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Radical innovation is still a debated concept in the field of innovation management. Very often, firms cannot pursue radical innovation due to the lack of access to markets, right expertise and financial resources. This issue is even more relevant nowadays, as companies have started to open their innovation activity to external partners. Despite the surging interest in the topic of radical innovation in a context of open innovation, scholars have shown how it can be difficult for companies to achieve the desired outcomes because of a failure to implement the right organizational forms of collaboration with external partners. The paper examines how companies implement successful open innovation cases that lead to successful radical innovations through dedicated organizational forms of collaboration.

The present article leverages three qualitative cases of open innovation projects where SAES group (or the “Company”), an Italian technology-based company, has exploited open innovation through dedicated organizational forms of collaboration to pursue radical innovation.

The findings show how the analyzed cases have required the Company to implement three different forms of collaborations: (1) equity alliance, (2) acquisition and (3) joint venture to pursue radical innovation. In addition, the results give some suggestions about the decision-making processes of the Company and show how a set of both rational and soft factors, such as technical, cultural, geographical, dimensional and human, have to be considered in implementing open innovation for radical innovation.

The results of this study reinforce and enrich existing research on the factors that decision-makers can evaluate for deciding which open innovation modes are the most suitable for leading to successful radical innovations.

Intellectual property protection mechanisms (IPPMs) include a variety of methods suitable for protecting valuable intangible assets of companies, and it is of great relevance to study how companies use these mechanisms to ensure the appropriability of innovation, in a context in which innovation is increasingly open. Indeed, there is a tension between the aim to share knowledge with external partners and the need to protect valuable know-how. The purpose of this paper is to investigate the relationship among the use of IPPMs, open innovation (OI), and the innovation performance of companies.

The study is based upon a survey conducted on 477 firms from Finland, Italy, Sweden, and UK in 2012.

The study shows that IPPMs have an indirect impact on innovation performance, mediated by the degree of openness. More precisely, IPPMs positively influence the level of openness, which, in turn, positively influences the innovation performance.

The empirical analysis contributes on two issues widely debated in the literature: the impact of IPPMs on innovation performance and the role of IPPMs as enablers or disablers of OI.

Focusing on some relevant constructs defined by the open innovation (OI) literature (i.e. determinants of openness; openness choices operationalized in terms of collaboration depth with scientific and business partners; organizational and social context; innovation performance in terms of novelty and efficiency), this paper investigates the relationships among such constructs. More specifically, the purpose of this paper is to empirically analyse two types of relationships: between some contextual factors and firms’ openness choices; and among openness choices, a set of organizational-managerial and social factors, and OI performance outcomes.

The authors carried out a theory testing survey, involving four European countries (Finland, Italy, Sweden and the UK). The authors applied descriptive statistics and a series of regressions.

The authors analysed the impact exerted by external and internal variables on the collaboration depth with scientific and business partners: technological trends are relevant to move firms towards external collaborations, with both types of partners; efficiency goals pursued in collaborations are related to the collaboration depth with both types of partners, while an aggressive innovation strategy is positively related only to scientific-partner depth. Besides, collaboration depths with both partners are positively related to the both sides of innovation performance (i.e. novelty and efficiency), but the organizational-managerial and social contexts emerge as relevant mediator variables. Organizational-managerial and external relational social capital exert a beneficial role on the both types of innovation performance, while internal relational social capital benefits only novelty.

The work shows important limitations such as the low level of the explanatory values in the regression models. Therefore, the results must be considered as preliminary explorative insights that may be useful to encourage further studies.

This work serves to raise managers’ awareness on the opportunity of developing organizational-managerial mechanisms, as well as on the importance of social capital to profit from collaborations.

Although during the last decade many researchers have claimed that we are in the era of OI, empirical works, which provide both a more comprehensive and detailed understanding of the phenomenon, are still few. Moreover, the specific action of the context (managerial, organizational and social) as possible mediator of the performance outcomes of openness is empirically under-studied. The authors’ work attempts to fulfil these gaps.

The study aims to test the success of university-industry (U-I) collaboration in terms of innovation process efficiency. Then, this study explores the moderating role of a set of organizational routines in the U-I relationship, which can help in overcoming the issues undermining the collaboration success.

The study is based on an international Open Innovation (OI) survey. The survey investigated the items to build the main variables of the conceptual framework, measured through seven-point Likert scales. Steps to ensure the reliability and validity of the variables were conducted. Then, hypotheses were tested with an ordinary least squares regression.

