Are there any differences between family and non-family firms in the open innovation era? Lessons from the practice of European manufacturing companies

Author(s):  
Valentina Lazzarotti ◽  
Federico Visconti ◽  
Luisa Pellegrini ◽  
Rafaela Gjergji
Author(s):  
Fernando G. Alberti ◽  
Stefania Ferrario ◽  
Fabio Papa ◽  
Emanuele Pizzurno

2018 ◽  
Vol 22 (02) ◽  
pp. 1850016 ◽  
Author(s):  
ANNA ARBUSSÃ ◽  
JOSEP LLACH

This paper contributes to the understanding of the context dependency of open innovation. It does so by empirically analysing the relationship between innovation activities, firm characteristics and the degree of innovation openness of manufacturing companies in three European countries with varying degrees of technological development. Logistic regression analysis is used to study CIS data from Germany, Portugal and Bulgaria. In line with the contingency approach to open innovation, the results suggest that the appropriate open innovation strategy is context dependent, with similar practices and firm characteristics obtaining opposite relationship signs in different countries. Hence, it is important to take country idiosyncrasies into account when designing policies to promote open innovation.


Author(s):  
Valentina Lazzarotti ◽  
Raffaella Manzini ◽  
Luisa Pellegrini

This chapter investigates the topic of how open innovation is actually implemented by companies, according to a conceptual approach in which open and closed models of innovation represent the two extremes of a continuum of different openness degrees; though, these are not the only two possible models. By means of a survey conducted among Italian manufacturing companies, this chapter sheds light on the many different ways in which companies open their innovation processes. Four main models emerge from the empirical study, which are investigated in depth in order to understand the relationship between a set of firm-specific factors (such as size, R&D intensity, sector of activity, company organization) and the specific open innovation model adopted by a company.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joan Freixanet ◽  
Joaquin Monreal ◽  
Gregorio Sánchez-Marín

Purpose The purpose of this study is to examine how family governance and technological capabilities influence the conversion of new knowledge obtained from exports into various innovation outputs, a phenomenon called “learning-by-exporting (LBE).” Design/methodology/approach To properly examine the causal links proposed in the study, first, the control for endogeneity. Second, a propensity-score matching longitudinal analysis is conducted, a particularly robust empirical method that enhances reliability in non-experimental data, over an average sample of 663 manufacturing companies for the period 2007 to 2014. Findings Family firms’ innovation strategies and abilities render them more likely to convert the new knowledge from exporting into product innovation and more efficient in this endeavor than non-family firms. This diverts family firms’ typically limited resources from process innovation, and they have a smaller LBE effect than non-family firms in terms of process innovation. Originality/value The study contributes to the internationalization literature by producing a more nuanced view of the learning-by-exporting effect which considers the type of innovation outcomes developed following export activity. It also helps to identify some of the firm-specific factors that shape the relationship between exports and innovation, by empirically examining for the first time the role of family governance in innovation capabilities and decisions.


2016 ◽  
Vol 20 (02) ◽  
pp. 1650025 ◽  
Author(s):  
PHILIPP NITZSCHE ◽  
BERND W. WIRTZ ◽  
VINCENT GÖTTEL

The concept or paradigm of open innovation has gained more and more attention over the last couple of years. Firms see open innovation nowadays as an important capability to build and maintain innovativeness, even in dynamic global markets. Nevertheless, there is still a lot of uncertainty regarding the question which factors determine successful innovation within the open innovation environment. In this regard, based on the dynamic capabilities view, we hypothesise that a firm’s openness, its absorptive capacity and its flexibility primarily determine innovation success in in-bound open innovation environments. To test these hypotheses, we analyse a large scale survey sample of 496 German manufacturing companies from different industries by applying structural equation modelling. As a main result, we find evidence for a positive association between the three mentioned constructs and innovation success.


2021 ◽  
Vol 7 (1) ◽  
pp. 101
Author(s):  
María Sonia Medina-Salgado ◽  
Fernando E. García-Muiña ◽  
Marco Cucchi ◽  
Davide Settembre-Blundo

Converging business, sustainability, and technology is a challenge that manufacturing firms face to create value and be competitive. Energy- and raw material-intensive manufacturing industries are particularly aware of environmental issues and circular economy practices due to the large amounts of resources they use. However, manufacturing companies must also be mindful of economic sustainability in order to make their business profitable. For this, appropriate economic evaluation tools are needed, one of which is life cycle costing (LCC). LCC, when applied to the manufacturing context, is often considered as a simple extension of the life cycle assessment (LCA). This is the main limitation of LCC, as it only contributes to determining the economic value of environmental damage. This research aims to overcome this limitation, analyzing the Italian ceramic tile manufacturing sector as a case study in order to conceptually develop, through the abductive methodology, a calculation framework that extends the potential of LCC by including circularity parameters. Subsequently, the conceptual framework is empirically validated using sectoral industrial costs by configuring two scenarios (with and without circularity practices) and building a benchmark for individual firms in this industry. Finally, the research includes some considerations on the positive implications and potential of life cycle costing in an open innovation context.


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