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The Knowledge Production System is a compound interaction-regulation system composed of recursive interaction units and layered mechanisms of validation, reproduction, and symbolic control over truth claims. It is deeply embedded in and co-evolves with its environment (culture, economy, polity).

Terminology

Innovation as a way of adaption.

The “National Innovation System” is not a system in the strict systems-theoretic sense, but a territorially anchored analytical construct used to study the institutional and organizational conditions shaping innovation within a nation-state.

National Innovation Systems (NIS) are the networks of institutions, organizations, and individuals that interact and collaborate to produce and diffuse new knowledge, technologies, and products within a specific country or region.

NIS can be strengthened and made more effective through the development of supportive policies and institutions that encourage collaboration, knowledge sharing, and investment in research and development.

Effective innovation systems require a balance between competition and cooperation, as well as a mix of public and private investments in research and development.

Different countries have different strengths and weaknesses in their innovation systems, and it is important to understand the unique characteristics of each system in order to promote successful innovation policies and practices.

NIS can reduce companies’ cost if a shared research program attaches the everyday problems of the industry - collaboration - and make money indifferentism ej (services, business model, customer support, etc.) …

The NIS includes formal and informal components, such as universities, research institutes, government agencies, private sector companies, venture capitalists, and innovation networks. These components interact and collaborate in various ways, such as through research partnerships, technology transfer agreements, and funding mechanisms.

A NIS aims to facilitate the flow of knowledge, resources, and ideas across different sectors and stakeholders to support innovation and economic growth. By promoting collaboration and coordination among various actors, an NIS can create a favorable environment for innovation and ensure that new technologies are effectively diffused and commercialized. Many countries worldwide have implemented policies and strategies to strengthen their national innovation systems and enhance their competitiveness in the global economy.

National innovation systems (NIS) are the networks of institutions, organizations, and individuals interacting and collaborating to produce and diffuse new knowledge, technologies, and products within a specific country or region.

A "Public Research Institute (PRI)" is a government-funded organization dedicated to conducting scientific research and development to advance knowledge and address societal needs. → See More in “”.

Basic Research Conducted to increase fundamental knowledge and understanding of phenomena without specific applications.

Applied Research We aimed to solve practical problems or develop new products, processes, or techniques.

Development Research findings and scientific knowledge are systematically used to produce new or improved products, processes, or services.

Exploratory R&D Focuses on investigating new ideas and concepts to assess their feasibility and potential impact.

Incremental R&D Involves making small, continuous improvements to existing products, processes, or technologies.

Breakthrough R&D Focuses on making significant, revolutionary advancements that can create new markets or disrupt existing ones.

Industrial R&D Conducted by companies to develop new prodNational Innovation Systems (NIS)ucts, improve existing ones, or enhance production processes.

Public R&D Funded and conducted by government or public institutions to address societal needs and challenges.

Private R&D Funded and conducted by private companies or organizations for competitive advantage and market gain.

Collaborative R&D Involves partnerships between different organizations, such as universities, government agencies, and private companies.

Basic Research Conducted to increase fundamental knowledge and understanding of phenomena without specific applications.

Applied Research We aimed to solve practical problems or develop new products, processes, or techniques.

Development Research findings and scientific knowledge are systematically used to produce new or improved products, processes, or services.

Exploratory R&D Focuses on investigating new ideas and concepts to assess their feasibility and potential impact.

Incremental R&D Involves making small, continuous improvements to existing products, processes, or technologies.

Breakthrough R&D Focuses on making significant, revolutionary advancements that can create new markets or disrupt existing ones.

Industrial R&D Conducted by companies to develop new products, improve existing ones, or enhance production processes.

Public R&D Funded and conducted by government or public institutions to address societal needs and challenges.

Private R&D Funded and conducted by private companies or organizations for competitive advantage and market gain.

Collaborative R&D Involves partnerships between different organizations, such as universities, government agencies, and private companies.

How to build an R&D system?

What’s the role of universities?

Design Cooperative R&D Schemes?

How can we make the research problem open and cheaper to experiment with?

Innovation: From the Latin Innovatio, it means 'the action and effect of creating something new.

Innovation: The Art of Creating or using Technology to Solve a Problem. Creating (Re-discovery / Engineering-Reserve / Ex-Novo / Adaptation / Imitative Innovation / Original Innovation).

Innovation, as the process of conceiving new technologies and improving existing ones to address specific problems, is the means through which societies advance and enhance their quality of life.

Inovation Phenomena: Technological Diffusion, Invention Genesis, Collaboration, Technology Transfer, User Innovation, Network Effects, Critical Mass, Innovation Policy, Actors Taxonomy, Innovation Network Interaction Models, Collaboration Models, Productivity Models, Sectorial Innovation, Sub National Innovation, National Innovation, Global Innovation.

Knowledge is the foundation of economic growth, and innovation is its engine. - Cesar Hidalgo

Innovation is not a solo sport. It requires collaboration, openness, and a willingness to share ideas. - Cesar Hidalgo

We are living in a world where we need to learn how to learn faster. - Cesar Hidalgo

The most valuable resource we have is not oil or gold, but human creativity. - Cesar Hidalgo

The National Innovation System refers to a framework that integrates actors and resources at the national level to promote and coordinate innovation in a country.

