Factors Affect Innovation

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Factors affecting innovation revisitedJos Molero y Antonio Garca

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ResumenEl propsito de este trabajo es contribuir a un mejor conocimiento de los factores que afec-tan a la innovacin mediante el anlisis de los microdatos de la encuesta de innovacin delas empresas espaolas de 2003. El estudio se aborda desde la elaboracin de una taxono-

ma de sectores combinando las Ventajas Tecnolgicas Reveladas de la industria espaolacon el dinamismo tecnolgico mundial; adems se introduce una clasificacin de las em-presas en funcin de la pertenencia o no a un grupo de empresas y de si esos grupos sonde nacionalidad espaola o extranjera.

Se utilizan tcnicas de Anlisis Factorial para reducir y organizar la abundante informacindisponible en Factores con significado econmico que despus son empleados como varia-bles explicativas de la innovacin de producto y de proceso. Se encuentran diferenciasentre ambos tipos de innovacin tanto por el nmero de factores significativos como en laintensidad de su capacidad explicativa. La taxonoma elaborada muestra su importancia almostrar patrones de comportamiento distintos entre los cuatro tipos de casos construidos.

AbstractThe aim of this paper is to contribute to a better understanding of factors affecting innova-tion by analysing the Spanish manufacturing sector using microdata of the 2003 SpanishInnovation Survey. To enrich the analysis a self developed sectoral taxonomy is used com-ing from the combination of both of the sectoral Revealed Technological Advantages(RTA) and worldwide technological dynamism of the sectors; moreover firms are classifiedaccording to the type of capital ownership: independent companies, companies belongingto a national group and subsidiaries of multinational enterprises. The abundance and het-erogeneity of variables advised us to use Factor analysis to reduce and organise the original

variables into a number of consistent and theoretically significant factors. We found differ-ences between product and process innovation, both in number of explicative variables(significant independent variables) and in relative effect of independent variables (even, insome cases, a sign change from product to process innovation). Taxonomy matters be-cause of some differences in explanatory (independent) variables for each sector andmodel explanatory power differences between sectors, and, on the other hand, because ofthe non significance of some significant variables once we control by sectoral taxonomy.

Key words: Innovation, Factors affecting innovation, Multinational enterprises, Sectoraltaxonomies, Spain.

Jos Molero, Antonio GarcaInstituto Complutense de Estudios Internacionales, Universidad Complutense de Madrid. Campus de Somo-saguas, Finca Mas Ferre. 28223, Pozuelo de Alarcn, Madrid, Spain.Facultad de Ciencias Econmicas y Empresariales. Universidad de Sevilla. Avda Ramon y Cajal, 1. 41018,Sevilla, Spain.

Jos Molero, Antonio GarcaISBN:Depsito legal:

El ICEI no comparte necesariamente las opiniones expresadas en este trabajo, que son de exclusiva responsabilidad de sus autores.


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ndice1. Introduction...7 2. Theoretical background.8

3. Methodology and data analysis........11

4. Some stylised facts of the innovation in the Spanish economy..13

5. Results15

5.1 Factor analysis .....15

5.2 Regression analysis......16

6. Concluding remarks.19

7. Annexe A...21

Annexe B22

8. References..26


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1.IntroduccinInnovation has experienced a remarkablechange in recent years as a consequence of anumber of factors including the advance of

science and technology and the increasingglobalisation of a number of markets and ac-tivities. The growing heterogeneity of sourcesaffecting the process of firms innovation hasled to the knowledge created out of the com-panies themselves achieving greater im-portance, and therefore to the central role tobe played by the capacity of integrating innerand outer sources of technological capabilitieswith other competitive forces. Similarly, theacceleration of internationalisation at mosteconomic and social levels has increased thenecessity for exploiting firms advantages at

international (sometimes world) level andseeking new competitive (technological) assetsin a multinational framework. Moreover, thespecialised research has reached a commonconclusion that sectoral features have a re-markable influence on the possibilities andorganisational modes of innovatory activity.

From Pavits seminal sectoral taxonomy oninnovation, there is a long tradition of usingseveral taxonomies or classificatory list ofproductive sectors according to their in-

novative characteristic or intensity. Both a-cademic and institutional taxonomies can bedescribed as closed aprioristic lists of sec-tors, built on rigorous studies but withoutflexibility to allow country differences on sec-tor characteristics. A main contribution of thispaper consists of grouping companies in dif-ferent categories of sectors in a non-aprioristicway: each sector is self-classified in a specifictype and not in any other according to par-ticular characteristics and innovative be-haviour in a given country (in our case,

Spain). To this end we have developed a ta-xonomy from the combination of (RTA1) ofeach sector of activity and the evolution of itsworld weight between 1993-1998 and 1999-2003. Original sectoral data come from patentsgranted by the USPTO by priority year at thenational level by sector of economic activity(NACE class derived through concordancewith International Patent Classification).

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RTAs for a sector of a country is calculated as follows: RTA ij =(Pij / Pwj )/ (PTi / PTw) where i is the country, j the sector, w theworld total for j sector, T is the total of the country and tw is theabsolute world total. All referred to patents in a period of time.

Using microdata from the Spanish InnovationSurvey2, we had the advantage of their qualityand statistical significance. These data are of a

great statistical validity insofar as an expertgroup coordinated by the Spanish NationalStatistics Institute has, on the one hand, drawnup a permanent sample of firms with the in-tention of creating a stable panel of data and,on the other, has controlled the statistical sig-nificance of the anonymous data vis--vis theoriginal micro data. In addition, this informa-tion allows us to separate firms according totheir independent feature or belonging to agroup, including the country of origin of themother house of MNCs.

Our topic to explain is the innovative activity(product and process innovation) of Spanishmanufacturing firms (both national and mul-tinational ownership), using as explanatoryvariables those included in the InnovationSurvey. The abundance and heterogeneity ofvariables advised us to use Factor analysis toreduce and organise the number of originalvariables in a number of consistent and theo-retically significant factors. We have made aseries of sectoral analyses in an iterative wayusing both PITEC original variables and its

transformations. Non-included variables havebeen rejected on the basis of KMO and MSAvalues. Once relevant factors are retained, wehave made two series of logistics regressionsfor both process and product innovation im-plementation, with factors and firms owner-ship as independent variables. In each series,firstly we regress once for the whole sampleand secondly we regress four times more con-trolling by sectoral taxonomy.

In the next section, we present the main theo-

retical background, in the third section wediscuss our data and methodological guide-lines, in the fourth section we present somestylised facts of innovation activities in Spainfor a better understanding of the context inwhich our empirical work is done, in the fifthsection we show the empirical results and fi-nally in the sixth section we enhance the mainconclusion

2 It is called the PITEC panel (Panel de Innovacion Tec-

nologica). See: www.technociencia.es. Due to the manipulationof the original survey data, the information of this panel cannotbe compared in absolute terms with data directly derived fromthe innovation survey used in the former section.


