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The use of social network analysis in innovation studies: Mapping actors and technologies
Abstract
The utilization of social network analysis (SNA) in policy development and evaluation is still very limited. The aim of this paper is to identify research themes in innovation that may benefit from the application of SNA, and to examine implications for management and policy that are derived from this application in the academic literature. Three relevant research themes were identified: 1) networks of collaboration; 2) communication networks; and 3) networks of technology. The implications for management and policy and promising directions for further research are discussed.
... Thus, the research presented in this dissertation seeks to identify potential gaps in the scientific discourse and knowledge base surrounding the management of biological invasions in South Africa, using the Working for Water (WfW) programme as a case study. Furthermore, it aims to identify and visually present and locate actors, institutions, and bodies of research at moments in time and dynamically track their interactions temporally using science mapping (Bollen et al., 2005;Rafols et al., 2010;van der Valk and Gijsbers, 2010;Leydesdorff and Rafols, 2011). The goal of the research presented is the improved understanding of the dynamics and outcomes of research collaborations by integrating various evaluation approaches to assess research concerning the WfW programme, with the intent of identifying opportunities where productive collaborations could be further encouraged (Lane et al., 2015). ...
... Science mapping (Leydesdorff and Rafols, 2009;Rafols et al., 2010;Koier and Horlings, 2015) as an approach for bibliometric and scientometric analysis has become increasingly useful in improving our understanding of the dynamics of science, particularly as science has become progressively more inter-and transdisciplinary. Science mapping allows for the generation of symbolic representation of scientific fields and organisations, the elements of which are associated with topics or themes, by making use of social network analysis (SNA) methods (van der Valk and Gijsbers, 2010;Vogel, 2012). These maps allow us to explore the relationships among elements, for example, authors, publications, institutes, and research topics, as is the case with its use in Chapter 4. Science mapping and bibliometric analysis can contribute to a better understanding of the cognitive and organisational dynamics of science, and the facilitation of research-related choices; for example, funding allocation, organisation of research efforts and capacity building (Leydesdorff, 2007;Rafols et al., 2010). ...
... Accordingly, the aim of this paper is to identify and explore the roles of researchers in shaping collaboration networks and associated research outputs, by mapping the co-authorship network that developed within the WfW funding context. Core researchers were identified and their role and influence on network structure, evolution and knowledge production explored (Rafols et al., 2010;van der Valk and Gijsbers, 2010;Mingers and Leydesdorff, 2015). Social network analysis (SNA) enables the identification of key actors who could potentially improve research integration across disciplines. ...
The pervasiveness of threats posed by biological invasions presents significant challenges to human well-being, biodiversity conservation, and natural resource management, which has contributed to the growth of invasion science as a discipline. However, several studies have shown that the social-ecological complexity of invasions, the compartmentalisation of knowledge into disciplines and the lack of integrative research approaches, current invasion research has not informed management decision making effectively. Thus, to maximise the impact of research investments, there is a need to explore and evaluate how research informs management practices and processes linked to biological invasions.
Accordingly, this dissertation outlines the state of invasion management-related research in South Africa, using the internationally recognised Working for Water (WfW) programme as a case study. Drawing on insights from science studies and evaluation research, a mixed-method approach is used to assess the processes, conditions and outputs associated with research produced under the programme’s auspices. The research comprised two areas of inquiry 1) the exploration of textual information (journal articles, grey literature, and their content), and 2) the social dimensions of research and decision making linked to invasion science and management, with a specific focus on collaborative relationships amongst scientists and decision makers. It sought to determine the extent to which published research aligned with the programme’s needs, research and management strategies. The research also aimed to identify effective ways for organising and producing knowledge relevant to decision making; and to provide insights into how the social dimensions, the people and organisations, their interactions and impact, have shaped research and decision-making processes.
Findings suggest that there are significant gaps in the knowledge base particularly in relation to the social dimensions of biological invasions, which were poorly represented and aligned with the mandate and priorities set by the programme. This research showed significant deficiencies in knowledge management and the uptake of research funded by the programme, despite its potential relevance to decision making as evidenced by the recommendations presented in the research. Moreover, research produced under WfW’s auspices was authored by a handful of key researchers who fulfil a significant role in shaping research collaborations both across disciplines and institutions. The loss of these key individuals, including those involved in management-related decision making, would be detrimental to the stability of collaboration networks and research productivity. Finally, findings show that research productivity, collaborative relationships between scientists within and across research organisations, and between research and decision-making processes are positively influenced by collegiality and cooperation between actors, while increased competition and bureaucratisation in the workplace negatively influence research productivity.
To address the shortcomings concerning the invasion research and management identified in this dissertation, efforts towards improving the relationship between researchers and decision-makers and building more resilient collaboration networks need to be implemented. Firstly, institutions must engage in and fund more targeted, long-term transdisciplinary or integrative research that incorporates appropriate structures that foster collaboration, knowledge coproduction and knowledge sharing. Secondly, systems and strategies for monitoring and evaluating research, including the use of bibliometric indicators, social network analyses and qualitative assessments, should be developed to ensure that research relevant to managing biological invasions is not lost to the decision-making process. Such an undertaking would in turn require the development of an integrated research strategy and action plan that accounts for both the knowledge management and the social processes underpinning research and decision making.
... However, network analysis methods have only begun to find their way into business (Bergenholtz &Waldstrøm, 2011) andinnovation (van der Valk &Gijsbers, 2010) journals in the past decade. ...