The National System of Innovation is not just a set of laboratories but is a cumulative process of learning by producing, learning by using and learning by the interaction of producers and users. - Freeman

Ontological Signature

Ontological Dimension Description
System Type Compound System
Core Ontological Class Cognitive-Institutional System
Constituent Elements
→ Interaction Units Scholars, institutions (e.g., universities, academies), technologies (e.g., printing press, libraries), networks (e.g., correspondence networks)
→ Interactions Research, publication, debate, peer review, apprenticeship, funding, censorship
→ Regulatory System Epistemic norms, research methodologies, paradigms, institutional rules, disciplinary standards
→ Tagging System Classification of knowledge (disciplines, taxonomies, fields), accreditation, intellectual authority hierarchies
→ State Representation Level of institutionalization, innovation capacity, fragmentation or integration of knowledge domains
→ Infrastructure Libraries, journals, laboratories, archives, observatories, conferences, digital platforms
→ Feedback Dynamics Recognition, replication, citation, innovation, obsolescence, scientific revolutions
→ Embeddedness in Society Embedded in broader political economy, ideology, and cultural worldviews
Ontological Category Recursive Cognitive System
Temporal Nature Evolves through paradigm shifts, cumulative knowledge, or disruptions (e.g., Kuhn's "normal science" vs "crisis")
Examples - Medieval Scholasticism
- Islamic Golden Age madrasa-science complex
- Modern research universities
- Industrial R\&D Labs
Ontological Primitive Role in the Knowledge Production System
Interaction Unit Individual researchers, institutions (universities, think tanks), epistemic communities
Interaction Research, teaching, publishing, peer review, debate, funding, citation
Regulation Epistemic norms, methodologies, disciplinary standards, institutional protocols
Tagging System Disciplines, fields, journals, citation indices, degrees, peer recognition systems
State Accumulated knowledge, institutional maturity, scientific paradigms, innovation output
Environment Broader society, economy, political system, technological base
Infrastructure Laboratories, libraries, digital platforms, conferences, data repositories
Mechanism Innovation cycles, institutional funding models, publication pipelines
Feedback System Citation, reputation, replication crisis, intellectual revolutions
Temporal Dynamics Cumulative evolution, punctuated equilibrium (e.g., paradigm shifts, scientific revolutions)

Taxonomy of Innovation

Innovation Output !!!

Innovation is not just about creating new products and services; it’s also about creating new organizational forms and new ways of working together. - Cesar Hidalgo

Innovation can take various forms, and researchers and business experts often categorize it into different types based on other criteria.

Type of Innovation Description
Technological Innovation Developing and implementing new technologies or applying existing ones novelly.
Knowledge Innovation Creation and application of new knowledge, intellectual property, or ways of thinking.
Product Innovation Introduce a new product or make significant improvements to existing products.
Process Innovation Improve or redesign internal processes to increase efficiency, reduce costs, or enhance quality.
Service Innovation Introducing new or improved services to meet customer needs and expectations.
Business Model Innovation Rethinking and redesigning how a business creates, delivers, and captures value.
Social Innovation Development of new solutions to address social challenges and improve societal well-being.
Design Innovation Focus on improving the design of products or services to enhance user experience and aesthetics.
Marketing Innovation Developing new marketing strategies, channels, or techniques to promote products or services.
Policy Innovation Introducing new policies or changes to existing approaches to drive positive outcomes in various domains.
Reverse Innovation Innovating in emerging markets and then applying those innovations in more mature markets.

Taxonomy

How to classify research?

  • Purporse: Why the research is conducted?
  • Metdhology: How knowledge is produced?
  • By Orientation - Epistemic Goal - Research Maturity: What kind of knowledge is sought?
  • Basic: Aims at understanding principles, laws, or mechanisms.
  • Apply: Targets practical problems using existing or new knowledge.
  • Translational: Bridges basic knowledge and applied implementation (common in biomedical and engineering contexts).
  • Action-Oriented: Research conducted within the process of intervention (e.g., action research).
  • Object of Study: What kind of inquiry object is studied?

