par Maghe, Virginie
Président du jury Gassner, Marjorie
Promoteur Cincera, Michele
Publication Non publié, 2019-02-18
Thèse de doctorat
Résumé : This thesis investigates the evolutionary foundation of the Innovation System concept and the quantitative techniques that could be used for a systemic evaluation of innovation policies. This topic has been covered through 6 chapters:
Chapter I: The innovation system concept, which is the central concept of this thesis, finds its foundations in the evolutionary theory of economics and the Schumpeterian point of view on the co-evolution of innovation, organizations and institutions. Developed by Nelson and Winter in 1982, this theory is based on the idea that the surviving firms on the markets are not necessarily the ones that maximize their profits. Indeed, their ability to survive is reinforced by the development of internal organizational routines allowing for a fast adaptation to their changing environment. Thus, when assessing performances in terms of innovation in general, the single firm should not by the only centre of attention anymore. The entire environment surrounding its innovation activities should by analysed to understand the conditions underlying its failure or success. The definition of the innovation system (IS) concept finds its roots in this theory: the environment in which innovation activities take place is as important as the decision of the single innovation actor. Defined as all the institutions and organizations involved in the creation and diffusion of new knowledge and technology, the IS includes not only stakeholders of the innovation process, but also all the transversal sectors affecting innovation near or far: labour market, finance, and education… In such a context, the main justification for public intervention shifted from the market failures described by the neo-classical theory, to systemic failures, i.e. the dysfunctions of the IS, on which governments may take actions. And this shift in the policy rationale also leads to specific evaluation techniques of public initiatives.
Chapter II: The IS concept is defined as all the institutions and organizations involved in the creation, diffusion and absorption of new knowledge and technology. An important question is raised by such a point of view: what is a system? What are its components? How does it foster innovation? This theoretical step is necessary to understand all the aspect of the innovation environment that are concerned by innovation policy design. How could a policy-maker integrate the systemic framework of the IS when initiating public action with the aim to improve performances in terms of science, technology and innovation? A large part of the economic literature is dedicated to the description of innovation systems. So the aim of this chapter consists of synthetizing the aspects referenced in the economic theory as the components of the IS in a normative exercise. First, the term “system” involves the articulation of several components and the relationships existing between them. Departing from this definition, three broad aspect of the IS are considered: the actors of the innovation process, the functions of the system and the resulting objectives that should be pursued by the stakeholders, and the instruments used by public authorities to intervene in such a systemic context. The actors involved in the innovation process are not only the recipient of a public policy, they are also policy makers, implementation agents and targets of the policy measures. The functions of the IS mainly concerns the creation, diffusion and absorption of new knowledge and technology. As the role of the State is to improve the performances of such a system, those functions should be considered as the objectives of public action. Finally, the instruments used by the State to reach these goals can also be detailed: innovation policies can be implemented through direct support measures (financial or fiscal tools), the improvement of the infrastructure allowing for the diffusion of innovation, or the general framework conditions affecting performances. The normative exercise ended up with an exhaustive taxonomy that may be used for further analysis
Chapter III: As the aim of this thesis is to develop analytical tools to integrate the IS point of view in public policy evaluation, the most important aspect of the work consisted in building an exhaustive database on innovation policies implemented in the EU28 Member States and its main non-EU competitors (Australia, China, Japan, the US, India, the Russian Federation, Brazil, South Korea and Canada). This database was constructed in the context of the ENIRI study conducted by the European Commission, between 2013 and 2015. This long-lasting work involved the collection of information concerning the innovation policy measures implemented in all the considered countries, both at the national and regional levels. This information was related to the IS dimensions highlighted in previous chapter. The main sources for data collection were the RIO (former Erawatch) and OECD STIP databases, the RIM Plus Monitor and national sources (Ministry websites), as well as national experts. The budgets was also included or estimated for the 2007-2013 period. Once the data were collected, the policy measures were classified according to the theoretical canvas developed through the taxonomy of chapter II. Functional matrices combining different aspects of the IS allowed for detailed information on the distribution of policy measures among the different dimensions of the system. For example, it is possible to estimate the percentage of policy measures implemented in one country that are dedicated to the fundamental research activities in SMEs. This distribution has been computed both in absolute and budget terms. This difference provided information on the contrast existing between governmental claims and intentions in terms of innovation policies and the effective use of money dedicated to the announced target. Indeed, it is not because a substantial number of policies are dedicated to a specific sector of beneficiary that the allocated budget will be more important. Thus, this policy database should shed a light on the way innovation policies are articulated at a national level, and how they are effectively implemented through their budgets
Chapter IV: The evolutionary foundations of the IS concept imply that there is no general equilibrium describing an ideal situation to which a specific case can be compared. In other words, there is no optimal innovation system, and no ideal configuration that should be imitated by the others. This absence of equilibrium and the systemic point of view adopted in this context lead to the use of alternative techniques to evaluate performances and policies. As suggested by Edquist (2006), this has to be done through a diagnosis of the IS, consisting in the identification of the systemic failures, and the elaboration of strategy to fix the problem. This demarche will be investigated in this chapter of the thesis and the following. In this section, a diagnosis of the IS of 37 countries (28 EU and their 9 non-EU competitors) will be realized through a typology based on innovation performances indicators. The aim of such an analysis is to see whether the different IS can be gathered in groups sharing the same characteristics, relative strengths and weaknesses. The expected results should reveal groups of countries sharing the same configurations in terms of innovation process, and facing the same type of weaknesses, dysfunctions or systemic failures. By doing so, one should be able to identify the needs of each IS, i.e. the components that may need improvement and eventually public intervention. To do so, a principal component analysis and a hierarchical ascendant clustering technique have been implemented on the 37 IS, revealing 4 clusters of countries, depending on their NIS characteristics and advancement: 1) The Asian economies, 2) The lagging-behind and catching-up NIS, 3) The small opened systems, 4) The technological leaders. This analysis has been realized for the 2003-2005 and 2013-2015 periods, revealing that, if the general features of the clusters do not tend to change over time, some countries faced a change a modification of their status: Korea left the Asian group to join the leaders, Cyprus and Ireland opened their boarders to a larger extent in a decade.
