The online publication details for this article are as follows:
Timeus, K. and Gascó, M. (2018) Increasing innovation capacity in city
governments: Do innovation labs make a difference?, Journal of Urban Affairs,
Online first. DOI: 10.1080/07352166.2018.1431049
Increasing innovation capacity in city governments:
Do innovation labs make a difference?
Krista Timeus, PhD*
ESADE Business & Law School
Carrer Sant Pere Mitja 21, 1-2
Dr. Mila Gascó
Center for Technology in Government and
Rockefeller College of Public Affairs & Policy
University at Albany
135 Western Avenue
Albany, NY 12203
Phone: +1 518 442 5244
Confronted with a range of complex challenges, cities and their governments are faced
with increasing pressure to improve their innovation capacity. In recent efforts to do so,
creating innovation labs within the city government’s organizational structure has become
a popular solution. This paper relies on the experience of the city of Barcelona to analyze
how innovation labs contribute to increasing innovation capacity. By applying an
analytical framework that includes the key elements of innovation capacity, the article
shows that innovation labs promote innovation capacity within a public organization
through their contribution to idea generation, to knowledge management, and to a human
resource strategy with a clear focus on innovation. However, the study also shows that
innovation labs can be too isolated from their parent organization, which limits their
overall impact on innovation capacity and questions the sustainability of innovation in
Innovation capacity, innovation labs, urban innovation, municipal government
Increasing innovation capacity in city governments: Do innovation labs make a
Over the past few decades, the challenges faced by municipal administrations, such as
urban growth or migration, have become increasingly complex and interrelated. In addition
to the traditional land-use regulation, urban maintenance, production, and management of
services, city governments are required to meet new socio-economic demands from
different actors regarding sustainability, education, equity and safety (Albrechts, 2006;
Naphade, Banavar, Harrison, Paraszczak, & Morris, 2011). Furthermore, today cities are
in strong competition for companies, tourists, and most of all, talent (Zenker, Eggers, &
Farsky, 2013). In the face of these issues, city governments are coming under increasing
pressure to become more innovative in how they deliver public services to improve the
urban environment and become more competitive (Cavenago, Trivellato, & Gascó-
As a response to these challenges, local governments around the globe are setting
up so-called “innovation labs” (i-labs) as a way to improve their innovation capacity
(Tõnurist, Kattel, & Lember, 2015). These innovation labs are usually embedded in the
executive government structure and can be inter-departmental (involving two or more
administrative departments) or intra-departmental (set up inside a specific administrative
department). They are particularly designed to ideate and develop innovations, and are
encouraged to experiment with various public sector innovation elements (Kattel,
Cepilovs, Kalvet, Lember, & Tõnurist, 2015). As of 2014, there were over 20 such teams
in governments around Europe, North America and increasingly in Africa and Asia
(Puttick, Baeck, & Colligan, 2014). Nonetheless, there is almost no academic research into
the role they play in increasing the innovation capacity of public sector organizations
(PSOs), especially at the municipal level. This paper addresses this gap directly by
answering the following research question: how do innovation labs contribute, if at all, to
increasing a city government’s innovation capacity?
To answer this question, this article proposes an analytical framework that allows
us to understand and assess how innovation labs attempt to increase a public organization’s
innovation capacity. The framework, which proposes four core organizational capabilities
that are necessary for innovation, is not only practically useful as an evaluative tool; it is
also analytically useful because it avoids the normative connotation that some of the
literature has given to innovation (De Vries, Bekkers, & Tummers, 2016) by asking
whether organizations have the capacity to innovate rather than how much they innovate.
This focus is important to avoid suggesting that more innovation is always desirable
(Jordan, 2013). Instead, the framework focuses on what capabilities are important when
organizations need to innovate.
Our paper contributes to the literature on public innovation and, in particular, to the
literature on public innovation labs. Innovation labs are considered a new organizational
arrangement within public sector organizations. The scarce literature addressing this topic
has focused on describing the characteristics and functioning of such labs. Yet, more
research is needed to assess their performance and contribution to an organization’s
innovation capacity. We aim at bridging this gap by proposing a framework to assess
innovation labs. In addition, we believe that this article also contributes to the public
innovation literature by clarifying the concept of innovation capacity, a term that has not
been clearly conceptualized in the literature. Finally, given the resources flowing into
public innovation, it is worthwhile to take these first steps in evaluating the impact of these
labs. The study focuses on innovation labs in city governments because city governments
have shown much interest in developing their innovation capacity in recent years, probably
due to the scale of challenges they face, including scarce financial resources and increasing
socio-economic pressures (Newman, Raine, & Skelcher, 2001; Walker, 2006).
The remainder of this paper is organized as follows: we start by examining existing
literature to explain the rise of innovation labs as a tool to increase governments’
innovation capacity. The following section introduces our proposed analytical framework
for studying innovation capacity. Next, the study context and the research design are
explained. Subsequently, we present and discuss the results of the fieldwork. Finally, we
describe the theoretical and practical implications of our findings and answer our main
research question. The article ends with a brief conclusion and a proposal of future research
INNOVATION LABS IN THE PUBLIC SECTOR: THE SOLUTION TO A
The aim of this article is to examine how innovation labs contribute, if at all, to public
organizations’ innovation capacity. We define innovation capacity as the set of
competences that public sector organizations have or need to utilize resources in order to
adopt or develop innovations (Anheier & Korreck, 2013; Lodge & Wegrich, 2014; Gieske,
van Buuren, & Bekkers, 2016). We borrow from the private sector literature to distinguish
between an organization’s innovation capacity and its innovation performance (Hurley &
Hult, 1998). Innovation performance is the result of an organization’s capacity to utilize
resources and external inputs to produce innovation. It can be measured, for example, in
terms of how many innovations an organization produces (Prajogo & Ahmed, 2006).
