Conference PaperPDF Available

THE INNOVATION CAMPUS: KEY CHALLENGES AND SUCCESS FACTORS IN DIFFERENT STAGES OF MATURITY

Authors:
  • Brabantse Milieufederatie

Abstract

The innovation campus is a new kind of innovation ecosystem. It is a physical location on a large organization's premises, with high quality real estate and shared facilities, with the aim to actively foster open innovation practices among its residents. To develop such a campus from inception to maturity in practice seems to be a difficult task. This study explores the specific characteristics of the emerging innovation campus concept and develops a maturity capability model. The model consists of four maturity stages and nine dimensions. We validated the model with 5 experts from different Dutch innovation campuses. We propose that there are necessary, as well as sufficient, conditions for maturity development, which enables decision makers to set better priorities for resource deployment. These results assist the different campus' stakeholders to align their roles and activities during transition over the maturity stages.
THE INNOVATION CAMPUS: KEY CHALLENGES AND SUCCESS
FACTORS IN DIFFERENT STAGES OF MATURITY
Sandor Löwik
University of Twente, s.j.a.lowik@utwente.nl
Wout Oude Alink
University of Twente, w.oudealink@gmail.com
Niels Pulles
University of Twente, n.j.pulles@utwente.nl
ABSTRACT
The innovation campus is a new kind of innovation ecosystem. It is a physical location
on a large organizations premises, with high quality real estate and shared facilities,
with the aim to actively foster open innovation practices among its residents. To
develop such a campus from inception to maturity in practice seems to be a difficult
task. This study explores the specific characteristics of the emerging innovation campus
concept and develops a maturity capability model. The model consists of four maturity
stages and nine dimensions. We validated the model with 5 experts from different Dutch
innovation campuses. We propose that there are necessary, as well as sufficient,
conditions for maturity development, which enables decision makers to set better
priorities for resource deployment. These results assist the different campus
stakeholders to align their roles and activities during transition over the maturity stages.
Further, we suggest avenues for future academic research
INTRODUCTION
The open innovation paradigm (Chesbrough, 2006) has become mainstream in
innovation literature and management practice. The main focus has been on individual
firms and on regional innovation clusters. However, some large established firms start
innovation clusters on their own company premises. This new and relatively
underexplored phenomenon is known as an innovation campus (BCI, 2009; Kooij et
al., 2014). We define an innovation campus as a physical location with high quality real
estate and shared facilities, with the aim to foster open innovation practices supported
by an active policy to facilitate knowledge exchange, collaboration, and new product
development (Boekholt et al., 2009). An innovation campus takes an intermediate
position between an incubator/start-up accelerator and an innovation cluster/business
& science park. Examples of such innovation campuses are the High Tech Campus
Eindhoven originally centered on Philips in the Netherlands, Brightlands Chemelot
originally centered on DSM in the Netherlands, and Novartis Campus in Basel,
Switzerland (Tödtling, Van Reine & Dörhöfer, 2011).
The innovation campus offers initiating firms and institutions several
advantages. Due to close proximity of campus residents, innovation and
entrepreneurship is stimulated. The key mechanisms are easier informal contacts
between campus residents which create trust and knowledge exchange, increased
business-to-business activities, supporting activities by the campus management,
shared state-of-the-art research and test facilities, and increased access to talented staff.
Also, establishing an innovation campus can generate income from selling or renting
out their own properties. (Boekholt et al., 2009).
However, the advantages are not that easily achieved in practice. In the
Netherlands, the High Tech Campus Eindhoven was the first of its kind, established in
1998 as a Philips campus, inspired by the Apple Campus in Silicon Valley, but driven
by cost-saving, re-focusing and image-enhancing strategies (Kooij et al., 2014). Since
not all buildings were occupied by Philips, the campus opened up for other companies
in 2003. Soon its real estate development with high quality architecture and landscaping
became an example for other companies and cities, resulting in at least 14 campus
developments in 2009 (BCI, 2009) to 39 in 2014 (BCI, 2014) in the Netherlands.
However, most innovation campus initiatives are still in the development stage.
According to consultancy firm BCI, only four campuses reached maturity in 2009
(including High Tech Campus Eindhoven) and only eight in 2014 (BCI, 2009, 2014).
This seems to suggest that innovation campus development from inception to maturity
is a rather difficult task.
Apparently, developing an innovation campus is difficult, despite the
knowledge available on open innovation and innovation clusters. It appears that
innovation campuses have specific characteristics and face different challenges over
time. This observation leads to our research question: “What factors determine
innovation campus growth and how do these factors change during campus’ maturity
stages?”
To answer this research question, we first define the main characteristics of an
innovation campus to clearly delineate from incubators on the one hand, and innovation
clusters and business & science parks on the other hand. Then, we develop a capability
maturity model. From innovation management and innovation cluster literature, we
derived nine critical success factors and we determined four maturity stages. Further,
we validate the model with experts from five innovation campuses in the Netherlands.
We contribute to theory and practice in four ways. First, we clearly delineate
and define the characteristics of an innovation campus to distinguish it from other
innovation eco-systems to guide future research. Second, our capability maturity model
for innovation campuses is, to our knowledge, the first that describes maturity levels at
the eco-innovation system level. Although the empirical cases show that campus
development is idiosyncratic and context-specific, we identify common capabilities
across cases. We propose a distinction in necessary and sufficient capabilities that
determine maturity levels. This enables decision makers to better set priorities in their
resource deployment for capability development. Third, whereas some studies on
innovation clusters argue that the relative importance of critical success factors decrease
over time (e.g. Tavassoli & Tsagdis, 2014), our maturity model suggests that it is not
the relative importance that changes, but that the capabilities’ contribution can change
per maturity stage. This implies that scholars and practitioners need to take a broader
perspective on the capabilities in all maturity stages. Fourth, the maturity model can be
used by practitioners as an audit tool to the different campus’ stakeholders to identify
the current stage, to discuss different perspectives on capability development, and to
align their interests and business models (West & Bogers, 2014).
This paper is structured as follows. We first define the innovation campus and
explain how it is distinctive from other innovation eco-system concepts. Then, we
discuss maturity models and their application in innovation management. After
explaining the research method, we design the capability maturity model for innovation
campuses. We briefly describe the main findings from the five experts and their cases.
In the discussion we derive two propositions regarding the relative importance of the
success factors for campus maturity. We conclude with new avenues for future research.
THEORETICAL BACKGROUND
The Innovation Campus
Although the innovation campus concept is emerging in literature, its distinctive
characteristics are still ambiguous. The innovation campus is a specific kind of
innovation ecosystem that takes an intermediate position between incubators and
accelerators on the one hand, and innovation clusters and business & science parks on
the other hand. Below, we discuss different dimensions of open innovation
communities, clusters, campuses and incubators (summary in Table 1).
- Strong focal firm: the innovation campus is centered around a large focal firm,
that takes the initiative and is the main property owner (at the start of the campus
development). Also, the open community (where a firm launches an idea or a problem)
and the incubator/accelerator center around one company. This is in contrast to the
innovation cluster and the business & science park, where a focal firm can be present,
but is not necessary.
- Geographic proximity: tenants of incubators and accelerators are often housed
in the same building. The campus ventures’ buildings are located on a clearly delineated
geographic area, often located at a former industrial compound. Incubators and
accelerators can be very well located at such an innovation campus. Business and
science parks are generally more spacious, and innovation clusters can cover whole
regions.
