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Interactions Academiy-Firms - Caso do México
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Transcript of Interactions Academiy-Firms - Caso do México
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Dr Gabriela Dutrénit
July 2009July 2009
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1. Issues under discussion about academy-
industry linkages
2. Data
3. Evidence
4. Final reflexions
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Higher Education Institutes (HEIs) & Public Research Centres (PRCs) can play a key role in the innovation process as producers and transmitters of knowledge
Why do academy and firms interact? Which are the main knowledge flows? Which are the benefits from interaction?
Differences by size, sector, ownership … Research on advanced countries:
• Focused on the commercialization/transfer of knowledge (patents, licensing, spin-offs, collaborative research projects with industrial firms)
• Limited exploration of the process of knowledge transfer through other channels (personnel mobility, informal contacts, consulting relationships, and human resources)
Research on developing countries:• Mostly reproduce the same research questions
A broad range of issues, levels of analysis, and methodologies
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Approach to the linkages:• Either from the industry or the academy• Some few approach both agents (Carayol,
2004; Bekkers & Bodas Freitas, 2008; Bittencourt et al, 2008; Giuliani & Arza, 2008)
Methodologies:• National Innovation Surveys• Secondary statistics• Case studies
Level of analysis• Individual (firms managers or researchers)• Organisational (firms or HEI/PRC)
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Higher Education Institutes & Public Research Centres (HEI/PRC) in developing countries:• Might be a vehicle through which
technologies and organizational forms of advanced countries can be absorbed locally
• Have the potential to generate knowledge that in close interaction with local firms can contribute to the generation of new products and processes
We need to better understand the perception of both agents
Developing countries….
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This presentation is about …..
Academy-industry interactions from both perspectives using individual level data R&D and product development firms managers Academic researchers
• Particularly, differences in the nature of the interactions across 3 stages of the linking process:
main reasons to interact (drivers) knowledge flows during the interaction results derived from interaction (benefits)
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The data
Firms survey
Researchers survey
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Descriptive statistics: firms survey
Two groups of firms:•Firms who benefited from public funds to foster R&D and innovation activities, such as the R&D fiscal incentives program and competitive funds to foster innovation from CONACYT, •A group of firms that do not receive public funds (control group)
Questionnaire directed to R&D and product development managers of firms
Sample 1200
Received questionnaires 391
% response 32.6%
Complete questionnaires 387
manufacture 335
services 52
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Descriptive statistics: firms survey
R&D performers (formal and continuous)
67.4%
R&D performers (informal)
24.3%
Use of public funds 54.0%
Collaborative firms 57%
Non-collaborative firms 43%
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Descriptive statistics: firms survey
R&D performers (formal and continuous)
67.4%
R&D performers (informal)
24.3%
Use of public funds 54.0%
Collaborative firms 57%
Non-collaborative firms 43%
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R&D activities and size. Manufacture
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Novelty of the innovations
Sample: 341 innovative firms
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Modes of interaction and size
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Modes of interaction and institutions
For all firms (average)
•HEIs: HR and training, R&D less
•PRCs: information, training and R&D
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Modes of interaction, institution and size (manufacture)
Difference by firm size:•information and training in the small firms•joint and contract research (knowledge absorption) in large and in micro (special group)
For all firms size, the most important modes are:•Human resources formation (most important)•training
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Significant differences, firms with fiscal benefits tend to have more interaction
Different linkages profile, but again human resources and training are common for all the firms
Modes of interaction and fiscal benefits for R&D
Innovation policy ¡not bad!
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Descriptive statistics: academic researchers survey
Two groups of researchers:•Firms who benefited from public funds to foster R&D and innovation activities, such as the R&D fiscal incentives program and competitive funds to foster innovation from CONACYT, •A group of firms that do not receive public funds (control group)
Questionnaire directed to R&D and product development managers of firms
Sample 5880
Received questionnaires 477
% response 8%
Completed questionnaires 461
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Descriptive statistics: researchers survey
Collaborators per knowledge fields
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Descriptive statistics: researchers survey
Modes of collaboration with SMEs (average of importance)
Modes of collaboration with large firms (average of importance)
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• Descriptive statistics
• Multivariate analysis multivariate to build three factors for firms (main reasons to interact, knowledge flows, and benefits from interaction) and two factors for academy (knowledge flows and benefits from interaction)
• Two regression models to determine the effects of the drivers of interaction, the main knowledge flows and the main benefits of interaction
PROBIT regression model for firms: Prob[COLL=1] = ƒ(NPDI, NPSI, R&D, F1, F2, F3) PROBIT regression model for academics: Prob[COLL=1] = ƒ(TO, RA, IEB, PEB, F4, F5) descriptive statistics
Methods
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Stage 1: Why universities/PRC and firms interact?
Firms´ main reasons for interaction
Sample: 172 collaborative/innovative firms
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Firms´ and academic researchers barriers169 non-collaborative firms 149 non-collaborative researchers
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Stage 2: Which is the main knowledge flows from academy-industry interactions?
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Impact of different collaborative results on firms´ innovation activities (Collaborative firms)Main benefits for academic researchers (collaborative researchers)
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Firms’ models
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• High correlation between product and process innovation and collaboration with academic researchers.
• R&D expenditures do not imply a high level of collaboration with academy.
• Industry sector does not result an important determinant for collaboration
• Knowledge flows and benefits from collaboration: positive effect on collaboration with academy.
• HEIs: human resources and collaborative R&D are the most important types of knowledge flows.
• PRCs: training is the most important, followed by networking and collaborative research. Benefits: use of laboratories and metrology instruments, and development of new techniques and instruments
• These two types of benefits from interaction are associated with the firms´ interest to increase product quality to satisfy market and customers´ demands.
Firms´ regression model:
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• The type of organization is not an important determinant for collaboration
• The type of research activity has an important effect on collaboration
• researchers that perform applied research and technology development collaborate more with firms than researchers that perform basic research.
• Economic benefits: not important determinants for collaboration
• Personal economic benefits: stronger impact on collaboration than institutional economic benefits.
• Knowledge flows from academy to industry: not a strong impact on collaboration
• Benefits: positive impact on collaboration, publications as the most important
Academic researchers’ regression model:
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• Firms seem to largely have basic/intermediate TC and limited absorptive capacities:• Reasons (human resources, test products, technological
advise)• Barriers (they have enough TC)• Main knowledge flows (human resources, information
and less R&D)• Benefits (use of installation and metrology)
• Firms that invest more in R&D and are product and process innovators interact more with academy, but still limited absorptive capacities
• There are two main drivers to interact: • activities that increase firms’ capabilities (mostly related
to identifying and hiring human resources)• activities that complement firms’ capabilities (mostly
related to getting technological advice to solve production problems, testing products/processes, and using of the university/PRC´s installations)
• Different perceptions about the role of HEIs and PRCs• Firms perceive that universities above all contribute with
human resources and PRC are valuable as they diffuse information. Collaborative R&D is less important from firms´ perspective.
• Academic researchers perceive that knowledge creation plays a more important role
Conclusion