While the literature is not always clear on this distinction, using the terms interchangeably
(Prajogo & Ahmed, 2006), the capacity framework asks ‘is the organization able to
develop new solutions?’ as opposed to ‘how many innovations has the organization
pursued?’ The former question emphasizes inputs while the latter emphasizes outputs.
In the public sector literature, only a few works have made explicit the
differentiation between innovation capacity and innovation performance (Brown &
Osborne, 2013; Gieske et al., 2016). Those who have focused on innovation capacity have
explored the factors that contribute to increasing/hindering it at one of three levels of
analysis: the individual, the organization, or the organization’s network (Gieske et al.,
2016). At the individual-level, Ricard, Klijn, Lewis, & Ysa (2017), show that public
employees are more innovative when there is a work culture that supports trust in their
decisions and when they feel they will not be punished for risk-taking. Also, Bysted &
Jespersen (2014) and Bysted & Hansen (2015) found that public employees view
innovative work as “extra work”, and are thus less likely to engage in it when they have
other priorities. In addition, Alpkan et al. (2010) showed that employees would be more
likely to innovate if they perceived it as an important part of their career development.
Individual-level factors to encourage innovative behavior, therefore, tend to focus on
reducing risk-aversion and explicitly communicating that innovative behavior is valued.
At the organizational level, important factors include policies, strategies, protocols
and managerial activities that shape behavior (Gieske et al., 2016). At the network level,
factors that have been identified as important include characteristics of the environment
within which the public sector organization is located (such as the political and
administrative context, the legalistic work culture of the public sector, and the state and
governance traditions) and the extent to which the organization is connected to other
organizations and firms (Considine, Lewis, & Alexander, 2009; Bekkers, Edelenbos, &
Steijn, 2011; De Vries et al., 2016; Voorberg et al., 2017). These individual-,
organizational-, and network-level elements will be analyzed here in terms of how
innovation labs contribute to their development.
This article argues that shifting the discussion from innovation performance to
innovation capacity is important for two reasons: first, it gives public organizations a clear
framework for evaluating their current capabilities to address complex problems that
require innovative solutions. Second, it addresses a criticism that has been raised in the
public management literature, which is that much of the discourse on innovation has been
normative, treating innovations as something the public sector “should” pursue because it
produces “good” results (Kobrak, 1996; Jordan, 2013). However, there are many
arguments that challenge calls for “more innovation” (Jordan, 2013; Mariano & Casey,
2015). These are both from a moral standpoint (e.g. what happens when highly innovative
governments turn against their citizens?) and from a pragmatic standpoint (e.g. innovation
development can distract PSOs from their main tasks and cause it to lose mission focus)
(Kobrak, 1996). Using an analytical framework focused on innovation capacity can help
scholars and practitioners assess i-labs pragmatically by evaluating whether organizations
have the skills and competences to innovate when necessary, rather than counting how
many innovations they are producing regardless of their needs.
Innovation labs in the public sector
Although there is little research into innovation labs in the public sector, a small collection
of literature consisting of scholarly studies and several practitioner-oriented reports and
guides shows that innovation labs in the public sector are seen as an organizational tool for
improving local government’s innovation capacity (Bason, 2010; Puttick et al., 2014;
Tõnurist, Kattel, & Lember, 2017). A recent study by Tõnurist, Kattel and Lember (2017),
for example, suggests that innovation labs have become the preferred organizational tool
to introduce innovation because their structure and mandate allows them to circumvent
certain characteristics of the traditional public administration that are often seen as
‘barriers’ to public innovation.
The ‘barriers’ to innovation capacity that are often cited in the public innovation
literature include claims about the administrative work culture and the structure of public
organizations. First, public sector professionals are thought to be reluctant to innovate
because the risk-taking behavior that innovation usually necessitates is often discouraged
in the public sector (Albury, 2005; Brown & Osborne, 2013). Additionally, it has been
argued that managers and other leaders must focus on operational and financial tasks and
lack the time and resources to manage innovation processes (Agger & Sørensen, 2014).
Public organizations are also accused of working in strict hierarchies and policy divisions
that impede cooperation across sectors and networks; this is said to reinforce silo mentality
and traditional roles, which are assumed to be characteristics that inhibit employees’ ability
to generate innovative ideas (Sørensen & Torfing, 2012). In sum, the traditional
characteristics of public organizations favor stability and predictability over innovation
In this context, the i-labs’ proposition is that by operating in a separate but adjacent
space from the rest of the organization, they are able to improve internal administrative
efficiency and drive cultural change (Tõnurist et al., 2017). Studies in the practitioner-
oriented literature (Bason & Carstensen, 2002; Bason, 2010) also show that i-labs are
allowed to experiment with new methods and focus expert knowledge on innovation
because they are somewhat shielded from the issues and constraints of the traditional
organizational structures. These studies suggest that governments see i-labs as a way to
introduce innovation capacity without disrupting the traditional bureaucratic structure
(Bason & Carstensen, 2002; Karo & Kattel, 2015, 2016).
Although there is very little research into i-labs’ structure, Tõnurist et al. (2017)
state that i-labs have an average number of six to seven people. In terms of their
composition, they employ a mix of people with backgrounds not traditionally found in the
public sector, such as designers, anthropologists, and social geographers, but also with
backgrounds from traditional fields, including political science, economics and law (ibid).
This non-traditional composition and their small size are thought to empower these labs to
introduce innovation in the public organization.