Model(s) to Characterize the Facet

Model Definition Example
Ownership Model Defines who owns and controls the National Innovation System (NIS). - Public (Government owned) - Private (Industry owned) - Public-Private Partnership
HR Model (Human Resources) Describes how the NIS attracts, develops, and retains skilled personnel for innovation. - Focus on STEM education (Science, Technology, Engineering, Mathematics) - Industry-academia collaboration for training programs - Talent mobility programs
Funding Model Identifies sources of funding for innovation activities within the NIS. - Government grants - Venture capital investments - Public-private partnerships for research funding
Research Strategy Model Outlines the overall approach for research and development (R&D) within the NIS. - Focus on basic research, applied research, or commercialization - Mission-oriented research programs - Multi-disciplinary research initiatives
Collaboration Model Defines how different actors within the NIS (e.g., universities, research institutions, companies) collaborate for innovation. - Joint research projects - Technology transfer partnerships - Innovation clusters
Governance Model Establishes the decision-making structures and processes for managing the NIS. - Centralized government control - Decentralized with regional or sectoral innovation agencies - Multi-stakeholder governance with participation from industry, academia, and government
Research Infrastructure Model Describes the physical and technological resources available for R&D activities. - Shared research facilities - High-performance computing resources - Advanced laboratories
Intellectual Property (IP) Management Model Defines how intellectual property generated within the NIS is protected and commercialized. - Patenting strategies - Licensing agreements - Open source models
Knowledge Translation Model Explains how research knowledge is disseminated and translated into practical applications. - Technology transfer offices - Public outreach programs - Training programs for industry
Innovation Model Describes the overall approach to supporting innovation activities within the NIS. - Open innovation model (collaboration with external partners) - Closed innovation model (focus on internal R&D) - Stage-gate model for managing innovation processes
Technology Transfer Model Defines how new technologies developed within the NIS are transferred to industry for commercialization. - Licensing agreements - Spin-off companies - Joint ventures
Training Model Identifies how skills and knowledge are developed to support innovation within the NIS. - Entrepreneurship training programs - Workforce development programs for new technologies - Innovation management training

Type of R&D Centers

Here is a table categorizing types of R&D centers by their role, considering the development stage of a country:

Type of R&D Center Role Developed Countries Developing Countries
University Research Centers Conduct basic and applied research, often in collaboration with industry Focus on cutting-edge technology and innovation Emphasize education and capacity building
Government Research Institutes Address national priorities, policy support, and public good research Advanced research in diverse fields Focus on agriculture, health, and infrastructure
Corporate R&D Labs Develop new products and technologies for commercial purposes High-tech, competitive innovations Adaptation and localization of existing tech
Non-Profit Research Organizations Research for societal benefit, often funded by grants and donations Specialized in niche areas like environment, health Address immediate social issues and development
International Research Centers Collaborative research on global challenges Lead global initiatives, set standards Technology transfer, capacity building
Industry-Specific Research Centers … … …
Public-Private Partnerships Labs Combine resources and expertise from both the public and private sectors to drive innovation …
National Laboratories Los Alamos National Lab (USA), RIKEN (Japan)

Innovation Actors

Here is a table summarizing the various types of innovation actors, their roles, and examples:

Type of Innovation Actor Role/Function Examples
Government Agencies Formulate policies, provide funding, support research and innovation National Science Foundation (NSF), National Institutes of Health (NIH), DARPA
Academic Institutions Conduct fundamental and applied research, educate future innovators Massachusetts Institute of Technology (MIT), Stanford University, University of California, Berkeley
Research Institutes Conduct specialized research, often in collaboration with other actors Fraunhofer-Gesellschaft (Germany), Max Planck Institutes (Germany), SRI International (USA)
Private Sector Companies Develop and commercialize new products and technologies, invest in R&D Google, IBM, Siemens, General Electric
Non-Profit Organizations Fund and conduct research, advocate for specific causes or technologies Gates Foundation, Wellcome Trust, Howard Hughes Medical Institute
Industry Consortia Foster collaboration on pre-competitive research, set industry standards Semiconductor Research Corporation (SRC), European Technology Platform (ETP)
Public-Private Partnerships Combine resources and expertise from government and industry to drive innovation National Network for Manufacturing Innovation (NNMI), European Institute of Innovation and Technology (EIT)
Venture Capital Firms Provide funding and mentorship to startups and early-stage companies Sequoia Capital, Andreessen Horowitz, Kleiner Perkins
Incubators and Accelerators Support startups with resources, mentoring, and networking opportunities Y Combinator, Techstars, 500 Startups
Patent Organizations Protect intellectual property, facilitate technology transfer United States Patent and Trademark Office (USPTO), European Patent Office (EPO)
International Organizations Provide funding, set standards, facilitate global collaboration World Bank, United Nations Industrial Development Organization (UNIDO), International Monetary Fund (IMF)
Researchers or Scientists Researchers are the central actors in basic science research. They are highly trained individuals who design and conduct experiments, gather data, analyze results, and draw conclusions. Researchers work in various scientific disciplines, such as physics, chemistry, biology, and mathematics.
Funding Agencies Government agencies, private foundations, and philanthropic organizations support basic science research financially. They offer research grants and funding opportunities to researchers and institutions.
Innovation Clusters Geographic concentrations of research institutions, companies, and support organizations that drive innovation and economic growth.

Funding Model

  • Minor Council of Strategic Investments (Clients)
  • Government
  • Industry
  • Industry Consortium
  • ….

