This document discusses evaluating the human element in clusters. It proposes that the human element includes dimensions like engagement, internal collaboration, and external interaction. It suggests measuring these dimensions at the firm and cluster level through surveys and self-assessment tools. Measuring the human element can provide evidence of impacts and the relationship between the human element and economic performance. Next steps include countries collecting data on the human element and discussing results to advance frameworks for evaluating and benchmarking the human element internationally.

1. Evaluating the human element in clusters
Emily Wise
Parallel 4.1 New Cluster Policies and Cluster Evaluation
12 November 2014

2. EVALUATING THE HUMAN ELEMENT IN CLUSTERS
EMILY WISE, PHD MADELINE SMITH
RESEARCH FELLOWAND CONSULTANT HEAD OF STRATEGY, INSTITUTE OF DESIGN INNOVATION
LUND UNIVERSITY AND IEC GLASGOW SCHOOL OF ART

3. CLUSTER POLICY ADDRESSES SYSTEM
(OR COORDINATION) FAILURES
The stated objective of cluster programmes (examples):
• Denmark: The objectives innovation networks are to strengthen
public-private collaboration and knowledge transfer between
public universities and private companies on research and
innovation, thus promoting knowledge-based growth in business
and industry.
• France: The goal of competitiveness clusters is to build on
synergies and innovative, collaborative projects in order to give
partner firms the chance to become first in their fields, both in
France and abroad.
• Germany: The Leading-Edge Cluster competition supports high-performance
clusters formed by business and science that enter
into strategic partnerships which boost Germany's innovative
strengths and economic success.
• Sweden: VINNVÄXT’s mission is to promote sustainable regional
growth by developing internationally competitive research and
innovation milieus in specific growth fields. Effective regional
innovation systems speed up industrial and business renewal
towards innovation-led sustainable growth.
Clusters address seven ”innovation gaps”
Source: Lindqvist, Ketels and Sölvell (2013), The Cluster
Initiative Greenbook 2.0

4. A GENERALLY ACCEPTED EFFECT
LOGIC FOR CLUSTERS?
Norwegian Innovation Clusters – programme effect logic
TACTICS handbook on impact evaluation of cluster-based policies
Evaluation Framework for US Regional Innovation Clusters

5. THIS LOGIC HIGHLIGHTS THE ROLE OF
COLLABORATION IN DRIVING
LONGER-TERM ECONOMIC EFFECTS
Input/Resources Activities Results/Outcomes Effects
...contribute to increased interactive
learning and collaborative R&I
projects
...which contributes to increased
innovation, international
attractiveness, productivity and
growth
Activities to strengthen or
upgrade a cluster/ innovation
environment...
3-10 years >10 years

6. NEED TO EVALUATE IMPACT ON
BOTH SYSTEM COORDINATION AND
ECONOMIC PERFORMANCE
Data/Indicators:
? Number/type/strength of engagement of actors
in cluster initiative
? Number/type/strength of
alliances/collaborations among cluster
participants
? Number/type/strength of
alliances/collaborations with related actors
outside the cluster
Methods of data collection/analysis:
- Surveys
- Interviews
- Social network analysis
Data/Indicators:
- Number/quality of publications and patents
(and other IP)
- Number of new products/processes/ services
- Number of new firms/firm growth
- Level of investments attracted (VC, FDI)
- Firm-level revenue/growth; export/growth;
employment/growth; and wages/growth
Methods of data collection:
- Surveys
- Interviews
- Business registers/national statistics
Impacts on System Coordination (aka the human element)
(engagement, linkages/interaction, collaboration)
Impacts on Economic Performance
(intermediate outcomes and productivity)
Note: see Giuliani et al. (2014) for additional elaboration on the ”two-stage” evaluation process

7. EVALUATING IMPACT OF THE HUMAN
ELEMENT MORE OF A “BLACK BOX”
CURRENT ISSUES
• Perspectives on what is included
in the human element vary
• Types of data collected and from
whom (cluster manager or firms)
differ
• Little possibility to benchmark
and learn across geographies
THE TASK AFTER BELFAST
• Shared perspective on the key
dimensions of “the human
element”
• Consensus on what should (and
could) be measured
• A systematic and easily-implementable
approach to data
collection

8. WHAT IS THE HUMAN ELEMENT?

9. KEY DIMENSIONS OF THE HUMAN
ELEMENT
DIMENSIONS
• Engagement/mobilisation
• Internal collaboration
• External interaction
CHARACTERISTICS (EXAMPLES)
• Key actors are engaged and guide the strategic
direction of activities
• A high percentage of cluster stakeholders
participate in activities
• There is regular interaction and dynamic
collaborative links between actors within the cluster
• There are perceived benefits and commitment to
pursuing joint activities (addressing common goals)
• The cluster has a clear value proposition and
positions itself in relation to a broader market
• The cluster proactively seeks ways to strengthen its
value proposition through external linkages

10. ADDITIONAL DIMENSIONS OF THE
HUMAN ELEMENT (?)
DIMENSIONS
• Orchestration
• Strategic orientation
CHARACTERISTICS (EXAMPLES)
• Leadership/management is familiar with the various
actors in the cluster
• There is a proactive attitude and effective approach
to identifying and acting on opportunities
• Leadership/management is knowledgeable of the
business area and its market
• Longer-term plans for cluster development are
anchored with the local/regional government

11. HOW TO MEASURE – FIRM LEVEL
Target Group Data/indicators Method of data collection
Core Cluster
Firms
• Strength of engagement in cluster
initiative
• Type of activity (networking, workshop,
project)
• Type of engagement (time, financial
investment)
• New cooperative activities with
cluster participants
• Type of partner (company, university,
research organisation, investor)
• Type of activity (networking, workshop,
project)
• New cooperative activities with
actors outside of the cluster
• Type of partner (company in same or
different sector, university, research
organisation, investor)
• Type of activity (networking, workshop,
project)
• Standard survey
questions
• Regular reporting
intervals

12. HOW TO MEASURE – CLUSTER
LEVEL
Target Group Data/indicators Method of data collection
Cluster
manager
Description of characteristics at
(four) levels of development
• Engagement/mobilisation
• Internal collaboration
• External interaction
• Orchestration
• Strategic orientation
• Self-assessment tool
rating perceived level of
development in relation
to standard descriptions
• Regular reporting
intervals

13. WHAT ARE THE STRENGTHS AND
BENEFITS OF THIS APPROACH?
• Evaluation of the human element
• Is an integral part of the ”generally accepted” effect logic for cluster policy
• Provides evidence of the impacts we already see (and explain qualitatively)
• Can be used to explain results (or lack of results)
• Can be used to examine the relationship between ”the human element” and
economic performance
• The proposal from members of the TCI working group
• Establishes an initial set of key dimensions
• Suggests a simple approach for measuring these dimensions at firm and cluster
level, which could be easily integrated into (existing) regular assessments
• Sets the stage for international peer learning, benchmarking and more in-depth
analysis

14. NEXT STEPS
• Innovation Norway and VINNOVA will pursue data collection on the
human element as part of their existing monitoring/evaluation
processes...others interested?
• Discussion of results from these national efforts in forthcoming
meeting of TCI evaluation working group
• As a core group develops, could pursue:
• Common portals for cluster-level self-assessments
• Approaches for sharing/benchmarking firm-level data
• Further joint development of frameworks – including analysis of relation between
human element and economic performance
• International peer learning and benchmarking