However, i-labs’ characteristics also raise concerns. Tõnurist et al. (2017) point out
that i-labs’ structure often isolates them from the rest of the organization. This would not
only limit the reach they have in the public organization but would also make them heavily
dependent on political support. As political priorities change, they can be easily dissolved
or their funding can be reduced. This aspect should also be taken into account when
analyzing their role in contributing to the innovation capacity of the public sector.
Because the literature on innovation labs is still at an early stage, it has not
examined the question of whether these labs actually enhance the innovation capacity of
their public sector organizations and how. Neither has it paid attention to labs that are
directly nested within a city government’s organizational structure. This article addresses
this gap in the literature by investigating how, if at all, innovation labs contribute to a local
government’s innovation capacity.
INNOVATION CAPACITY: AN ANALYTICAL FRAMEWORK
To analyze the contribution of innovation labs to the innovation capacity of public
organizations, we propose an analytical framework for analyzing innovation capacity that
consists of four organizational capabilities: 1) capabilities for idea generation, 2) a
knowledge management system to acquire and use new information, 3) a human resource
strategy focused on innovation, and 4) the intensity of technology use in the organization.
We propose these four capabilities based on the reviewed literature about the individual,
organizational and environmental antecedents to innovation and argue that these
capabilities allow organizations to address the limitations to innovation that have been
cited in the literature. The rest of the section offers research supporting how each of these
elements is important for innovation capacity.
The first element of innovation capacity is the ability to generate new ideas. This
is widely considered in the innovation literature as the first stage of the innovation process
(Howell & Boies, 2004; McAdam & McClelland, 2002). Among important factors that are
thought to impact an organization’s idea generation capacity are its available resources, its
internal structure, and its relations to external actors: in the public innovation literature,
research on innovation networks has shown that organizations will have greater innovation
capacity when their internal divisions and hierarchies enable communication across levels
(Considine et al., 2009), and when the organization participates in networks where
information and knowledge are exchanged (Ansell & Torfing, 2014). Similarly, people
will also be better able to develop new ideas when there are available resources (including
time, personnel and financial resources) (Singh, 1986; Damanpour, 1992) that can be
dedicated to innovation.
The literature has also argued that the ability to generate new ideas only contributes
to innovation capacity if there are also systems in place to manage knowledge in the
organization (Jantunen, 2005; von Hippel, 2009). As such, the second component of
innovation capacity is organizational knowledge management. Organizational knowledge
refers to the collective experiences, values, information and expert insight that becomes
embedded in an organization’s documents, routines, processes, practices and norms and
that frame how new experiences and information will be understood by the organization
and its employees (Davenport & Prusak, 1998). This literature argues that existing
organizational processes to acquire and utilize knowledge are paramount to an
organization’s ability to innovate (Jantunen, 2005) because they enable the organization to
acquire new knowledge from external sources, to identify unmet needs in the population
and to then mobilize the organization’s capabilities to address them (Teece, Pisano, &
Shuen, 2009). Especially given the recent focus on co-creation and co-production
(Voorberg, Bekkers, & Tummers, 2015), the public organization needs to be able to
process and utilize feedback provided by service users and other stakeholders, such as
partner organizations, political actors and civil society organizations (von Hippel, 1988).
Firms that have structures and processes for managing knowledge will thus have a greater
capacity to innovate (Jantunen, 2005).
The third cornerstone of innovation capacity is an innovation-focused human
resources strategy. Current research shows that employee attitudes are important
antecedents of innovation (Gieske et al., 2016). The claim here is that attitudes that favor
conservatism, conformity and risk-avoidance are an internal barrier for innovation in an
organization (O’Connor, Roos, & Vickers-Willis, 2007). According to existing literature,
human resource strategies that increase innovation capacity include: hiring talented staff
who are willing and able to pursue innovation (Meijer, 2014); hiring people from diverse
backgrounds and fields not typically found in the public sector, such as design and
anthropology, to increase the heterogeneity of experience and information, which can lead
to new ideas (Vissers & Dankbaar, 2002; Hess, 2007); providing continuous training (Kor
& Leblebici, 2005; Brogaard, 2017); and promoting a human resource strategy that
supports managed risk taking and encourages learning from errors (O’Connor et al. 2007).
Because innovation often requires a shift in existing work routines, it is often expected that
public professionals will resist it if they are not involved and motivated in the innovation
process from the early stages (Brown, 2007). It is, therefore, relevant to include an
innovation-focused human resources strategy in the capacity framework.
The fourth element of innovation capacity is the use of technology, especially
information and communication technology (ICT). According to existing studies,
businesses and organizations who report using ICT intensively are likely to be more
innovative than those who report using them less (Brynjolfsson & Hitt, 2000; Gago &
Rubalcaba, 2007). This is due to two characteristics of ICT that generally make it a driver
of innovation. The first is its ability to access, store and analyze large amounts of
information and data. This ability to access information and knowledge that is outside the
organizational and geographical boundaries can drive the generation of new ideas, and the
creation of networks that can accelerate the diffusion of innovations (Considine & Lewis,
2007; Lewis, Considine, & Alexander, 2011; Gieske et al., 2016). The second
characteristic of ICT is its ability to be used as a “platform” upon which services can be
created and delivered (Spiezia, 2011). For example, ICT platforms facilitate innovative
forms of interaction between users and government, e.g. through web applications or
mobile apps (Bekkers & Homburg, 2005, 2007). The degree of intensity to which
technology is used in the organization and the role it plays in the innovation process, are
therefore, important components of innovation capacity.
