Innovation process within the firm

Previous sections described the search mode for innovations, the possible motiva-tion and constraints for creating innovamotiva-tion strategies. Finally, I will introduce a model of the innovation process that will elaborate the processes described before.

The model presented here is somewhere along the fifth, and currently last, gener-ation of innovgener-ation process models (Rothwell, 1994). There have been several, if not dozens, of innovation process models presented in the previous four genera-tions (Godin, 2015). Since the fifth generation model is an expansion of previous models, I will only briefly mention the biggest improvements.

The first generation is called a technology push model or linear innovation model.

It forms a direct sequential relationship between basic science, design and devel-opment, manufacturing, marketing and sales.³ This is a straightforward process where all innovations can be traced back to basic science. The simplicity is one explanation for the heavy focus on R&D in innovation policies (Caracostas, 2007).

The criticism of the lack of demand factors in the linear model led to the second generation of innovation process models — the demand push model (Godin and Lane, 2013). The model contrasted the technology push model by iterating the market need as the first step of the sequential relationship towards innovations.

3This model also has no clear authors. A review of its history can be found in Godin (2006)

Innovations come from market needs, which are then developed (basic science and R&D), manufactured and commercialised.

The third model of innovation — an integrated model — combined both supply and demand factors (Marinova and Phillimore, 2003). The innovation process was still considered to be a linear process but with feedback loops (Rothwell, 1994). Processes can contain loops and feedback mechanisms to assess whether they should continue, be revised, follow through to next steps or be abandoned altogether (Kline and Rosenberg, 1986).

The fourth generation of models combined this knowledge and started emphasis-ing systems (Marinova and Phillimore, 2003). One example is the national inno-vation system (Edquist, 1997; Lundvall, 2010), where the role of actors outside the firm is highlighted. Another advancement is the cyclic nature of the innovation process (Berkhout et al., 2006), where firms have to work with similar processes continuously, learning-by-doing and building capabilities.

Currently, the most comprehensive innovation process model is described and drawn by Carac¸a et al. (2009), shown here in Figure 2.1.

It is a cyclical model, where the innovation process can begin at any stage within the firm — either in the invention and basic research phase, design or prototyping phase, or perhaps in the commercialisation phase. Therefore, it encompasses both the demand-pull and science-push models, where the catalyst for innovation can come from either creation of new knowledge or from the feel of market demand.

The model also depicts feedback loops within every stage within the firm, high-lighting the contribution of the third wave of innovation models, especially the chain-linked model by Kline and Rosenberg (1986).

The model illustrates the role of the micro and macro environment and the avail-able knowledge base and market messages. These form a relationship with the firm through interfaces, which can be thought of as the organisational capability to understand its environment (Cohen and Levinthal, 1990). The influence of the fourth wave of innovation models is apparent.

Finally, the model also positions possible outputs of the innovation process.”The outcome of learning can be either product or process innovations, or the cre-ation of new market segments and new approaches to organise business routines”

(Carac¸a et al., 2009, p. 864). This is clearly influenced by the Schumpeterian perspective of possible innovation outcomes.

These outputs are in line with the empirical part of this thesis as well. Described in detail in the data section in Chapter 4. In brief, the data used in this thesis also measures these four possible innovations as outputs. Other elements of this

Figure2.1:Themulti-channelinteractivelearningmodelofinnovation.Source:Carac¸aetal.(2009)

model are also captured in the data used in this thesis, both micro and macro environment, all three interfaces and the internal processes.

The whole Chapter 2 describes the elements depicted in this model in detail. I will highlight the most important connections briefly starting from the outer layer of the model.

Technological regimes and trajectories are describing the scientific and techno-logical research connection with the firm. The technotechno-logical trajectories approach highlights especially the role of existing scientific and technological knowledge.

Firms have a search mode for new technological breakthroughs, but they are bounded by possible (and most logical) paths. The search for new knowledge is not random. It is guided by what is already available and what are the most rea-sonable, cost-efficient, or rational options to go forward (Dosi, 1988b). Insights from the technological trajectories and regimes approach imply that firms have some commonalities within economic activities that are based on similar techno-logical levels. These could be what are commonly known as sectors of economic activities (such as NACE), but they may not align.

The interface with the scientific and technological base is dependant on the ca-pabilities of the firm (Cohen and Levinthal, 1990). Since knowledge exchange is not easy nor cheap, it takes time and effort to create a working interface. These concepts are at the very centre of the fourth wave of innovation models, but are also clearly part of the strategic management idea of creating core competences.

Without a working interface, the firm is not able to capture the benefits of R&D done outside the firm. It leaves only internal processes, or, as is often the case, firms are not able to keep up with the competition.

Business methods research and organisational knowledge illustrates the role of practices, core competences within the firm, capabilities, best practices, and rou-tines. Scholars in the technological regimes literature tend to describe these as routines and capabilities, and in the strategic management literature as best prac-tices and internal competencies. They both highlight very similar ideas.