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2.Theoretical backgroundIt is not our intention to develop a completetheory of factors affecting innovation. First ofall this is because such a theory is not avail-

able, as demonstrated by both the attempts togather the most relevant empirical investiga-tions (Tidd, Bessant and Pavitt, 1997), and thelist of issues included in seminal books as is-sues affecting innovation (Rothwell andDodgson, 1995; Fagerber et al, 2006). On thecontrary, our aim is to briefly review the mostsignificant contributions to find some theoreti-cal guidelines for our empirical research. Inthis regard, to briefly summarise the panoramaof theoretical visions of the conditions whichpromote successful innovative activities offirms, we can cluster them together in two

fundamental groups. On the one hand arethose belonging to the long tradition of in-dustrial organisation theory which basicallysearch for a few determining factors of thecapacity of innovation and, on the other, thosemore representative of the relatively recentapproach of the evolutionary theory which isbased on the analysis of variety and diversityof innovative modes and frequently uses theclassification of cases as a basic theoreticaltool.

Starting from the tradition of industrial organi-sation studies, one must remember their cen-tral methodological characteristics consistingof the combination of the three classical stepsof structure-conduct-performance (Schererand Ross, 1990). As formerly for other e-conomic issues, the analytical work is orientedto finding out one or a few factors (never alarge number) which can explain the in-novatory activity of the firms in a satisfactoryway3. Without a doubt these two are the mostfrequently researched elements: the size of the

firm and the concentration level of the marketsin which firms carry out their innovative ac-tivities.

In spite of the huge number of studies madeabout both of theses issues, the current situa-tion is that there are no conclusive results al-lowing us to assert the sign and intensity ofthe impact those factors have to induce in-novation. In fact, as far as the size of the firmis concerned, we can share the argument of

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Orsenigo (1989) suggests they use a dichotomous perspective:large versus small size, concentrated versus non-concentratedmarkets, etc. Cohen (1995) calls them studies in the Schum-peterian tradition.

Freeman and Soete (1997, page 193) that thesize certainly influences what kind of projectscan be attempted in terms of technology, com-plexity and costs but does not in itself de-termine the outcome.

This inconclusive conclusion is the result of alarge amount of empirical research relating tothe size of the firms and innovative activitiesof the firms. Perhaps the most classic one isthe association of size with R&D expenditure.In this case, the available research shows thereis a concentration of R&D expenditure in largecompanies, basically determined by the size ofR&D programmes instead of the size of thefirm (Freeman and Soete, 1997). Nevertheless,it is more difficult to find a clear associationbetween the increase of the size and the inten-

sity of R&D expenditure. In fact, mainly aftercontrolling by sector, the association seems tofollow a growing trend (the larger the size themore intense is R&D effort) but just to a cer-tain extent; from this point onward the do-minant relation is a proportional one (Cohen,1995). With regard to small firms, the evi-dence points to a twofold situation: whereas avast majority of small firms do not performany specialised R&D programme, in severalcountries those small firms that do performR&D have above average R&D intensities(Freeman and Soete, 1997, p. 232).

The situation is even less clear if innovationreplaces R&D activities; more qualificationshave to be incorporated, such as, for example,the possible advantage of small companies inearly stages of innovative work and the lessexpensive but more radical innovation,whereas large firms have advantages in thelater stages and improvement and scaling up ofearly breakthroughs (Freeman and Soete,1997, 234). More generally, Rothwell andDodgson (1995, 323) arrive at the following

conclusions:

I. Innovatory advantage is unequivocallyassociated neither with large nor smallcompanies. Small firm advantages aremainly behavioural while those of largefirms are mainly material.

II. Available data suggests that the firmsize/innovation share relationship is U-shaped.

III. Small firms innovatory contribution va-ries significantly from sector to sector.


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IV. Small and large firms do not operate inisolation from each other and they enjoya variety of complementary relationshipsin their technological activities.

V. Any study of the roles of small and large

firms in innovation should be dynamic:their relative roles vary considerablyover the industry cycle (Shepherd, 1991;Utterback, 1994).

The situation is more confusing if the aim is toassociate levels of concentration (or monopo-listic power) with a superior innovative per-formance. The reason is that there are twodifferent angles to approach that relationship:one is the passive and direct association ofhigher levels of concentration with more in-

tensive behaviour and the second the moredynamic and complex one that postulates theneed for a monopolistic reward to encourageinnovative activities (Orsenigo, 1989; Cohen,1995). In the first case no strong conclusiveresult can be shown and the second is verydifficult to test; therefore, some idea of a si-multaneous determination of concentrationand innovation can be proposed (Cohen,1995).

To complete that uneven perspective we canconclude that to generalise about size of thefirms, scale of R&D, inventive output and in-novation needs to be heavily qualified. In-dustry, technology and history matter4 (Free-man, 1982; Freeman and Soete, 1997). Thereare not many other features so deeply investi-gated. In general, progress has been poor intopics such as the influence of cash flows ordiversification (Cohen, 1995). Nevertheless, itis important to highlight the importance givento some organisational characteristics in theseminal SAPPHO project (Rothwell et al,1974) and the renaissance of those elements in

the literature and policy practices (Nel-son&Sampat, 2001; Nelson, 2008; OECD,2005).

Following a methodology of comparing suc-cess and failure of innovation, the SAPPHOproject spotlighted a number of organisationalvariables, mainly marketing related, exter-nal communication and firm management.

4 It is important to remember a number of empirical limitswhich seriously make it difficult to arrive at general conclusions.

According to Cohen (1995), we can mention the fact that sam-ples are mostly not random, in many cases there are other firmsvariables out of control and the multisectoral character of mostlarge firms.

Freeman cleverly summarised it by saying:the fact that the measures which discrimi-nated between success and failure includesome which reflected mainly on the compe-tence on R&D, others which reflected mainlyon efficient marketing and some which meas-

ured characteristics of the business innovatorwith good communications, confirms thatview of industrial innovation as essentially acoupling process (Freeman, 1982, 125).

The former notwithstanding, the innovationtheory reoriented the approach to investigatethe role of the firms. Precisely the cited bookof Freeman, together with seminal works suchas Rosenberg 1976, Nelson and Winter, 1982,Dosi, 1984 and Pavitt, 1984 made claims for abetter understanding of technology and inno-

vation that enables to create a more accuratetheoretical approach. Apart from other generalconsiderations (Orsenigo, 1979; Dosi, 1984) asfar as this paper is concerned, the centralchange has to do with the introduction of vari-ety and diversity as opposed to the mainstream perspective of general determinants offirms innovation; furthermore, the notion oflearning occupied a central position as aconsequence of considering technology andinnovation as specific kinds of knowledge(Pavitt, 2006).

As a consequence of this new orientation theapproach to firms innovatory behaviour in-corporates a number of remarkable modify-cations. Four of them are particularly sig-nificant for the objectives of this investigation:the role of systems of innovation, the im-portance of non-technological innovation, therelevance of the sector of activity and the in-troduction of taxonomies to map the hetero-geneity of conducts.