Of the four elements, technology is especially relevant for city governments, who
face growing pressure to develop online services, such as e-government platforms on
which citizens can complete many administrative tasks, such as filing taxes or applying for
permits (Caragliu, Bo, & Nijkamp, 2011). These services necessarily rely on ICT to
evolve. Nonetheless, including technology as the fourth cornerstone of innovation does not
imply that the result of innovation will necessarily be technological and limited to “digital
government” solutions or that innovation cannot happen in the absence of technology. It
does mean, however, that even for non-technological innovation, the use of ICT can
improve an organization’s capacity to innovate more systematically.
We acknowledge that “leadership” is absent from this analytical framework in its
abstract form. While the literature has argued that having leaders in the organization that
support innovation is an important driver of an organization’s innovation performance
(Tummers & Knies, 2013; Ricard et al., 2017), this article’s proposed analytical framework
views managerial support as a necessary but not sufficient factor for innovation: it is only
effective if employees have the competences and skills (the capacity) to act on the
leadership’s signals. Furthermore, leadership plays a more critical role when innovations
developed inside innovation labs need to be institutionalized across the rest of the
organization. Bekkers, Edelenbos, & Steijn (2011) refer to linking leaders who 1) act as
boundary spanners (Williams, 2002), reaching across different departments and units to
build relationships, interconnections and interdependencies, and 2) connect the political
realm with the innovations, gaining political support in the institutionalization process
(Considine et al., 2009; Voets & De Rynck, 2011). The framework, therefore, only
includes leadership to the extent that the four cornerstones are dependent on leadership and
Table 1: The four cornerstones of innovation capacity: an evaluative framework
Idea generation ability
- Do employees have time and resources to develop new ideas?
- Is there collaboration with diverse actors?
- Is there communication across policy divisions?
- Do employees feel ‘safe’ suggesting and testing new ideas?
- Are there systems for acquiring, storing and utilizing knowledge?
- Are there feedback- and learning- systems in place?
Human resource strategy
- Can managers hire talented and qualified staff?
- Is there a ‘zero error’ culture or is risk-taking encouraged?
- Do employees receive training for developing innovation?
Intensity in the use of
- How intensively do managers and employees utilize technology?
- How is technology shaping innovation processes within the local
- What is the role of ICT in innovation processes?
Table 1 shows how the different elements of the analytical framework are
operationalized in practice based on the literature summarized above. Using this analytical
framework, the article will explore how innovation labs contribute to a city government’s
The aim of this study is to analyze how innovation labs contribute to increasing city
governments’ innovation capacity. In order to do so, we examine an illustrative case of a
city government that has integrated innovation labs into its structure: the city of Barcelona.
Case studies show how particular practices are developed in particular organizations and,
therefore, help refine theory (Scapens, 1990). Qualitative case studies also allow us to
study the research question in depth while leaving room for unexpected interesting findings
that can form the basis for concrete hypotheses to be tested in future research (Marshall &
Rossman, 2011; Yin, 2013). This is particularly useful when there is little existing research
on the topic (Yin, 2013), as is the case here. A qualitative analysis of innovation labs in
Barcelona can help us understand how this organizational tool can contribute to developing
public organizations’ innovation capacity in an urban setting.
The Barcelona city government was chosen as a suitable case to analyze because
of its pioneering experience creating innovation labs in several of its administrative
departments. Innovation has actually always been at the core of the city government’s
modernization processes (Gascó, 2016). Yet, over the past few years, and particularly since
2011, an explicit political strategy of government-driven innovation based on technology
has been prioritised to address the city’s socio-economic challenges, clearly contributing
to Barcelona’s reputation as a city with high potential for innovation. The European Capital
of Innovation award (iPrize), which Barcelona won in 2014 “for introducing new
technologies to bring the city closer to citizens” (van der Voet, Ysa, Gascó, & Albareda,
2015), as well as the city’s position in global rankings on innovation, such as the
Innovation Cities Index 2016-2017, are only two examples of the city’s successful image
as an innovative city. We believe that this particular feature makes Barcelona a relevant
case for studying innovation capacity in a municipal setting. What’s more, using Tõnurist
et al. (2017)’s words, Barcelona’s pioneering experience may be considered “the new
common sense” and may give rise to isomorphism processes across other cities. We also
focus specifically on the period between 2011 and 2015, which is when these innovation
labs were created under Mayor Xavier Trias’ government and when they first developed
their innovation strategy. Thus, understanding how and why these labs were created within
the city government is key in terms of both practitioners’ implications and further research.
Barcelona City Council: European Capital of Innovation
Barcelona has considered itself a “city of transformation” for over 30 years and has
gradually introduced innovative technologies and programs into the municipal agenda over
this time. In 2011, these efforts were taken further when mayor Xavier Trias of the
Democratic Convergence of Catalonia party (a liberal, regionalist Catalonian party) came
into office and promoted an official, political strategy of government-driven innovation to
tackle the city’s socio-economic challenges (especially in light of the European Union
financial crisis). The strategy, promoted under the umbrella name “city of the people,”
had two main goals: to use new technologies to foster economic growth and to improve
the welfare of citizens (Kattel et al., 2015). With this political support, the municipal
government went from implicitly supporting external innovation to explicitly pursuing it
as a government strategy.
The innovation strategy rapidly led to organizational restructuring in some of the
main municipal departments. As of 2011, for the first time, directorates (or labs) of
Ciudad de las personas in Spanish.!!
innovation were created within the organization of four large administrative departments:
the Department of Urban Habitat; the Department for Quality of Life, Equality and Sports;
the Department for Economy, Business and Employment; and the Office of Culture,
Knowledge, Creativity and Innovation. Each of these innovation labs had a “director of
innovation” and a staff ranging from a few to a dozen people. The director was in most
cases appointed by the department’s political leadership either from the outside or from
within the departmental ranks and answered to the executive leader.
