Geographical characteristics for Living labs success
in the search for sustainable transition
Smart grid experiments, living labs and guides to success
University of Utrecht
Department of Geosciences
Author
Supervisor
Words:
Robin Teeken (3978753)
Dr. Simona Negro
5500
Abstract
This paper aims to empirically test geographical characteristics that
contribute to the success of Living Labs. Literature from the regional
innovation system and proximity advantages prescribed factors which
contributed to the innovation processes, but were not related to Living
Labs in the smart grid industry. Living Labs are important for the transition
to another socio-technical regime. In the search for sustainability the smart
grid industry is on the frontier to change the socio-technical regime. With
the use of semi-structured interview success factors are empirically tested
for their presence and searched for other success factors. When the success
factors are identified they contribute to the academic literature and also to
the society, since project leaders are aware of success factors which should
stimulate the rate of success. Ultimately new factors have been identified
such as infrastructures and work ethics and barriers to success as deadlines.
Moreover identification is made between different type of Living Labs and
their influence is tested on the success different success factors.
Preface
This paper is a part of the promotion research by Harm van den Heiligenberg. This research is
conducted by multiple bachelor students each looking for success factors and sharing the
same questionnaire. Eventually within the smart grid group data was exchanged in the point
of rankings on the different geographical factors. Between peers a total of 29 cases have been
studied including 8 of my own.
The results of this and other smart grid based papers will be shared with Harm van den
Heiligenberg, including audio files of the interviews (with the permission of the interviewees)
and reports based upon the interview.
Table of Contents
Abstract ...................................................................................................................................................... 2
Preface ........................................................................................................................................................ 2
1.
Introduction ........................................................................................................................................ 4
2.
Theoretical framework ....................................................................................................................... 5
2.1.
Importance of niches ................................................................................................................................................... 5
2.2.
Geographical context and proximity advantages......................................................................................................... 6
2.2.1.
Vision and institutional....................................................................................................... 6
2.2.2.
Network, culture and learning ............................................................................................ 6
2.2.3.
Demographics ..................................................................................................................... 7
2.3.
Types of LL’s.............................................................................................................................................................. 7
2.4. Conceptual model ............................................................................................................................... 7
3.
Methodology ...................................................................................................................................... 8
3.1.
Research method and data collection .......................................................................................................................... 8
3.2.
Sampling ..................................................................................................................................................................... 8
3.3.
Research quality .......................................................................................................................................................... 8
3.4.
Data analysis ............................................................................................................................................................... 8
4.
Operationalization .............................................................................................................................. 9
5.
Results ................................................................................................................................................ 9
5.1.
Success factors .......................................................................................................................................................... 10
5.1.1.
Vision Factors (4,11) ........................................................................................................ 10
5.1.2.
Regional Network factors (3,79) ...................................................................................... 10
5.1.3.
Learning factors (4,32) ..................................................................................................... 10
5.1.4.
Cultural factors (3,62) ...................................................................................................... 11
5.1.5.
Governmental factors (3,86) ............................................................................................. 11
5.1.6.
Demographic factors (3,18) .............................................................................................. 11
5.2.
Barriers ..................................................................................................................................................................... 11
5.3.
Types of LL’s............................................................................................................................................................ 11
5.3.1.
Urban and Rural factors (Graph 2) ................................................................................... 12
5.3.2.
Guided and Grassroots factors (Graph 3) ......................................................................... 12
5.3.3.
Technical and Social innovation (Graph 4) ...................................................................... 14
6.
Discussion ........................................................................................................................................ 14
7.
Conclusion ........................................................................................................................................ 14
8.
References ........................................................................................................................................ 15
9.
Acknowledgement ............................................................................................................................ 16
10. Appendix .......................................................................................................................................... 17
A: Interview............................................................................................................................................................................. 17
B: Results ................................................................................................................................................................................ 20
C: Leaflet ................................................................................................................................................................................. 21
1. Introduction
Sustainability becomes more and more important and more political attention is moved
towards a sustainable society. Horizon 2020 is an example of the rise of awareness for
sustainability and society’s main question now lies in how to move towards a more
sustainable society. The technology has already been invented, but is costly or the transition
towards these new green technologies is one with barriers and has not been able to conquer
the socio-technical regime.
Living Labs (LL’s) are important for the transition towards a new socio-technical
regime. They have the ability to take over a socio-technical regime. LL’s are experiments
where users are a part of the creation process of innovation, together with developers and
researchers (Almirall & Wareham, 2008). Lead users are used to test the innovation and using
them to optimize the innovation and for that they are an important part of LL’s.
“Lead users are users whose present strong needs will become general in a marketplace
months or years in the future. Since lead users are familiar with conditions which lie in the
future for most others, they can serve as a need-forecasting laboratory for marketing
research.” (Von Hippel, p.791, 1986)
This will be elaborated on in the theoretical background with the help of Strategic
Niche Management (SNM), a Multi-level perspective (MLP) and geographical sustainability
transition (GST) literature (Rotmans et al. 2001 qtd in. Grin et al. p.126, 2010, Grin et al.,
2010, Rip & Kemp, 1998, Kemp et al. , 1998, Cooke, 2007). SNM argues the importance of
niches (a context for LL’s) and their vital role in innovation, GST will show how niches
evolve into common features of life and MLP will show how niches are able to change sociotechnological regimes and the context in which they do this. Different types of experiments
are influenced by different factors (Malerba et al., 2007). However there is a lack of
identification of geographical factors in smart grid LL’s in the literature. Boschma (2010),
Cooke (2007) and others have shown how regional proximity and spatial distances influence
the innovational capacities of a region. The gap in the literature is the absence of geographical
factors in the transition literature. The regional innovation system and proximity literature
show the importance of geographical factor in an innovation system.
