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Services in an open innovation context
The majority of research works on open innovation do not clearly distinguish between open innovation in services and open innovation in the service context. Very few studies exist on the applicability of open service innovation explicitly though. Some previous research, for instance, indicates that although open innovation is beneficial for both product and service innovation, there are differences among industries on how they adopt it. This is consistent with the view that specific mechanisms and outcomes of open innovation depend to a great extent on context and contingency (Tidd & Hull 2003).
Hipp (2010) identifies the intangibility of services as a characteristic that may hinder the trad-ing of the service and hamper the ability to protect the related intellectual property via tradi-tional links. This is very important in the open innovation context as the protection of intellec-tual property is one of the biggest challenges and barriers to open innovation (especially in software development (Blind et al. 2006)). Nevertheless, it was shown that service firms col-laborate at the same intensity as manufacturing firms, although there was variety between different countries and industries (Tether et al. 2001; Hipp 2010). Moreover, based on an analysis of the data of the Community Innovation Survey (CIS-2) in UK, Tether (2002) finds that high technology service firms are more likely to cooperate for innovation (he also argues that his findings are consistent with previous literature) (Tether & Tajar 2008). These firms are more likely to cooperate with consultants, clients and others but are less likely to cooper-ate with universities (Tether 2002). Finally, Fasnacht (2009) acknowledges the benefits of open innovation in financial services by highlighting the importance of open and flexible business models that integrate clients in the innovation process more effectively. However, the fact that the applicability of open innovation in the service context has emerged as an interesting research topic very recently is surprising for two reasons. Service innovation is attracting attention increasingly and the characteristics of services make service innovation open by definition (intense collaboration with clients, easier licensing etc.). Indeed, Chesbrough (2011, p.4) in his book on open service innovation argues that: “Open innovation accelerates and deepens service innovation and growth by promoting specialization within the customers, suppliers, makers of complementary goods and services and other third parties surrounding the business, resulting in more choice and variety for customers”.
Chesbrough (2011) defines the open process in service innovation as a value web (Figure 6), i.e. a highly interactive process, where customers play a central role but also other actors con-tribute significantly. The value web naturally reminds us the discussion of Gallouj and Savona (2011) about how service innovation challenges the linear models of innovation and is more in line with the interactive model (Kline & Rosenberg 1986; Sundbo & Gallouj 2000). We can, therefore, acknowledge the similarities of the nature of service innovation and open in-novation.
The operational side of service innovation: the New Service Development (NSD) pro-cess
The development of service innovation inherently contains an operational side as well which is represented by the operational side of innovation, namely the New Service Development (NSD) process. Innovation may seem as an abstract concept, however in order to achieve the development of an initial idea to real service, a well-defined process is needed (Voss et al. 1992; de Brentani & Ragot 1996). Thus, there is a need to formalize the development of new services in a certain process; the NSD process. This is even more important in the case of ser-vices which are by definition abstract and therefore require more a procedural approach in the innovation activities. The NSD process and the relevant models have been much discussed in the respective litera-ture. Nevertheless, the bulk of relevant research has been concentrated on product innovation and the relevant New Product Development (NPD) process. One of the first models that were created was the famous NPD model proposed by Booz, Allen and Hamilton (1982); this was called the BAH model (from the initials of the authors’ names) which identifies six distinct stages: idea generation, screening, commercial evaluation, development, testing, and market launch. Moreover, Saren (1984) presents his departmental model which structures the innova-tion process according to the departments that are involved in the innovation process, such as R&D, Design, Engineering, Product and Marketing. However, the departmental-stage model is not very well suited for formalizing the NSD process since most service firms are very small to have specialized NSD departments (de Jong et al. 2003). Cooper et al. (1994) have also proposed their own version of the NPD model, consisting of five steps/stages, namely preliminary assessment, business case preparation, development, testing and full launch. Five relevant “gates” can also be found in this model in between the above mentioned stages. Fi-nally, Kline and Rosenberg (1986) propose a chain linked model which is a highly iterative model. Nevertheless, the validity of such NPD models in the context of services remains to be demonstrated (Stevens & Dimitriadis 2005).