A central element of the city’s innovation strategy was the “smart city” paradigm.
This strategy promoted innovation with the goal of developing a new economy of
sustainable urban services (Gavaldà & Ribera-Fumaz, 2012). An example of an innovation
project promoted under this strategy was the Smart City Campus at 22@, a project that
transformed two hundred hectares of industrial land in the Poblenou district of Barcelona
into an innovative district offering modern spaces for the strategic concentration of
intensive knowledge-based activities in five strategic fields: media, ICT, energy, medical
technologies, and design. Another important goal of the innovation strategy was to increase
citizen participation in urban development. In line with this, the city government promoted
a “City Protocol”: a collaborative innovation framework that fostered city-centric
solutions, which benefited citizens and their quality of life. Such projects necessarily
required innovation capacity because they represented a new way of delivering public
services, which in turn, demanded an internal organizational transformation to change the
way services were designed and delivered. Some years after these efforts, we examine
whether and how these arrangements have contributed to increasing the city government’s
Data and methods
Data for the study was gathered between February and March 2015 through semi-
structured interviews with public sector professionals working on innovation in the
Barcelona City Council. The interview selection proceeded in two phases, as follows:
In the first phase, we interviewed people working directly in innovation labs to
gather qualitative data on how the labs worked. The first step was to identify the directors
of innovation in each of the administrative departments through online research. There
were four directors, only one of whom was not available for an interview but he directed
us to a high-ranking employee working in the innovation lab. Additional interviewees were
identified using the method of referral sampling. We asked the first four interviewees to
refer us to other colleagues in the innovation labs who “were important for innovation
processes”, who then referred us to a colleague, and so on. We stopped once referrals
became repetitive. This process yielded 16 names, of which we were able to interview 11
people. Because the innovation teams were still quite small, we were confident that we
interviewed a majority of people with authority over innovation.
In order to get a more balanced idea of how innovation labs contributed to the local
government’s overall capacity, we undertook a second interview phase. This time, we
started by identifying additional interview partners who were not working directly in an
innovation lab, but who could nonetheless assess their role in developing the city’s
innovation capacity. We expected that people in strategy and general management
positions, who played a role in creating and assessing the innovation labs, would be able
to complete the picture on their role in the context of the larger organization. We also
expected that other people working on innovation projects outside the labs would be able
to share a view of the labs’ role that we could compare or contrast to that of people inside
the labs to see if and how they differed.
The mayor’s office directed us to the “general manager for strategic projects”, who
coordinated the city’s innovation strategy. This person agreed to an interview and referred
us to three other contacts: an expert advisor from the private sector who sat on the
innovation roundtable and who was involved in assessing the innovation labs’ work, and
two managers who were responsible for strategic innovation projects, one in the
Department for Urban Habitat and another in the Department for Quality of Life, Equality,
and Sports. This amounted to four new interviews. Finally, we asked the coordinator of
innovation in the mayor’s office to review our sample and recommend new names. She
only suggested one additional name, who was unavailable for an interview. We are,
therefore, confident that our sample contains almost all crucial interview partners and that
we included close substitutes for those who were unavailable for an interview. In total, this
process yielded fifteen interviews. A summary of the interviewees by position in the
municipality can be found in the Appendix.
All semi-structured interviews were based on almost identical interview guides,
which were only slightly adapted to reflect the interview partner’s position in the
administration. All interviews were conducted and recorded by the same researcher in
person at the interviewee’s office, and they all lasted between 60 and 90 minutes. Interview
partners were first asked to explain their role in their administrative department and to
explain how they were involved with the city’s innovation strategy. Following these
introductory questions, everybody was also asked the following: 1) why were “innovation
labs” created in the Barcelona government?, 2) what are the hiring practices for the i-lab
and for the rest of the organization?, 3) how is risk managed in the innovation labs?, 4)
how does the innovation lab try to develop new ideas?, 5) is there collaboration with
diverse actors?, 6) what practices or systems are in place to manage and organize
knowledge?, 7) how intensively do managers and employees use technology?, and 8) what
is the role of ICT in innovation processes? Finally, everybody was asked to provide advice
to a hypothetical innovation manager just starting out in another City Council.
The recordings were transcribed and hand-coded line-by-line by a single person to
ensure consistency (Saldaña, 2015). Given how little literature there is directly on
innovation labs in the public sector, we used a mixed inductive/deductive strategy to code
the interview data: this entailed using the existing literature on the antecedents of
innovation to code data that matched existing concepts of innovation capacity (i.e. data
referring to resources, ICT, work routines, etc.), while also remaining open to new codes
emerging from the data, following a grounded theory approach (Glaser & Strauss, 2009).
The results of the coding process are summarized in table 2.
Table 2: Examples of codes used in the data analysis
Analytical framework dimension
Too busy to innovate
Innovation not a priority
Innovation seen as more work
Innovation seen as a trend
Political pressure to show results
Idea generation capabilities
Partnerships with outside actors/funding
Pilot projects/small trials
Strategy for selecting and evaluating projects
Ability to assess and select ideas
Brainstorming sessions/support new ideas
Knowledge management system
Resistance to change
Fear of failure and risk
Acceptance of failure
Bottom-up vs. top-down innovation
Isolated from organization
Dependent on continued political and financial support
Human resource strategy for
Smart city services
Technological innovations (as an output)
ICT in new services
Intensity of technology use
In rest of the
In rest of the
Generally speaking, the findings show that, in the case of Barcelona, innovation labs have
facilitated the development of at least three of the four main components of innovation
capacity. The information collected shows an ability to harness human resources for
innovation (e.g., by hiring new staff from outside the bureaucracy), to generate new ideas
(e.g., by having weekly brainstorming sessions), and to manage knowledge within the team
through staff rotation, regular meetings and a strategy for assessing and selecting new
ideas. There was less support for the idea that the labs have a particularly strong focus on
technology although two of the labs did utilize ICT extensively in their innovation
initiatives. This section discusses these findings.