The concept of systems of innovation (Free-

man, 1987; Lundvall, 1992) basically rein-forced the idea of systemic interaction amongfirms and a large amount of institutions. Thus,in the context of this paper, the relevant issueis the necessity of incorporating internally andexternally sources of knowledge to the firm,either on a collaborative mode or throughmarket mechanisms. In other words, the i-solated consideration of firms characteristicsis not enough to fully understand the innova-tive practice of enterprises (Rothwell, 1995;Tidd, Bessant and Pavitt, 1997); hence va-

riables measuring such an interaction must beincorporated.


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Regarding non technological innovation, thefirst consideration is what aroused in theSAPPHO project: organisational factors considered form a broad perspective- play acrucial role for the overall innovative strategyof the firms. More recently, Nelson and others

(Nelson&Sampat,2001, Nelson, 2008) haveinsisted on the necessity of fully integratingsocial and physical technologies at microand macro level. Furthermore, Teeces contri-bution to firms innovatory attitudes put agreat demand on the necessity of including thecomplementary assets into the theoreticaland empirical explanation of innovation(Teece, 1986). As for the case of systems ofinnovations, the incorporation of variablesreferring to those non technological factors isabsolutely needed.

The issue of sector of activity is not new inindustrial economics. To a great extent it is theneed to consider competitive conditions in theanalysis; perhaps the most developed versionin the industrial organization tradition is themodel of competitive forces by Porter inwhich he combines five elements driving in-dustry competition. 1.- Relations with clients;2.- Relations with buyers; 3.- New entrants; 4.-Substitute products and 5.- Rivalry amongestablished firms (Porter, 1980)5.

The former notwithstanding, recent develop-ments within the general approach of the evo-lutionary theory spread the concept in thedirection of incorporating other sectoral con-ditions (Malerba, 2002, 2006) and/or the con-ditions for a sectoral model of accumulativetechnological change based on different Tech-nological Regimes or Innovation Patterns(Nelson and Winter, 1992, Malerba and Ors-enigo, 1995, 1997; Pavitt, 1984). In otherwords, as sectoral conditions for innovationare different, any efforts to understand that

process ought to incorporate sectoral di-fferences as a central analytical element; inPavitts words: increasing specialisation in theproduction of artifacts, and their underlyingknowledge bases, has made innovative proc-esses increasingly path-dependent. As a con-sequence, several aspects of innovation are

5 The strength of this model is the deep understanding of thecompetitive environment in which the business firms operates,and in which it must consciously try to position itself in itstechnology strategy, as well as in other dimensions of corporatepolicy (Tidd, Bessant and Pavitt, 1997, 67) although its main

weakness is that it underestimates the power of technical changeto transform industrial structures and overestimates the powerof managers to decide and implement innovation strategies(idem, 68).

contingent on sector, firms and technologyfield (Pavitt, 2006).The latter drives us to the fourth point: thetaxonomic exercise. As a general expression ofmost theoretical revisions, the concepts ofvariety and diversity came to substitute the

previous search for uniformity and universaldeterminisms. On the contrary, the evolution-ary theory postulates the existence of a hetero-geneous cluster of sources of knowledge, com-peting technologies, organisation models, waysof profiting from innovation and so on (Ors-enigo, 1989; Pavitt, 1984; Dosi, 1984; Dosi etal, 1988, etc). However, the scientific approachto the diversity requires further theoreticalefforts and it is here where the creation of tax-onomies emerges6. In fact, there have beenmany of them insofar as any taxonomy is de-

duced from some particular aspect the re-searcher wants to illuminate; albeit in thiswork we wish to underline two which haveinfluenced our empirical investigation: Pavitttaxonomy and Technological Regimens.

Pavitt taxonomy starts from the notion oftechnological trajectories as expression of thesectoral patterns of technological change. Theaim is to supply an empirical method to or-ganise the manifested variety of innovativeactivities into a group of trajectories on thebasis of 1) the sectoral sources of technologyused , differentiating between those internallygenerated from others coming from differentsectors. 2) Institutional sources and the natureof the technology 3) Characteristics of theinnovative firms.

The result is the establishment of several ca-tegories of technological trajectories to buildin which Pavitt combines some elements of thefirms themselves with others concerning thesources of knowledge and its diffusion throughproducts or process innovations; depending on

whether the innovation is used in a differentsector than the one in which they have beenproduced or if they are used in the same sectorin which they have been created (Pavitt,1984). The lesson for us is the need to con-sider those kinds of factors in any explanationof a firms innovation and that the distributionbetween product and process innovation canshed light on substantial aspects of the in-novation process. As a complementary consi-

6 Another significant effort has to do with the concept of rou-

tines which organises the otherwise random behaviour of thefirms and interactions markets and institutional forces to givesense to the complex activity of technology creation. See amongothers, Dosi et al, 1988.


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deration we wish to quote Edquist et al,(2001) when they prefer to include organisa-tional innovation as part of the process in-novation. We shall see how in our research thepossibility of comparing product and processinnovations upgrades the understanding of the

role of institutional aspects.

With regard to Technological Regimes, itsmost worthy contribution in this analysis is toenrich the approach to firms activity by a-llowing us to classify different strategies. Clas-sic and recent works (Malerba and Orsenigo,1996; Corocher, Malerba and Montobbio,2007) insist on the necessity of elaboratingmeasures which enable the analysis to discernthe underlying characteristics of the differentpatterns of innovating, according to the level

of opportunity, cumulativeness and appropri-ability of the different technological regimens.The dichotomy of two main Regimes, fo-llowing the Schumpeter analysis (SchumpeterI and II) allows us to distinguish how in eachof them we have a number of intra-firm cha-racteristics as well as others related to the in-teraction with the surrounding system: hightechnological opportunities, low appropriabi-lity and a low degree of cumulativeness (at thefirm level) for Schumpeter I, and high a-ppropriabiliy and cumulativeness (at the firmlevel) for Schumpeter II.According to the previous argumentation ourempirical research on the patterns of innova-tion of Spanish companies will be organisedunder the following guidelines:

1. Factors influencing innovation arevaried and partly belong to the devel-opment of innovative projects, part tothe firm as a whole and part to theenvironment (Rothwell, 1995)

2. It is absolutely necessary to base the

study on a statistical source whichcan provide information about eco-nomic features of the firms, their in-ternal innovative strategy and the in-teraction with the system in order tocapture the importance of inner andouter sources (Cantwell, 20067).

7 Interestingly enough are the arguments Cantwell provides toexplain the lesser independence of firms and their deeper de-pendency on background knowledge: 1) The increase of inter-company flows. 2) The increasing role for government and othernon-corporate institutions in knowledge creation. 3) The grow-

ing importance of science for technology and 4) the tendencytowards a more rapid codification and the formation or spread-ing of professional and scientific communities (Cantwell, 2006,561).

3. The fundamental role of organiza-tional aspects both for the generalimplementation of innovation and aspart of the general innovative activi-ties of firms and institutions (La-zonik, 2006)

4. It is also crucial to take into consid-eration the role of the sector of activ-ity. In spite of the existence of quitefrequently used categories (e.g. theOECD classification according to thetechnological content of the sectors)we have chosen another option con-sisting of the elaboration of a sectoraltypology according to their own in-ternational technological position. Inother words, we prefer a self contai-

ned classification.

5. The distinction between product andprocess innovation to assess to whatextent the factors are common forboth types; particularly when in bothcases the sectoral typology is applied.

