The heterogeneity in the innovation processes

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Capitalism dynamics has created contingent innovation processes. Groups of firms that have a specific way to introduce innovations are formed. They differ according to their economic sector, type of innovation and their field of knowledge. Over time, technologies and the nature of firms has changed. This heterogeneity reflects the emergence of new opportunities in markets. The waves of new technologies especially since the nineties have reinforced the emergence of specialized fields of knowledge. Consequently, an important source of sustainable competitive advantage of firms is conditioned by mastering new fields of technological knowledge (Pavitt, 2006).

Moreover, the importance of financial resources dedicated to innovation has been reinforced by the privatisation of innovation activities (notably through the growing access to financial markets) going hand in hand with the vanishing hand of managers and the growth of human capital (Langlois, 2003).

Most importantly, the evolution of firms has been conditioned by the knowledge-intensive economy, where specific human assets seem to be a fundamental asset for firms to gain competitive advantage.

Hence, in an evolutionary perfective, it is time to reconsider the positive relationship between the firm's performance and the industrial operations, and to preserve corporate coherence.

The latter assessments have major implications for the study of innovation processes. Firms have to be endowed with increasingly sophisticated specific and technological competences in order to meet the nature of modern industries (Schumpeter, 1942). As a consequence, we can observe that knowledge is transformed into economic effects through firms circumcised to achieve an efficient allocation of resources in a two way process: these changes come either from companies or from markets.

On the one hand, at the organizational level, firms maintain the private rewards form innovation by maturing their internal technological capabilities in an active inertia (Sull, 1999). In this context, internal knowledge encompasses firms' technological capability (Dosi, 1988) and their absorptive capacities (Cohen and Levinthal, 1990). In this sense, contemporary theorising abandons the idea of the Marshalian quasi-rent in favour of competitive strength and viability of a company that depends on "core competences" and its relations with its customers and suppliers. Hence, the core competencies firms develop are crucial to maintain technological leads that are conditioned by the new technologies they put on the market (Prahalad and Hamel, 1990). These assets embody a set of differentiated technological skills, complementary assets and routines that are the basis of competitive capacity (Dosi, Teece et Winter, 1990).

On the other hand, at the industrial level, innovative firms gain temporary market shares and are more profitable that non innovators. Firms continue to benefit from these temporary rents until rival imitators appear (Aghion and Howitt, 1992; Klepper, 1996). As firms generally show different levels of competitiveness, building a project of innovation without considering a loss of value once the product is put on the market is not possible, being given the complexity of the innovation process. Indeed, the coordination of actors and factors on the market is not always optimal (Arrow, 1971), resulting in uncertain flows of outcomes especially being given the uncertainty of innovation output whatever the amount of the initial investment is.

1.2. Methodology

Our work re-examines an old questioning addressed in economics of innovation, related to innovation performance and its efficiency: what are the determining factors of technological innovations within firms? The factors that enhance the innovative capability of firms are often classified as the sources or/and drivers of innovations.

The basic reason for this reexamination is the growing availability of innovation-surveys micro-data provided by Community Innovation Surveys (Hereafter, CIS). These surveys have been carried out since the nineties and offer extremely rich and diversified tools to explore innovation patterns.

CIS follow a subject approach of innovation. Their main aim is to stress out the widespread of innovation activity in manufacturing and services. Questionnaires are based on the definition of the Oslo Manual (OECD, 1992, 1996, 2005). Hence, starting from the nineties, the development of a methodology is concretized by OECD and Eurostat in order to measure innovation uniformly across countries, and to achieve structural comparisons. It is finally in 1991, that OECD adopted the Oslo manual as a guideline of innovation statistics, intended to be revised before the waves of innovation surveys, and agreed by member countries. The purpose of the manual is to give a large spectrum of indicators on the different types of innovation carried out in firms. It also specifies guidelines to measure the sources of knowledge as well as the nature of expenditures related to innovation activities. Actually the Oslo Manual (OECD, 1992, 1996, 2005) purpose was to give a clear definition of innovation, the different degrees of innovation and its measures : "An innovation is the implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations. Innovation activities are all scientific, technological, organizational, financial and commercial steps which actually, or are intended to, lead to the implementation of innovations" (Oslo manual, 2005).

Thus, not only CIS can be used to assess the innovation profile of firms, but these surveys also provide the characteristics of technological activities as well as the factors that boost innovation. In fact, this data allows for the identification of firms that innovate and (who innovates) and various facets of innovation (how innovation is made). Therefore, within the scheme of CIS, it is possible to have comprehensive data on the decision making at the firm-level regarding innovation strategies and hence, innovation modes.Based on the evolution of the content of the Oslo manual, CIS are performed at regular intervals of four years for up to 2005 and at two-year intervals since 2007. So far there exist five waves of CIS (CIS1 for 1990-1992, CIS2 for 1994-1996, CIS3 for 1998-2000, CIS4 for 2002-2004 and CIS2006 for 2004-2006). CIS provide information on innovation trends at the firm level, for each statistical unit (meaning the enterprise). More precisely, the results are decomposed in basic information (as activity, turnover, employees, geographical situation, etc…). It also gives various aspects of innovation activity (products and process innovation, R&D expenditures, intramural and extramural R&D, knowledge acquisition, factors hampering innovation, etc…).