Idea generation ability
The interviews reported that the innovation labs were able to pursue their own idea
generation strategies. Interviewees said that innovation labs provided space and resources
dedicated to innovation, which made it easier for people to develop, discuss and test new
ideas. An important factor was that the labs had their own budget specifically earmarked
for innovation, indicating clear political support. Dedicated funding allowed the labs to
have autonomy to make decisions, to have a flexible structure, and to implement a different
work process to develop and test new ideas without being excessively concerned with the
risks of failure. One lab director mentioned: “since our budget is specifically assigned to
encourage innovation, there is more liberty to use it even if the idea might fail. In the rest
of the organization, we would be under pressure not to waste public resources… Of course,
we have small budgets so that also limits how much we can lose if an idea fails.” Such
statements show that having their own budget, even a small one, frees innovation directors
from the traditional pressures and accountability measures that could limit innovation
outside of such labs.
Interviewees also stressed another important element: having a formal unit in the
organizational structure granted the innovation efforts some legitimacy within the
organization. The appointed “directors of innovation” were seen as having authority and
both financial and decision-making autonomy, and were thus, able to champion projects
and initiatives that might have otherwise been dismissed. Actually, all participants working
in the labs mentioned that their official position in such labs gave them some degree of
authority to pursue innovative projects, whereas outside the labs, innovation had to be
pursued more gradually. One director commented that many people in the city government
saw “innovation” as a strategy to cut costs and resources, so they rejected it out of fear for
losing their jobs. “For this reason,” he said, “it has been essential to have my own
innovation unit that allowed me to pursue projects independently of the other departments.
This meant I was not imposing any new agenda on them, but our municipal department
could pursue new ideas through my team. This is the only way the rest of the staff here
could accept us.”
Moreover, by creating a dedicated team for innovation, these labs enabled the staff
to develop a primary “task focus” on innovation, as opposed to as a secondary concern. In
contrast, interviewees reported that when innovation was promoted organically throughout
an organization, employees tended to see it as “additional work” that distracts them from
their main tasks, and thus, tend to reject it. As such, it can become a burden to the staff if
imposed from the top. One innovation director commented that precisely because
innovation projects were “additional work”, it was very important to have at least one small
team that was completely dedicated to it. Otherwise, she said, “the innovation projects will
be the first ones dropped when there are too many other priorities.” At the same time,
because they were just one unit, they did not have to conflict with the core tasks of the rest
of the organization.
Another driver of idea generation, according to the analytical framework, is
network participation. Interestingly enough, our analysis did not reveal that labs were
especially well connected to external actors. In fact, the interviews revealed a tendency in
the labs to work alone (as a team) on innovation projects without including other areas of
their parent organization. When the innovation labs were part of larger networks, it was
because the projects were large and necessarily required cooperation (such as in the
development of smart city infrastructure projects).
Knowledge management systems
Our findings show that innovation labs in Barcelona created knowledge management
systems for innovation. Having a strategy of innovation was a clear contributor in this
respect. The strategy guided the operations of the labs and helped systematize the process
of innovation, which according to the interviewees, included risk management. The
strategy also forced the innovation labs to have specific systems and processes in place to
absorb, organize and utilize new knowledge. Actually, three innovation labs explicitly
mentioned a system for assessing and selecting ideas, as well as for evaluating pilot
projects in the mid-term and final stage to gather the “lessons learned”. In one of the labs’
directors’ words: “the most important thing we have done is to establish a very clear
strategy for innovation. This did not exist before…[now] we only pursue ideas that fit into
that strategy. This really helps us to select projects and then to evaluate whether they have
met the objectives.”
Interviewees also mentioned more freedom to develop non-traditional systems for
managing knowledge, such as constant staff rotation within the unit to disperse knowledge
among the team. However, at the same time, it appears that innovation labs were not able
to disseminate this knowledge throughout their parent organization. The director of
strategic processes said: “the problem I have noticed is that now that we have an
innovation lab, everybody assumes that the lab will ‘take care’ of innovating instead of
trying to make sure that the lab is promoting innovation in the rest of the organization…
their work is isolated.” This shows that knowledge management worked but only in the
context of the lab.
Human resources strategy
The interview data show that innovation labs allowed the city government to develop a
human resource strategy that supported innovation. All three directors of innovation said
that they had authority to hire and train qualified staff that fitted with the labs’ innovation
goals. Regarding the composition of their team, all the directors mentioned their focus on
hiring “creative” people, ideally from different backgrounds. In one of the units, we
actually interviewed an engineer in computer science, a sociologist and an economist,
confirming such diversity. Similar diversity was also highlighted in the other units, arguing
that such diversity is advantageous for bringing new ideas and new paradigms to work.
This autonomy over staffing decisions allowed the directors of the labs to foster a
“culture of innovation”—a working environment in which experimentation, risk-taking
and some level of failure was accepted. One of these directors said: “to encourage
innovation you need people who are creative and who have an open mind… In the
innovation unit we have freedom to select those people for the team.” The directors also
said that being in a separate team from the rest of the organization also meant that their
staff could be completely focused on innovation tasks. In contrast, interviewees reported
that staff in the rest of the organization tended to see innovation as “extra work” or as
unimportant. Another lab director explained: “it is essential to have a team that is
completely dedicated to fighting for the innovation projects because it requires a lot of
work and it sometimes means going against the tide, so nobody does it unless it is their
main job.” Overall, the interviewees agreed that developing this human resource strategy
was possible because the i-lab had specific authority to hire its own staff and develop its
own work culture.