Results show that the higher the collaboration intensity (depth) with universities, the higher the innovation process efficiency. Furthermore, organizational routines aimed at improving firms' assimilation absorptive capacity further strengthen the positive effects of intensive collaboration on innovation process efficiency.

Findings indicate that R&D managers should strive to build deep collaborations with universities to enhance process efficiency and invest in the quality of these relationships. Managers should create and maintain an internal environment that further enhances the positive effects of intensive collaboration on innovation process efficiency.

The OI literature has not reached a shared view on the positive contribution of universities toward industrial firms' innovation performance. The study adopts a process-efficiency view, rarely used by other OI studies usually focused on output indicators; this study unpacks, respectively, the role of the intensity of collaboration and the organizational routines, thus disclosing the benefit of U-I collaboration on innovation efficiency.

The measure of companies' Innovation Performance is fundamental for enhancing the value and decision-making processes of firms. The purpose of this paper is to present a new measure of Innovation Performance, called Innovation Patent Index (IPI), which makes it possible to quantitatively summarize different aspects of firms' innovation.

In order to define the IPI, a secondary source, i.e. patent data, has been used. The five dimensions of IPI, i.e. efficiency, time, diversification, quality and internationalization have been defined both analyzing the literature and applying three different machine learning algorithms (regularized least squares, deep neural networks and decision trees), considering patent forward citations as a proxy of the innovation performance.

Results show that the IPI index is a very useful tool, simple to use and very promptly. In fact, it is possible to get important results without making time consuming analysis with primary sources. It is a tool that can be used by managers, businessmen, policymakers, organizations, patent experts and financiers to evaluate and plan future activities, to enhance the innovation capability, to find financing and to support and improve innovation.

Patent data are not widely used in all the sectors. Moreover, the pure number of forward citations is not the only forward looking indicator suggested by the literature.

The demand for a useable Innovation Performance tool, as well as the lack of tools able to grasp different aspects of the innovation, highlight the need to develop new instruments. In fact, although previous studies provide several measures of Innovation Performance, these are often difficult for managers to use, do not appreciate different aspects of the innovation and are not forward looking.

This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/14601060510578556. When citing the article, please cite: Vittorio Chiesa, Elena Gilardoni, Raffaella Manzini, (2005), “The valuation of technology in buy-cooperate-sell decisions”, European Journal of Innovation Management, Vol. 8 Iss: 1, pp. 5 - 30.

This paper faces the problem of the decision maker who has to identify the most appropriate organisational mode for the external acquisition of a certain technology. Its objective is twofold: to explain the rationale behind the choice of a definite mode of collaboration, i.e. to understand which aspects of the specific technological collaboration are considered by companies when selecting the organisational form; and to describe the process through which the choice is actually made, i.e. to understand which is the logical path which leads to selection of a definite organisational form. A framework is proposed and then applied to a case study.

The purpose of this study is to shed further light on determinants of the openness degree to give a more conclusive evidence to the research in the field. In particular, the influence exerted by the technological strategy is still debated, in that evidence on the relationship between the technological strategy and openness is conflicting.

The authors put forward a structural equation model which enriches the state-of-the-art literature by explicitly testing the interplay among technological strategy, openness (innovatively measured in terms of partner intensity, phase intensity and variety in terms of partners, phases and contents) and innovation performance. Our study relies on data from 415 firms based on a research survey developed in Finland, Italy and Sweden.

Findings show that openness, if measured in terms of partner intensity and phase intensity, fully mediates the relationship between technological strategy and innovation performance, by suggesting that the effectiveness of a firm’s technologically aggressive behavior is strongly related to the intensification of collaboration with the partners along the innovation funnel. Conversely, openness variety seems to play an opposite role and is influenced differently by partner and phase intensity. This result likely emphasizes how the cost-side of open behavior becomes harder to manage, and thus costly, when it involves too many different types of partners, phases and contents.

Firms that adopt a technologically aggressive strategy are recommended to deeply open their innovation process to foster innovation performance. However, because of the fact that a high level of openness variety could generate some drawbacks, managers should be very careful in the management of different phases, sources and content. Therefore, what clearly emerges is a call to find adequate strategies for effectively managing the collaboration process to avoid the waste of resources and initiatives.

Originality and the value of the paper reside in a more fine-grained definition of the openness concept, which takes into consideration other facets of openness compared to those usually analyzed in the literature, and a powerful statistical model, such as structural equation modeling, offering great advantages and flexibility in matching the theoretical model with the data.