- Real estate orientation: the innovation campus has a clear real estate venture
orientation. Owing to production outsourcing and concentration on core capabilities,
large firms have unoccupied real estate that they look to sell or rent. Just like incubators,
accelerators, and business & science parks the innovation campus offers facilities and
housing services to its associated ventures.
- Business development process orientation: similar to incubators and
accelerators, the innovation campus actively supports the growth of its residents.
Specific programs are aimed at supporting the ventures’ management, for instance with
training and education and offering financing support.
- Shared facilities: related to the previous aspects, owing to geographical
proximity and business development process orientation, incubators/accelerators,
innovation campuses, and to a lesser extent business & science parks, offer shared
facilities to their inhabitants. For instance, shared research and production facilities, or
shared canteens to promote knowledge exchange.
- Active management: since the shared facilities need management, innovation
campuses and incubators/accelerators have an active support organization and
management. These management activities can be done by the focal firm, or by an
independent support organization.
- Knowledge diversity: since an innovation campus needs a clear identity and is
centered around a focal firm, knowledge diversity is limited. Mostly, it is theme-driven,
such as biotechnology, nanotechnology, chemistry, food & health. In contrast, business
& science parks, regional innovation clusters and incubators can be more diverse.
- Partner diversity: the diversity in companies and institutions - such as large
firms, SMEs, start-ups, universities is the highest in the regional clusters and business
& science parks. Most innovation campuses are organized around large firms, leading
to less partner diversity. Housing an incubator or accelerator on campus grounds
contributes significantly to more partner diversity. Within an incubator or accelerator
partner diversity is low, since these are mostly all start-ups and small enterprises.
Dimension
Innovation
community
(open source)
Regional
innovation
cluster
Business &
science park
Innovation
campus
Incubator
Strong focal firm
X
0
Geographic
proximity
X
0
Real estate
orientation
X
0
Business
development
process
orientation
X
0
0
(Shared) facilities
X
X
0
Active
management
X
X
0
Knowledge
diversity
0
Partner diversity
0
0
X
Table 1: Comparison of different innovation eco-systems. √ indicates that the dimension is
present, 0 means that it is neutral, X indicates that it is absent.
Looking at Table 1, we conclude that the innovation campus shares commonalities with
incubator/accelerators, as well as with business & science parks and innovation clusters,
while at the same time being sufficiently distinctive from these innovation systems.
So far, only a few studies have addressed characteristics of the innovation
campus. These have covered topics of spatial planning (Kooij et al., 2014; Kooij, 2015)
and regional cultural differences (Tödtling et al., 2011). Furthermore, in the
Netherlands a few consultancy firms have published reports for governmental
institutions (BCI, 2009, 2014; Boekholt et al., 2009) that described the current state of
innovation campuses. However, how innovation campuses develop remains unclear.
Use and Limitations of Maturity Capability Models
Maturity capability models measure the as-is capabilities to indicate their
developmental stage, to derive and prioritize improvement measures, and to control
progress (Pöppelbuss & Röglinger, 2011). Maturity models originated in quality
management and the software industry with the Capability Maturity Model (CMM)
being one of the most well-known (Paulk et al., 1993).
Maturity is often defined as “the extent to which a specific process is explicitly
defined, managed, measured, controlled and effective” (Paulk et al., 1993). Maturity
increases over time from initial stage to full capability development (Kazanjian &
Drazin, 1989). By distinguishing multiple stages that represent different levels of
capability development, maturity models can serve three different goals (Pöppelbuss &
Röglinger, 2011). First, the model can be used for descriptive purposes. It indicates the
current as-is state, and serves as a diagnostic tool, Second, the model’s purpose can be
prescriptive, which means that the model provides guidelines on how to achieve higher
maturity levels, through improvement measures and capability development. Third, the
model can serve as a comparative tool to benchmark capabilities internally and
externally.
Despite their abundant use, or arguably due to this, maturity models are subject
to criticism (Fraser et al., 2002; Pöppelbuss & Röglinger, 2011). The models would be
“step-by-step recipes” that oversimplify reality, suggest a “one best way”, and lack
empirical foundation. Related to this, maturity models suggest a sequential process to
a desired end state, without taking the processes of evolution and change and
contingencies into account. Other criticisms concern the lack of rigorous design of
many maturity models and the multitude of almost identical models. To address this
criticism, we will clearly explain the purpose and use of our model, outline our design
process, and explain how our model differs from others.
Maturity Models in Innovation Management
In the innovation management literature, maturity models are gaining interest, because
they suggest firms how to develop their (dynamic) capabilities. Initially, maturity
models in innovation management were used to assess product design and new product
development processes. Fraser et al. (2002) provide a review of several maturity models
used in product design and new product development. They conclude that there are
many maturity models for different purposes and uses. For instance, Chiesa, Coughlan
and Voss (1996) developed a technical innovation audit to assess managerial innovation
processes and performance. Moultrie, Clarkson and Probert (2006) created a maturity
model for design processes in new product development for SMEs. Kahn et al. (2006)
and Kahn et al. (2012) developed a new product development best practices framework,
to benchmark internally (comparing against the highest level) or externally (comparing
against competitors).
More recently, the focus has shifted form new product development towards
innovation management capabilities. Essmann and Du Preez (2009) developed the
Innovation Capability Maturity Model (ICMM). Their comprehensive three-
dimensional maturity model includes five maturity stages based on Paulk et al.’s (1993)
CMM (ad-hoc innovation, defined innovation, supported innovation, aligned
innovation, synergised innovation), three innovation capability constructs (innovation
process, knowledge & competency, organisational support) and five organisational
constructs (strategy & objectives, function & processes, organisation & management,
data & information, customers & suppliers). This model is used by Enkel, Bell, and
Hogenkamp (2011) to develop their open innovation maturity model. Their model
includes three dimensions, which are typically related to open innovation practices:
partnership capacity, innovation climate, and systems and tools.
All mentioned maturity models take an organization-level of analysis. Instead,
our study takes the innovation campus as level of analysis. Since innovation eco-
systems have specific characteristics and capability development needs, we propose a
specific maturity model for innovation campuses.
METHOD
We used a qualitative research method to develop the descriptive maturity model. This
method is commonly used in literature (e.g. Enkel et al. 2011) and is appropriate since
the maturity model is developed and tested according to existing notions of good
practice, using experience-based principles and interviews (Fraser et al., 2002).
We applied design principles of Maier et al. (2012), Pöppelbuss and Röglinger
(2011) and De Bruin et al. (2005) to develop a maturity model. We used a seven-step
approach:
1. Determining the scope of the model in terms of purpose, target group, and class of
entities under investigation.
2. Differentiating from related maturity models (this is explained in the foregoing
literature section)
3. Determining design process and extent of empirical validation (which is explained
in this methodology section)
4. Determining the maturity levels, based on literature
5. Determining the dimensions, based on literature
6. Determining assessment criteria, based on literature
7. Validating the maturity model with experts from five empirical cases
For the empirical assessment we consulted expert from five empirical cases. We
selected five innovation campuses in the Netherlands based on their maturity level and
diversity in characteristics. The cases have high maturity levels, according to BCI
(2009, 2014), which enables us to explore the transition through the stages. To reach
sufficient diversity, two cases are centered around a university (Leiden Bio Science
Park and Wageningen Campus), two cases are centered around large firms (High Tech
Campus Eindhoven Philips, and Brightlands Chemelot DSM), and one case is a
hybrid of a university and a business park (Kennispark Twente). The main
characteristics of these innovation campuses are listed in Table 2.
