Introduction

Co-creation links distributed sources of knowledge (Tanev et al., 2011) and conceptualizes innovation as the collaborative development between two or more stakeholders. Co-creation is also described as the act of creating value to the mutual benefit of two or more actors, beyond creating actual product or service innovation in a collaborative way (Allen et al., 2009). In particular, living labs are regarded as an emerging open innovation approach that involves multiple stakeholders, including users, to co-create value that eventually leads to innovation. Living labs are a new way of structuring research and help companies rapidly commercialize and upscale an innovation through validation and testing in real-life contexts (Leminen and Westerlund, 2012). Living labs offer a more reliable market evaluation than test markets, and they give users power in innovation processes (Salter and White, 2013).

To date, there exists no consistent and commonly accepted definition of the living lab. Instead of a general definition, several authors have suggested various key characteristics and principles or have tried to harmonize the different methods and tools (cf. Mulder et al., 2008). However, none of these efforts link the characteristics or principles of living labs to tangible outcomes. Therefore, the objective of this study is to: i) investigate the different building blocks of a living lab environment, and ii) examine how they contribute to the outputs of innovation projects launched within the lab, based on an analysis of actual living lab projects and experiences. To reach this objective, we first discuss the definition and basic characteristics of living labs. Second, we establish our framework, based on living lab literature, to detail the triangulation between environment, approach, and outcome in living labs. Then, we describe the research design constructed for a validation of our proposed framework based on data of four living labs, and we report the results and lessons learned from our empirical study. We conclude by providing guidelines for innovation practitioners and explaining avenues for future research.

Multiple Definitions of the Living Lab Concept

The living lab concept appeared in academic discussion in the 1990s, but really took off only in 2006 when the European Commission kicked off projects to advance, coordinate, and promote a common European innovation system based on living labs (Dutilleul et al., 2010). Several international organizations, representing industrial living lab initiatives in information and communication technologies (ICT), were founded in order to stimulate living lab research. The European Network of Living Labs (ENoLL) is the most influential initiative covering living labs from all over the world. Living labs were put forward as an institution to overcome the "European Paradox" or the gap between research leadership and commercial success of innovation. This increasing attention and the accompanying monetary support for living labs has unfortunately led to a wide variety of projects carried out under the "living labs" umbrella, and a proliferation of research papers that use the term “living labs” in a sense that is only loosely relate to the subject.

Despite the booming interest in living labs, they remain an under-researched area due to the lack of common understanding of the concept and its underlying mechanisms (Bergvall-Kåreborn and Ståhlbröst, 2009). They have been discussed from different perspectives, and a wide diversity of thematic approaches, constellations, methodologies, and tools for living labs exist (Almirall et al., 2012). The living lab has been conceptualized as an environment (Ballon et al., 2005), a methodology or innovation approach (Bergvall-Kåreborn et al., 2009), an organization or an innovation intermediary (Schuurman et al., 2012), a network (Leminen and Westerlund, 2012), and a system (ENoLL, 2007). This lack of common understanding makes it difficult to advance research focused on living labs.

We follow the definition by Westerlund and Leminen (2011) because it stresses the multi-stakeholder aspect, the real-life context, and the various stages of the development process. They view living labs as “physical regions or virtual realities where stakeholders form public-private-people partnerships (4Ps) of firms, public agencies, universities, institutes and users, all collaborating for creation, prototyping, validating and testing of new technologies, services, products and systems in real-life contexts”. In the living lab environment, different stakeholders can cooperate and share their resources, knowledge, and expertise, which is crucial to startups and small firms that have challenges acquiring venture capital (Eriksson et al., 2005). Living labs can have a demographic or geographical focus, they are either research or industry driven, and they are led by utilizers, enablers, providers, or users (Leminen et al., 2012). Although the implementations vary, notions about the role of users and their engagement in the innovation process remain central. Living labs research the whole innovation process from concept to effective usage (Salter and White, 2013).

The Living Lab Triangle

Based on a literature review and the authors’ earlier research (Veeckman et al., 2012), a comprehensive framework was established to analyse the link between the building blocks of living labs and their effect on the living lab outcomes. The Living Lab Triangle framework (Figure 1) has three pillars and consists of 11 key characteristics. The foundation of our framework is based on the characterizing purposes of Følstad (2008). Making a distinctive profile of each living lab was initially difficult, because Følstad’s characteristics were both insufficient to identify the main building blocks of living labs that act as differentiators and incapable of assessing the impact of the living lab’s R&D activities. Every living lab obtained the same score for the setup of their innovative characteristics, whereas in practice they had different outcomes. Therefore, some of the Følstad’s characteristics were adjusted and combined with the key principles of good practice by Eriksson et al. (2005).

Figure 1. The Living Lab Triangle: The triangulation between environment, approach, and outcome in living labs (Veeckman et al., 2013)

The identified characteristics are divided on a generic level (i.e., the living lab environment) and on a project level (i.e., the living lab approach). The set of characteristics on the generic level refers to material, immaterial, and contextual elements of a living lab environment, and the set on the project level defines the methodological aspects.