Intensity of technology use
Finally, we did not find any evidence of how technology contributed to increasing
innovation capacity. Interviewees in two of the four innovation labs (the one in the
Department for Urban Habitat and the one in the Department for Economy, Business and
Employment) mentioned high intensity of technology use, but their focus on technology
might have been due to their department’s inherent reliance on technological tools. In these
departments, many of the innovation projects mentioned by interviewees were related to
smart city services (e.g. smart traffic lights, light sensors on streets, parking meters linked
to apps) and the use of smart phone applications for citizen services such as personal
information platforms where people could register a change of address or request a tax
number. These inherently depended on ICT as a central component. Overall, however, the
rest of the interviewees did not emphasize a central role of ICT in the innovation process,
nor any influence on technology use in the rest of the city government, suggesting that
whether the innovation labs utilized technology for innovation depended more on their
organization’s overall policy goals and innovation strategy than on their specific
Isolation from rest of the administration
The data from the interviews also point to an unexpected finding related to innovation
capacity that was not anticipated in our analytical framework: several interviewees
reported that i-labs have not succeeded in promoting innovation capacities in the rest of
their parent organization; their skills and competences have remained largely contained
within their team. The person in charge of strategic processes, who considered his work as
being related to innovation but who did not work in an i-lab, explained the problem: “now
everyone [in my department] assumes that the i-lab will take responsibility for solving all
their problems in an innovative way instead of trying to use the i-lab as a way to train and
promote innovative behavior skills in the ‘normal’ departments of the
organization…people [in my department] now think they should not worry about
innovation because the i-lab will do it.” Innovation lab directors also referred to being
isolated from the rest of the organization. They said that they did not always felt accepted
by other departments and struggled to collaborate with them in innovation projects. When
asked about the impact of this situation on their role in the city government, interviewees
said they could be dissolved without systemic consequences to other departments, making
their survival very dependent on political and financial support.
This study aimed at analyzing the role and contribution of innovation labs in a city
government through an analytical framework of innovation capacity. The case study
evidence lends support to the first, second and third cornerstones of innovation capacity
offered in the article. First, the i-labs had the autonomy to hire their own staff from both
within and from outside the bureaucracy, and to create their own strategy for managing,
training and promoting staff without being bound to established procedures that apply to
the rest of the organization. This meant the director could have a team of people who were
more willing to take risks and who came from different backgrounds, and thus, create a
“culture of innovation” in the lab. Secondly, the i-labs could develop greater capacity to
generate ideas. This was in great part due to the fact that the team was dedicated primarily
to innovation so they could make that their core task. Autonomy over human resources
also meant that managers could hire people from different backgrounds to enrich the
diversity of ideas. Finally, the labs were also able to develop their own knowledge
management systems as a result of their relative autonomy within the organization. This
meant they could establish their own procedures to assessing, testing and selecting ideas,
bypassing traditional procedures that can be considered cumbersome for innovation
purposes. In the case of Barcelona, the interviews showed that these three elements were
particularly possible because the i-labs operated separately from the rest of the
organization. They could, therefore, overcome many of the commonly cited barriers to
innovation that relate to the traditional bureaucracy’s structure and procedures (Albury,
2005; Sørensen & Torfing, 2012; Brown & Osborne, 2013; Agger & Sørensen, 2014).
We can argue, therefore, that the role of innovation labs is to provide an
organizational structure where a strategy for human resources, idea generation and
knowledge management solely focused on innovation can be developed without requiring
major change in the rest of the organization. Innovation labs did not play a strong role in
introducing technology into the organization. In our specific case, technology was
important only when the results of the innovation were technological.
These findings fit in well with the previously mentioned literature on the
antecedents of innovative behavior in public organizations, which increases our confidence
in the results of the data analysis. At the individual level, recent studies show that public
employees are more innovative when there is an organizational work culture that fosters
trust in employees and that makes them feel they will not be punished for risk-taking
(Alpkan et al., 2010; Ricard et al., 2017). Further, innovative employees view innovation
as part of their core tasks and as part of their career development (Bysted & Jespersen,
2014; Bysted & Hansen, 2015). Not only are the findings of this research echoed in the
analysis of our data, they also help illustrate the mechanisms by which labs contribute to
an organization’s innovation capacity.
More generally, the findings suggest that innovation labs were, in the case of
Barcelona, a “design solution” to the commonly cited barriers to public innovation. Their
design as a sub-component of a larger administrative department allowed them to develop
competences solely focused on promoting innovation. To answer the research question,
their role in developing the public sector’s innovation capacity was to provide an
organizational structure within the public sector where innovation capacity could be
expanded without disrupting the traditional bureaucratic structures. This made them a
practical and seemingly effective way for governments and public managers to meet
external pressures to “be more innovative” while avoiding large-scale reforms. These
conclusions echo findings in the literature about the rationale for innovation labs (Bason
& Carstensen, 2002; Puttick et al., 2014; Tõnurist et al., 2017).
Similarly, our findings are aligned with the work of Schuurman & Tõnurist (2016),
who have shown that innovation labs have not yet managed to become an “organic”
component of the public sector. We found that because of their organizational design, labs
operated in isolation from the rest of the organization. While that was the source of their
ability to develop innovation capacity, as the interviews showed, it was also a potential
threat to their ability to disseminate knowledge to the rest of the organization. In this
regard, we identified at least three significant trade-offs for the city government to consider
regarding these labs.
