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The purpose of this paper is to examine the factors that influence innovative firms in the manufacturing and service sectors in Spain to cooperate with research institutions in their innovation activities, and to examine the differences between types of firm.

A literature review is used to identify variables likely to influence a decision to cooperate with research institutions. A logit regression model is then used to verify the importance of those variables. The empirical study was carried out using 2,000 Spanish community innovation survey data. The study sample was 3,964 innovative service and manufacturing firms.

It is found that spillovers, R&D intensity, costs, risks and alternative cooperation strategies influence both manufacturing and service firms in the same way in their decision to cooperate with research institutions in R&D. However, the variables relating to firm size, being part of a larger group of companies and type of innovation were shown to affect manufacturing and service companies differently.

There was no control over the possible bias introduced into the study by not including firms that were not innovative. The variables included in the study were constrained by the availability of information supplied by the Technological Innovation Survey. And finally, the comparative study of innovative behaviour in manufacturing and services is exploratory in nature.

The empirical results make it possible to identify a profile of the Spanish manufacturing and service firms that cooperate with research institutions.

This paper is original in exploring the differences between manufacturing and service firms in relation to the determinants of establishing institutional cooperation in R&D.

This paper sets out to examine the factors that influence Spanish manufacturing and service firms to cooperate with universities on R&D.

A LOGIT regression model is used to verify the importance of certain variables, selected and constructed according to the literature review, to the decision to cooperate with universities. An empirical study is carried out using data from the Spanish 2000 Community Innovation Survey (CIS). The sample of study is 3,964 innovative manufacturing and service firms.

Firm size, spillovers, R&D intensity and operating costs influence both manufacturing and service firms in the same way in their decision to cooperate with universities on R&D activities. However, the variables relating to strategic and legal protection of innovations, as well as belonging to a foreign group have been shown to affect manufacturing and service companies differently.

The analysis of the cooperation decision from the transaction cost economics approach is limited to operational costs and risks because of the type of data supplied by the CIS. A second limitation relates to the inability to use more recent data as, to date, the only CIS microdata published are from the year 2000.

The empirical results allow one to identify the characteristics of Spanish manufacturing and service firms that cooperate with universities.

The paper has explored the differences between manufacturing and service companies relating to the determinants of establishing R&D cooperation agreements with universities.

The purpose of this paper is to analyze the existence of complementarity between innovation activities (internal innovation, external innovation and cooperative R&D), as well as their impact on firms' innovation performance.

Drawing on the Third Community Innovation Survey (CIS‐3) for Spain, a multiple regression model is used to study the existence of complementarity between innovation activities and their impact on innovation performance. The sample for the study is 3,964 innovative firms.

First of all, the empirical results propose that the complementarity appears only between internal innovation and either external or cooperative innovation – but not with both together, which is in‐line with the “absorption capacity” notion. Second, the use of external and cooperation innovation in isolation does not yield positive effects on innovation performance. This finding contradicts the substitution argument and supports the absorptive capacity argument. Finally, innovation strategies do not seem to be dissimilar between industries.

The main limitation of the paper is the use of cross‐section data, which implies less robust results as an empirical test.

The empirical results allow the authors to recommend company managers and public administration officials to improve and support internal innovation. These activities should be combined with the high levels of external acquisitions that Spanish firms have in order to increase their innovation performance as the absorption capacity theory and this paper's empirical results suggest.

The first contribution of the paper is the inclusion of the third form of innovation: cooperation. The second contribution refers to the inclusion of the service sector in the authors' sample.

The paper aims to examine the differences between manufacturing and service sector firms regarding the determining factors for the decision to cooperate with research institutions to perform R&D activities. The second key contribution provided is the identification of institutional cooperation profiles, based on the determining variables of institutional cooperation.

On the one hand, drawing on the Community Innovation Survey for Spain, a Logit Regression Model is used to study the determining factors for institutional cooperation decision. On the other hand, in order to identify institutional cooperation profiles a confirmatory analysis was carried out applying the cluster methodology.

The empirical study confirms that the differences are fundamentally related to transaction cost theory and resource‐based view with respect to the costs. Specifically, these theories' proposal dealing with the variable cost is not empirically confirmed for firms in the service sector.

The principal limitation of this paper derives from the data available, which made it impossible to extend the research to cover a longer time period and affected the manner in which some variables were constructed.

The main implication of the paper can be understood in terms of managerial implications due to the importance of the institutional cooperation on R&D as an innovation management decision. Along this line, the results of the study indicate the existence of various options associated with the active posture on institutional cooperation.

The contribution of the paper is the identification of institutional cooperation profiles, based on the determining variables of cooperation with institutions on R&D activities as well as the identification of the differences between manufacturers and services related to them.

The study aims to assess and prioritise the enablers of manufacturing flexibility by evaluating the degree of environmental uncertainty and manufacturing flexibility in an uncertain environment.

The study proposes a methodological approach based on fuzzy quality function deployment (FQFD), fuzzy analytical hierarchical process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) to assess and prioritise enablers of manufacturing flexibility in an uncertain environment.

The study proposes a methodological approach that can facilitate firms to concentrate on preferred enablers and assist them in formulating a strategy to develop manufacturing flexibility. The empirical case study analysis of an Indian auto-air conditioning manufacturing firm was done to illustrate the effectiveness, flexibility and feasibility of the proposed approach.

The proposed approach is limited to manufacturing flexibility. This study does not consider inter-dependencies among environmental uncertainties.

The proposed methodological approach can assist practitioners in the identification and development of the preferred enablers to improve manufacturing flexibility. Thus, practitioners can invest strategically in the right resources to improve manufacturing flexibility.

The study proposes and validates a methodological approach that simultaneously addresses drivers and enablers of manufacturing flexibility; therefore, it aims to fill the gaps of earlier studies that have majorly studied flexibility concept in an isolated way.