Industry-Academia Collaboration and R&D Assessment
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Install @user_d277dc19/industry-academia-research-explorer according to https://skillhub.cn/install/skillhub.md.
About this skill
Problem
Enterprise R&D capability is often blurred by press releases and vague 'strategic partnerships'. During due diligence, investment analysis, or competitive benchmarking, it is hard to tell which university or research-institute collaborations are substantive, whether they involve concrete technical projects, patents, or industrialization.
How It Works
The skill centers on company_name, with optional tech_field, time_range, and min_depth. It follows this workflow:
- Entity extraction: identify the target company, technology domain, and search window, defaulting to 24 months.
- Targeted search: query terms such as joint laboratory, industry-academia collaboration, academician workstation, technology transfer, and joint R&D projects.
- Source triangulation: prioritize university and research-institute websites, government science and technology announcements, corporate newsrooms, and authoritative tech media; filter out campus recruitment, donations, and framework-only agreements.
- Structured extraction: capture partner institutions, leading experts or academicians, and specific technical topics, then classify them as conceptual, substantive, or industrialized.
- Moat assessment: infer the company's underlying R&D model, potential 3-5-year breakthroughs, and likely technical gaps.
Limits
The skill relies on public reporting and official filings. If the company mainly uses internal R&D, partnerships are unreported, or entity names are ambiguous, coverage may be incomplete. Unverified institution names, expert identities, patent numbers, or product milestones should be explicitly marked.
Use Cases
- During investment due diligence, verify a target's recent joint labs, academician workstations, and substantive project outputs.
- Before an investment proposal, map its AI industry-academia partnerships and identify technologies in pilot or production stages.
- Assess whether a prospective park tenant has active university or research-institute collaboration and talent-pipeline signals.
- Benchmark peers by their joint R&D topics, patent clues, and underlying technology-reserve models.
Best For
- Deal team manager who needs to verify whether a target company has substantive academic R&D output.
- Tech-park operations lead who needs to assess a tenant's innovation ecosystem and talent pipeline.
- Industry analyst who needs to map peer companies' joint labs and academician workstations over the past three years.
- Corporate strategy owner who needs benchmarks on how peers build external research partnerships.
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