Ownership Models

  • Public
  • Private
  • Mix
  • Non-Profit Public / Private
  • Non-Profit Private

Models of Incentives System for Research

  • Patent System
  • Buying Licenses
  • …

Regional Inovation

  • Cooke, Philip, Mikel Gomez Uranga, and Goio Etxebarria. "Regional innovation systems: Institutional and organisational dimensions." Research policy 26.4-5 (1997): 475-491.
  • Zabala-Iturriagagoitia, Jon M., et al. "Regional innovation systems: how to assess performance." Regional Studies 41.5 (2007): 661-672.
  • D'Allura, Giorgia, Marco Galvagno, and Arabella Mocciaro Li Destri. "Regional innovation systems: a literature review." Business Systems Review 1.1 (2012): 139-156.
  • Tecnalia (Spain)
  • …

Innovation Model

An innovation model is a structured framework or representation that helps describe, explain, or guide the innovation process and its key components.

  1. Invention Genesis Models:
    1. The linear model of Innovation represents innovation as a linear process, moving from research through development to production and marketing.
    2. Innovation Ambidexterity Model: Encourages organizations to simultaneously explore new possibilities (exploration) and exploit existing competencies (exploitation) for sustained innovation.
    3. S-Curve Model: Describes the life cycle of a technology, showing how it starts slowly, accelerates, reaches maturity, and eventually declines.
    4. Technology Life Cycle: Describes the evolution of technology from its inception to maturity and eventual decline.
    5. Stage-Gate Model: Divides the innovation process into stages, with gates for evaluation and decision-making.
    6. Innovation Funnel Model: This represents the narrowing down of ideas as they progress through stages of screening, development, testing, and implementation.
    7. Kondratiev's (Long Waves) Theory proposes that technological innovations occur in long cycles and influence economic development.
  2. Technology Adoption:
    1. Technology Adoption Lifecycle: Describes the acceptance and adoption of innovations over time, from early adopters to laggards.
    2. Rogers' Diffusion of Innovations Theory: Classifies adopters of innovations into categories such as innovators, early adopters, early majority, late majority, and laggards.
  3. Collaboration Models:
    1. Open Innovation Model: Emphasizes the importance of external sources and collaboration in innovation.
    2. Innovation Ecosystem Model: Views innovation as a result of interactions among various stakeholders, including government, industry, academia, and startups.
    3. Triple Helix Model: Describes innovation as a collaborative process involving government, industry, and academia.
    4. Living Lab Model: Real-world environments where users and stakeholders co-create, test, and implement innovations.
    5. Open Source Model: Involves sharing source code and allowing anyone to contribute to software development or other projects.
    6. Technology Clusters Model: Focuses on developing innovation clusters and ecosystems that foster the growth of related technologies.
  4. Tipping Points Models:
    1. Radical and Incremental Innovation Model: Distinguishes between radical innovations that bring significant change and incremental innovations that make more minor improvements.
  5. Co-Evolution Model: Describes the mutual influence and adaptation between technology and society over time.
  6. NIS Models: National Innovation Systems (NIS) refer to the complex networks of institutions, organizations, and resources contributing to a country's innovation and technological development. Various models and frameworks have been proposed to analyze and understand national innovation systems.
    1. Freeman's Model of National Innovation Systems: Developed by Christopher Freeman, this model emphasizes the importance of institutions, policies, and the interactive learning process among different actors in fostering innovation.
    2. Lundvall's Innovation System Model: Developed by Bengt-Åke Lundvall, this model highlights the role of formal and informal institutions, including education systems, firms, and government, in shaping a country's innovation system.
    3. Porter's Diamond Model: Proposed by Michael Porter, this model identifies factors such as factor conditions, demand conditions, related and supporting industries, and firm strategy, structure, and rivalry that influence a nation's competitiveness and innovation.
    4. Nelson and Rosenberg's Model: Richard R. Nelson and Nathan Rosenberg contributed to the understanding of innovation systems by emphasizing the importance of knowledge diffusion, learning, and the role of institutions.
    5. Malerba's Innovation System Model: Giovanni Malerba's model focuses on the processes of innovation, technological trajectories, and the role of different actors in shaping the dynamics of innovation systems.
    6. Edquist's Systems of Innovation Approach: Developed by Charles Edquist, this approach considers the broader socio-economic context, institutions, and policies that influence innovation, emphasizing the importance of systemic interactions.
    7. Freeman and Perez's Techno-Economic Paradigms: Christopher Freeman and Carlota Perez introduced the concept of techno-economic paradigms, which represent long waves of technological and economic development within national innovation systems.
    8. Schumpeterian Innovation System Model: Based on Joseph Schumpeter's ideas, this model focuses on entrepreneurship, creative destruction, and the business cycle in shaping national innovation systems.
    9. Triple Helix Model: Proposed by Henry Etzkowitz and Loet Leydesdorff, this model emphasizes the collaboration and interaction among government, industry, and academia in fostering innovation.
    10. Innovation Ecosystem Model: This model views innovation as part of a broader ecosystem involving various stakeholders, including businesses, government, research institutions, and startups, working collaboratively to drive innovation.
    11. Clark and Feldman's Regional Innovation System Model: This model focuses on the role of regions in innovation, emphasizing the interactions between local institutions, industries, and knowledge flows.
    12. Mowery and Nelson's Institutional Analysis: Mowery and Nelson's work emphasizes the impact of institutions, policies, and historical factors on shaping national innovation systems.
  7. Absorbative Capacity Models:
    1. "Toward a Knowledge-Based Theory of the Firm" by Gary P. Pisano, Amy Shuen (1997)
    2. "Innovation and Learning: The Two Faces of R&D" by Ashish Arora and Andrea Fosfuri (2003)
    3. "Toward a Knowledge-Based Theory of the Firm" by Gary P. Pisano, Amy Shuen (1997)
  8. Innovation Diffusion Model
    1. "Diffusion of Innovations" by Everett M. Rogers (1962)
    2. Technology Fusion Model: Emphasizes the integration of different technologies to create new and more robust solutions.
  9. Productivity Models
    1. "Improving Research and Development Productivity in the Pharmaceutical Industry" by P. S. Jupe and R. D. Pickett (Nature Reviews Drug Discovery, 2006).
    2. "Measuring R&D efficiency in the OECD countries" by C. G. Edquist and R. Hommen (Technovation, 1999).
    3. Brown, Mark G., and Raynold A. Svenson. "Measuring R&D productivity." Research technology management 31.4 (1988): 11-15.