For each case, we studied secondary data, such as websites, campus brochures,
presentations, and newspaper articles. Some cases have been described in academic
research. Further, we took an interview with expert representatives of each case. The
functions of these experts were directly related to the development of the innovation
campus, such as campus developer, campus director, business developer or cluster
developer. The interviews were semi-structured, took around seventy minutes each, and
were recorded. The interview topics concerned: brief history of the campus
development, success factors, development of these factors over time, encountered
difficulties, assessment of dimensions derived from literature. The recordings were
analyzed and transcribed in twenty-four pages of text. These were presented to the
campus experts for validation, which led to only minor adjustments.
Leiden Bio Science
Park
Wageningen Campus
Kennispark Twente
High Tech Campus
Eindhoven
Brightlands Chemelot
Campus
1984
1998
2006
2003
2012
Academic (Leiden
University)
Academic
(Wageningen University)
Academic (University
of Twente) and
business
Business (Philips)
Business
(DSM)
Life sciences
Agro, food, biobased and
healthy living
environment
Industrial innovation
Health, energy and smart
environments
Materials, health, food,
smart services
Organizations: 173
130 Companies:
93 Medical, 37 Other
19 Research Institutes
10 Healthcare
organizations
14 Others
Organizations:
90 Companies
9 Research Institutes
Organizations:
400 Companies
360 Start-ups
Organizations: 145
132 Companies
13 Institutes
36 Multinationals
55 Start-ups
Organizations: 85
74 Companies
11 Research Institutes
16,907
1,800 + ± 5,000
Wageningen UR
personnel located in
Wageningen (50:50
University and research
insitutes)
5,741 + 3,000
University
10,000
1,540
110
50
12 Ha campus,
20 Ha total
103
20
2015
2014
2014
2014
2014
Table 2: Overview of main characteristics of cases
The Design of the Innovation Campus Maturity Model
Scope
As noted, our maturity model relates to innovation campuses. We define an innovation
campus as a physical location with high quality real estate and shared facilities, with
the aim to foster open innovation practices supported by an active policy to facilitate
knowledge exchange, collaboration, and new product development (Boekholt et al.,
2009). Our maturity model differs from others in the innovation management literature
by taking the innovation campus as the level of analysis, instead of the firm-level. This
makes our model useful for all stakeholders of the innovation campus, such as the focal
organization, participating organizations, the campus support organization and
governmental bodies.
The purpose of the model is descriptive. The model can serve as an audit tool to
provide a common understanding and to build consensus among the different
stakeholders. It is intended as an improvement tool, to identify gaps in capability
development, rather than a normative performance measurement tool (Essmann & Du
Preez, 2009; Fraser et al., 2002). Our descriptive maturity model is a first, yet necessary,
step towards a prescriptive or comparative maturity model (De Bruin et al., 2005).
Maturity levels
The number of maturity levels generally varies between three and six (Fraser et al.,
2002), where an increasing number of levels provides a more fine-grained
understanding of maturity, but also increases complexity in delineating exactly the
boundaries of the stages (Fraser et al., 2002). The design of the model has to meet the
users’ needs and requirements. We chose four levels of maturity for the following
reasons. First, four stages are sufficiently distinctive and can be well-defined without
getting unnecessarily complex . Second, four levels yield a logical progression through
the stages (De Bruin et al., 2005). An innovation campus can be considered as an eco-
system, which has a similar evolutionary character concerning four life-cycle stages of
innovation clusters: birth, growth, maturation, adaptation (Arthurs et al., 2009; Martin
& Sunley, 2011; Menzel & Fornahl, 2009) (and the fifth decline which we do not
consider here), which corresponds well with a logical sequence of maturation. Third,
the use of four stages in maturity levels has been used in innovation literature before,
for instance by Arthurs et al. (2009) and Kahn et al. (2006).
In addition, the four levels are chosen based on repeatability and effectiveness
(Arthurs et al., 2009; Fraser et al., 2002), which corresponds well with Paulk et al.’s
(1993) maturity definition as “the extent to which a specific process is explicitly
defined, managed, measured, controlled and effective”.
- Level one: Emergence: a focal firm has real estate property and starts to develop an
innovation campus. The concept is developed and the first residents are attracted. The
focus is mainly on real estate development and on creating a physical infrastructure.
Innovation processes are ad-hoc and incidentally managed by a rudimentary support
organization.
- Level two: Development: the number of residents increases. The focus on real estate
management starts to shift towards business and new product development. The support
organization invests in linking organizations to stimulate knowledge sharing and
opportunity recognition. Some common activities among campus residents are
developed, but not systematically managed.
- Level three: Established: the number of residents has reached a critical mass. Next to
the large firms, there is a mixture of SMEs, start-ups, and knowledge institutions. Spin-
offs from campus firms are the proof of innovative and entrepreneurial collaborations
and new business development. The campus supporting organization manages
processes systematically. The campus is widely acknowledged and recognized as an
innovation eco-system.
- Level four: Transformational: the campus residents and the campus organization are
flexible to transform to changing technologies and market developments. The vision
and strategy can be adapted to avoid stagnation and decay.
Dimensions
To determine the dimensions of innovation campus maturity, we conducted a literature
review on innovation campus and clusters’ development indicators and critical success
factors. Arthurs et al. (2009) developed a set of six main factors and sixteen sub-factors
to indicate cluster development of Canadian innovation clusters. Tavassoli and Tsagdis
(2014) reviewed the literature on ICT innovation clusters’ critical success factors and
identified 15 factors. Su and Hung (2009) identified five key success factors in bio-tech
clusters. BCI (2009, 2014) used four dimensions to define innovation campuses in the
Netherlands, and Enkel et al. (2011) distinguished three dimensions for open innovation
maturity models. We analyzed these critical success factors and dimensions from
literature, which finally resulted in nine dimensions (see Table 3):
1. Involving an evident knowledge carrier/strong anchor actor: is embodied by the
presence of a large evident knowledge carrier who is physical and substantially
involved and acts as the ‘anchor tenant’ at the campus, thereby taking responsibility
and providing structure. There are several types of potential knowledge carriers, such
as: a multinational, a university, an academic medical centre or a large research
institute. The term ‘evident’ illustrates that the company or institute is of substantial
size and has a strong reputation in relation to a specific theme or technological field.
2. Establishing and maintaining a support organization: an intermediary campus
organization that facilitates campus promotion, establishes campus cohesion, provides
guidance (finance, intellectual property, human resource management), manages shared
facilities, stimulates inter-firm collaboration, provides training and coaching to
entrepreneurs.
3. Attracting diversity of campus residents: a mix of thriving start-ups, SMEs,
multinationals and research institutes is important to have a continuous inflow of new
knowledge and to create dynamism. The diversity mix is critical since the residents
need to have sufficient absorptive capacity (Cohen & Levinthal, 1990) to capture value
from new knowledge.