Prior to continuing a definition must be given to the word success. In this paper the
same definition of success will be shared with Almirall and Wareham. Success in the
transition process however is the ability to evolve and take a bigger market share. Almirall
and Wareham also call it; “the ability to scale” (2008). Since the technology must diffuse and
scale up in order to be successful. LL’s are at the basis of the diffusion process and need to
scale up to conquer the market.
Which geographical factors are there that promote the success of Living Labs in the smart
grid industry?
The Smart grid industry is chosen for multiple reasons. One of the reasons is that
smart grid is important for sustainability. Electricity production from windmills and PV
panels rises with externalities in the power supply. Smart grid helps to overcome these
externalities. Smart-grid also gives inside in the power usage which leads to the second
reason; smart grid contains user involvement which is important for LL’s. Smart grids provide
overview in electricity consumption which raises awareness and stimulates efficiency. Also
application like vehicle to grid is concerned with user involvement
This paper will aim to provide the basis of new theory and fill the gap in the literature
and provide geographical factors which stimulate the success of LL’s. Further research will be
needed to test whether the possible characteristics that will be found, indeed contribute to the
rate of success in experimental projects. This may eventually result in a guideline for project
management of LL’s which would to a higher success rate.
This research paper will be structured along the following route; first the literature will
be given and possible factors will be provided. This will be summarized in the conceptual
framework, after which the methodology will be elaborated and how the interview will be
operationalized. This will be followed by the results, which leads to them discussion and
conclusion.
2. Theoretical framework
The theoretical framework will start off with a description on why LL’s are important using
SNM, MLP and GST literature. After that geographical factors will be identified and
categorized in 5 factors. The theoretical framework will be concluded with a suggestion that
different experiments are influenced by different factors.
2.1.
Importance of niches
In the sustainable transition literature the diffusion of innovation is projected following along
an S shaped curve. Along four phases the transition takes place to a new technology
paradigm. The four phases are; 1. The pre-development phase 2. The take-off phase 3. The
acceleration phase and 4. The stabilization phase, (Rotmans et al. 2001 qtd in. Grin et al.
p.126, 2010). In phases 1&2 niches are of importance. They provide secure niches (secure
niches can be compared to LL’s) for improvement and development, until they are ready to
evolve and scale-up.
SNM stresses the crucial role of niches in the transition literature (Raven & Verbong
qtd in. Coenen et al., p.293, 2010). Niches hold certain characteristics that are probable for the
success of the experimental projects. Niches are important for radical innovation and facilitate
the setting in which a radical innovation can come about (Truffer & Coenen, 2012, Grin et al.,
2010, Schot & Geels, 2008).
MLP shows how niches can evolve in respect to the different layers in society. MLP
consists of three layers; 1) socio- technical landscape, 2) socio-technical regimes, 3)
technological niches. Each layer has its own characteristics and illustrates another part of the
processes and design of the context.
1) The socio- technical landscape is the most rigid design of the three. Socio- technical
landscape consist of long term changes like climate change or rapid shifts which come about
by for example prices change of oil and war (Grin et al., 2010).
2) The socio-technical regime accounts for the stability and lock-in of socio-technical
systems. These systems consist of actors within a technical regime; users, scientists, policy
makers and other special interest groups. A socio- technical regime is less rigid than the
landscape and may change over time. It provides stability for actors within the regime and
adaption to technological paradigms which lead to efficiency and ability for incremental
progression. Rip and Kemp describe it as a; “rule-set or grammar in a complex of engineering
practices, production process technologies, products characteristics, skills and procedures – all
of them embedding institutions and infrastructures.” (p.338, 1998)
3) Technological niches are small networks which are unstable. These niches consist
of entrepreneurs and innovators that are willing to take a chance (Grin et al., 2010). They
consist of experimental projects, where actors are able to experiment in a relatively protected
setting and from there can be exposed to a selection environment of fine-tuning (Rip & Kemp,
1998). More details on niches and the characteristics and advantages of these characteristics
will be elaborated on in 2.3.
The three distinctive layers are able to interrelate and change, because of each other.
This happens when features of the different layers align. Niches can only scale up when they
co-evolve and make society lock-into the technological paradigm, such as the need for gasstation for cars with combustion engines (Kemp et al., 1998).
2.2.
Geographical context and proximity advantages
Now the importance of niches has been shown, the geographical success factors need to be
identified. The Regional Innovation System shows how knowledge and culture are important
in the geographical context (Cooke, 2007). Also in the transition literature the spatial
dimension gets more and more attention (Hansen & Coenen, 2014). Different aspects of the
regional context may be identified in which niches are stimulated. These are vision,
institutional, network, culture, learning, cultural, and demographics.
2.2.1.
