This document proposes a pragmatic approach to evaluating collaborative dynamics in clusters through monitoring key dimensions like network ties, engagement, and shared vision. It suggests indicators for each dimension that could be measured through firm surveys. These include things like new linkages formed, quality of partnerships, commitment levels, and perceptions of common goals. Testing this approach across multiple regions could help establish standard evaluation methods and provide insights into better understanding cluster dynamics.

1. Exploring the Miracle:
a Pragmatic Approach to Evaluating
Collaborative Dynamics in Clusters
Emily Wise, Research Fellow Lund
University, Sweden
Parallel Session 1.2: Analysis of Cluster Models and Cluster Ecosystems

2. A ”generally accepted” effect logic for cluster
programmes, but still lots of evaluation
challenges
...contribute to increased interactive
learning and collaborative research
and innovation projects
...which contributes to increased
innovation, international attractive-
ness, productivity and growth
Activities to
strengthen or
upgrade a
cluster/
innovation
environment...
Input/Resources Activities Results/Outcomes Effects
3-10 years >10 years
Structural
capital
(tangibles)
Social capital
(intangibles)
Results/Outcomes
3-10 years

3. In particular, how can we better understand
the ”miracle” in the middle?

4. Previous academic work provides an overview of the
importance and characteristics of collaborative
dynamics
• Saxenian (1994) points out the importance of an ”open management
culture” and ”repeated interaction and mutual trust” to foster collective
learning and collaboration
• Gordon and McCann (2000) introduce the ”social network model” of
clusters where firms engage in ”more risky cooperation without fear of
opportunism” in order to pursue ”mutually beneficial goals”
• Smith and Brown (2009) propose a five-stage conceptual model that
helps explain how a cluster develops, based on changes in company
behaviour and company interaction at different stages of development
• Giuliani et al. (2013) highlight that a ”significant element of clusters is the
development of non-market-related networks…that are expected to
improve economic coordination and reduce transaction costs”
• Aragón et al. (2014) highlight the interaction between structural,
relational and cognitive dimensions of social capital which drive networking
behaviour and affect network outcomes

5. So what are the dimensions of collaborative dynamics
we think are important to monitor and evaluate?
Collaborative Dynamics can
be characterized by...
• Increased interaction and knowledge sharing
between different types of actors
• Increased trust and deeper types of
collaboration (from information and knowledge
sharing to strategic collaboration)
• Participating actors’ perception of benefits
from pursuing joint activities (addressing
common goals)
• Participating actors’ commitment to collective
action (without guaranteed reciprocity)
• Participating actors’ perception and support of
a shared rationale or value proposition for
collective action
• Participating actors’ perception and support of
a shared identity
Proposed Dimensions
• Linkages/network ties –
both internal and external
(structural)
• Engagement/trust/
commitment (relational)
• Shared vision and identity
(cognitive)

6. Alternative approaches to monitoring and
evaluating collaborative dynamics
StarDust WP7 Question Set
#2
Stimulation and
Acquisition of
relevant
research and
development
L5 FUTURE FOCUS
LOOP
Performance of
individual firms
Overall
performance of
all firms in the
zone
Intensity of
differentiated
competitive
performance
Motivation for
competitive
innovation
Degree of
enhancement of
competitive
innovation
Competitive
level of
platform for
innovation
Sharing of
critical
sectoral
knowledge
Extent of
collaborative
initiatives
Extent of
shared response
to common
challenges
L1 INTER-FIRM RIVALRY LOOP
L2 INTER-FIRM CO-OPERATION
LOOP
Global competition
and external
market pressure
Type of cultural
context
L3 COLLABORATIVE
ADVANTAGE
LOOP L4 VENTURE
ATTRACTIVENESS
LOOP
The Principal Dynamic Loops
Competitive
power of
cluster
Social Network Analysis
Firm-level Surveys
Cluster-level Interviews/Surveys

7. A proposed pragmatic approach (in ”20
questions or less”)
Dimensions
• Linkages/network ties –
both internal and external
(structural)
• Engagement/trust/
commitment (relational)
• Shared vision and identity
(cognitive)
Indicators
• quantity of new linkages
• type/proximity of partner (company or knowledge in
stitution – within or outside the cluster)
• quality of linkage (contact/info, project, commercial,
strategic)
• type of engagement (e.g. participated in joint activities
that could bring value to the cluster even if the activities were
not a company priority)
• level of (company) commitment/reciprocity
(e.g. provided support with resolution of issues raised by
others that could contribute to the improvement of the
competitiveness of the group)
• common vision (e.g. perception that the identification of
challenges and strategic objectives coincides with other
members of the cluster)
• collective action (e.g. perception that there is always
someone within the cluster who can help, when have a problem that
can’t be resolved in isolation)

8. Conclusions
• Interaction, knowledge sharing and collaborative
action are core drivers of increased innovation and
productivity (the aim of cluster programmes)
• Existing approaches to monitoring and evaluation
of collaborative dynamics may not include all
dimensions, or are considered ”too bulky” for
regular implementation
• A common, pragmatic approach (developed by
members of the TCI working group) could be used
as part of regular reporting processes and foster
international policy learning

9. Next steps (a wish list)
• Establish a ”coalition of the willing” (a group of regions/
countries who want to work together to develop
approaches to better understand cluster dynamics)
• Agree on a limited list of questions to be incorporated in
firm-level (and cluster-level) surveys conducted as part of
regular reporting/monitoring processes
• Test and work together to establish ’standard’ methods of
data collection and analysis – and compare results