4. Developing a clear vision and brand name: a clear vision and strong brand name
attracts campus residents that fit the campus’ profile, investments and venture capital,
and skilled workers. A clear and shared vision among the campus residents creates
commitment to the campus’ longer term strategy, and offers legitimacy to external
partners and policy makers.
5. Attracting a talented workforce: without a talented workforce, an innovation campus
cannot develop and mature. Next to brand name and image, quality of place is important
(Florida, 2005), but also close connections to schools and universities to scout talented
and creative students.
6. Developing an open innovation culture: this concerns two aspects: 1) investing in an
entrepreneurial and innovative climate, with high R&D capacity (knowledge, skills,
facilities), and 2) investing in an open climate, that fights the ‘not-invented-here-
syndrome’, and stimulates knowledge sharing among the campus residents and with
regional and international partners.
7. Providing access to finance/venture capitalists: this is essential (especially for start-
ups) for stimulating innovation. Financial support can be provided by the government,
financial institutions, venture capitalists and business angels among others.
8. Creating and maintaining campus cohesion: campus residents take part in a small
society. They work and live in close geographic proximity, which requires to align each
other’s and campus’ interests. Cohesion is fostered through clear communication about
vision and strategy, creating a campus identity, and building trust among the residents.
9. Creating and maintaining physical infrastructure: a good physical infrastructure
includes good accessibility and basic services, such as energy and communication.
Besides, the campus can also offer shared facility services, research laboratories and
test facilities.
From the literature review, we derived two other success factors, which we consider to
be contingency factors. The first is regional attractiveness, which relates to business
climate (quality of local lifestyle, relative costs, relative regulations and barriers), local
availability of suppliers and customers, government policies and programs, and the
environmental competitiveness. The second is the extent to which there is pre-existing
knowledge, for instance in certain technologies, due to established firms or knowledge
institutes. This factor can be an important enabler to start an innovation campus.
Dimension in maturity
model
Arthur et al. (2009)
(Innovation cluster policy)
Tavassoli &
Tsagdis (2014)
(ICT clusters)
Su & Hung (2009)
(biotechnology
cluster)
BCI (2009, 2014)
(innovation campus)
Enkel et al. (2011) (open
innovation maturity
model)
1. Involving an evident
knowledge carrier/strong
anchor actor
Responsibility and structure
Strong actor
Evident knowledge
carrier
2. Establishing and
maintaining support
organisation(s)
Innovation and firm support;
Business and product
development capabilities;
Community support
Support
organizations
Internal processes and tools
(IP protection, managing
processes)
3. Attracting diversity of
campus residents
Critical mass ( number and
size of cluster firms, number
of spin-off firms),
Dynamism (growth of new
firms and firm growth)
Entrepreneurship;
Growing company
base
Entrepreneurship;
Strong science-
industry base
Partner capacity
(collaboration forms and
structures; absorptive
capacity)
4. Developing a clear
vision and brand name
Identity (external awareness)
Right vision; Brand
name
5. Attracting a talented
workforce
Human resources (access to
qualified personnel, local
sourcing of personnel)
Staff attraction
6. Developing an open
innovation culture
Export orientation; Internal
linkages; Innovation (R&D
spending, relative
innovativeness, new product
revenue)
Networking
(collaboration);
Innovation/R&D
capacity;
Entrepreneurship
Networking
Active open
innovation; Focus on
R&D/innovative
activities
Entrepreneurial climate
7. Providing access to
finance/venture
capitalists
Local availability of capital
Finance providers
Finance supporting
mechanisms
8. Creating and
maintaining campus
cohesion
Identity (internal awareness)
Trust; Geographical
proximity
Social capital
Partner capacity
(commitment and trust;
institutionalization and
reputation of partners)
9. Creating and
maintaining physical
infrastructure
Transportation (quality of
local and distant
transportation)
Physical
infrastructure
High-end physical
business locations and
research facilities
Internal tools and processes
(research center and shared
facilities)
Table 3: Overview of literature to identify capability dimensions
Challenges and Success Factors in Maturity Stages
In Table 4, we listed the success factors as assessment criteria for each dimension in
each maturity stage. These assessment criteria are the result of the literature review and
the empirical evaluation with the campus’ experts. Below we will discuss the most
relevant findings from the experts’ evaluations.
Leiden Bio Sciences Park
Leiden could be classified as being in the development stage. The first two decades
were characterized by organic growth in the emergence and development stages. Its
main success factors are the strong presence of the Leiden University and the Leiden
University Medical Center as main sources of new knowledge, technology and students.
Their presence, together with a clear focus on life sciences, attracted large multinational
firms and multiple start-ups.
However, these large multinationals also have a downside. An example is one
large multinational with a strong presence at the campus. This multinational attracts a
large share of the available talent and acquires many of the promising technologies. As
a reaction, other campus members aim to protect their assets and intellectual property,
which does not stimulate trust and campus cohesion. In addition, the campus struggles
with its support organization. Currently, the campus has several organizations, such as
1) the campus foundation, 2) the park management, maintenance and joint facilities, 3)
a start-up incubator, and 4) a knowledge exchange center. The campus management is
currently investigating the opportunities to establish one support organization.
Next to lack of a strong and effective support organization and an
underdeveloped open innovation climate, another challenge is the limited access to
finance. Especially in bioscience, where technology development is costly, access to
financial resources is important. Since universities have limited investment funds for
new business development, private or governmental funds are needed. The absence of
a regional investments fund was found to be a disadvantage in comparison to other
regions.
Wageningen campus
This campus emerged from Wageningen University, which has a long lasting
international reputation on agriculture, food and health. This combination of the
university as eminent knowledge carrier and the strong brand name as an agriculture
center of excellence, together with clear vision, appeared to be an important success
factor in the early days.
Now, we position Wageningen campus in the development stage. One of the
main reasons is that the open innovation and collaboration activities are only starting to
develop. According to the expert, many companies settled on the campus to acquire
academic knowledge, to attract talented students and staff, and to profit from the
Wageningen brand. Since campus support and real estate management is still governed
by the university, an independent campus support organisation is lacking. This strong
position of the university might hamper further open innovation practices, due to
different interests and limited campus cohesion. For instance, the expert indicated that
universities have to publish their findings, while companies try to protect these for
future commercialization.
Kennispark Twente
The University of Twente (founded in 1964) was the first Dutch university that was
developed as a university campus with educational, living, working and sporting
facilities at one location. The adjacent business & science park became the natural
habitat of the start-ups that emerged from academic research. However, there was still
a perceived distance between academia and business. This resulted in the formation of
the Kennispark Twente Foundation, as a joint initiative of two educational institutions
(among which the University of Twente) and three local and regional governmental
bodies. A fly-over between the university campus and the business & science park was
replaced by a level road-junction to emphasize unity and close physical proximity to
each other. The Kennispark Twente Foundation acts as an independent intermediary
organization and actively supports and guides start-ups and spin-offs from the
university. We position Kennispark in the development stage.
Although the campus has a wide variety of organizations, such as large firms,
SMEs, start-ups, and an university, it is still difficult to establish new collaborations,
co-developments and joint-initiatives. In contrast to the other four cases, the Kennispark
innovation campus does not have a clear technological focus or strong vision yet.
Although, the University of Twente en Kennispark campus create most start-ups in the
Netherlands, access to financial services for these start-ups is still problematic, and
holds back further developments.