The first trade-off we found is between developing a “culture of innovation” in
these labs (as a result of having greater autonomy over their human resource choices) and
becoming too isolated from the rest of the organization. In the eyes of most interviewees,
creating a separate team was positive for innovative projects because, in their opinion, the
more protected the innovation team was from the traditional organizational structures of
the organization, the more creatively it could think and experiment. This indicates that, in
fact, there was little incentive to introduce innovation strategies and encourage innovative
behaviors in every day work routines throughout the rest of the organization. One
interviewee quoted in the findings, who was in charge of internal processes, noted that
most of his staff referred their problems to the “innovation team” instead of addressing the
innovation potential directly. While innovation labs developed internal innovation
capacity, they did not necessarily transfer the skills and competences to the rest of the
organization. This is a concern that has been raised as well regarding innovation labs by
Tõnurist et al. (2017), who found that innovation labs are a long way from becoming an
organic component of the public sector.
The second trade-off is that while these labs are a relatively simple organizational
approach to introduce—as one director put it half-jokingly “it just required a new box to
be drawn in the organization chart”—they can just as easily be excised from those
organizational charts when innovation loses priority in the political agenda or, in the worst
case, when some blameworthy event happens calling the innovation agenda into question.
Despite the benefits of political support and dedicated funding, these might be short-lived.
As Tõnurist et al. (2017) have previously argued, the close relationship with the political
level is simultaneously an innovation lab’s greatest source of autonomy and its greatest
vulnerability. Interestingly enough, and although this is beyond the scope of our research,
which was limited to the years between 2011 and 2015, this has precisely been the case of
i-labs in Barcelona (Gascó, 2016). In fact, the new left-wing government, which came into
office in mid-2015 after the completion of the research, perceiving innovation as a
conservative, right wing agenda, decreased the flow of financial and human resources to
some of the innovation labs. Some of the directors who were politically appointed also left
the city government entirely or moved to other positions. This highlights the fragility of
innovation initiatives that are not fully integrated into the organization and undermines any
innovation capacity gains achieved.
Finally, we point out that having labs staffed with people solely dedicated to
innovation means that they can tend towards innovation for innovation’s sake. This can be
problematic because, as previous work shows, not all innovation is necessarily good or
useful (Jordan, 2013). With a team whose mandate is to innovate, there is no internal
pushback against spending resources on innovations whose risks might not have been fully
assessed. Moreover, the case of the government of Barcelona shows that, given this task
focus on “innovation”, labs were spending resources on developing and testing dozens of
pilot projects at any given time rather than focusing on scaling-up a few promising projects.
This limits the impact, sustainability, and institutionalization of innovation efforts and
questions whether labs are a sensible use of resources, especially if their lifespan is short.
In sum, this assessment of how innovation labs can develop the public sector’s
innovation capacity has a nuanced conclusion. Based on this study, it seems that given the
organizational and institutional constraints to public sector innovation described in the
literature, the role of innovation labs is to serve as a practical organizational method for
developing innovation capacity within public organizations. As such, seen in isolation,
innovation labs do make a considerable contribution to increasing innovation capacity.
However, their influence on the rest of the organization is limited: separating the
innovation team from the rest of the organization creates a strong, focused but isolated
innovation strategy but a crucial limitation for its widespread diffusion and sustainability.
CONCLUSIONS AND FURTHER RESEARCH
This article examined how innovation labs are used as an organizational arrangement to
develop the city’s innovation capacity. The article makes two theoretical contributions to
the literature: first, it offers an analytical framework for analyzing innovation labs’
contribution to innovation capacity. This framework encourages future work to shift the
debate from a normative focus on the innovation performance of public organizations to
the more useful analytical framework of whether organizations are able to innovate when
they need to. Second, our study provides additional evidence on the role of innovation labs
in a city government, showing that they aim at being a legitimate separate space within the
public organization that has the autonomy and resources to generate and test new ideas, to
develop its own knowledge management system for selecting and assessing innovations,
and to decide its own human resource strategy to select a staff that is open to
experimentation. In this respect, innovation labs become the tool political leaders use to
increase the organization’s innovation capacity without disrupting the rest of the
This case study has some limitations that should be considered. The main limitation
is the subjective nature of interview data and the inability to draw generalizable
conclusions from case studies. Yet, this limitation is mitigated by both the similarity
between innovation labs in the literature (Puttick et al., 2014) and the worthiness of
studying a pioneering example that may spark imitation processes in other cities, making
the findings of our study applicable to new contexts. Further, our research article did not
intend to produce generalizable findings but to make a theoretical contribution to the
literature on public innovation—namely, to focus the debate on how to build up city
governments’ innovation capacity—and to explore this argument’s soundness through an
Future studies can test this article’s conclusions in deductive studies designed with
generalizability in mind. For example, this article could inspire comparative research into
how innovation labs function across different political contexts to better understand how
sustainable such labs are in the long term. We also call for future research that uses this
framework to investigate the effectiveness of other methods aimed at improving an
organization’s innovation capacity (e.g. staff training, collaboration), and how different
organizational methods affect the type and scale of the innovations produced. Given the
increasing popularity of these labs, it is important to improve our understanding of their
contribution to innovation capacity in the public sector.
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The following is a summary breakdown of the interviewees by position in the
• 3 directors of innovation in the Department for Urban Habitat, the Department for
Economy, Business and Employment, and the Office of Culture, Knowledge,
Creativity and Innovation
• 8 staff members of the different “directorates of innovation”
• 1 external expert advisor to the innovation roundtable from the private sector
• 1 manager coordinating the roundtable for innovation in the mayor’s office
• 1 director of the “strategic processes division” in the Department for Urban Habitat
• 1 director of the “citizen agreement” project in the Department for Quality of Life,
Equality and Sports