Vision and institutional
Geographical context has multiple factors which influence the innovation system, one of
which is vision. Vision is shared with a network and creates a common goal. Boschma sees
shared routines, common habits and values and believes as important factors for successful
innovating (2010). Innovation is often seen as something uncertain with risk and money
without a direct return. Vision helps to overcome this barrier to strife for something new and
willingness to innovate as the early adopters of Rogers (1983). Tidd & Bessant describe
vision with the commitment to innovate and strife to a common goal (2013). Vision is
contextual, since challenges differ for each region. Moreover the willingness differs from
each region, regarding to demographics as will be explained in 2.2.3.
Vision also comes back in the institutional factors (Cooke, 2007). Laws, rules,
subsidies and taxes influence the ability to innovate and the alignment with the sociotechnical regimes. Regulations like CO2 emissions effect the direction of the innovation
(Bridge et al., 2013). The visions of the entrepreneurs need to align with the vision of the
region and therefor government otherwise barriers to innovate hinder the innovation process.
2.2.2.
Network, culture and learning
Regional context provides a context where actors can work closely. Through social
interaction, networks are formed which provide connections and alliances can be made.
Factors like; trust and openness are a part of relationships between actors. Openness and trust
in a relationship helps the relationship by the willingness to share ideas and confront dialogue
(Tidd & Bessant, 2013). It stimulates conversations and promotes the willingness to share
good (innovative) ideas. Trust results in knowledge spillovers which contribute to the
innovation process (Cooke, 2007, Hansen & Coenen 2013). Also network provides sets of
ideas which both opposes ideas and brings new insights which helps to construct an overview
of the pros and cons of a concept (Boschma, 2010). This all leads to the sharing of a common
goal and concrete vision to pursue a shared set of interest.
Trust opens conversations and willingness to share ideas as said above. This stimulation of
proposing ideas should promote a creative climate. Creative climate is a part of the
innovativeness of a firm (Tidd & Bessant, 2013). A culture within a project which stimulates
creativity, should cause more successful innovation and therefor a bigger chance the LL
project is successful.
2.2.3. Demographics
The population plays an important role in the innovation process. They both have to
produce, invent and adopt the innovation. For LL’s the population plays an even more
important role, since LL’s test the innovation in a semi-real life user setting. Since regions
differ in population, inhabitants of a certain region can impact the innovation processes
differently than other regions. Rogers sees early adopters as critical in the diffusion of
innovation. Early adopters are key factors due to their leadership and gate-way to the rest of
the population for an innovation (Rogers, 1983). Opinion leaders are young and tend to advise
others on their consumers choices. More so, early adopters are characterized by begin more
educated. Better educated early adopters are able to comprehend the innovation and advise the
lesser educated members of society (Rogers, 1983). Besides young and educated population
there is a third characteristic which helps the innovation process. Tidd and Bessant see a
creative climate as a way to stimulate innovative firms and projects as said before (2013).
Creative climate also includes creative people from the region to stimulate innovative output
and therefor success of the LL’s.
2.3.
Types of LL’s
Not every LL is the same and deals with the same kind of innovation. They are constructed
differently and have different goals. Grin et al. have identified differences in LL’s (2010). The
different kinds of innovation are; social innovation and more technological innovation. Social
innovation consists of innovation which is based on the use of already existing, but in a new
social paradigm. An example of which is the new trend in car sharing, cars (may be electric
which includes a bit of the technological innovation) which are no innovation itself, but the
way they are used is innovative. Creating a system where you can rent cars on the spot.
Technological innovation is more on new types of technology; heat-pumps, hydrogen
application (Grin et al., 2010). These different innovations may vary in success factors.
Another distinction in LL’s can be made in the way they are started/organized. R&D projects
resulting in prototypes and LL’s are guided by an organization of initiated by the government.
These are top-down/guided LL’s. On the other side citizens may initiate a project which
involves users and is constructed from a bottom-up approach. These are called grassroots by
Grin et al. (2010).
Feurstein et al. (2008) and Bergvall-Kareborn (2009) also describe differences in the
type of region. There are differences in rural and urban areas. Proximity differentiates and
infrastructure differs between rural and urban regions. Whereas the rural areas may be provide
an isolated affect for the living lab where it is les bound to established practices and lock-ins.
Urban areas may be more advantageous due to better infrastructure and demographics.
2.4.
Conceptual model
In Figure 1 the conceptual model is shown.
It illustrates how different factors
contribute to stimulate LL’s.
Figure 1: Conceptual Model
3. Methodology
In order to answer the research question, a qualitative research strategy will be used.
Qualitative research is used to take an interpretivist standpoint and therefore trying to
understand through examination of participants the characteristics for a successful
experimental project (Bryman p.366, 2008). This will be combined with a representative case
study. As shown in the theory, there are characteristics in related fields of study which give
reason whether an experimental project has more opportunity of success than others, but now
these characteristics will be tested in respect to the smart grid projects.
3.1.
Research method and data collection
Qualitative research strategy will be combined with semi-structured interview. The
advantages of the semi-structured interview type are that the interviewee has the ability to
deliver his own input, but that the researcher has the opportunity to further investigate topics
which correlate with the theoretical framework (Bryman, 2008). This is done, so that every
interview delivers the same input and a descriptive analysis is possible.
3.2.