High Tech Campus Eindhoven
The High Tech Campus Eindhoven is the only case that we would position in the
established maturity stage. Originated as the Philips campus, Philips management
invested large amounts of money (500 million euros), to give the campus a kick-start.
Owing to a clear vision and the campus’ high tech profile, a diversity of campus
residents were attracted, such as global firms, research institutes, service companies,
SMEs and start-ups. After some years, a separate campus support organization HTCE
Site Management was formed, which was responsible for maintaining and expanding
the facilities, ensure campus promotion, improve campus cohesion, stimulate new
business development and attract new residents. In 2012, Philips sold the campus to
Ramphastos, which led to new investments and full independence of the supporting
organization. According to the expert, this support organization is one of the key
success factors by organizing hundreds of events per year, varying from arranging small
direct partnerships between firms till large high-tech conventions to share new
knowledge. Further, the campus profile is heavily guarded, and potential residents can
be refused.
The expert stated three main challenges during campus development. The first
was the dominant position of Philips during the emergence and growth stage. Since the
initial idea of Philips was “to run the campus by and for themselves, through the
attraction of firms that ought to take over parts of Philips product developments”
(expert’s quote), other firm felt threatened. This did not contribute to campus cohesion
and an open innovation culture. Second, the support organization was also controlled
by Philips, which limited its effectiveness. Third, in 2012, the campus needed new
financial resources to sustain development, but Philips was not willing to contribute
any more. The latter problem was solved by selling the campus to Ramphastos.
Dimension in maturity model
Emergence
Development
Established
Transformational
1. Involving an evident
knowledge carrier/strong
anchor actor
Strong anchor actor (university or
multinational) taking a leading
role: Investing in the campus
intellectually, financially and
setting up the campus organisation.
Conduct selection and acquisition
of new organisations fitting the
profile. Building a plan. Focus is
on real estate management.
Maintaining strong campus
positioning, preferably aided by a
campus intermediary. Attract new
organisations from all different
levels focuses on stimulating the
campus. Beware of being to
dominant (deterring effect). Keep
investing if possible. Focus
gradually shifts from real estate
management to new business
development
Preferably transfer the ‘campus
power’ to intermediary/support
organisation to avoid dominance
deterring effect and to strengthen
intermediary. Ideally now, there
are more strong actors.
Other firms can become evident
knowledge carriers, through
changing technologies and market
developments. The initial evident
knowledge carrier is willing and
able to hand over its leading role to
other firms.
2. Establishing and maintaining
support organisation(s)
Often starts with the evident
knowledge carrier acting as an
(unnatural) support organisation
aiming to support campus start (see
evident knowledge carrier)
When founded, the support
organisation should aim to foster
external promotion, social campus
cohesion (through events, and
programmes) and to focus on
selection and acquisition of new
organisations. Beware of strong
actor dependency.
The campus intermediary, acts as
thriving innovation factor.
Responsible for dynamic company
base, providing guidance for firms,
linking innovation nodes, and
promotional activities. If possible
the organisation takes a proactive
role and searches for new
opportunities.
Facilitates the transition process,
by defining new vision and
strategy, attracting new kinds of
residents, establishing new
linkages internally and externally.
3. Attracting diversity of
campus residents
These years form the start-up
phase, making it difficult to already
built a dynamic company base.
Nevertheless, the initiator should
start building a clear (profile
fitting) company base. Real estate
interests may precede over
diversity interests.
Becoming increasingly important
due to campus dynamics. Selection
and acquisition fitting the profile
appears to be of great importance.
Possibly start with incubator or
firm guiding programmes. Do not
just focus on one type of
organisation, but aim to attract all
relevant parties.
Acknowledged as greatly
important, since all parties benefit
from one another (e.g. knowledge
spill overs, sharing facilities,
attracting talent, joint operations,
etc.). Aim to attract varying parties
keeping the campus ‘healthy’.
Firmly use the campus profile.
Grow sideways with campus
participants.
Transition to other type of
residents can conflict with existing
profile. Parting from residents that
do not fit the campus’ profile any
more can be difficult.
4. Developing a clear vision
and brand name
Setting a clear vision determines
future activities and prospects. A
too narrow vision might hamper
speedy campus development, too
broad vision might weaken brand
name. Brand name initially
depends on the reputation of
evident knowledge carrier.
Vision is guiding principle
throughout campus development.
during selection and acquisition..
Brand name shifts from evident
knowledge carrier to campus brand
name.
Vision is guiding principle, but
should perhaps be slightly altered.
Evaluate the profile based on
changes in the influencing
surroundings. Brand name is
clearly established and used in
promotional activities. The campus
is internationally recognized.
The vision needs change to adjust
to changing market developments
and technologies. The brand name
is changed accordingly.
5. Attracting a talented
workforce
Design of the campus facilities
support ‘quality of place’, such as
spacious and green surroundings.
Connections with universities and
schools are developed.
With more diverse campus
residents, new talent and creative
employees are attracted. Schools
and universities deliver students for
internships.
When sufficient trust is built,
trainees and employees can work at
different campus companies.
Schools and universities have
educational programs with campus
residents. International talent is
attracted.
A continuous inflow of talented
and creative students and
employees enable the transition to
new technologies and markets.
6. Developing an open
innovation culture
At the start, the evident knowledge
carrier needs to have an open
innovation culture and the
willingness and ability to share
knowledge. The selection of new
residents should also be based on
R&D intensity and an open
innovation culture.
Initiating new collaborations
between campus residents through
stimulating inter-firm relationships,
setting up meetings and
presentations, stimulating sharing
facilities and explaining the value
of (joint) innovation. The results
are some joint collaborations and
new products and services.
Open innovation is mainstream on
campus. New businesses and spin-
offs are the proof of joint
collaborations and effective open
innovation practices.
The open innovation culture
facilitates the transformation
process. Established campus
residents welcome new entrants.
7. Providing access to
finance/venture capitalists
Initially, the evident knowledge
carrier will have to invest in
infrastructure, facilities, promotion,
support, etc. Probably public funds
are needed to get started. Need for
finance through real estate
development could attract residents
that do not fit the profile well
Access to finance becomes
increasingly important for campus
participants, especially start-ups.
Landing of incubators and
accelerators is needed to facilitate
start-ups. Obstacles in obtaining
finances can greatly affect campus
development.
Access to finance for start-ups and
good business ideas is established.
Connections with venture
capitalists and financial
organizations are established. The
campus intermediary organisation
can play a role in attracting capital
for residents’ initiatives.
Transformation to new
technological domains requires
risk-taking capital providers. An
own campus fund can co-invest
and lower risks for capital
providers.
8. Creating and maintaining
campus cohesion
Aligning campus interests is of key
importance. Own interests of
evident knowledge carrier can even
foster distrust among other campus
residents or repel potential
residents. For academic-driven
campuses ‘cognitive distance’
impedes aligning interests of both
university and campus companies.
The supporting organization can
facilitate interest alignment and
cohesion by clear communication
of the vision and creating a campus
identity. Several campus events are
organized. Less power of the
dominant actor promotes trust and
campus cohesion.
Campus identity is established. The
campus residents have a general
consensus about the campus
direction, activities and
responsibilities. A strong support
organisation effectively bridges the
different campus residents’
interests.
Campus cohesion is endangered
by the transformation process. Not
all campus residents feel the same
need and urgency to change.
