The document explores the effects of global and local collaboration on innovation, focusing on findings from the Basque Country in Spain. It highlights that global partnerships drive technological innovations, while local collaborations tend to produce incremental and non-technological innovations by leveraging tacit knowledge. The analysis includes empirical data from a firm-level panel spanning 2005 to 2011, emphasizing the significance of both types of collaboration for innovation outcomes.

1. Divergent Impacts of Global
and Local Cooperation on
Innovation : Key Insights
from Spain
EURAM Conference
5th June 2014
Henar Alcalde
M.D. Parrilli

2. Index
1. Introduction
2. Research question
3. Hypotheses
4. Sample
5. Results
6. Conclusion

3. Introduction
• The literature on innovation management has been
largely concerned about external knowledge flows
and innovation outcomes (Kline and Rosenberg,
1986; Teece and Pisano, 1997; Teece, 2007).
• In the current era of globalization, firms are
involved in a Schumpeterian competition:
– rapidly evolving industries
– where competitive capabilities are transitory
– opportunities are quickly closed by competitors

4. Introduction
• Firms must obtain relevant knowledge flows in
order to develop new and effective innovations
with continuity.
• Complementarily, firms must balance their
capacity to develop know-how with the ability to
introduce new products in the market.
– This evidence suggests the importance of exploring how
collaboration practices mediate in such a process.

5. Introduction
• Understanding the impact of collaboration practices
remains an important and under-researched topic
– what aspects of OI activities make this concept effective
according to the selection of partners
– what type of networks favor innovation
• In this paper we want to contribute to this debate
by providing evidence of the types of agents that
most effectively help firms to develop different
types of innovation.

6. Research Question
• We add new insights in three relevant areas of
business innovation studies. Our main
contributions arise from:
1. Impact on a complete set of innovation outputs (i.e.
product, process, organization and commercial) of both
scientific and market types of collaboration (within and
outside the supply chain).
2. Specific attention to the geographical dimension (regional
vs extra -regional) of the different partnerships
3. Panel data from the Basque Country (Spain) from 2005
to 2011. This enables us to move beyond previous
studies on cross-sectional data, considering the economic
recession.

7. Hypotheses 1: Scientific
collaboration
• The scientific-type of interaction does not usually
focus on commercial exploitation, but on
exploring new technological opportunities.
• Scientific knowledge resources should be unique,
relevant and based on new basic knowledge.
• The access to this type of sources entails high
expenditures related to transaction costs,
opportunity costs, and management time costs.

8. Hypotheses 1: Scientific
collaboration
• Scientific collaboration at REGIONAL
LEVEL is likely to entail well-known
scientific resources and homogeneous
educational patterns.
• This situation is likely to limit the novelty
of the knowledge-based interaction.
– Homogeneity of the codified and scientific
knowledge bases.
– Constrains the firm ability to develop
technological innovations.
– Firms are more likely to exploit traditional
knowledge resources by improving internal
organizational management.

9. Hypotheses 1: Scientific
collaboration
• Scientific collaboration at INTER-
REGIONAL LEVEL might be associated with
diverse scientific sources
• Provide heterogeneous sources of
advanced codified knowledge
– More likely to promote technological
innovation.
– Codified nature of scientific knowledge is not
context-specific and does not require personal
interaction and face-to-face contact.

10. Hypotheses 1: Scientific
collaboration
• H1a: “Distance in scientific
collaboration induces technological
innovation”.
• H1b: “Proximity in scientific
collaboration does not induce
technological innovation, but it might
support non-technological types of
innovation”.

11. Hypotheses 2: Market-based
collaboration (within SC)
• Partners face common practical problems
and experiences
• Directly related to problem-solving
• Exploit their current knowledge pool and
new incremental process and product
solutions
• Specific contextual knowledge and know-
how

12. Hypotheses 2: Market-based
collaboration (within SC)
• Market collaboration within the SC at
REGIONAL LEVEL might be associated to
homogeneous ‘tacit’ knowledge that:
– Would lead to competence traps, lack of
novel sources and over-specialization lock-
ins.
– Myopia by restricting their innovation
output to current technological
combinations
– Importance of tacit knowledge flows (e.g.
learning-by-doing and learning-by-using)

13. Hypotheses 2: Market-based
collaboration (within SC)
• Market collaboration within the SC at
INTER-REGIONAL LEVEL might be
associated to dissimilar knowledge
– May maximize the returns on specialization
and complementary spillovers in different
markets
– Capture knowledge and information
spillovers from different markets
– Overcome intrinsic lock-in risks
– Generate a significant effect on
technological innovations.

14. Hypotheses 2: Market-based
collaboration (within SC)
• H2a: “Distance in supply-chain
collaboration mainly induces
technological innovation”
• H2b: “Proximity in supply-chain
collaboration does not induce
technological innovation, but it might
induce non-technological innovation”

15. Hypotheses 3: Market-based
collaboration (outside SC)
• Market collaboration with competitors focus
on carrying out basic research and establish
standards
• Knowledge spillovers are more an unintended
consequence of the relationship
• Fear of helping rivals and the lack of trust are
the main barriers
• Common values and problem sharing is not
enough to encourage the exchange of specific
knowledge and information inputs.

16. Hypotheses 3: Market-based
collaboration (outside SC)
• Market collaboration with competitors at
REGIONAL LEVEL might be associated to
– Generate trust among competitors, to
identify common goals
– Informal interactions based on face-to-face
contacts
– Implies repeated interactions around the
current knowledge patterns
– May lead to overspecialization

17. Hypotheses 3: Market-based
collaboration (outside SC)
• Market collaboration with competitors at
INTER-REGIONAL LEVEL might be
associated to
– Fail in generating trustful relationships
– Need to invest in informal interactions
based on face-to-face contacts
– Hinder the transfer of tacit knowledge with
the subsequent negative impact on
innovation.

18. Hypotheses 3: Market-based
collaboration (outside SC)
• H3a: “Proximity in collaboration with
competitors induces non-technological
innovation”
• H3b: “Distance in collaboration with
competitors does not induce
technological innovation”

19. Sample
– The source of the empirical analysis is
the Innovation Survey (CIS).
– Firm-level panel of data compiled by
Eustat (Basque Institute of Statistics)
– Period from 2005 to 2011
– The panel contains 1431firms during the
7-year period

20. Results

21. Conclusion
– Global partnerships, both scientific and supply
chain-based, are likely to be the most relevant
drivers of disruptive innovation (technological
innovation)
– Local and regional collaborations are more
likely to generate a higher impact on
incremental/non-technological innovation.
– The higher local/regional impact on
incremental process and organizational and
commercial innovation rely more on tacit
knowledge flows that benefit from learning-by-
doing and learning-by-interacting.