Sampling
The interviews will be held on purposive sampling (Bryman 2008). This is done to collect
cases which are relevant for the search for success factors for LL’s. The database of JRC on
smart grids was used to find projects which were of value to this research. Experiments that
involved tags as; smart-metering, smart home, smart customer and smart network
management which recently ended or were still operating. For more response also snowball
sampling was used to find more projects which were eligible for this research. Furthermore
snowball sampling provided projects which weren’t necessarily subsidized.
To stimulate the response rate a promise was made to share the results of the findings
from this research, which could help and provide insights for project coordinators in setting
up a project in the future. A leaflet was provided to stimulate the response. The leaflet can be
found in C: Leaflet.
This project is done with multiple co-researchers. Together a part of the insights gained for
the interview is shared to provide a more detailed account in the importance of the different
success factors. A total of 29 cases are studied, including 8 of my own interviews.
3.3.
Research quality
In order to ensure research quality the internal and external validity and reliability and
replication will be discussed below. These factors are indicators of a well setup research
method on which proper conclusions can be drawn based on the data collected and analysis.
The internal and external validity are low. Success is unknown for the projects and factors
that are mentioned do not have to lead to success, so no causal connection can be concluded.
Also there are case studies used. Therefore no theory can be based upon the results. It does
however provide a basis to statically analyze factors for future theoretical creation. The
reliability is also low since the interviewees are and the interviewer is subjected to
subjectivism. This research is however replicable, since sample and interview are able to be
replicated.
3.4.
Data analysis
The aim is to identify both the importance of factors compared to each other as well as to
identify sub factors within the main factors. This leads to two different analyzes. One is the
using of Likert scales to determine the importance of the main factors that have been
identified in the literature. Second analysis is the identification of different factors.
To determine the importance of the different factors, Likert scales are added in the
semi-structured interview to determine how important that ought to be for the project. Since
this is a case study and know statistical analysis can be made upon the data collected from the
interviews, an average of the main factors will be taken from the ranking scales. Averages are
used to provide insight in the order of importance between factors. A descriptive analysis will
be used to analyze the factors and rank them in order of importance.
In order to identify factors that contribute to the success of a project the interviews
will be analyzed for factors that are provided by the interviewees. Interviewees will be asked
for argumentation why a main factor is important. The sub factors will be labelled and
compared to the existing factors provided by the literature and group them. This is done to
diminish the variety of main factors and keep the success factors organized. The different sub
factors will be categorized between the main factors. Each factor provided by the interviewee
will be tried to put in an existing main factor. If not possible a new main factor has to be
created or adapted to fit multiple sub factors and provide a structured view of the success
factors.
4. Operationalization
The semi-structured interview is designed in such a way that the interviewee is encouraged to
provide input on what they think is important for the success of their project, after which the
interviewer will go through the main factors. This is done to prevent coached answers and to
identify the factors which seem to be important by the interviewee.
Vision
Regional Network
Learning
Culture
Institutional
Demographic
A shared vision and/or cohered goal for solving e.g. societal challenges.
Presence of citizens groups, firms, government, NGO’s, knowledge
institutes that are willing to work together.
Factors which include learning to use an innovation or understand the theory
behind the innovation.
Willingness to cooperate, trust and openness, leading to a creative culture.
A match with regulations and funding by governmental organs.
The involvement of young, creative and highly educated people.
Table 1: indicators
Besides the success factors which are explained above, the differences in LL’s will also be
identified according to factors indicated in 2.3. Urban/Rural, Guided/Grassroots and
technical/social innovation will be identified to see whether they have an effect on the success
factors.
Since the results of the interviews will be shared with Harm van den Heiligenberg, likert
scales are used for the different success factors. In this report the likert scales will be used to
provide extra descriptive insights on the success factors and no statistical analysis will be
made on these results. The complete interview is available in A: Interview.
5. Results
Firstly the different factors will be elaborated on, providing a more detailed account on why
interviewees thought they were of importance to the success of the project, after which the
barriers will be discussed and a comparison is made between the differences within LL’s
using suggestions made in the literature. For a complete overview of the data, result tables are
provided in B: Results.
5.1.
Success factors
The averages of the score regarding the different success factors are presented in graph 1.
Learning and Vision come out as the more important factors. For the ability to scale up it is
important that learning factors are present, since information must be passed on to the future
generation. In the upcoming paragraphs each factor will be elaborated on and provide
concepts that were given by interviewees when asked why these factors are important for
success.
Average of Success Factors
5
4.5
4
3.5
3
2.5
2
1.5
Success Factors
Vision
Regional
Networks
Learning
Cultural
4.11
3.79
4.32
3.62
Governmen Demographi
t
cs
3.86
3.18
Graph 1: Average of success factors
5.1.1.
Vision Factors (4,11)
When asking about vision factors, multiple respondents answered that they were trying to
stimulate renewable energy and to promote sustainability. These societal challenges were a
common goal for a project to pursue. There was willingness to innovate, create something
new and in this case; something sustainable. In a case, it was mentioned that vision helped in
the beginning of the process to work a common goal, but it became less important over the
course of the project. In the end it became more important to survive, since subsidies ended or
diminished.
5.1.2.