Besides the application of the NPD models in NSD, there have also been some attempts to model the NSD process separately. Shostack (1984) developed one of the earliest linear mod-els comprising ten discrete steps. Moreover, Scheuing and Johnson (1989) created their fif-teen stages model (based on the BAH model) where they emphasized the importance of the concept development phase. Furthermore, Edgett and Jones (1991) propose a sequential mod-el comprising 16 stages, including market research, business-plan, IT development, agreement and post-launching evaluation. What is important though is that the authors have identified the importance of co-operative behaviour among departments (Stevens & Dimitriadis 2005). Nevertheless, the weaknesses of linear and sequential models were quickly acknowledged in service innovation (as in goods innovation). Bitran and Pedrosa (1998) created a generic de-velopment model (inspired by NPD models) which consisted of six stages, namely strategic assessment, concept development, system design, component design, implementation, feed-back and learning. Tax and Stuart (1997) created an iterative model that shows that new ser-vices can be born in or out of existing service systems. De Jong et al. (2003) see the NSD process as a process comprising two stages: the search stage and the implementation stage, with three activities in each one: idea generation, screening and commercial evaluation for the search stage and development testing and launch for the implementation stage. Furthermore, Johnson et al. (2000) discuss the general iterative four-stage model involving design, analysis, development and full launch. The role of enablers (teams, tools, organizational culture) that facilitate the process of designing or redesigning the service delivery system is underlined in this model. Finally, more recently Zhou and Wei (2010), after reviewing various NSD pro-cesses, proposed a generic three-stage model comprising the idea phase, the development phase and the introduction phase.
Summarizing, we can conclude that the process aspect of service innovation is very im-portant. It can generally comprise several concrete stages that do not have to be implemented in a linear but rather in an iterative and highly flexible way that address the particular nature of each service innovation project.
Service Innovation through the lens of the Resource Based View (RBV) of the Firm
The Resource Based View (RBV) of the firm, based on the seminal work of Penrose (Penrose 1959), shows that there is a link between the internal characteristics of a firm and its perfor-mance (Barney 1991). In fact according to the Resource-Based View (RBV), it is the organi-zation’s special and unique resources that ensure sustained competitive advantage (Barney 1991; Penrose 1959). Competitive advantage comes from a bundle of organizational resources that have four distinctive attributes; namely they are rare, valuable, imperfectly imitable and without equivalent substitute (Barney 1991).
Resources and capabilities are often discussed simultaneously in the literature. This is ex-pected as these are two concepts that are empirically strongly interrelated. Some scholars ac-tually define resources in a broad way to include capabilities in them (Ethiraj et al. 2005). However, we choose to align with the view that capabilities represent the firm’s capacity to deploy their available resources, thus: “a capability does not represent a single resource in the concert of other resources […] but rather a distinctive and superior way of allocating resources” (Schreyögg & Kliesch-Eberl 2007, p.914).
The capability of an organization to perform certain activities depends on its resources and the way these resources are exploited and combined internally in order to develop the respective capabilities. Penrose (1959) in her seminal work argues that resources are a bundle of poten-tial services and while these resources are available to all firms the ‘capability’ to deploy them effectively is not always present (Ethiraj et al., 2005). Therefore, a capability represents an action or repeatable patterns of actions that an organization can use to achieve certain goals (Sanchez 2001). That is why capabilities have raised a lot of attention from researchers, as the competent organization has become a new ideal (Schreyögg & Kliesch-Eberl 2007).
But organizational capabilities bear also inherent risks and perils; for instance, the threat of remaining static. In turbulent environments, like the ones innovative organizations have to compete in nowadays, the threat of organizational inertia and lock-in in “old” practices is ex-istent. Therefore, there is a pervasive need for change and adaptation. This is especially rele-vant in the case of service innovation where new services are easily initiated but also easily imitated (Voss et al. 1992). Therefore, it is not merely enough to develop capabilities, but also being able to manage and change them when needed. This is why the notion of dynamic capabilities has gained such an interest among scholars. Although there is no general consensus what a dynamic capability is, we present some recent definitions that are generally accepted6.