Chapter V: Innovation policy typologyThis chapter is focused on the construction of an innovation policy typology based on the distributions of policies obtained in the database presented in chapter III. The results of this typology will be compared with the diagnosis realized in previous section to see if the weaknesses and needs of the NIS are effectively targeted by public action in innovation. Also, the aspects that could enhance or weaken such action, and their combination with other component of the NIS could be better understood. To this purpose, a multiple factor analysis has been implemented on the distributions of policy measures in terms of NIS components, followed by a hierarchical ascendant clustering, revealing groups of countries sharing the same characteristics in terms of policy design and implementation. 34 NIS have been examined (India, Brazil and Russia have been removed from the sample due to the bad quality of the information), using both the budget-weighted and non-budget-weighted distributions of measures on the 2007-2013 period. However, the results of this typology cannot be interpreted separately from the general innovation framework in which the public action is implemented. Indeed, countries having the same features in terms of beneficiaries and/or objectives in terms of policy do not necessarily share the same kind of IS. These implementation characteristics should rather be interpreted in light of the results obtained in the NIS diagnosis typology, in order to examiner if the public money effectively go where it is needed. In general, the different examined countries seem to effectively tackle their weaknesses, but countries facing the same types of problems do not implement the same type of policy mix, reinforcing the hypothesis that the innovation process is embedded in a large institutional framework that my orient public action in a direction rather than another. Two specific cases hold the attention in those results: South Korea, whose leader status came along with an improvement of the in force regulatory framework and a focus on private research, and Japan, dealing with research in the pharmaceutical research and ageing-population issues.
Chapter VI: The impact of macroeconomic and IS factors on the efficiency of public R&DAnother point of view can be adopted in an attempt to integrate the IS representations in policy evaluation techniques: the analysis of their impact on the efficiency of public R&D in leveraging private investments. In this chapter, a combination of two types of analysis is used to examine the problematic: the study of the efficiency of public R&D expenditure and its determinants on one hand, and the investigation of a possible crowding out effect of public R&D on the private one on another hand. The crowding out effect is translated into efficiency analysis, considering the BERD funded by government as an input, and the BERD funded by business as an output. And if an increase in the output leads to a decrease in the output, public intervention is considered to crowd out private initiative, as the firm may decide to replace its own investment with public money, instead of using it as an extra resource to increase its R&D activities. In this context, the IS as environment of R&D activities can be seen as a determinant of this efficiency, as it can strengthen or weaken this crowding out effect. The question asked in this section is the following: how to quantify and model the interdependencies existing between the different components of a NIS in order to integrate them in a quantitative analysis. This has been done in this study by implementing factorial analysis (Buesa, 2010) on a set of indicators collected in the Global Competitiveness Index database, and considered as descriptors of the different aspects of the innovation system. Those IS factors are: 1) the general STI environment, 2) the accessibility of the financial markets, 3) the internationalization of the system, 4) barriers to entrepreneurship and 5) the flexibility of labour regulation. Afterwards, these variables have been added as efficiency determinants in a stochastic frontier model assessing a possible crowding out effect between public and private initiatives. The main results showed that there is an additional effect of public R&d expenditure on private R&D investments (no crowding out). Moreover, the general STI environment and accessibility of financial markets have a positive impact on this efficiency, contrary to the presence of foreign stakeholders in the system. The two last factors remain insignificant. Those results suggest that, if public intervention should have an effect on the performances of the NIS, this relationship is also reciprocal: a well-functioning NIS may have a positive effect on the results of a policy measure.

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