These models provide different perspectives on the components, interactions, and dynamics of national innovation systems, reflecting the interdisciplinary nature of innovation studies. Researchers and policymakers often draw on these models to analyze and design strategies for fostering innovation within a country.

Interaction Model

...

R&D Strategy

Indeed, here's a list of various research and development (R&D) strategies that organizations may adopt to drive innovation and growth:

  1. Basic Research Strategy: Focuses on fundamental scientific principles and knowledge without a specific application.
  2. Applied Research Strategy: Directs efforts toward solving specific problems or developing practical applications.
  3. Developmental Research Strategy: Involves refining and optimizing existing products or processes.
  4. Product Innovation Strategy: Emphasizes creating new or improved products to meet market demands.
  5. Process Innovation Strategy: Concentrates on enhancing or re-imagining the methods and procedures within the organization.
  6. Open Innovation Strategy: Collaborates with external partners, customers, and stakeholders to gather ideas and expertise.
  7. Incremental Innovation Strategy: Focuses on minor, continuous improvements to existing products or processes.
  8. Disruptive Innovation Strategy: Aims to introduce groundbreaking products or processes that disrupt existing markets.
  9. Platform Innovation Strategy: Focuses on developing a platform for creating various products or services.
  10. Collaborative R&D Strategy: Engages in partnerships or alliances with other organizations to share resources and knowledge.
  11. Market-Pull Strategy: Driven by market needs and demands, with R&D efforts aligned with customer requirements.
  12. Technology-Push Strategy: Driven by technological capabilities and innovations, seeking applications for developed technologies.
  13. Digital Transformation Strategy: Utilizes digital technologies to transform business processes, services, or products.
  14. Sustainability-focused R&D Strategy: Emphasizes environmentally friendly and sustainable practices in product development.
  15. User-Centric R&D Strategy: Involves users in the innovation process, considering their needs, preferences, and feedback.
  16. Blue Ocean Strategy: Seeks uncontested market space by creating innovative products or services.
  17. Global R&D Strategy: Expand R&D activities across international borders to leverage worldwide talent and markets.
  18. Agile R&D Strategy: Adopts agile methodologies to enhance flexibility and responsiveness in the innovation process.
  19. Outsourcing R&D Strategy: Involves contracting external entities for specific R&D tasks or projects.
  20. Intrapreneurship Strategy: Encourages employees to act as entrepreneurs within the organization, fostering innovation.
  21. Concortionm
  22. Reverse Engineering / Indginerazion R&D

Organizations often tailor their R&D strategies based on their industry, goals, and the competitive landscape. Additionally, systems may evolve in response to changing market dynamics and technological advancements.

Financing R&D

Research and Development (R&D) funding models vary based on the nature of the projects, the industry, and the organizations' goals. Here is a list of standard R&D funding models:

  1. Government Grants and Funding: Obtaining financial support from government agencies through grants, subsidies, and research contracts. This includes funding from national research foundations and governmental bodies dedicated to scientific and technological advancement.
  2. Private Sector Investment: Attracting investments from private companies, venture capitalists, or corporate investors interested in supporting R&D initiatives. This can involve equity investments, partnerships, or strategic collaborations.
  3. Public-Private Partnerships (PPPs): Collaborative ventures between public institutions (universities or research organizations) and private companies. PPPs leverage both sectors' resources, expertise, and funding to advance R&D projects.
  4. Industry Consortia: Forming alliances with multiple companies within the same industry to pool resources and fund joint R&D projects. Consortia are particularly common in sectors that require collaborative efforts.
  5. Venture Capital Funding: Raising capital from venture capital firms that fund early-stage and high-growth potential technology and innovation projects. Startups and innovative ventures often seek venture capital financing.
  6. Angel Investors: Individual investors, often with a background in the industry, who fund R&D projects. Angel investors may contribute their expertise and mentorship in addition to financial support.
  7. Research Foundations and Nonprofits: Receiving funding from research-focused foundations and nonprofit organizations dedicated to advancing knowledge and addressing specific challenges. These entities may fund academic and applied research.
  8. Crowdfunding: Raising funds from many individuals through online crowdfunding platforms. This model is prevalent for smaller projects or those with broad public appeal.
  9. Technology Incubators and Accelerators: Joining technology incubators or accelerators that provide funding, mentorship, and resources to startups and innovative projects. These programs often culminate in a demo day where startups pitch to potential investors.
  10. Corporate Innovation Programs: Large corporations may allocate internal funds for innovation and R&D activities. This can include dedicated budgets for research labs, innovation centers, and intrapreneurship programs.
  11. Strategic Alliances and Licensing: Forming strategic alliances with other companies or licensing intellectual property to generate revenue for R&D. This model involves sharing technology, expertise, and risks.
  12. Collaboration with Academic Institutions: Partnering with universities and research institutions to access their resources, expertise, and funding opportunities. This can involve joint research projects, grants, and industry-academic collaborations.
  13. Tax Incentives and Credits: Governments may offer tax incentives, credits, or deductions to encourage companies to invest in R&D. This can reduce the overall cost of R&D activities.
  14. Innovation Competitions and Prizes: Participating in innovation competitions or applying for prizes from industry associations, governments, or private organizations. Winning or placing in these competitions can provide funding and recognition.
  15. Philanthropic Contributions: Receiving contributions from charitable organizations and individuals interested in supporting research and innovation for social or environmental purposes.
  16. Development Bank
  17. Pioneer Bank (Bank that Invests in New Industries)
  18. China Government Guidance Fund
    1. Understanding Chinese Government Guidance Funds
  19. Innovation Vouchers: Providing small and medium-sized enterprises (SMEs) vouchers to access research and innovation services.
  20. …

Organizations often use a combination of these funding models to secure the resources needed for their R&D initiatives. The choice of a particular model depends on factors such as the nature of the research, the industry, and the organization's strategic goals.

Tax Credit: “Tax credit” refers to an amount of money that taxpayers can subtract directly from the taxes they owe. This is different from tax deductions, which lower the amount of an individual’s taxable income.

Firm R&D Incentive System

How to Incentivise Companies to do R&D?

…

  • Patent System
  • Share R&D Cost (Partial Grants):
    • 66% Government Funding
      • 33% Institutional Funding: Salaries, Facilities, …
      • 33% Competitive Funding
    • 34% Industry
  • …

References

R&D Grants

It’s key to group R&D projects; so one can apply and define policies correctly.

Sectorial Innovation System

  • Bigliardi, Barbara, et al. "Innovation models in food industry: A review of the literature." Journal of technology management & innovation 15.3 (2020): 97-107.
  • Intarakumnerd, Patarapong, Pun-arj Chairatana, and Rungroge Kamondetdacha. "Innovation system of the seafood industry in Thailand." Asian Journal of Technology Innovation 23.2 (2015): 271-287.
  • …

🔁 Key Ontological Functions

  • Production → Generation of new symbols, models, theories, and explanations
  • Validation → Establishment of truth, reliability, and validity via epistemic protocols
  • Reproduction → Training and credentialing of knowledge producers
  • Diffusion → Circulation of knowledge through networks and infrastructure
  • Boundary Management → Differentiating disciplines, legitimate knowledge, and "pseudoscience

Interaction

  • Diffusion
  • Commercialization
  • Knowledge Brokerage
  • Human Capital Formation