Regional Network factors (3,79)
Knowledge institutes were frequently mentioned by interviewees when asking them about
regional network factors. They were an important factor to progress in relation to learning and
being able to set up a diffusion process. Government, citizen groups and firms were also
mentioned as important regional networks factors, however they were mentioned as
contributors to the success, but not as relational partners where intensive contact was
maintained, whereas knowledge institutes were.
5.1.3.
Learning factors (4,32)
Learning factors were the most important factors during this research. Although they were
answered as most important, fewer factors were mentioned. This is the case proabably,
because of the high level of abstractness in the term learning. Learning is a process which
often happens unconsciously and therefor hard to identify. The suc factors that were
mentioned are; the ability to understand, use the innovation and progress with the type of
technology were mentioned as success factors. Another learning factor was mentioned in case
7, where the behavior of users was seen as learning factor. If they want to scale up, they
would know how to deal with users more efficiently. Behavior towards innovation and the
implementation difficulties were taught and they saw it as they were better equipped to handle
this if scaling up.
5.1.4.
Cultural factors (3,62)
Cultural factors were by some interviewees seen as non-contributors to success, while other
interviewees thought of it as an important factor. The lack of interest by some may be because
of the same reason as learning factors. They are around and coped with unconsciously which
makes them hard to identify. The factors that were mentioned were; creative climate and a
cooperative culture during the interviews. Another factor which came up during the
interviews was the work ethics and participation to contribute. This is different from
cooperative culture, since it not only when working together, but also counts on the individual
level and the effectiveness of the individuals.
5.1.5.
Governmental factors (3,86)
Funding was the most frequently answered response, when asked why government was
important for success. A few answered differently with risk-bearing and support of the
project. Besides that regulation and legislation helped some, but other projects were seeing
this as barriers.
5.1.6.
Demographic factors (3,18)
Higher educated and creativity were often answered when asking about the demographic
factors. This was answered for both the users/customers as well as employees of the project.
In one case the interviewee remarked that young people were not able to buy the technology,
but were able to adapt more to the social innovation. Older people were according to the same
case more able to afford the technical innovation, but less able to adapt to the social
innovation.
5.2.
Barriers
The lack of a success factor mentioned above can be seen as a barrier. In this paragraph only
new barriers acquired from the interviews are presented. One of the barriers mentioned by
interviewees was the deadlines they had to deal with. The limitation of time resulted in the
restriction of the amount of implementation that they had envisioned to do. One of the reasons
this originated and was also mentioned as barrier was the conflict of different opinions
between actors. This debating resulted in a waste of time and inefficient use of resources.
Other barrier mentioned was limitations of infrastructure, this was said by rural
located projects. A difficulty to get supplies to the rural areas to implement the innovation.
Also an urban project mentioned infrastructure in respect to the electricity infrastructure as a
barrier. This was seen as a lock-in and hard to overcome. Other barriers were shortage of
money and lacking engagement of users and stakeholders. Inertia, lock-in and competition of
vested interest were seen as barriers that were difficult to overcome
5.3.
Types of LL’s
LL’s differentiate in multiple dimensions from one another. These different dimensions are
whether the LL is based in a Urban or Rural environment, difference in origin and difference
in innovation type.
5.3.1.
Urban and Rural factors (Graph 2)
Urban and rural have their own characteristics which can make them suitable for LL’s.
Whereas the rural areas may be provide an isolated affect for the living lab where it is les
bound to established practices and lock-ins. Urban areas may be more advantageous due to
better infrastructure and demographics. This came forward in the interviews, a rural case had
problems with supplies and infrastructure as described in 5.2. Another case described another
disadvantage of rural areas. A rural area was less attractive for young, creative and educated
people, which resulted in a runaway of skilled personnel. They went off to major cities with
universities and colleges, leaving behind a region where young, creative, educated population
disappeared. The highest average spread between rural and urban is seen in the regional
network with a 0.4 difference. Networks are more easily maintained in urban areas, since the
average distance between actors is smaller than in rural areas.
5.00
Average of Success Factors sorted by Urban/Rural
4.50
4.00
3.50
3.00
2.50
2.00
1.50
Vision
Ragional
network
Learning
Cultural
Government
Demographics
Urban
4.16
3.80
4.47
3.67
3.95
3.21
Rural
4.40
3.40
4.20
3.60
4.20
3.20
Both
3.67
4.33
3.67
3.33
3.00
3.67
Graph 2: Average of success factors sorted by Urban/Rural
5.3.2.
Guided and Grassroots factors (Graph 3)
In the interviews came forwards that network were not important for citizens originated
projects, because they had done it themselves. Citizens and firms did it themselves, opposed
to a combination and government. Therefore network is seemed less important to them. Firms
and citizens still needed government for funding. Citizens that do it themselves are not
involved that much with government. In a citizens initiated project, government was used to
set up a business plan and funding, but were distanced to use government, since they were not
a part of the community. They were relational partners in developing these projects.