Teece, Pisano and Shuen (1997, p.516) define ‘dynamic capability’ as ‘the firm’s ability to integrate, build, and reconfigure internal and external competences to address rapidly chang-ing environments’. Dynamic capabilities ‘reflect an organisation’s ability to achieve new and innovative forms of competitive advantage despite path dependencies and core rigidities’ (Teece et al. 1997, p.516). Zollo and Winter (2002) argue that a dynamic capability is a learned and stable pattern of collective activity that gives the organization the ability to sys-tematically generate and modify its operating routines in pursuit of improved effectiveness. Furthermore, Zahra et al. (2006) state that dynamic capabilities represent the ability to recon-figure a firm’s resources and routines in a manner envisioned by its principal decision-maker(s).
Complementing the RBV: The resource-process framework for service innovation
It is not however only the efficient exploitation of resources that results in the development of innovation capabilities. Recent developments on service innovation capabilities have added a complementary view to the RBV perspective in the development of service innovation capa-bilities. Although resources are rent-generating assets (Ethiraj et al., 2005), sole resources cannot be a source of competitive advantage; they need to be exploited in order to create the relevant capabilities that will drive the innovation process effectively and efficiently. This is the reason why performance differs between service firms (Menor and Roth, 2008). The same resources can result in different capabilities if they are deployed in a different way and in dif-ferent combinations (Ethiraj et al., 2005).
Table of contents :
1 General introduction
2 Getting acquainted with Research and Technology Organizations (RTOs)
2.1 Defining RTOs
2.2 The funding model of RTOs
2.3 Motivation for establishing RTOs: The valorization of public research
2.4 The collaborative innovation model of RTOs, their position in national innovation systems and the focus on services
2.5 RTOs challenges and transformation process
3 An internal perspective of RTOs: RTOs unique service innovation capabilities
3.1 Theoretical Background
3.1.1 Understanding services and service innovation
3.1.2 Services in an open innovation context
3.1.3 The operational side of service innovation: the New Service Development (NSD) process
3.1.4 Service Innovation through the lens of the Resource Based View (RBV) of the Firm
3.1.5 Complementing the RBV: The resource-process framework for service innovation
3.2 Research Strategy: Research Objective and Research Design
3.2.1 Research Question 1
3.2.2 Research Design
3.2.3 Conceptualizing the theoretical framework of service innovation capabilities in RTOs
3.2.4 The qualitative part – Multiple case studies in European RTOs
Data collection
Data analysis
3.3 Main Results 1 – Identifying the distinct service innovation capabilities of RTOs
3.3.1 A theoretical framework for the development of service innovation capabilities in RTOs
Main Contributions
3.3.2 A proposed grid for mapping the service innovation capabilities of RTOs
Main contributions
3.3.3 Reinforcing creativity in service innovation – 7 relevant capabilities
proposition
Main contributions
3.3.4 Conclusions of the first part of the research project
4 An external perspective: The role of RTOs vis-à-vis universities in the public researchindustry open innovation relationship
4.1 Theoretical Background
4.1.1 The dimensions of openness
4.1.2 The debate around open innovation
4.1.3 Open Innovation: benefits versus risks and challenges
4.1.4 Reducing the risks and challenges of open innovation through innovation intermediaries
4.1.5 Open innovation relationships between industry and the academic world
4.2 Research Strategy: Research Objectives and Research Design
4.2.1 Research Question 2
4.2.2 Research Design
4.2.3 Comparing RTOs to TTOs/universities as intermediaries in the scienceindustry relationship
4.2.4 The quantitative part – Statistical analysis of the Eurostat’s Community
Innovation Survey microdata (year 2012)
4.3 Main Results 2 – The role of RTOs vs universities in the science-industry relationship
4.3.1 RTOs vs TTOs as intermediaries: reduction of transaction costs vs. knowledge creation
Main contributions
4.3.2 RTOs vis-à-vis Universities as sources of knowledge and the different impacts on innovation
Main contributions
4.3.3 Conclusions of the second part of the research project
5 Discussion and Concluding Remarks
5.1 Synthesis of Results and Discussion
5.2 Practical Implications
5.2.1 Managerial Implications for RTOs
5.2.2 Managerial Implications for the industry
5.2.3 Policy Implications
5.3 Further research avenues
5.3.1 Replication with more case studies and/or in another context
5.3.2 The role of RTOs in bringing more openness to innovation and the implications for their Intellectual Property management
5.3.3 The role of RTOs in supporting entrepreneurship
5.3.4 The internationalization of RTOs: is it feasible?
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