Different interests lead to tensions
among residents. The support
organization plays a key role in
maintaining cohesion and trust.
9. Creating and maintaining
physical infrastructure
The problem is mainly, what
comes first: infrastructure or
residents. The answer depends on
existing infrastructure and
investment capital. Basic
infrastructure needs to be in place.
Absence of high-end facilities can
hamper campus development.
New and existing residents have
general and specialized high end
laboratories, test labs, etc. which
can be used by campus residents.
Especially start-ups can benefit
from these facilities. The campus’
infrastructure, architecture and
landscaping are attractive.
The physical infrastructure is
highly valued and residents
increasingly use shared facilities..
Transformation requires new and
improved infrastructure (basic and
specific). Campus real estate is
modernized. New laboratories and
test facilities are created.
Table 4: Capability Maturity Model for Innovation Campus
Brightlands Chemelot Campus
The Brightlands Chemelot Campus was founded on the grounds of petrochemical
company DSM and can be assigned to the development stage. The Campus has three
stakeholders, which are DSM, the Province of Limburg, and the University of
Maastricht. From the start, DSM and the province have invested quite some money in
campus development. A key success factor was the willingness of the global companies
DSM and SABIC (to which DSM had sold part of its activities) to engage in open
innovation through co-creation and co-development. The vision was clear and
ambitious: to be a world leading innovation campus. In the process, a strong campus
support organization was formed, whose tasks is not only to manage the facilities and
infrastructure, but also to create added value through a pro-active attitude and
developing new business. This support organization creates dynamism through
programs, trainings and events. They even create their own start-ups and scout
companies all over the world for possible acquisition. Campus residents commitment
to these activities is high and firms provide high quality mentors to support other firms
and start-ups with finance, IPR, legal, management, etc.
Regarding the campus development, the expert mentioned two big challenges.
The first relates to the relatively old and dilapidated buildings and complementary
facilities at the start. This made attracting new residents quite hard and even resulted in
unsuccessful attempts to interest prospects. The second challenge was the dominant
attitude of DSM in the beginning. They regarded the campus as their own property,
which did not coincide with the open innovation vision, and chased prospects away.
DISCUSSION
This study aimed to find the success factors that determine innovation campus
development, and how these factors change during campus’ maturation. We addressed
this question by developing a maturity capability model. Building on existing literature
we derived dimensions and maturity stages, and we validated the model with expert
interviews from five cases.
From the cases we learn that the innovation campus comes in different
appearances, that they start from different origins and serve different goals. This could
lead to the criticism that a maturity model is inappropriate, due to the huge variety in
development trajectories (Pöppelbuss & Röglinger, 2011). However, dynamic
capability literature argues that, although capability development is organization-
specific and idiosyncratic to some extent, there are also commonalities that can explain
why some organizations perform better than others (Eisenhardt & Martin, 2000). In our
cases we do observe such commonalities.
First, in the transition from the emergence stage to the transformation stage the,
role of the evident knowledge carrier changes. In the early stages, this anchor tenant is
needed to initiate campus development, provide funding, and to attract new residents.
However, when this anchor tenant becomes too dominant, it might scare off potential
residents. In the later stages, the anchor tenant needs to allow room for other evident
knowledge carriers to develop, to strengthen the campus profile, to allow more diversity
among residents, and to become less dependent on the initiating organization.
Second, a strong, active and independent support organization is important for
innovation campus development. This organization not only takes care of campus
management and facilities, but also actively facilitates open innovation activities, such
as campus meetings, conferences, and bootcamps. Particularly when the support
organization is independent from the evident knowledge carrier, it plays an important
role in establishing trust and campus cohesion.
Third, attracting a diversity of campus residents is essential for campus
development. All cases show that a good mixture of large firms, SMEs, start-ups,
knowledge institutes, and commitment of governments, helps to stimulate open
innovation practices. Good selection of residents is key, since it is difficult to remove
residents, particularly when they have become owner of the real estate. Here, the
challenge for early stage campuses is to not to give in on short term real estate profits,
but to bear long term innovation capabilities in mind. This requires the power to say no
to prospective residents in the early stage where capital is more than welcome.
Fourth, a clear vision and good brand name attracts large capital-intensive
organizations, attracts talented and creative people, attracts creative start-ups, and
clearly presents its distinctive character compared to other campuses. The evident
knowledge carrier’s reputation can be important at the start (e.g. Philips or Wageningen
University), but only when this organization embraces the open innovation
management paradigm. After the initial developments, the campus needs to establish
its own identity that is internally and internationally recognized.
From the expert interviews, these four dimensions were all listed among the
most important and most critical ones for innovation campus success. Therefore we
derive the first proposition:
Proposition 1: The capability to (1) involve an evident knowledge carrier, (2)
establish and maintain a support organization, (3) attract a diversity of campus
residents, and (4) develop a clear vision and brand name, are necessary
conditions for effective campus maturity development.
The experts acknowledged the relevance of the other maturity factors as well. Although
these factors are not necessary to develop, they do stimulate and facilitate the
maturation of the innovation campus and a lack of these capabilities could slow down
campus development. Based on this observation we derive the second proposition:
Proposition 2: The capability to (5) attract a talented workforce, (6) develop an
open innovation culture, (7) provide access to finance/venture capitalists, (8)
create and maintain campus cohesion, and (9) create and maintain a physical
infrastructure, are sufficient conditions for effective campus maturity
development.
Contributions to Theory and Practice
This study is a first attempt to explore the maturity development of a relatively new
innovation eco-system: the innovation campus. Our first contribution to theory and
practice is that we defined the boundaries of an innovation campus compared to other
innovation-eco-systems, such as incubators, business & science parks, and innovation
clusters. The innovation campus concept is emerging and well delineated boundaries
contribute to adequate theory development.
Second, we developed a maturity capability model at the eco-innovation system
level. This extends the many existing maturity levels at firm-level. Our model can be
used by innovation campus management to map their current situation and to identify
the capabilities that need further attention (Fraser et al., 2002). Our distinction between
necessary and sufficient capabilities can assist decision makers to set the right priorities
to make campus development effective and efficient as possible. This distinction in
relative importance of critical success factors is rarely discussed in innovation eco-
system literature, such as innovation clusters (Tavassoli & Tsagdis, 2014).
Third, our capability maturity model shows that the critical success factors
change over time and during maturity development. Only a few others studies have
addressed this issue recently in innovation clusters (e.g. Tavassoli & Tsagdis, 2014),
and here we notice some commonalities and differences. Our identified sufficient
capabilities coincide well with the critical success factors that Tavassoli and Tsagdis
(2014) identified to be relatively stable during innovation cluster development.
However, where they argued that importance of other critical success factors, such as
vision, strong actors, support organizations and a growing company base decrease
during the cluster’s life-cycle, we argue that these capabilities remain important in all
stages, yet that their role changes, and some may even become more important. For
instance, the role of the evident knowledge carrier changes from initiator in the
emergence stage to facilitator in the maturity stage. Only in the transformation stage,
its importance diminishes. Further, the role of the supporting organization becomes
even more important during maturity growth in facilitating and stimulating open
innovation culture and campus cohesion. These contradictory findings once again
illustrate that the innovation campus has its own characteristics and dynamics, which
are different from innovation clusters.