Average Score or Success Factor sorted by Innovation Type
5.00
4.50
4.00
3.50
3.00
2.50
2.00
1.50
Vision
Ragional
network
Learning
Cultural
Government
Demographics
Technical
4.40
4.30
4.40
3.50
4.40
3.67
Social
3.50
4.25
4.25
3.50
3.50
3.25
Both
4.08
3.54
4.33
3.73
3.33
2.92
Graph 3: Average of success factors sorted by Origin
Average Scores of Success Factors sorted by Origin
5.00
4.50
4.00
3.50
3.00
2.50
2.00
1.50
Vision
Ragional
network
Learning
Cultural
Governmen
t
Demographi
cs
Government
4.00
4.08
4.42
4.00
3.73
2.82
Firm
4.33
2.00
3.67
3.67
4.33
3.00
Citizens
3.50
2.50
4.00
3.00
3.00
3.50
A combination
between them
4.20
4.30
4.56
3.00
3.80
3.70
Graph 4: Average of success factors sorted by Innovation Type
5.3.3.
Technical and Social innovation (Graph 4)
Technology scored higher or equal to social innovation success factors. This may be caused
by that technology is tactile and therefore more real. This may lead to more enthusiasm in
both project management as stakeholders, such as government funds. Technical scores an
average of 4.18, social 3.71 and both a 3.80.
6. Discussion
First the limitations will be discussed after which recommendations are made if possible to
improve future research.
In this research paper, purposive sampling was used and projects were found with the
use of JRC database. JRC database is however a database composed out of projects funded by
the European Union. This explains the high amount of response that funding is an important
success factor. Luckily however some projects were found using snowball sampling which
opened another area of projects which weren’t registered. This lead to other cases which
weren’t funded by the European Union. The sample still remains biased towards government
as a success factor. This is also the reason for having fewer citizen initiated projects. This also
leads to the next limitations; the limitations of cases in this study.
Due to time constraints and lack of response, a fewer number of cases have been
studied to what was hoped. This caused a total of 29 cases with only 2 cases of projects which
originated by citizens and 3 firm cases, which also leads to a less stable data descriptives. This
can be solved by future research when more cases are found through grassroots’ approaches.
If more cases are gathered and combined a statistical analysis can me made upon the results of
the interview. When a statistical analysis is made more conclusions can be drawn and more
insights are gained. This research is yet of an explorative nature and may be used in future
studies to find geographical success factors.
This leads to future recommendations on how to improve the interview and therefore
improve the response and data obtained by the interview. One of the findings in this paper is
the barrier of infrastructure. This can both be seen as a barrier as well as a success factor.
Infrastructure and other barriers mentioned like, energy infrastructure could be combined into
a new factor called agglomeration. Agglomeration would entail more than just demographics
and include an overlooked geographical factor which influences the innovation process.
Agglomeration would cover; characteristics of the population, educational facilities,
transportation facilities, energy infrastructure (in regard to the smart grid industry) and other
facilities which contribute the innovation processes which are specific for a region.
Another limitation due to time constraints is the inability to know whether a LL would
be successful. There are two ways to solve this problem. One is to choose for a longitudinal
research design. The second is to interview projects which are completed / or ongoing for a
lengthy period of time when interviewed. This promises a more probable result towards
success factors. The reason why did wasn’t done in this research is because of the difficulties
in the degree of response from retired projects. This may be caused by a variety of reasons;
outdated contact data, less members that are familiar with the project and harder to find out
whether they were dealing with an innovation.
7. Conclusion
In this paper the aim was to identify geographical factors which promoted the success of
Living Labs Experiments in the smart grid industry. This was done by identifying
geographical factors in the literature and empirically tests their existence in the real world.
This was done by using semi-structured interview. Learning and vision factors were seen as
the most important factors, followed by government, network, cultural and demographic
factors. New factors were found e.g. infrastructure and work ethics. Some examples of
barriers that were found are; vested interest, lock-in, deadlines and shortage of money. Also
characteristics in LL’s were identified to see if they explain differences in success factors.
Technical innovation scored higher than social innovation and Firm and citizens originated
LL’s scored low on network factors. Although these only a few number of cases they argued
that the network was not important, since they would do it themselves. Differences between
urban and rural LL’s were minimal; the biggest difference with a 0.4 average difference was
the network factor, which can be explained to density differences between urban and rural
regions. Furthermore technical innovation always scored higher in main factors or equal than
the social innovation.
8. References
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Electronic Journal for Virtual Organizations and Networks 10.3 (2008): 21-46. Web.
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lab approach." System Sciences, 2009. HICSS'09. 42nd Hawaii International Conference on.
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Boschma, R. 'Proximity And Innovation: A Critical Assessment'. Regional Studies 39.1
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Bridge, G, S. Bouzarovski, M. Bradshaw, and N. Eyre. 'Geographies Of Energy Transition:
Space, Place And The Low-Carbon Economy'. Energy Policy 53 (2013): 331-340. Web.
Bryman, A. Social Research Methods. Oxford: Oxford University Press, 2008. Print.
Coenen, L., R. Raven, and G. Verbong. 'Local Niche Experimentation In Energy Transitions:
A Theoretical And Empirical Exploration Of Proximity Advantages And Disadvantages'.
Technology in Society 32.4 (2010): 295-302. Web.
Cooke, P. 'Regional Innovation Systems, Clusters, And The Knowledge Economy'. Industrial
and Corporate Change 10.4 (2001): 945-974. Web.
Feurstein, K, A. Hesmer, K.A. Hribernik, K.D. Thoben and J. Schumacher. "Living Labs: a
new development strategy." European Living Labs-A New Approach for Human Centric
Regional Innovation (2008): 1-14. Web.
