Exploring the Miracle: a Pragmatic Approach to Evaluating Collaborative Dynamics in Clusters

Emily Wise, Research Fellow Lund Univer-sity, Sweden

Parallel Session 1.2: Analysis of Cluster Models and Cluster Ecosystems

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

How to capture and evaluate

collaborative dynamics?How to evidence broader regional

socio-economic impacts?

Which data and indicators?How to benchmark and

learn from others?What is the role and effect of

cluster management?

In particular, how can we better understand

the ”miracle” in the middle?

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

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)

Alternative approaches to monitoring and evaluating collaborative dynamics

StarDust WP7 Question Set #2

Stimulation andAcquisition of

relevant research and development

L5 FUTURE FOCUS LOOP

Performance of individual firms

Overall performance of all firms in the

zone

I ntensity of diff erentiated

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 I NTER-FI RM RI VALRY LOOP

L2 I NTER-FI RM CO-OPERATI ONLOOP

Global competition and external

market pressure

Type of cultural context

L3 COLLABORATI VEADVANTAGE

LOOP L4VENTUREATTRACTI VENESS

LOOP

The Principal Dynamic Loops

Competitive power of cluster

Social Network Analysis

Firm-level Surveys

Cluster-level Interviews/Surveys

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

institution – 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)

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

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