Among the studies based in order to evaluate the returns on innovations based on firm level data, a large number of them acknowledged that there is a wide range of factors driving growth. But innovations remain considered to be as a key success factor for growth in the long term. Yet, the observed results on the estimation ran on international micro-level data (especially those using innovation surveys) show that some firms do better than others in terms of technological wherewithal improvements. These differences are caused by their endowments that might vary depending on heterogeneous organisational features and institutional ones.

These studies emerge as a result of researches on innovation in which technical change can be assumed to be studied by rival methods, while there are actually only different schools referred to as innovation economics, all influenced by Schumpeter's seminal work. Actually, the reason why empirical findings remain unclear about innovation returns is the major criterion of firm differentiation: that is to say technological opportunities that impulse R&D efforts. In this sense, empirical findings show a positive but weak link (at least unclear and not straightforward) between R&D and the economic results of firms (Hall and Mairesse, 1995).

To enrich these results, we base our work on the revised outlines of Schumpeter's seminal work. Schumpeterian approaches based researches emphasize vital issues in the innovation process as its costly, risky and uncertain nature. The same fields of literature stress out the importance of appropriability for the economic benefits of innovation in a large sense. In this framework, a successful innovation is described as the introduction of technological advance at the origin of profit generation rather than qualifying innovative activities in the large sense as a performance (Schumpeter, 1942). The Schumpeterian vision of economics as a dynamic process permeates the entire economics innovation framework and particularly growth theory against a wide range of neoclassicism work on technological change (ibid). The implication in terms of dynamic efficiency is that innovations are greater under monopoly than in competitive industries, and that innovativeness is higher for large firms. This fact is directly linked to an important feature of firms, meaning their evolution as well as firms' interactions with a changing and heterogeneous environment (as suggests the Schumpeterian scheme). This view puts innovation and competition at the core of the analysis: "it is not that competition which counts but competition from the new commodity, the new technology ... Competition which strikes not at the margins of the profits of existing firms but at their foundations and their very lives" (ibid, pp. 82-85). The point of most interest is that the Schumpeterian analysis of technological change differs from the neoclassical microeconomic approaches of innovation because it deals with product or production quality and not quantities or prices. These neo-Schumpeterian approaches have pointed out the importance of industry features for the competitive capability of firms and share a common interest for the comprehension of the drivers and dynamics of innovation.

Contemporary economists move away from the Schumpeterian vision, thus supporting a collective view of the innovation process instead of only one actor game. We base our analysis on these recent approaches of innovation, particularly the evolutionary theory. The point of most interest for us is that this field has described innovations as not linear but sequential and developed through evolutionary learning complex processes with many feedback circuits (Nelson and Winter, 1982). In fact, innovation theory acknowledges this complexity, for instance, chain-linked models (Rosenberg, 1976). But evolutionary approaches highlight the learning element in innovation. They also emphasize on the fact that not actors with full knowledge and information are cooperating together but individuals. This stream of the literature shows that changes in the knowledge and know-how bases imply significant discontinuities in the ways that knowledge is generated and economically exploited (Dosi, Teece and Winter 1990).

These statements let us consider the actors of innovation as well as the possible interactions with the organization. According to theoretical literature, firm's capabilities are embedded in the organizational practices and the latter are influenced by both the current position and their future path of evolution. Hence, organizational capability -that improves corporate performance- is a strong driver of innovation. The conversion of formal or informal knowledge and the creation of new knowledge originate from processes of internal diffusion.

It also provides a prospective tool in order to analyze "dynamics first" (Nelson and Winter, 1982), which is determined by the selection process, the innovation-imitation process, and the process capacity of accumulation. Innovations are described as not linear but sequential and developed through evolutionary learning complex processes with many feedback circuits: "Search and selection are simultaneous, interacting aspects of the evolutionary process: the same prices that provide selection feedback also influence the directions of search. Through the joint action of search and selection, the firms evolve over time, with the condition of the industry in each period bearing the seeds of its conditions in the following period" (Nelson and Winter, 1982, p.19). In fact, specific decisions emerge from routinized search methods - as rules of thumb pouce - are described in the framework of the Darwinian metaphor (Metcalfe, 2008). These routines also known as "the best it knows and can do", include not only operating rules as regard with production and supply factors for production but also strategic and investment rules aiming at decision-making. They are considered as a repository of knowledge and skills with an ability to replicate, even when no effort is provided by the firm (Nelson and Winter, 1982). Consequently, each firm reacts according to cognitive representations that are highly subjective and hard to model in actual facts, especially since "fitness" is predetermined by "search" rather than "optimizing" behaviors. As a consequence, the accomplishment of objectives in order to obtain the desired result depends on firms' capabilities, in turn depending on competitive contexts, in a particular time, relying on technological change and competitive standards.