6. Finally, the consideration of differenttypes of firms ownership, especiallyas far as the internationalisationprocess is concerned. The issue of thereciprocal invasion of innovationsystems demands a necessity of un-derstanding of the innovatory modesemployed by domestic and interna-tional companies and to what extentthe increasing internationalisation ishomogenising (or not) the innova-tion activity.

In section 3 we shall develop the way in whichwe have made operative those guidelines.

3.Methodology and data ana-lysis.To carry out the investigation, we count ontwo important mainstays. On the one hand, wehave developed a self-classificatory ta-xonomy of manufacturing sectors in terms ofinnovative dynamics and performance; on theother, the recent availability of anonymousmicro-data of the Spanish Innovation Survey8

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It is called the PITEC panel (Panel de Innovacion Tec-nologica), and is designed and built as a statistical instrumentfor monitoring technological innovation activities of Spanishfirms. See: http://sise.fecyt.es/Estudios/PITEC.asp.


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with a great statistic validity endorsed by theSpanish National Statistics Institute, the S-panish Foundation for Science and Techno-logy (FECYT), and COTEC Foundation.

To build our taxonomy we have systematically

compared the percentage evolution rate be-tween two periods (1993-1998 and 1999-2003) both of patents granted for each sectorof activity and their Revealed TechnologicalAdvantages (RTA9) using data from patentsgranted by the USPTO by priority year at thenational level by the sector of economic activ-ity (NACE class derived through concordancewith International Patent Classification).

With two classification axes, we are able toclassify each NACE sector in one of four cate-

gories. Presented vertically we find technologi-cal advantage (upper) or disadvantage (lower)while horizontally we see worldwide evolution(positive on the right hand side and negativeon the left one); for technical details, see An-nexe A)10. As a result, we define the followingfour categories: Dynamic specialisation ifthere are RTA advantages in dynamic sectors;it is the best of the cases insofar as the speciali-sation of the Spanish economy fits perfectlywith the international technological dynamic.Retreat, with RTA disadvantages in sectorsin retreat; it is a residual case also with posi-tive aspects. Lost opportunity, with RTAdisadvantages in dynamic sectors; it is theworst possibility because the Spanish economyhas not been able to adapt to the internationaldynamism. Finally Stationary specialisation,includes RTA advantages in sectors in retreat;this also reflects a less favourable position in-sofar as it shows the Spanish specialisation isproduced in internationally less dynamic sec-tors. Classification of PITEC sectoral defini-tion is shown in Table 3 of Annexe B11.

This taxonomy has the main advantage de-rived from its self-classificatory to put each

9 RTAs for a sector of a country are calculated as follows: RTA ij =(Pij / Pwj )/ (PTi / PTw) where i is the country, j the sector, w theworld total for j sector, T is the total of the country and tw is theabsolute world total. All refer to a period of time. 10 A note of caution has to be introduced in these types of classi-fications because it is not the same to be far from the crossingpoint of the two axes than to be near it. However, we under-stand it is valid for a first approach, irrespective of the possibil-ity of further qualifications.11 Although it is not the central issue of this paper, it is impor-tant to highlight the not very favourable position of Spain in

considering two aspects. First, the weak specialisation of Spainin most ICT technologies and second the abundance of cases ofadvantages in sectors which in the last decade have had a rela-tive stagnation with regard to World dynamism.

NACE sector into one of our four categories.Thus, we can avoid a-prioristic and rigidclassifications (following OECD technologicalcontent classification, Pavits taxonomy orothers) that could not be appropriated to a-nalyze the characteristics of intermediate

countries, as is the Spanish case. In opposition,our taxonomy is flexible because classificationresults from sectoral characteristics on eachcountry; so it can be adapted from one countryto another and each sector moved from onecategory to another, if necessary, but the crite-ria to construct categories remain unchanged.

Furthermore, this taxonomy allows us toevaluate overall sectoral specialisation of acountry as a whole in terms of innovative andtechnological performance. If most of the sec-

tors (in number and in GDP percentage) areplaced in main diagonal (Dynamic and Re-treat) this country is well adapted to interna-tional innovative and technological dynamics;in the contrary case, if most of the sectors areplaced on the inverse diagonal (Stationaryand Lost Opportunities), country specialisa-tion is contrary to international one.

The great statistical validity of anonymousmicro-data is derived from the fact that anexpert group coordinated by the Spanish Na-tional Statistics Institute has, on the one hand,drawn up a permanent sample of firms withthe intention of creating a stable panel of dataand, on the other, has controlled the statisticalsignificance of the anonymous data vis--visthe original micro data. This information al-lows us to separate firms according to theirindependent feature (Independent companies,ICs) or belonging to a group, including thecountry of origin of the mother house of thecluster. If the headquarters is located in Spain,we can assume most of them can be expectedto behave as Spanish multinationals, following

some international literature (Evangelista,2005). Nevertheless, as it is not possible toconfirm this multinational character of thegroup we shall call them National groups(NGs) versus Multinational Groups(MNGs)12. Using the original variables of thepanel we have calculated some additional onesthat are listed in Table 1 of Annexe A. Afterthese calculi, we work with variables listed inTable 2 of Annexe B.

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Here we introduce an MNG definition to enhance the fact ofbelonging to a group of enterprises versus individual companiesin our empirical analysis. Nevertheless, both MNG and MNEmust be interpreted similarly.


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The method proposed has two steps. In thefirst step, we use factor analysis to see howdifferent variables behave relative to othersand to reduce the information to be used inthe explanatory phase. Once factors have beenobtained, the next step is to include them as

explanatory variables in different Logit mod-els13 in order to estimate which of them (and towhat extent) affect any observed firms imple-mentation process or product innovation.Using extracted factors as explanatory var-iables, it is possible to show the most signifi-cant variables or factors explaining the di-fferences between innovative and non-innovative firms. Including dummies to con-trol the fact of belonging to a multinationalgroup or to be an individual firm, we can de-tect the different-tiated impact MNGs have

upon the Spanish Innovation System. In thefinal stage, the analysis will be made introduc-ing the sectoral typology of the sectors as afactor to be controlled.

To tackle this task we have carried out a seriesof alternative Logits. Firstly, we have studiedthe model in which the dependent variable isINNPROD (1 for companies which have suc-cessfully introduced a product innovation; 0for the opposite), without distinguishing in-dependent or national group firms, or splittingthe survey by type of sector; typology of firmsownership is introduced as a potentially ex-planatory variable. Afterwards, we have re-peated the analysis by splitting the survey bysectors. The same analysis is made for a modelin which the dependent variable is INPROCC(1 for firms having successfully introduced aprocess innovation; 0 for the opposite), in-itially without sectoral cuts in the sample andafter controlling by sectoral taxonomy; in bothcases with firms ownership types as poten-tially explanatory variables.

4.Some stylised facts of theinnovation in the Spanisheconomy.In order to provide a minimum framework tocontextualise our empirical work, we under-stand it is worth summarising some stylisedfact which characterises the situation of the

13 The choice of this regression technique responds to twofold

criteria, On the one hand, the comparison of pairs of groups andon the other, to detect the relative effect of each factor to explaindifferences between groups of firms. See Wooldridge (2000) fora detailed exposition of logit and probit models.

innovation in the Spanish economy, with par-ticular attention paid to firms.