Ineraction Unit

Interaction Type Unit Role Description Category
Research Interaction Researcher Knowledge generator Produces new knowledge through inquiry, experimentation, and analysis. Primitive
Research Group Knowledge generator Collaborative unit generating new knowledge through coordinated research. Primitive
Laboratory Knowledge generator Physical space and system for empirical research and experimentation. Primitive
Principal Investigator Knowledge generator Leads research agendas and integrates intellectual and material resources. Primitive
Postdoctoral Fellow Knowledge generator Contributes advanced expertise to ongoing research initiatives. Primitive
Peer Communication Peer Reviewer Quality controller Critically evaluates knowledge outputs before formal validation. Derivative
Review Panel Quality controller Collective evaluation body for assessing validity and significance. Derivative
Scientific Community Quality controller Broad community engaged in informal validation and contestation of ideas. Derivative
Institutional Embedding University Structural enabler Provides infrastructure and legitimacy for long-term knowledge work. Derivative
Research Institute Structural enabler Specialized institution focused on knowledge production and analysis. Derivative
Think Tank Structural enabler Policy-oriented organization conducting applied research. Derivative
Department Structural enabler Sub-unit organizing research and teaching by discipline or focus. Derivative
Knowledge Translation Editor Knowledge refiner Selects, shapes, and prepares content for wider dissemination. Derivative
Curator Knowledge refiner Organizes and contextualizes knowledge artifacts for accessibility. Derivative
Science Communicator Knowledge refiner Bridges expert and lay audiences through narrative and explanation. Derivative
Content Strategist Knowledge refiner Plans knowledge formats, audiences, and delivery pathways. Derivative
Knowledge Circulation Journal Dissemination channel Publishes peer-reviewed knowledge outputs. Derivative
Conference Dissemination channel Facilitates face-to-face knowledge exchange and networking. Derivative
Preprint Server Dissemination channel Enables rapid, pre-validated knowledge sharing. Derivative
Newsletter Dissemination channel Regularly summarizes and distributes curated knowledge. Derivative
Indexing Platform Dissemination channel Structures and surfaces knowledge for discoverability and access. Derivative
Normative Control Ethics Committee Legitimacy filter Evaluates ethical implications of research practices. Derivative
Institutional Review Board Legitimacy filter Regulates research involving human subjects. Derivative
Standards Body Legitimacy filter Defines and enforces formal standards for data, methods, and ethics. Derivative
Cognitive Infrastructure Library Memory system Curates and makes accessible physical or digital knowledge resources. Derivative
Database Memory system Stores structured data for reuse and integration. Derivative
Repository Memory system Hosts and organizes digital artifacts such as publications or code. Derivative
Archive Memory system Preserves historical or sensitive knowledge materials. Derivative
Ontology Platform Memory system Structures conceptual domains for semantic interoperability. Derivative
Technological Mediation Simulation Platform Enabler of experimentation and observation Enables modeling, prediction, and virtual experimentation. Derivative
Laboratory Infrastructure Enabler of experimentation and observation Tools and space for empirical testing and observation. Derivative
Instrumentation System Enabler of experimentation and observation Provides precision tools for measurement and data collection. Derivative
HPC Cluster Enabler of experimentation and observation Supports large-scale computation and data-intensive workflows. Derivative
Knowledge Reception Learner Knowledge integrator Actively assimilates knowledge into personal or professional repertoire. Derivative
Student Knowledge integrator Engages in formal processes of knowledge acquisition and reproduction. Derivative
Apprentice Knowledge integrator Learns by doing under supervision in a domain of practice. Derivative
Classroom Knowledge integrator Physical or virtual space for structured learning activities. Derivative
Online Course Knowledge integrator Digitally delivered instructional content for autonomous or guided learning. Derivative
Funding Interface Grant Agency Resource allocator Provides competitive research funding. Derivative
Donor Organization Resource allocator Allocates funds according to strategic or philanthropic priorities. Derivative
Foundation Resource allocator Enables long-term or high-risk research through discretionary funding. Derivative
Venture Philanthropy Resource allocator Invests in high-impact research with measurable social returns. Derivative
Policy Feedback Government Demand shaper / Direction setter Sets national research agendas and funds public priorities. Derivative
Regulator Demand shaper / Direction setter Imposes constraints or incentives through rules and oversight. Derivative
Planning Ministry Demand shaper / Direction setter Aligns research with long-term national strategies. Derivative
Advisory Council Demand shaper / Direction setter Provides expert input to guide policy-research alignment. Derivative
Industrial Linkage R&D Department Application driver Integrates research insights into commercial products and processes. Derivative
Technology Transfer Office Application driver Facilitates movement of research into market and practice. Derivative
Innovation Lab Application driver Experiments with prototypes and applied research in real-world contexts. Derivative
Industrial Partner Application driver Co-develops and tests knowledge products for market or operations. Derivative

Economic Impact

  • , Graff Zivin, J., Li, D. & Sampat, B. (2019) ‘Public R&D and Private Patenting: Evidence from NIH Funding’, Review of Economic Studies 86(1): 117‑152.|
  • [2] Moretti, E., Steinwender, C. & Van Reenen, J. (2024) ‘The Economic Spillovers of Defence Research’, Review of Economics & Statistics 106(2): 235‑256.
  • [3] Babina, T., He, J., Howell, S. et al. (2023) ‘Cutting the Innovation Engine’, Quarterly Journal of Economics 138(4): 2201‑2260.
  • [4] Agrawal, A., Rosell, C. & Simcoe, T. (2020) ‘Tax Credits and Small‑Firm R&D: Evidence from Canada’, American Economic Journal: Economic Policy 12(3): 1‑30.
  • [5] Jacob, B. & Lefgren, L. (2011) ‘The Impact of Research Funding on Scientific Output’, Journal of Public Economics 95(9‑10): 1168‑1177.
  • [6] Kealey, T. (1996) The Economic Laws of Scientific Research. Springer.
  • [7] Kealey, T. & Ricketts, M. (2014) ‘Modelling Science as a Contribution Good’, Research Policy 43(6): 1014‑1024.
  • [8] Damrich, S., Kealey, T. & Ricketts, M. (2022) ‘Crowding In and Crowding Out within a Contribution‑Good Model of Research’, Research Policy 51(1): 104400.
  • [10] Romer, P. M. (1990) ‘Endogenous Technological Change’, Journal of Political Economy 98(5): S71‑S102.
  • [11] Aghion, P. & Howitt, P. (1992) ‘A Model of Growth through Creative Destruction’, Econometrica 60(2): 323‑351.
  • [12] Jones, C. I. & Williams, J. C. (1998) ‘Measuring the Social Return to R&D’, Quarterly Journal of Economics 113(4): 1119‑1135.
  • [13] Grossman, G. M. & Helpman, E. (1991) ‘Quality Ladders in the Theory of Growth’, Journal of Political Economy 99(3): 433‑449.\
  • [14] [9] Liang, J. & Mu, X. (2020) ‘Complementary Information and Learning Traps’, Quarterly Journal of Economics 135(4): 1929‑1984.
  • https://repositorio.uam.es/server/api/core/bitstreams/fb0cfa83-44f9-468b-864a-2e891191b1e6/content
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References