Routines and practices are relevant to distinguish why some firms are able to gen-erate new knowledge or understand market needs and other firms are not. In the technological regimes literature, the emphasis is on R&D, how firms organise their operations. However, organisational knowledge also captures other aspects, such as logistics, supply-chain management and internal creativity support. These aspects of organisational capabilities are often discussed in the strategic manage-ment literature. Finally, the interface also influences how dynamic these capabili-ties are. Are firms nimble enough to change their routines and avoid harmful path dependencies? Are they able to absorb best practices?

The third direct link with feedback loops to the firm is market research and design.

In essence, it captures the firms ability to understand the needs and preferences of its users. Although it is drawn near the commercialisation phase, the role of users can be influential in earlier phases as well (Hippel, 1986, 1988). The demand driven innovation process emphasises this in full. Firms first try to understand what is needed, then develop based on this (Scherer, 1982).

The interface with market research and knowledge about markets illustrates two aspects: first, the firms’ capabilities to understand signals from the market and the firms’ clients; second, the firms’ ability to appropriate its knowledge from the other side of the market — its competitors. The latter is important since it positions the firm within market forces. If it develops some knowledge about the market and users needs, competitors are also interested in this knowledge, preferably without costs. Intellectual property is a mechanism to both protect and also exhibit this knowledge.

The macro environment is based on large institutions that are guiding our whole economy. In the context of innovation process, these have been noted on both sectoral (Malerba, 2002) and national (Lundvall, 2010) levels. Institutions in this context are”sets of common habits, routines, established practices, rules, or laws that regulate the relations and interactions between individuals and groups”

(Edquist and Johnson, 1997, p. 46). Organisations are governing these institutions by providing related services.

An example to illustrate the differences between organisations and institutions in the macro environment for a single firm. The education system as an institution can be described as the propensity of people to learn and exchange new ideas such as the established practices on how teaching is organised, how much the society values education and what aspirations students have. Organisations are schools, the education board or ministries, universities, etc. A firm can interact with schools and universities if it demands knowledge or labour. However, the institutions overall influence whether the firm has any probable partners to even interact with. If educational institutions are very weak, societies are unable to provide the high-skilled workforce which may be needed to attract firms.

Similarly, firms are dependant not only on organisations that finance endeavours.

Access to banks, risk capital and other financing schemes are influenced by insti-tutions within the innovation system. If there are weak regulations, lack of trust and enforcement of rule of law, access to additional capital is severely hampered.

The macro environment influences most firms in the innovation system simulta-neously. Possible system influence depends on the level of analysis as well. Inno-vation systems are a framework to think in, not well-defined theoretical models.

Therefore, if the analysis of the innovation system is on the sectoral level, there

are effects on some industries and not others. For example, the education system could be very well suited for producing high-skilled computer scientists, but not wood chemists. Attitudes and public support as institutions matter a lot in these contexts. If the national innovation system is considered as the level of analysis, a wider picture emerges that depends on access to capital or labour, willingness to take risks, efforts of different organisations to mutually benefit each other or work in silos, and so forth.

An element which is not pictured in Figure 2.1 is STI policies. They are part of the science and technology system (if they exist), and their focus is usually in developing the innovation system. A more detailed description of the scope and ambition of innovation policies is in Section 3. The section also shows that STI policies can influence many organisations and institutions beyond the science and technology system.

The micro environment relates to the firm’s ability to engage with potential part-ners and knowledge sources. These are suppliers, users, competitors, distributors, etc. The list in Figure 2.1 is an example. In reality, firms can have many more potential partners in their micro environment. Extreme examples are like Nokia, a single firm which was the centre for ICT innovations in Finland for a long time (Ali-Yrkk¨o and Hermans, 2004).

Based on their position in the micro environment, some taxonomies of innovative practices have also been created (Castellacci, 2008; Pavitt, 1984; Pavitt et al., 1989). They highlight various roles a firm can have in the innovation system depending on the relationship with its micro environment. These relationships define the flow of knowledge, sources and partners for innovative activities and new technologies — also the types of activities that are internal and outsourced.

The micro environment and the firms’ role in it is a major characteristic of how any firm chooses to be innovative.

The internal processes of the firm depend on the available knowledge of new tech-nologies, new processes, market needs, internal capabilities and chosen projects.

Potential projects are chosen, developed and commercialised. What is relevant here is the firm’s own capability to develop these projects. If firms lack resources in any of these stages, innovative activities may fail. Secondly, firms can develop innovations without going through all the stages illustrated in Figure 2.1. Innova-tions are often without any changes to core concepts, reinforcing and developing on what is successful in the marketplace (Henderson and Clark, 1990).

The innovation process model encompasses all possibilities for firms to innovate.

In reality, most firms skip several of these stages or outsource them to others. The empirical part of this thesis investigates how firms have been creating their inno-vative strategies. The model presented here allows us to picture all possibilities for any firm.