Grin, J., J. Rotmans, and J. Schot. Transitions To Sustainable Development. New York:
Routledge, 2010. Web.
Hansen, T. and L. Coenen. 'The Geography Of Sustainability Transitions: Review, Synthesis
And Reflections On An Emergent Research Field'. Environmental Innovation and Societal
Transitions (2014). Web.
von Hippel, E. 'Lead Users: A Source Of Novel Product Concepts'. Management Science 32.7
(1986): 791-805. Web.
Kemp, R., J Schot and R Hoogma. 'Regime Shifts To Sustainability Through Processes Of
Niche Formation: The Approach Of Strategic Niche Management'. Technology Analysis &
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Malerba, F., R. Nelson, L. Orsenigo and S. Winter. 'Demand, Innovation, And The Dynamics
Of Market Structure: The Role Of Experimental Users And Diverse Preferences'. Journal of
Evolutionary Economics 17.4 (2007): 371-399. Web.
Rip, A. and R. Kemp. Technological change. Battelle Press, 1998. Web.
Rogers, Everett M. Diffusion Of Innovations. New York: Free Press, 1983. Print.
Schot, J. and F. W. Geels. 'Strategic Niche Management And Sustainable Innovation
Journeys: Theory, Findings, Research Agenda, And Policy'. Technology Analysis & Strategic
Management 20.5 (2008): 537-554. Web.
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9. Acknowledgement
This paper is part of my graduation for the trajectory Innovation Sciences within the study
Liberal Arts and Sciences. I want to thank my supervisors; , prof. dr. Marko Hekkert , Harm
van den Heiligenberg and especially dr. Simona Negro for their insights and support. They’ve
kept me on the right track and helped me progress and finish this thesis.
10.Appendix
A: Interview
1.
1.1.
1.2.
1.3.
1.4.
1.5.
1.6.
Basic information
Date:
Name interviewee:
Email:
Organization:
Job description:
Name interviewer:
2.
2.1.
General questions
What is the name of the project
2.2.
Who is the leader of this project
2.3.
Is there an innovation tested in this project, or in a part of it?. Please describe (briefly).
2.4.
Are users involved in this test? Please indicate involvement on a five-point scale
0
0
0
0
0
no
high
2.5. Where is the project located (which administrative region, in a rural or urban area)
Region:
Urban/rural:
<<decision by interviewer: does this project meet the criteria? STOP or CONTINUE>>
3.
3.1.
Type of project
Is this project guided by a government or firm, or initiated by citizens?
3.2.
Is the subject of the test something technical (a new product or component) or something social
(new ways to find solutions, new ways of doing things).
4.
4.1.
Success factors
How do you define success in this project?
4.2.
We define success as being able to scale up. This means that in the future more people will be
involved with this novelty, on this location or on other locations. Which three factors are the
most important for success, using our definition? Please indicate their importance on a fivepoint scale.
0
0 0 0
0
low
high
0
low
0
0
0
0
high
0
low
0
0
0
0
high
4.3.
Vision factors: we like to know whether a local, regional or sectoral vision is important for
success. Maybe this vision contains elements (societal challenges, economic specialization,
spearheads for innovation) which have a match with your project.
Question: Which factor, related to visioning, is important for your success? Indicate importance
on a five point scale.
0
0 0 0
0
low
high
4.4.
Regional network factors: we like to know whether local or regional networks are important for
success. Networks might contain people from various groups (for instance from citizen groups,
firms, government, NGO’s, knowledge institutes). Often face-to-face interactions and informal
relationships are important. Also the support of these groups might be important.
Question: Which factor, related to networks, is important for your success? Indicate importance
on a five point scale.
0
0 0 0
0
low
high
4.5.
Learning factors: we like to know whether learning factors are important for success. This may
involve learning to use the innovation, but also the change of assumptions.
Question: Which factor, related to learning, is important for your success? Indicate importance
on a five point scale.
0
0 0 0
0
low
high
4.6.
Cultural factors: we like to know whether cultural factors are important for success. This may
involve many issues, for instance trust, openness, a cooperative culture, a creative culture or
other cultural values.
Question: Which factor, related to culture, is important for your success? Indicate importance on
a five point scale.
0
0 0 0
0
low
high
4.7.
Government: we like to know whether the government is important for success. The
government can for instance support projects with funding or create an area with less
regulations, where experiments are possible.
Question: Which factor, related to government, is important for your success? Indicate
importance on a five point scale.
0
0 0 0
0
low
high
4.8.
Regional demographics: we like to know whether demographics is important for success. This
may involve issues like the presence of young people, creative people, highly educated people
and so on.
Question: Which factor, related to demography, is important for your success? Indicate
importance on a five point scale.
0
0 0 0
0
low
high
4.9.
Other factors: maybe you have other success factors, not yet mentioned. Maybe about the
people involved in the project, the motivation of these people, physical things who are available,
or other factors.
Question: Which other factors are important for your success? Indicate importance on a five
point scale.
0
0 0 0
0
low
high
0
low
5.
5.1.
0
0
0
0
high
Barriers
Which factors form a barrier for this project (e.g. shortage of money or support, the presence of
existing routines or vested interests, resistance by groups in society). Which three factors are the
most important?
6.
6.1.