Fourth, since the innovation campus develops over time, roles and structures of
the evident knowledge carrier, campus residents, supporting organizations,
governments an finance providers change as well. This means that the actors need to be
aware of the campus’ maturity stage in order to align their roles and activities. Our
maturity model can assist the campus’ stakeholders in achieving a common
understanding of the challenges and success factors that are currently at play, and to
take appropriate action accordingly (Essmann & Du Preez, 2009).
LIMITATIONS AND FUTURE RESEARCH
This study is not without limitations. First, the empirical part of this study was
conducted in the Netherlands. Although there seems to be consensus in the Western
world about key success factors in new product development (Kahn et al., 2012),
caution should be taken to generalize our findings. Therefore, we encourage studies on
innovation campuses in other countries, to assess the critical success factors and their
relative importance in each maturity stage.
A second limitation is that we developed the maturity model for descriptive use.
However, the model can be refined for prescriptive and comparative use. To enable
benchmarking, the next step is to develop more fine-grained measurement items for
each dimension and maturity stage (Pöppelbuss & Röglinger, 2011). Then, studies in
several different contexts, as well as more quantitative studies are needed to enable
comparison of capability development and performance of different innovation
campuses (De Bruin et al., 2005; Essmann & Du Preez, 2009). We hope that our study
provides a solid foundation for these follow-up steps.
Third, since the innovation concept is relatively new, we did not have any cases
in the transformation stage yet. While many life-cycle theories follow a deterministic
approach from birth to decline, we follow an adaptive approach in which eco-systems
can transform to adjust to new circumstances (Martin & Sunley, 2014). This would call
for more attention to context-specific characteristics and would warrant more
longitudinal case studies.
A fourth limitation is that we propose necessary and sufficient capabilities based
on qualitative results. Due to the aim of this research and the limited number of cases,
we did not perform any quantitative tests of these propositions. However, we encourage
studies that would use a set-theoretical approach (Fiss, 2007, Ragin, 2008) with a
qualitative comparative analysis (Rihoux & Ragin, 2009). We strongly believe that such
holistic research method accounts for the complex relationships between the
capabilities, and also provides empirical evidence for the relative importance of the
capabilities in each maturity stage.
REFERENCES
Arthurs, Cassidy, Davis and Wolfe (2009). Indicators to support innovation cluster
policy. International Journal of Technology Management, 46 (3-4), 263-279.
BCI (2009). Fysieke investeringsopgaven voor campussen van nationaal belang. Den
Haag: Buck Consultants International.
BCI (2014). Inventarisatie en analyse campussen. Den Haag: Buck Consultants
International.
Boekholt, Nagle and Zuijdam (2009). Campusvorming. Studie naar de meerwaarde van
campussen en de rol van de overheid met betrekking tot campusvorming.
Amsterdam: Technopolis.
Chesbrough (2006) Open innovation: A new paradigm for understanding industrial
innovation. In Open innovation. Researching a new paradigm, eds. Chesbrough,
Vanhaverbeke and West, 1-12. Oxford: Oxford University Press.
Chiesa, Coughlan and Voss (1996). Development of a technical innovation audit.
Journal of Product Innovation Management, 13 (2), 105-136.
Cohen and Levinthal (1990). Absorptive capacity - a new perspective on learning and
innovation. Administrative Science Quarterly, 35 (1), 128-152.
De Bruin, Freeze, Kaulkarni and Rosemann (2005). Understanding the main phases of
developing a maturity assessment model. Australasian Conference on Information
Systems (ACIS), Sydney, Australia,
Eisenhardt and Martin (2000). Dynamic capabilities: What are they? Strategic
Management Journal, 21 (10/11), 1105-1121.
Enkel, Bell and Hogenkamp (2011). Open innovation maturity framework.
International Journal of Innovation Management, 15 (6), 1161-1189.
Essmann and Du Preez (2009). An innovation capability maturity model - development
and initial application. International Journal of Social, Behavioral, Economic,
Business and Industrial Engineering, 3 (5), 382-393.
Fiss (2007). A set-theoretic approach to organizational configurations. Academy of
Management Review, 32 (4), 1180-1198.
Florida (2005). Cities and the creative class. New York, NY: Routledge.
Fraser, Moultrie and Gregory (2002). The use of maturity models/grids as a tool in
assessing product development capability. IEEE International Engineering
Management Conference, 244-249.
Kahn, Barczak and Moss (2006). Perspective: Establishing an NPD best practices
framework. Journal of Product Innovation Management, 23 (2), 106-116.
Kahn, Barczak, Nicholas, Ledwith and Perks (2012). An examination of new product
development best practice. Journal of Product Innovation Management, 29 (2), 180-
192.
Kazanjian and Drazin (1989). An empirical test of a stage of growth progression model.
Management Science, 35 (12), 1489-1503.
Kooij (2015). Object formation and subject formation: The innovation campus in the
Netherlands. Planning Theory, 14 (4), 339-359.
Kooij, Van Assche and Lagendijk (2014). Open concepts as crystallization points and
enablers of discursive configurations: The case of the innovation campus in the
Netherlands. European Planning Studies, 22 (1), 84-100.
Maier, Moultrie and Clarkson (2012). Assessing organizational capabilities: Reviewing
and guiding the development of maturity grids. IEEE Transactions on Engineering
Management, 59 (1), 138-159.
Martin and Sunley (2011). Conceptualizing cluster evolution: Beyond the life cycle
model? Regional Studies, 45 (10), 1299-1318.
Menzel and Fornahl (2010). Cluster life cycles-dimensions and rationales of cluster
evolution. Industrial and Corporate Change, 19 (1), 205-238.
Moultrie, Clarkson and Probert (2006). A tool to evaluate design performance in SMEs.
International Journal of Productivity and Performance Management, 55 (3-4), 184-
216.
Paulk, Curtis, Chrissis and Weber (1993). Capability maturity model for software,
version 1.1, Technical report cmu/sei-93-tr-024, esc-tr-93-177. Pittsburgh,
Pennsylvania: Software Engineering Institute.
Pöppelbuss and Röglinger (2011). What makes a useful maturity model? A framework
of general design principles for maturity models and its demonstration in business
process management. ECIS 2011 Proceedings, Paper 28.
Ragin (2008). Redesigning social inquiry. Fuzzy sets and beyond. Chicago: University
of Chicago Press.
Rihoux and Ragin (2009). Configurational comparative methods. Qualitative
comparative analysis (QCA) and related techniques. Thousand Oaks: SAGE
Publications, Inc.
Su and Hung (2009). Spontaneous vs. Policy-driven: The origin and evolution of the
biotechnology cluster. Technological Forecasting and Social Change, 76 (5), 608-
619.
Tavassoli and Tsagdis (2014). Critical success factors and cluster evolution: A case
study of the Linköping ICT cluster lifecycle. Environment and Planning A, 46 (6),
1425-1444.
Tödtling, van Reine and Dörhöfer (2011). Open innovation and regional culture-
findings from different industrial and regional settings. European Planning Studies,
19 (11), 1885-1907.
West and Bogers (2014). Leveraging external sources of innovation: A review of
research on open innovation. Journal of Product Innovation Management, 31 (4),
814-831.
ResearchGate has not been able to resolve any citations for this publication.