The first aspect to consider is the relativelyreduced level of innovation in Spain, clearlybelow the potential level offered by its eco-

nomic development offers. According to thelast Innovation Scoreboard (see figure n 1)Spain occupies the 25th position of 37 OECDcountries analysed: the Summary InnovationIndex (SII) of Spain is 0.31, while the EU a-verage is 0.45 and the leading countries arearound 0.7. The cluster analysis carried outwith all those countries includes Spain in thelast position of Modest Innovators, thethird of four clusters.


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Source: Innovation Scoreboard 2007

On splitting the SII into its main components see figure n 2- we arrive to a second deter-mining feature of the Spanish situation: theworse performance shown by aspects relatedto entrepreneurship and creation and appli-cation of knowledge. From another perspec-tive we can complete it by underlining the fact

that the participation of private companies in

the overall financial effort and R&D executionis significantly below the average of countrieswhich lead the innovation dynamism interna-tionally.

Figure n 2: The Main Components of SII in Spain and the EU (Spain is the black line)

Source: Innovation Scoreboard, 2005.

Another significant aspect to mention refers tothe combination of internal and externalsources of information for the innovativetasks. Data of the last Spanish Innovation Sur-vey (2006) show that only 9.10% of firms con-sider their own internal sources to be veryimportant against versus 8.87% which givethat importance to market sources, 1.29% offirms to Institutional sources (mainly Univer-sities and Research centres) and 2.64% to

Other sources. If we focus only on the Indus-trial sector the corresponding figures are:16.35 % for internal sources, 15.07% for mar-ket, 2.63 for Institutions and 4.78% for others.Two main elements arise from those data: firstthe greater confidence of firms in outersources of information and, second, the littleimportance given to non-entrepreneurialsources; the clearest example is just 1.24% of


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manufacturing firms mention the University asan important source.

An outstanding feature concerns the type ofinnovation. Generally speaking, there is a clearpredominance of process versus product in-

novation. Thus, the 2006 Innovation Surveyshows that there are 25% more firms claimingto carry out process innovation rather thanproduct one (33,767 versus 27,085); in indus-trial firms the proportion is even higher, 34%more process than product innovation (12,098versus 9,007).

More complete is the information given by the2005 edition of the Innovation Scoreboard.There they clustered innovative firms in fourtypes. Strategic, Intermittent, Modifiers and

Adopters. Figure n 3 shows the result ofcomparing Spanish and EU situation: the out-standing majority presence of mere Adoptersin Spain accurately qualifies the situation.

Figure n 3: Spain Innovation Mode

Source: Innovation Scoreboard 2005.

Lastly we want to mention the magnitude ofthe internationalisation of innovation. On the

one hand we must say the weight ofMNEsR&D activity is relatively high, one ofthe heaviest in West Europe14 (see figure n 4).On the other, that presence is clearly asy-mmetric insofar as the R&D MNEs carry outin Spain is of relative importance for them (onrare occasions it is strategic) while for theSpanish economy it represents a great propor-tion of the overall private effort.

14 Nevertheless Spain is practically the only case in which thatweight has decreased in the last years.

Figure n 4: Multinational CorporationR&D expenditures over total national

Czech Republic

Hungary (1)

United Kingdom

Turkey (2,3)

Sweden (1)

Spain (3)

Poland

Portugal (2,3)

Netherlands (1)

Italy

Ireland (1,3)

Germany (1,3)

France

Finland

Japan (1)

United States (1)

Canada

0

10

20

30

40

50

60

70

80

0 10 20 30 40 50 60 70 80

Production (%)

R&D expenditure (%)

Source: OECD, 2007

5. Results.5.1. Factor analysis.As a first step in the explanatory phase wehave made a series of trials in an iterative waywith variables listed in table 2 of the annexe,and using the principal components method.Non-included variables have been rejected onthe basis of KMO and MSA values. After se-veral tests we have eliminated FUNIV, FIPSFLand FEXT (for those only 7 observations pre-

sent values different from zero) and alsoFEMPEXT and FEMP (with 24 and 73 obser-vations that present values different fromzero). The KMO ratio rises at acceptable values(0.54) and explained variance goes as far as63%. To continue eliminating variables givesus very low KMO improvements, does notimprove explained variance, and distorts Fac-tor results; we stopped the process at thispoint.

In those tests, Factor structure remains verystable with few changes: 9 factors (8 when weeliminate the last variables). Individual Factorexplained variance has four levels (level I, 1 or


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2 factors between 9.5% and 10.5%; level II, 3or 2 factors between 7% and 8.5%; level III, 3factors between 5.5% and 6,5%; level IV, 2factors around 4,5%).

The more solid Factor structures are:

NESTR, NGEST, NORG, NMARK,NESTE, always in the first level andusually the first factor.

GMAQUI, GTECNO, GPREP, usuallyin the second level, we find a tendencyto incorporate GFORM also.

PATNUM, FPRO, usually in the se-cond level. GINTID has a tendency tolink this factor.

INNOVEM, INNPROD, sometimes inthe second level, others in the third.

PIDTEJpw, FAP, sometimes in thesecond level, others in the third.

TAMMED, GEXTID, GMARKET, u-sually in the third level.

INNNOVET, INNPROC, always in thelast level.

INNOVEC, INFUN, always in the lastlevel too.

Our selected Factor structure is shown in Ta-ble 1 and its quite reasonable possibility ofbeing interpreted in economic and innovativeterms must be underlined; each factor is ac-companied by the variables that cluster to-gether and the name we have assigned to makeexplicit its economic or innovative signifi-cance.

TABLE 1: extracted factors.EXPLAINED VAR (%)Factor DESCRIPTIONEach factor Accumulated

1 Organizational Innovation (ORGINNV) 10.53 10.53

2 Non-R&D innovative expenditures(NRDEXPEND)

10.42 20.95

3 Own R&D and results (RD&PAT) 7.5 28.454 Product innovation on inner effort (PRODINNER) 7.15 35.65 Human resources and Public funds

(HUMCAP&FUNDS)6.15 41.75

6 Size and external knowledge integration(SIZE&INTEGRATION)

6.05 47.8

7 EU funds attraction (UEFUNDS) 5.81 53.618 Basic research and cooperation

(BASICR&COOP)4.82 58.43

9 Process innovation on external sources(PROCEXTER)

4.81 63.24

Source: Own elaboration from PITEC; principal components method.

5.2 Regression analysis.This phase of the analysis has been donethrough the estimation of regression modelsusing the former factors as independent va-riables to explain the innovative activity of thefirms. Following the research path proposed,we have estimated a number of logistic re-gressions with several characteristics:

We have separated product and pro-cess innovation on the understanding

that there can be significant differencesbetween them. In both cases modelstry to explain the probability of any

firm belonging to the innovative groupor not.