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  • Magro, Edurne, and James R. Wilson. "Complex innovation policy systems: Towards an evaluation mix." Research policy 42.9 (2013): 1647-1656.
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  • https://en.wikipedia.org/wiki/Innovation_system
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  • Alcorta, L., and W. Peres. “Innovation Systems and Technological Specialization in Latin America and the Caribbean.” Research Policy 26 (1998).
  • Service Innovation
  • The labor effects of R&D tax incentives: evidence from VC-backed startups
  • https://academic.oup.com/rof/article-abstract/28/5/1451/7730581
  • Firm Innovation
  • Innovation Economics
  • Yang, Siying, Shunyu Ma, and Jingjing Lu. "Can government venture capital guidance funds promote urban innovation? Evidence from China." Growth and Change 53.2 (2022): 753-770.
  • The Promise and Pitfalls of Government Guidance Funds in China - Yifan Wei & Yuen Yuen
  • KfW - German Development Bank
  • Intarakumnerd, Patarapong, and Pattarawan Charumilin. "Japanese Financing Policies for Innovation Since the 1990s." STI Policy Review 4.2 (2013): 55-73.
  • Pioneers Banks (Give Money to People Diversification the Economical Structure)
  • Kobayashi, Yohei. "Effect of R&D tax credits for SMEs in Japan: a microeconometric analysis focused on liquidity constraints." Small Business Economics 42 (2014): 311-327.
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  • An Innovation System That Works
  • Technology Policy for Industrialization: An Integrative Framework and Korea's Experience - Linsu Kim
  • Management Behind Industrialization: Readings in Korean Business - Tong-gi Kim
  • Bae, Yong-Ho, et al. "Case study on technological innovation of Korean firms." 연구보고 (2002): 1-189.
  • Huang, Ya-Ling, and Patarapong Intarakumnerd. "Alternative technological learning paths of Taiwanese firms." Asian journal of technology innovation 27.3 (2019): 301-314.
  • Intarakumnerd, Patarapong, and Meng-Chun Liu. "Industrial technology upgrading and innovation policies: A comparison of Taiwan and Thailand." Emerging States at Crossroads (2019): 119-143.
  • Intarakumnerd, Patarapong. "Technological upgrading and challenges in the Thai automotive industry." Journal of Southeast Asian Economies 38.2 (2021): 207-222.
  • Intarakumnerd, Patarapong, and Peera Charoenporn. "The Roles of IPR Regime on Thailand’s Technological Catching Up." Intellectual Property Rights, Development, and Catchup: An International Comparative Study (2010): 378-411.
  • Intarakumnerd, Patarapong, Pun-arj Chairatana, and Tipawan Tangchitpiboon. "National innovation system in less successful developing countries: the case of Thailand." Research policy 31.8-9 (2002): 1445-1457.
  • Intarakumnerd, P., and P. Brimble. "Thailand at the crossroads: The dynamics of Thailand’s national innovation system." Science, Technology Policy And The Diffusion Of Knowledge-Understanding the Dynamics of Innovation Systems in the Asia Pacific. Cheltenham: Edward Elgar (2007).
  • Pittayasophon, Siriporn, and Patarapong Intarakumnerd. "University-industry collaboration in Thailand: firm characteristics, collaboration modes and outcomes." Institutions and Economies (2016): 37-59.
  • Intarakumnerd, Patarapong. "Industrial innovation in Thailand: The electronics, automotive and seafood sectors." Southeast Asia beyond Crises and Traps: Economic Growth and Upgrading (2017): 167-192.
  • Li, Xiaoli, and Hongqi Wang. "An exploratory study of how latecomers transform strategic path in catch-up cycle." Sustainability 13.9 (2021): 4929.
  • Intarakumnerd, Patarapong. Mismanaging innovation systems: Thailand and the middle-income trap. Routledge, 2017.
  • Intarakumnerd, Patarapong. "Thailand’s national innovation system in transition." Asia’s Innovation Systems in Transition, Cheltenham, UK and Northampton, MA: Edward Elgar (2006): 100-122.
  • Plan Estatal de Investigación Científica y Técnica y de Innovación (PEICTI)
  • Technology innovation and entrepreneurial state: the development of China's high-speed rail industry - by Zhe Sun
  • Intarakumnerd, Patarapong, and Cristina Chaminade. "Innovation policies in Thailand: towards a system of innovation approach?." Asia Pacific Business Review 17.02 (2011): 241-256.
  • Intarakumnerd, Patarapong, and Akira Goto. "Technology and Innovation Policies for SMEs in East Asia." SMEs (2016): 24.