Upscaling: what happened before, what might happen in future
Is this project based on previous projects? What was transferred? Where are these projects
located? (indicate name of region)?
Yes/no What?
Where?
6.2.
Has this project been an example for others. Will this project be an example for others. Where
are these projects located (indicate name of region)?
Has been?
Will be?
Where?
6.3.
END
What was done in this project to help this upscaling?
- Thank you very much
- With the results of this research, we like to help sustainability projects to become more successful.
Are you interested in receiving the results?
B: Results
Guided by government,
Urban/Rural Firm, citizens
Case Country/city
Technical
/Social
vision
score
learning cultural government demographics
network score
score
score score
score
1 Vienna, AT
Urban
A combination between them Both
5
4
5
1
1
4
2 Venlo, NL
Urban
A combination between them Both
5
5
4
4
5
4
3 Shatlands islands, UK
Rural
A combination between them Technical
5
5
5
4
5
4
4 Trento, IT and Stockholm, SE Both
A combination between them Social
3
5
4
3
3
4
5 Boekarest, RO
Urban
A combination between them Technical
4
5
5
1
4
5
6 Limburg, BE
Rural
A combination between them Technical
5
4
3
2
4
4
7 Texel, NL
Rural
Citizens
Both
4
3
4
4
3
3
Firm
Both
4
1
5
5
5
4
8 Trento, IT and Stockholm, SE Urban
Table 2: factor scores
Case vision factors
network factors
learning factors cultural factors government
regional demographics
1-
Relationships between actors
-
-
Educated workers
Green and sustabianle
2 office building
Knowledge institutes and
involvement of third parties
-
Creative Region,
interaction with
Funding and risk
industry
bearment
3-
Govenment and university
to progress
cooperation
funding
Beginning it is important,
4 willing to innovate
-
-
Cohesion,
local authorities,
legislation
educated
depending on flexible or economic
sense. Old is economic independent
and less flexible and the other way
around.
Societal challenge,
5 efficiency, awarness
Knowledge institutes, and other
dissimination
-
Collaboration
Funding
Young and creative
Green yet economically
6 responsible
Local authoritites
-
Openness for
social project
Funding
Educated
7 Societal challenges
Citzens were involved with each
other, but no real ties with
outsiders other than supplier.
The way users
react (behavior)
to new things
It's rural and
therefor close
bonded
Funding, knowledge
sharement about the
business picture
Motivated
8 Societal challenges
-
Learning to use
the innovation
Table 3: Factors
-
-
Case Barrier 1
Barrier 2
Barrier 3
1 -
-
-
2 scale-up problems
Monetary funds
How to make the results
visible (conflict of interest)
3 -
-
-
4 infrastructure
demographic
5 Lock-in
Inertia
6 Project management (deadlines)
Public support
7 Shortage of money
Technical possibilities
Vested interest
8
Table 4: Barriers
C: Leaflet
Research project “Living lab regions for sustainability”
You have been asked to participate in a questionnaire on sustainability experiments in
Europe. This survey is part of a project carried out by drs. Harm van den Heiligenberg (PhD
student), from the Faculty of Geosciences of Utrecht University, The Netherlands.
Supervisors of this project are prof. Marko Hekkert and prof. Frank van Oort from this
University.
With this research we like to help sustainability experiments to be more successful. The
results will be available at the end of this year. If you are interested we will send you these
results.
Societal background
Sustainable development is the most important challenge of our times. On the global scale,
issues like hunger, poverty, climate change, water availability and biodiversity loss request
our urgent attention. On national and regional scales, there is much to improve in our food,
mobility and energy systems. These challenges have to be balanced with local social issues
like cohesion, participation and health.
Transitions needed
The challenges for sustainable development are massive. We need to change our systems
(for instance our energy, food, mobility and care systems) in a fundamental way. These
changes, so-called transitions, may take several decades.
For these transitions, innovations are needed. These innovations are developed and tested
somewhere on earth, on a spot or in a region where favorable conditions exist.
Regions act as “living labs” for sustainability innovations. In these labs, inventions are tested
in real life. There are big expectations in society that a test in real life with a lot of user
involvement will help to be successful in the introduction in markets and society afterwards.
This so-called experimentation phase seems to be crucial. When this phase is successful,
the experiment is followed by more experiments and a scaling-up process, in which the
invention is improved and spreaded out towards other locations and regions in the world.
However, at the moment a lot of local and regional sustainability experiments fail. The OECD
states in a recent report that “during experimentation, many new firms and their green
innovations will fail” (OECD, 2014). More than half of about 30 sustainability experiments in
the province of Utrecht were ended five years later. The reasons for this are not clear. The
first policy question is how to improve the success of these experiments.
In recent years, we see a growing commitment to sustainable development on the local and
regional scale. In recent years there is a massive growth of grassroots initiatives, for instance
for local energy, food or care. These initiatives are often done by local civic groups with a
cooperative structure. These groups might become very important for the upscaling of
sustainability initiatives, because of a strong motivation of the participants.
The second policy question is how to support these bottom-up initiatives, and at the same
time how to connect these initiatives to the long term challenges of the region, the country
and the world.
Thank you for your cooperation!
Drs. Harm van den Heiligenberg
Utrecht University
Faculty of Geosciences
Address
Heidelberglaan 2
3584 CS UTRECHT
The Netherlands