Apart from the factors we have in-cluded as independent variables twodummies trying to control the fix e-ffect of firms belonging to any of thethree groups in which we have dividedthe sample: independent Spanish com-panies (EIN), firms belonging to a na-tional group (GN), and firms be-longing to foreign multinationalgroups (GMN). The idea is to considerthe importance of the growing interna-


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tionalisation of the innovation in theSpain.

In addition to the general regressionsfor products and processes we have es-timated in each case four other regret-

ssions corresponding to the types ofsectors formerly explained.

The results are shown in tables 2 and 3 fromwhich we can deduce as the main findings thefollowing.

TABLE 2: Logit coefficients for innprod (product innovation)Variable GLOBAL DYNAMIC STATIC LOST

OPP.RETREAT

ein .226**gmn

basicr_coop .209*** .241*** .182*humcap_funds .981*** .977** .526*** 1.29***

nrdexpend .406** -5.26*** .804** -6.13***orginnv .424*** .435*** .402*** .439*** .393***

rd_pat .449*** 1.57*** .65***Size_integr .238** 2.06*** .324*** .146* 2.12***uefunds .195** .46*** .437*constant .677*** 1.22*** .618*** .915*** .582***

N 3691 805 1362 1086 438ll -2213 -427 -852 -634 -250

ll_0 -2395 -500 -900 -695 -294chi2 363 144 96.1 123 87r2_p .0758 .144 .0534 .0881 .148

aic 4445 869 1713 1284 509bic 4500 902 1739 1324 525

legend: * p


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GENERAL FINDINGS.1. Generally speaking we obtain a better

explanation for process than forproduct innovation. It is reflected inthe higher pseudo R2 values and in

the higher homogeneity found acrosstypes of sectors. Nevertheless, signi-ficant factors are rather similar, al-though size & integration is moreimportant in product innovation.From a more speculative point ofview we ask if those differences are areflection of the Spanish innovationcharacterised, among other elements,by a lesser presence of radical andstrategic innovations and a heavierweight of adoptions and by a lesser

dependence on foreign inputs inprocess technologies (Buesa&Molero, 1992; Molero, 2007).

2. The association between human ca-pital (personnel) and the access topublic funds changes its signs: posi-tive for product innovation and nega-tive for process. All the remainingfactors maintain the same sign inboth cases.

3. The kind of sector emerges as muchmore important than the type offirms ownership, confirming whatwas expected. Once we control forthe first, we only find a case in whichthe type of firm is relevant: ICs inprocess innovation of Stationary Spe-cialisation sectors. Importantlyenough it must be said that thisgroup gathers a non negligible num-ber of so called traditional industriesin which independent companies arestill the bulk of the activity.

4. Organizational innovation arises asthe most important factor explainingthe behaviour of innovative firms. Itsuniversal presence in both types ofinnovation and in all kinds of sectors,always with a positive sign, allows usto assert that this new evidence con-firms and reinforces what theory andprevious studies predicted.

5. After controlling for type of sector, a

number of differences can be found.It is so both for the explanatory ca-pacity of the models and for concrete

factors which are significant in somecases but not in others (sometimeschanging the sign). In our opinionthis confirms and justifies the re-levance of the taxonomy used. More-over the level of adjustment varies

significantly between the sectors be-tter adapted to the international dy-namism (Dynamic Specialisation andRetreat) and the other two more im-balanced sectors (Lost Opportunitiesand Stationary Specialisation).

PRODUCT INNOVATION1. The type of firm is not significant in

any of the cases. However the size &integration factor has a favourable

effect in all cases.

2. Expenditures on non R&D in-novative activities have a positiveimpact in Lost Opportunities, ne-gative in Dynamic Specialisationand Retreat and are non- significantin Stationary Specialisation. Thispoints out to a greater necessity ofproper R&D activities in more dy-namic sectors to follow the worldevolution whereas in dynamic sec-tors in which Spain has technologi-cal disadvantages, non R&D activi-ties can be considered as an alter-native to build some capacities to becompleted afterwards through R&D.

3. The already mentioned role of or-ganisational innovation shows ahigher effect in the two sectors withweaker adaptation to the world dy-namic: Stationary Specialisation andLost Opportunities. In other words,it is for those sectors that this non

technological innovation seems toplay its most important role.

4. The joint effect of R&D expenditureand Patents is a factor which po-sitively influences product in-novation in internationally dynamicsectors, regardless of having tech-nological advantages or disadvan-tages. That is to say, in mature sec-tors the technological effort mea-sured through R&D and patents is

not a discriminating factor betweeninnovative and non innovativefirms; whereas it positively dis-


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criminates in dynamic sectors. Inthese cases R&D and patents appearas a requirement to get technologi-cal advantages. A similar commentcan be made with regard to UEfunds; this factor can be understood

as an index of innovative dynamism.

5. Basic research and Cooperation isonly significant in the two sectorswhich reveal a bad international a-daptation: Stationary Specialisationand Lost Opportunities. Thereforewe can send a message for policyconsiderations: to strengthen thoseactivities is essential to improve thesituation of the firms in Lost Oppor-tunities sectors.

PROCESS INNOVATION1. Independent companies are more ac-

tive in Stationary Specialisation sec-tors, together with Size & Integra-tion factor. The weight of traditionalsectors with independent companiessome of them of noticeable size- a-llows us to interpret this result as asituation in which foreign companiescome to follow or adapt the be-haviour of national companies withremarkable technological advan-tages.

2. Basic Research & Cooperation is fa-vourable in the four cases, albeit itseffect is relatively higher in sectorswith bad international adjustment:Lost Opportunities and StationarySpecialisation. This result supportswhat was said in the analysis ofproduct innovation: financing basicresearch and cooperative activities

positively influences innovation inproduct and process.

3. Non R&D innovative expenditureshave a negative impact in all sectorsexcept in Lost Opportunities. More-over, the size of the effect is muchgreater in sectors positively adaptedto international evolution. Again,most dynamic sectors are muchmore dependent on R&D while inother cases non R&D activities can

be a preliminary step to create R&Dcapabilities.

4. Organisational innovation, as always,favours innovation and its effect isgreater in internationally dynamicsectors, particularly if it is a sectorwith technological disadvantages.

5. The positive sign of Human Capitaland Funds suggests in processeswith more systematic and in-cremental innovation, the stability ofhuman resources is important andthey seem to be strongly connectedwith the availability of public funds.

A complementary way of exploiting the find-ings can be made through the point of view ofthe kinds of sectors to highlight some relevantregularities. The starting point is the existence

of more similarities between sectors with goodfitness concerning international dynamism, onthe one hand, and between those badlyadapted, on the other.

As far as the first two are concerned we canpoint out that in the Dynamic Specialisationcategory two factors are common to productand process innovation: Organisational In-novation, with a positive impact, and nonR&D expenditures, with a negative one. An-other two show different signs in product andprocess: Human capital and Funds and R&Dand Patents- both have a positive effect inproduct innovation and a negative effect inprocess.

Regarding Retreat Sectors, only two factorsarise as common to product and process: Thesalient fact is that Organisational Innovationand Non R&D expenditures are common toboth Dynamic and Retreat and both types ofinnovation, product and process. The first hasa regular positive influence and the second anegative one.

