emphasizing real-world impact.
01
Overview
Technology Management and Startup Dynamics
Exploring the DNA of successful technology ventures and corporate innovation creation
Social Implementation of New Technologies
Analyzing conditions for new technologies like AI and robotics to be socially accepted and truly contribute
Science of Science (Scientometrics)
Mapping and understanding the evolution of science itself and the structure of knowledge
02
Frontier 01
Evidence-Based Innovation Policy and Strategy
How can we design more effective national science, technology, and innovation strategies using data?
Through collaboration with government agencies and utilization of platforms like the Cabinet Office's e-CSTI, we support evidence-based policy formation. Our research directly contributes to national-level decision-making through specific themes such as identifying priority technology areas and analyzing R&D productivity.
Technology Mapping through Patent and Publication Analysis
Mapping emergence patterns of AI technologies in healthcare and building predictive models for next-generation technologies
Patent Analysis
Bibliometrics
Machine Learning
Government R&D Budget Impact Analysis
Development of public funding impact assessment methods using government R&D budget data
Policy Evaluation
Causal Inference
Econometrics
Priority Area Analysis Platform
Trend analysis and strategic recommendations for national priority technology areas using the e-CSTI system
Policy Support
Data Integration
Visualization
03
Frontier 02
Technology Management and Startup Dynamics
What is the DNA of successful technology ventures? How can large corporations avoid R&D "spinning wheels" and create innovation?
Through research on startups, industry-academia collaboration, and R&D management, we analyze corporate-level data to explore the factors of growth, innovation, and failure. By optimizing technology management, we aim to revitalize Japan's innovation ecosystem.
Startup Success Prediction Model
Development of machine learning models to predict startup success based on founder characteristics and funding patterns
Machine Learning
Venture Analysis
Prediction Models
Corporate R&D Strategy Evolution Analysis
Analysis of the relationship between R&D strategy changes and outcomes through text mining of corporate annual reports
Text Mining
R&D Strategy
Corporate Analysis
Industry-Academia Collaboration Impact Quantification
Quantitative analysis of outcomes and influencing factors in university-industry collaboration projects
Industry-Academia
Impact Measurement
Network Analysis
04
Frontier 03
Social Implementation of New Technologies
What is needed for new technologies like AI and robotics to be socially accepted and truly contribute?
Through research on social acceptance of telepresence robots and considerations of the broad social impacts of AI, we conduct research that directly connects technology with human experience. We identify challenges and opportunities in technology social implementation and support sustainable technological development.
Social Sentiment Analysis toward Generative AI
Temporal analysis of Japanese public sentiment toward generative AI using social media data
Sentiment Analysis
Social Media
AI Implementation
Ethical Implementation of Autonomous Systems
Framework design for ethical implementation of autonomous systems in public spaces
AI Ethics
Autonomous Systems
Social Implementation
Robot Service Acceptance Survey
Acceptance survey and improvement proposals for interpersonal services by mobile robots
Robotics
Social Acceptance
Service Design
05
Frontier 04
Science of Science (Scientometrics)
How does science itself evolve? How can we map and understand the structure of knowledge?
Using bibliometric and network analysis methods, we analyze research trends in specific fields such as cybersecurity and dental implants. This demonstrates the lab's meta-level expertise while providing insights that form the foundation for science and technology policy.
Quantum Computing Research Network
Mapping and trend analysis of global researcher networks in quantum computing
Network Analysis
Quantum Technology
Research Trends
SDS Field Evolution Analysis
Analysis of research theme evolution and interdisciplinary development in the Social Data Science field itself
Interdisciplinary
Field Evolution
Topic Modeling
Cybersecurity Research Bibliometric Analysis
Bibliometric analysis of the cybersecurity field using e-CSTI
Cybersecurity
Bibliometrics
Research Evaluation
06
Approach
Our Research Approach
Mission-Driven
Research focused on solving clear social challenges rather than mere methodology development
Interdisciplinary Integration
Comprehensive approach combining data science, economics, policy studies, and management
Qualitative × Data-Driven Fusion
We organically fuse deep, field-grounded qualitative inquiry with rigorous data-driven analysis, reaching a depth and breadth of insight neither approach achieves alone
Implementation-Oriented
Emphasizing real-world application to policy and industry alongside academic contributions
07
Join
For Those Considering Research Participation
The Shichijo Lab seeks motivated researchers to challenge together in these research frontiers. Please check the details to see if your interests align with our mission.