Pillar 1: Building blocks of the living lab environment

1. Technical infrastructure: When assessing or co-creating innovations, a technical component should be available for the test users within the living lab. In ideal circumstances, the testing of the innovation also includes monitoring of the technical performance during usage and non-usage of the innovation.
2. Ecosystem approach: Various stakeholders, from industrial partners to users and research organizations, interact to develop and evaluate a certain process, product, or service within the living lab ecosystem. Similarly, ad-hoc business ecosystems are constructed within the living lab projects (Peltoniemi and Vuori, 2004). When creating an ecosystem, it is important to create value to attract and retain members, and to share the value within the ecosystem (Iansiti and Levien, 2004). In practice, this means that there should be an added value for all partners involved, in order to create long-term engagement and identification with the living lab or at least on a project level (cf. Apollon project, 2012).
3. Level of openness: One of the key principles in living labs is that the innovation process should be as open as possible, because a multitude of perspectives might speed up the development and bring more innovative ideas (Bergvall-Kåreborn et al., 2009). This study incorporates two levels of openness, namely how intellectual property rights are being handled (i.e., the extent of knowledge sharing) and the degree to which new partners are embraced.
4. Community: Users participating in the living lab are part of a community, which can range from a "community of interest" to a "community of practice", whether or not it is geographically bound. For example, in a community of practice, the panel members are informally connected by what they do together and by what they have learned through their mutual engagement in these activities (Wenger, 2000). It is important to know what drives users to participate and contribute in order to keep them motivated and engaged (Ståhlbröst and Bergvall-Kåreborn, 2011).

5. Lifespan: This characteristic refers to the duration of the living lab, and not of a single innovation project launched within the lab. For example, a short-term living lab initiative might last less than six months, whereas a long-term initiative might have a two-year duration, and a very long-term initiative might have an indeterminate end date.
6. Scale: This characteristic refers to the number of users involved in living lab research activities such as the living lab panel. A small-scale living lab panel may involve fewer than 100 users, whereas a large-scale living lab may have more than 500 users. These numbers are defined on the generic level of the living lab, and not on a project level because the type of innovation or user study will define how many users can participate within the project or research activity.
7. Real-world context: Users should be studied within a real-life context, which implies a familiar context that reflects the users’ natural environment as much as possible. For example, users are studied within their home environment rather than in a laboratory setting.

Pillar 2: Building blocks of the living lab approach

1. Evaluation, context research, and co-creation: Within a living lab setting, test users are involved through different phases of the innovation cycle in which they can test, evaluate, and co-create the innovation. This means that test users must be able to give a positive or negative assessment of the innovation through, for example, surveys or in-depth interviews. Test users should be given the opportunity to shape the innovation in interaction with researchers and developers. Co-creation should be iterative and make use of, for example, participatory methods. Furthermore, the usage context should be taken into account as a critical element that influences usage behaviour through, for example, ethnographic tools (cf. Veeckman and Lievens, 2013).
2. User role: Leminen, Westerlund, and Nystöm (2014) identified four distinct user roles in living labs on the basis of the degree of user activity and the firm’s view of co-creation: i) informant, ii) tester, iii) contributor, and iv) co-creator. We propose that user roles depend on the view that companies pursue for integrating users in living labs and the degree of user activity within these living lab activities.

Pillar 3: The innovation outcome

To evaluate the success of a living lab, the innovation outcome must be considered. Knowledge of the tangible outcomes enables us to assess impact and determine which approaches worked best. Thus, the living lab setup can be improved, which leads to better implementation of future living lab projects. However, the literature is silent about which components affect the outcome in living labs, with the exception of Leminen, Westerlund, and Kortelainen (2012) who found that it depends on: i) strategic intention; ii) passion; iii) knowledge and skills; iv) other resources; and v) partners in the living lab network (Table 1).

Table 1. Components of the innovation recipe in living labs (Leminen, Westerlund and Kortelainen, 2012)

Operationalization

We operationalized the previously discussed building blocks on a four-point scale. A low score means that a specific characteristic is not present and a high score means that it is clearly identifiable and contributes to the operation of the living lab. We modified several of the Følstad’s characteristics based on the findings by Veeckman and colleagues (2012). For instance, “discovery” and “familiar context” were covered by other concepts and left out on the level of the living lab environment. The former is a principle maintained during the whole living lab process, and it forms an integral part of the way the methodologies are set up. The latter is a principle of testing in a real-world context and implies a familiar context that reflects the users’ natural environment as much as possible.

We also added four new building blocks: i) the ecosystem approach, ii) level of openness, iii) community aspect, and iv) user role. We also added a new pillar: innovation outcome. These adjustments will lead to a better characterization of living labs and are essential to assess the impact of diverse setups of living lab operations. The new pillar will make a more direct link between the building blocks of a living lab setup and the outcomes of innovation projects launched within the lab. Through these additions, the interplay between the living lab environment and its projects will be considered more attentively, as we assume that the environment intentionally and unintentionally shapes the projects. Table 2 details the operationalization of our framework.

Table 2. Operationalization of the framework with options for each building block