In Dynamic sectors the role of human capitaland funds and R&D and patents is also re-markable. The two are significant for bothtypes of innovation, although with differentsigns; positive for product and negative forprocess.

Coming to sectors with negative internationaladjustment, it is noticeable that there is lessregularity than in the former cases. The mostoutstanding are the following.

Apart from the systematic presence of or-ganisational innovation, there also arises the


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regular presence of Basic Research and Co-operation. This, on the one hand, explains theinsufficient role played insofar as it has notbeen enough to guarantee a better interna-tional adjustment. This is why we insisted onthe idea that policy has to foster those activi-

ties in order to upgrade the situation.

A second regularity has to do with HumanCapital and Funds. This factor is common tothe two sectors and types on innovation, al-though for the last one, the sign changes frompositive in product to negative in process.

6.Concluding remarks.As on many occasions, the distance betweenthe theoretical debate and empirical findings

has been non-negligible in this research exer-cise. In fact, the theory about factors affectingfirms innovation has still a long way to gobecause the analytical object is complex anddifficult to set limits for, as our review of theliterature has shown. In spite of those difficul-ties we have tried to cast some light on thebases of the study of the Spanish case withsome noticeable features: first, the importancegiven to the category of sector by constructinga new taxonomy through the combination ofsectoral technological RTAs and the interna-

tional dynamism; second, the utilisation of avery reliable database, which, based on the CIShas been statistically improved and ready to beused prepared by a group of specialists; third,the combination of a very large number ofvariables in order to capture the richness andcomplexity of the innovatory process; fourth,the inclusion of a separate study of productand process innovation; and fifth, the incorpo-ration of the type of company by differentia-ting between national independent enterprisesfrom either national or multinational groups.

The results obtained allow us to make explicitthe following remarks:

1. First of all, the methodology hasdemonstrated its usefulness becauseboth the sectoral taxonomy and theseparation of product and process in-novation show significant differences.

We should like to underline the im-portance of typological analysis in theoverall theoretical effort.

2. Particularly important are some find-ings about differences across catego-ries of sectors. If in a preliminary ap-

proach we differentiate between thepositive diagonal (dynamic and re-treat sectors) and the negative one(lost opportunities and stationaryspecialisation), we arrive at the con-clusion that our estimations are

stronger for the positive one, both forproduct and process innovation. Inother words, the influence of thevariables grouped in factors, allowsus to assert that there is a better inte-gration and functioning in the casesin which the Spanish specialisationcoincides with the world dynamic.

3. Similarly, although less clearly, theseparation of product and process hasshown its usefulness. In general

terms the better adjustment of themodel for explaining process innova-tion is adequate to Spanish innova-tive specialisation which is moreprocess oriented. Even though withthe necessary caution, we can re-member the demonstrated bias of theSpanish pattern towards less inten-sive and more adoption based kindsof innovations. Furthermore, the ex-traordinary importance of machineryand equipment purchases as sourcesof innovation for a majority of firmsfits well into our findings.

4. On the contrary, the type of firms ac-cording to the distinction betweennational and foreigners does not shedmuch light. Very much in accordancewith previous works (Molero & Gar-cia, 2008), our results do not find ex-traordinary differences between com-panies belonging to national or mul-tinational groups. Although a num-ber of qualifications must be in-

troduced regarding the organisationof innovative process, our study findsmore similarities than differences re-garding the innovatory efficiency.Thus notwithstanding, we find outsome differences for companieswhich are not members of a group(regardless of its nationality) particu-larly in sectors named as traditionalor of low to medium technologicalintensity.

5. To explain differences sectoral tax-onomy is clearly more relevant thanfirm ownership typology. This fact


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point to, both, on the relevance oftaxonomy and on the adaptative stra-tegies of MNCs.

6. Public grants enhance product in-novation, perhaps because they help

to solve problems with human re-sources expenditures on concreteproject development. But, on theother hand, they hamper process in-novation, revealing weakness in hu-man resources expenditure financingwhile for process innovation stabilityand temporal continuity they are ur-gently required.

ANNEXE A: SECTORALCLASSIFICATION

Two criteria have been combined: the positionof the sector in the Spanish economy accord-ing to its Revealed Technological Advantage(RTA) and the international dynamism of thesector in terms of its percentage in world totalpatents. The source has been the US patent

office and the period selected 1993-2003, di-vided into two sub periods. 1993-1998 and1999-2003. Patents have been obtained at twodigit level of NACE classification as providedby Eurostat. RTA has been calculated for thesub period 1999-2003 while the technological

dynamism of the sectors has been estimatedthrough the difference between the percent-ages each sector has in total patents in thesecond period compared with the same per-centage in the first one.

Combining the two criteria we arrive at a ty-pology with four cases: 1: sectors with RTA > 1and an increase of its percentage in world pat-ents between the two periods (Dynamic Spe-cialisation). 2: sectors with RTA 1 and a decreas-ing participation in world technological dyna-mism (Stationary Specialisation) and 4: sectorswith RTA < 1 and an increasing participationin total patents (Lost Opportunities).

SECTORAL CLASSIFICATIONLost Opportunities SectorsTanning, dressing of leather; manufacture ofluggage

Manufacture of fabricated metal products,except machinery and equipmentManufacture of office machinery and com-putersManufacture of electric motors, generatorsand transformersManufacture of accumulators, primary cellsand primary batteriesManufacture of lighting equipment and elec-tric lampsManufacture of electrical equipment n.e.c.Manufacture of electronic valves and tubesand other electronic components

Manufacture of television and radio transmit-ters and apparatus for line telephony and linetelegraphyManufacture of television and radio receiv-ers, sound or video recording or reproducingapparatus and associated goodsManufacture of industrial process controlequipmentManufacture of optical instruments, photo-graphic equipmentManufacture of watches and clocksManufacture of motor vehicles, trailers and

semi-trailersManufacture of other transport equipment

Dynamic Specialisation SectorsManufacture of textilesManufacture of wearing apparel; dressing;

dyeing of furManufacture of basic metalsManufacture of machinery for the productionand use of mechanical power, except aircraft,vehicle and cycle enginesManufacture of other general purpose ma-chineryManufacture of agricultural and forestry ma-chineryManufacture of machine-tools (split intoDK2941, DK2942 and DK2943 in NACERev.1.1)Manufacture of other special purpose ma-

chineryManufacture of domestic appliances n.e.c.Manufacture of electricity distribution andcontrol apparatus, manufacture of insulatedwire and cable


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Manufacture of furniture; manufacturing n.e.c.