Article
Full-text available
This paper investigates the variation in the importance of critical success factors (CSFs) in the evolution of the Linköping ICT (information and communication technology) cluster in Sweden. The international empirical evidence of CSFs in ICT clusters reported in the literature is systematically reviewed. On this basis an object-oriented conceptual model is developed encompassing fifteen CSFs; each attributed to one or more objects: for example, firms, institutions, entrepreneurs. The lifecycle of the Linköping ICT cluster is delineated and its stages segmented. The existence and importance of each CSF at each stage of the cluster lifecycle is established empirically on the basis of interviews with key experts. The main findings comprise a stage-specific group of CSFs whose importance varies across the cluster’s lifecycle stages with different patterns. The findings are aimed to stimulate policy makers and researchers alike to pursue further the line of enquiry developed in this paper. Keywords: ICT clusters, critical success factors, cluster lifecycle, cluster evolution
Article
Full-text available
Efforts continue to identify new product development (NPD) best practices. Examples of recognized studies include those by the Product Development and Management Association's Comparative Performance Assessment Study and the American Productivity Quality Center NPD best practices study. While these studies designate practices that distinguish top-performing companies, it is unclear whether NPD practitioners as a group (not just researchers) are knowledgeable about what represents a NPD best practice. The importance of this is that it offers insight into how NPD practitioners are translating potential NPD knowledge into actual NPD practice. In other words, are practitioners aware of and able to implement NPD best practices designated by noteworthy studies? The answer to this question ascertains a current state of the field toward understanding NPD best practice and the maturity level of various practices. Answering this question further contributes to our understanding of the diffusion of NPD best practices knowledge by NPD professionals, possibly identifying gaps between prescribed and actual practice.
Article
Full-text available
Purpose – The creation of well-designed products is widely acknowledged as an important contributor to company success. In principle, an effective design process, as part of the wider new product development (NPD) process, should result in well-designed products. This paper aims to present a tool to enable a design team to evaluate their design process in a workshop setting, with a view to targeting improvements. Design/methodology/approach – This tool is based on literature and has been iteratively developed using a mixed research approach, including detailed exploratory cases and application in action research mode. Findings – The resulting tool comprises two main components. A “process audit” based on process maturity principles, which targets the design-related activities in NPD. The process audit enables a company team to identify improvement opportunities in the design process. A product audit enables perceptions towards product characteristics to be assessed. The audit tool does not seek to be a benchmarking tool, but aims to capture “good design” principles in a form which is accessible and useful to practitioners. Practical implications – In use, the tool enabled managers to balance their concern with meeting budget and timescale demands against the importance of producing well-designed products. By first focusing on the tangible output of the design process – the product – practitioners are better able to understand the way in which design decisions influence product usability, desirability and producibility. Evidence from cases confirms the value and originality of this tool. Originality/value – Previous tools addressing product development have focused on strategic and managerial concerns. This novel assessment tool focuses explicitly on design issues, within the wider context of NPD.
Article
This article reviews research on open innovation that considers how and why firms commercialize external sources of innovations. It examines both the “outside-in” and “coupled” modes of Enkel et al. (2009). From an analysis of prior research on how firms leverage external sources of innovation, it suggests a four-phase model in which a linear process — (1) obtaining, (2) integrating and (3) commercializing external innovations — is combined with (4) interaction between the firm and its collaborators. This model is used to classify papers taken from the top 25 innovation journals identified by Linton and Thongpapan (2004), complemented by highly cited work beyond those journals. A review of 291 open innovation-related publications from these sources shows that the majority of these articles indeed address elements of this inbound open innovation process model. Specifically, it finds that researchers have front-loaded their examination of the leveraging process, with an emphasis on obtaining innovations from external sources. However, there is a relative dearth of research related to integrating and commercializing these innovations. Research on obtaining innovations includes searching, enabling, filtering, and acquiring — each category with its own specific set of mechanisms and conditions. Integrating innovations has been mostly studied from an absorptive capacity perspective, with less attention given to the impact of competencies and culture (including not-invented-here). Commercializing innovations puts the most emphasis on how external innovations create value rather than how firms capture value from those innovations. Finally, the interaction phase considers both feedback for the linear process and reciprocal innovation processes such as co-creation, network collaboration and community innovation. This review and synthesis suggests several gaps in prior research. One is a tendency to ignore the importance of business models, despite their central role in distinguishing open innovation from earlier research on inter-organizational collaboration in innovation. Another gap is a tendency in open innovation to use “innovation” in a way inconsistent with earlier definitions in innovation management. The article concludes with recommendations for future research that include examining the end-to-end innovation commercialization process, and studying the moderators and limits of leveraging external sources of innovation.
Article
A central question within planning theory is how changes between the relations of ‘grand institutions’ such as state, market and education influence the formation of objects ‘on the ground’. Drawing upon Foucault’s work, this article contributes to the understanding of these relations and argues that Foucault’s work provides a powerful set of tools to understand the formation of subjects and objects in spatial planning. It presents the case of the ‘innovation campus’ in the Netherlands, a model which originated from the ‘university campus’. Through an analysis of multiple campus-building ‘events’, the innovation campus appears as a model to entice and shape a new object: the entrepreneurial researcher.
Book
Configurational Comparative Methods paves the way for an innovative approach to empirical scientific work through a strategy that integrates key strengths of both qualitative (case-oriented) and quantitative (variable-oriented) approaches. This first-of-its-kind text is ideally suited for "small-N" or "intermediate-N" research situations, which both mainstream qualitative and quantitative methods find difficult to address. Benoit Rihoux and Charles C. Ragin, along with their contributing authors, offer both a basic, comparative research design overview and a technical and hands-on review of Crisp-Set QCA (csQCA), Multi-Value QCA (mvQCA), and Fuzzy-Set QCA (fsQCA).
Article
In this paper, we reflect on the role of concepts in spatial planning as reproductive devices of discursive configurations. In contrast to instrumentalist interpretations of spatial concepts, we start from the idea that spatial planning concepts are inherently political. Building on post-structuralist strands of thought, we discuss the theoretical concepts of “empty signifier” and “master signifier” and instead, after analysis, put forward “open concepts”, in order to grasp the richness of meanings and functions of seemingly vague concepts. This manoeuvre allows us to analyse the trajectory and performance of the spatial concept of the “innovation campus” in the Netherlands. This, in turn, opens the door to an analysis of planning concepts as crystallization points and enablers of discursive configurations. The Dutch innovation campus is shown to be a result of a confluence of various national and international discourses, an open concept, flexible enough to enable the continuation of the planning game within the familiar set of coordinates. Because of the particular set of expectations associated with the innovation campus, promising structural change, it is bound to produce disappointment.
Article
The biotechnology industry is at the heart of the fast-growing knowledge-based economy. One of the distinguishing characteristics of this industry is clustering. A cluster, like an organism, experiences origin, growth, and decline/reorientation. Our study constructs a framework to analyze biotechnology clusters with different origins, “spontaneous” and “policy-driven”, through their life cycles. We use the Bay Area in the United States and Shanghai Zhangjiang Hi-Tech Park in China as two cases to represent spontaneous and policy-driven biotechnology clusters. This study fills the gap in the literature by comparing these two types of biotechnology clusters in an evolutionary perspective. The key success factors of both biotechnology clusters are their own human and financial capital, but they differ in their underlying processes for creating and sharing these resources. The most fundamental differences arise from the impact of entrepreneurship, social capital and network patterns on the cluster's configuration.