However, industry is generally significantly heterogeneous in terms of firms' strategic orientations and innovative capabilities. Consequently, empirical studies show that private returns to R&D impulse research effort processes within a firm: firms exploit a windfall of technological opportunities, thus reinforcing the incentives to carry out projects and consequently at the origin of scientific knowledge accumulation. In fact, organizations with a high innovative capacity are the ones grasping higher opportunities and consequently higher payoffs on R&D efforts. These firms can easily increase their innovative capacity because they are more likely to incorporate external technologies in their products and processes. Moreover, employees are also more likely to understand and diffuse technologies since the firm is R&D intensive. In fact, if firms' resources are highly heterogeneous, companies do not have the same capacity to appropriate the returns of their investments. Their capabilities are drown form routinized knowledge, the latter being highly idiosyncratic. In this framework, sectoral dynamics tally with the microeconomic approaches of learning by doing and the selection approaches focus on inter-industry interactions.

The sources and drivers of innovations are also associated in the literature to the technological environment in which modern firms operate, in terms of opportunities; appropriability conditions, and the base of knowledge. A useful understanding of the sources and drivers of innovation at the firm level can be derived from the Dosi's (1997) evolutionary analysis which identifies five factors as seem to be particularly important:

(1) The firm's technological opportunities, which vary by industry because of the relative ease and costs of innovation from industry to industry. Technological opportunities are referred to as the ease of achievement of technological improvements associated with the intensity of dedicated resources to research and development. Firms in industries with higher technological opportunities will have higher rates of innovation and higher R&D intensities (Crépon et al., 1998).

(2) The firm's incentives to exploit opportunities, which the literature has identified as depending crucially on the structure of the market, including the strength of competition, ease of entry, numbers of new entrants, etc.

(3) The firm's capabilities to individually achieve technological change, which Archibugi and Lundvall (2001) have found to be linked to a strong knowledge base including an R&D capacity and a well-trained workforce.

(4) The firm's organisational arrangements and mechanisms for cooperation beyond itself. Teece (1992) has shown that strategic alliances, constellations of bilateral agreements between firms, and networking strategies are increasingly necessary to support sustainable innovative activities.

(5) The appropriability conditions for innovation, which differ greatly across industries, determine the ability of the firm to generate and maintain rents from leadership in technological activities (see Levin et al., 1987 and Cohen et al., 2000). Appropriability conditions determine the firm's capacity to transform technological effectiveness into economic performance.

1.3. Contribution

The concepts developed in this thesis they deal with the sources and drivers of innovation in a novel approach. In particular we develop two aspects of the innovation process:

(1) First, we explicitly distinguish innovation performance per se and the performances resulting from innovation.

In the first stage, we wish to identify the economic mechanisms that generate variety in innovation behaviour. In light of this situation, we study the nature of firms' technological capabilities that provides them new opportunities, and how they manage to turn them in new technological processes, but not only.

In the second stage, innovation feedbacks are is valued with the economic results of firms. This performance describes the ability of companies to transform their technological capability into economic success. In fact, we explore how the firm creates costs advantages at the firm level in a first stage, in turn creating economies of scale at the industry level in a second step by providing new processes.

This "double step" ("a cumulative causation") view of innovation is rather well confirmed/consolidated by the literature (Le Bas, Picard and Suchecki, 1998).

(2) Secondly, we retain a productive system division in "sectoral technological trajectories", so as to show that the "sources and drivers of the innovation" have different impacts on firms' innovation performance.

The main elements that emerge from the literature about technological trajectories are the amount of technological opportunity connected to technology, the degree of knowledge cumulativeness that is necessary for the firm in order to foster its capabilities in the technology and the appropriability conditions that are associated with the technology. Pavitt (1984) has identified three determinants of sectoral technological trajectories as decisive: the degree of intramural and extramural sources of technology, client's expectations, and the appropriation of innovation outputs which combination resulted in a classification of firms in different groups. It implies that these groups differ in their modes of innovation adoption and the benefits they get from it.

1.4. Thesis structure /design

This thesis is structured in three chapters/essays.

The first chapter describes exhaustively four waves of CIS surveys. These data sets being longitudinal, we could analyse innovation patterns of the firms that innovate and those that do not between 1994 and 2006. In this sense, we will study the importance of continuous innovation for firm's persistence. We will base our study on a sample of 431 firms. To study this process, we will present an analytical framework in which the probability to produce a successful innovation is confronted to firms characteristics and industrial ones.

The second chapter of this thesis presents a general model, in which we explore the conditions under which companies benefit economically from their research investments. We use an original data set to estimate the magnitude of the impact of the degree of innovativeness on sales and profitability. We use a sample of 7742 firms in manufacturing and services that we have constructed and used in chapter 2; which provides a comprehensive coverage of firm-level innovation for the period 2002-2005.

In the third chapter we replicate this work for different "the sectoral technological trajectories", in order to study the differences in innovation distribution between different sectoral classes. Our study aims at showing that the technological capability of firms depends on industry changes which follow technological trajectories (Dosi, 1982), specific to sectoral patterns. These sectoral technological trajectories are based on Pavitt's (1984) revised taxonomy of innovation for industry and also services.