Retreat SectorsManufacture of tobacco productsManufacture of wood and of products ofwood and cork, except furniture; manufactureof articles of straw and plaiting materials

Manufacture of other non-metallic mineralproductsManufacture of medical and surgical equip-ment and orthopaedic appliancesManufacture of instruments and appliancesfor measuring, checking, testing, navigatingand other purposes, except industrial processcontrol equipment

Stationary Specialisation SectorsManufacture of food products and beveragesManufacture of pulp, paper and paper prod-uctsPublishing, printing, reproduction of recorded

mediaManufacture of coke, refined petroleum prod-ucts and nuclear fuelManufacture of basic chemicalsManufacture of pesticides and other agro-chemical productsManufacture of paints, varnishes and similarcoatings, printing ink and masticsManufacture of pharmaceuticals, medicinalchemicals and botanical productsManufacture of soap, detergents, cleaning,polishing

Manufacture of other chemical productsManufacture of man-made fibresManufacture of rubber and plastic productsManufacture of weapons and ammunition

Source: Own elaboration

ANNEXE B

TABLE B1: Calculated Variables.VARIABLE CALCULUS FROM PITEC VARIABLES AND DESCRIPTIN

EGTINN (GTINN/CIFMED*100) Innovation effort

GTINNpw (GTINN/TAMMED) Expenditure in innovation per worker

PIDTEJCpw (PIDTEJ/TAMMED*100) R&D staff per 100 workers.PGINTID (GINTID/GTINN*100) % Internal R&D expenditure

PGEXTID (GEXTID/GTINN*100) % External R&D expenditure

PGID (PGINTID+PGEXTID) % R&D expenditure

PGMAQUI (GMAQUI/GTINN*100) % Expenditure in acquisition of machines, equipment andsoftware

PGTECNO (GTECNO/GTINN*100) % Expenditure in acquisition of external know-how

PGPREP (GPREP/GTINN*100) % Expenditure in preparation for production/distribution.

PGFORM (GFORM/GTINN*100) % Expenditure in training

PGMARKET (GMARKET/GTINN*100) % Expenditure in introduction of innovations

FPRO (F1) Own funds

FEMP (F2+F3+F4) Funds from other firms

FEMPEXT (F11+F12) Funds from other foreign firms

FAP (F5+F6+F7+F8) Funds from AAPPs

FUNI (F9+F15) University funds

FIPSFL (F10+F16) Funds from IPSFLsSource: Own elaboration from PITEC.


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TABLE B2: Variables.NAME DESCRIPTIN

TAMMED Average number of workers in the sphere of activity to which the firm belongs.CIFMED Average figure of businesses in the sphere of activity to which the firm belongsEXPMED Average export volume in the sphere of activity to which the firm belongs.

INVMED Average gross investment in material goods in sphere of activity it belongs to.INNOVE Carries out innovation activities.INNOVEM Innovation developed by firm or group.INNOVEC Innovation developer in cooperation with other firms or institutions.INNOVET Innovation developer by other firms or institutions.INNPROD Innovation products from (t-2) to tINNPROC Innovation process from (t-2) to tGINTID Figure for internal R&D expenditure.GEXTID Figure for external R&D expenditure.GMAQUI Figure for expenditure on acquisition of machinery, equipment and software.GTECNO Figure for expenditure on acquisition of external know-how.GPREP Figure for expenditure on product/distribution preparation..GFORM Figure for expenditure on training.GMARKET Figure for expenditure on introduction of innovations.EGTINN Innovation effortPIDTEJpw EJC staff in R&D per 100 workers.INFUN Basic or fundamental researchINAPL Applied researchDESTEC Technological development.FPRO Own fundsFEMP Other firms fundsFEMPEXT Funds from other foreign firms.FAP AAPP funds

FUNI University fundsFIPSFL IPSFL fundsFUE EU program fundsFEXT Other funds from abroadCOOPERA Cooperated from (t-2) a t with other firmsPAT Request for patentsPATNUM Number of requests for patentsPATOEPM OEPM PatentsPATEPO EPO PatentsPATUSPTO USPTO PatentsPATPCT PCT Patents

PATINT International Patents (outside OEPM)NESTR Non-technological innovation strategyNGEST Non-technological innovation managementNORG Non-technological innovation organizationNMARK Non-technological innovation : marketingNESTE Non-technological innovation: aesthetic or subjective change

Source: Own elaboration from PITEC.


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TABLE B3: Correspondences of PITEC sectoral classification and RTA-Dynamismsectoral typology.

PITEC SECTORRAMAI

DDESCRIPTION NACE_RE

V_1

SECTORALTYPOLOGY

02 Manufacture of food products and beverages DA_15 3 (lost opportunities)

03 Manufacture of tobacco products DA_16 2 (retreat)04 Manufacture of textiles DB_17

1 (dynamic speciali-sation)

05Manufacture of clothing / dressing and dyeingof fur DB_18


06Tanning and dressing of leather/ manufactureof luggage, handbags, saddlery, harness andfootwear

DC_19 4 (stationary specia-lisation)

07Manufacture of wood and of products of woodand cork, except furniture/ manufacture ofarticles of straw and plaiting material

DD_20 2 (retreat)

08Manufacture of pulp, paper and paper prod-ucts DE_21 3 (lost opportunities)

09 Publishing, printing and reproduction of re-corded media

DE_22 3 (lost opportunities)

10Manufacture of coke, refined petroleum prod-ucts and nuclear fuel DF_23 3 (lost opportunities)

11Manufacture of chemicals and chemical prod-ucts (except Manufacture of pharmaceuticals,medicinal chemicals and botanical products)

DG_24except24.4

3 (lost opportunities)

12Manufacture of pharmaceuticals, medicinalchemicals and botanical products

DG_24.4 3 (lost opportunities)

13 Manufacture of rubber and plastic products DH_25 3 (lost opportunities)14 Manufacture of ceramic tiles and flags DI_26.3 2 (retreat)

15

Manufacture of other non-metallic mineral

products (except Manufacture of ceramic tilesand flags)

DI_26

except26.3 2 (retreat)

16 Manufacture of basic iron and steel and offerrous alloys and ferrous products

DJ_27.1,27.2, 27.3,

27.51,27.52


17 Manufacture of basic precious and non-ferrous metals and non-ferrous products

DJ_27.4,27.53,27.54


18Manufacture of fabricated metal products (ex-cept machinery and equipment)

DJ_284 (stationary specia-

lisation)

19 Manufacture of machinery and equipmentn.e.c DK_291 (dynamic speciali-

sation)

20 Manufacture of office machinery and com-puters

DL_30 4 (stationary specia-lisation)

21 Manufacture of electrical machinery and appa-ratus n.e.c.

DL_31 4 (stationary specia-lisation)

22Manufacture of electronic valves and tubesand other electronic components DL_32.1

4 (stationary specia-lisation)

23 Manufacture of radio, television and commu-nication equipment and apparatus

DL_32except 321


24Manufacture of medical, precision and opticalinstruments, watches and clocks DL_33 2 (retreat)

25Manufacture of motor vehicles, trailers andsemi-trailers DM_34


26 Building and repairing of ships and boats DM_35.14 (stationary specia-

lisation)27 Manufacture of aircraft and spacecraft DM_35.3 4 (stationary specia-


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lisation)

28 Manufacture of other transport equipmentDM_35,except

35.1, 35.3


29 Manufacture of furniture DN_36.1 4 (stationary specia-lisation)

30 Manufacture of games and toys DN_36.5 4 (stationary specia-lisation)

31 Manufacture of games and toysDN_36,except

36.1,36.5


Source: Own elaboration from PITEC and OECD patent d


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