... There are however, emerging trends toward the collection of longitudinal network data (e.g., Choi, 2017;Roesler & Broekel, 2017;Töpfer, Cantner, & Graf, 2017) and statistical modelling of network data (e.g., Arza & Carattoli, 2017;Broekel & Mueller, 2017;Roesler & Broekel, 2017). Overall, network analysis remains relatively underutilized and underdeveloped in innovation studies (Bergenholtz & Waldstrøm, 2011;Glückler & Doreian, 2016;van der Valk & Gijsbers, 2010). ...
... There are a few applications of network analysis in innovation studies that are worth highlighting. Sophisticated applications of network analysis have been used to expand our understanding of regional industry dynamics (Cantner & Graf, 2006;Giuliani, 2005Giuliani, , 2013Giuliani & Bell, 2005), particularly university-industry interaction (Balconi, Breschi, & Lissoni, 2004;Breschi & Catalini, 2010;Giuliani et al., 2010;Kauffeld-Monz & Fritsch, 2013;van der Valk & Gijsbers, 2010). In innovation studies, network analysis has been used to evaluate the relative position of network actors (e.g., Balconi et al., 2004;Gay & Dousset, 2005;Gilsing et al., 2008;Salman & Saives, 2005;Takeda, Kajikawa, Sakata, & Matsushima, 2008), to identify the factors that influence a network's structural composition (e.g., Cantner & Graf, 2006;R. ...
Because there is a lack of empirical research on public innovation in goods, the importance of public organizations for innovation may be underestimated. I show that public organizations engage in the development of important and novel ocean science instrumentalities-instruments and techniques-in Nova Scotia, Canada. I conducted structured first-person interviews to collect data on 27 public and private organizations and the 702 possible interactive learning relationships between them. I use quantitative network analysis methods to confirm the importance of public organizations within this innovation system and to also investigate the nature of interorganizational interactive learning. I find that public organizations have greater degree centrality than private companies and that the removal of public organizations would result in greater network fragmentation than the removal of private companies. I also find that both public and private organizations perform more complex roles than suggested by the limited prior research on scientific instrumentality innovation. The majority of learning interactions between public research organizations and private companies in this network are symbiotic-multiplex and bidirectional. The most important relationships in the network involve bidirectional learning partnerships. These findings contradict the oversimplified view of innovation as linear market transactions. My work reinforces calls for goods to be included in studies of public innovation, makes several methodological contributions that can be used to reveal dark innovation, and identifies the anchoring and quartermastering roles that appear present in this particular scientific instrumentalities innovation system.
... Besides, providing a theoretical framework, by which it is possible to investigate the effects between the structures of a network and the innovation output, as well as the impact of a particular position occupied by an actor on the network and the individual innovation performance. 12,15,16 The effects of network characteristics exert a direct impact on firms' innovative performance. 4,17 In highly dense and clustered networks, the resource flows are more easily accessible to the players. ...
... 16,34 In recent innovation network studies, the SNA techniques have been applied extensively. 15 The SNA is based on the relations of a set "nodes" linked by a set of "edges." 16,34 In this research, the nodes of networks represent patents' owners (organizations; it is worth mentioning that co-ownership with individuals (natural persons) is not considered in this research because this study aims to analyze the innovation networks at the interorganizational level), and the undirected connections between nodes will be established by a co-ownership of a patent. ...
This study has the purpose of conducting a dynamic comparative analysis of interorganizational innovation networks of Brazilian and Spanish biotechnology companies. It aims to explore the differences between the network characteristics and their actors’ positions and types as well as to analyze the temporal evolution of these networks. Although analyses of the evolution of networks are relevant in supporting comprehension of paths for innovation, they are incipient, particularly as cross-country studies. Considering that, this comparison between Brazil and Spain, which are at different levels of biotechnology development, may contribute to the advancement of this area. Social network analysis techniques are employed to draw and measure the network characteristics constructed under the information of patent applications by biotechnology companies located in Brazil and Spain in the period of 1990–2012. The results demonstrate an impressive growth of innovation networks from both countries but show an inferior position for Brazilian data in terms of constancy, volume of partnerships, partner diversity, and main actor types. Thus, this article reveals patterns of evolution over time for each country, which allows for the determination of the implications for public policy and managerial experts.
... Badania prowadzone wewnątrz dużych korporacji transnarodowych dowiodły, że pozycja podmiotu w sieci kontaktów biznesowych utworzonej wewnątrz firmy wpływa na możliwości dostępu do nowej wiedzy, która jest kluczowa w rozwoju nowych produktów lub innowacyjnych idei (por. Hansen, 2002;Shan i in., 1994;Tsai, 2010;van der Valk, Gijsbers, 2010). Założyć zatem należy, że analogiczna zależność zachodzi wewnątrz inicjatyw i organizacji klastrowych, które stwarzają możliwości dostępu do przydatnych informacji i wiedzy. ...
Powszechnie uważa się, że do zjawisk zachodzących w klastrach gospodarczych należą współpraca i przepływy wiedzy. Ich generowanie stało się w ostatnim czasie jednym z głównych celów zakładania i promowania sformalizowanych inicjatyw i organizacji klastrowych (które można określić wspólnym mianem porozumień klastrowych). Poprzez politykę klastrową UE (która stanowi jedno z międzynarodowych uwarunkowań kształtowania innowacyjności i rozwoju polskiego przemysłu) tematyka ta stała się aktualna również w Polsce. W publikacjach podejmujących to zagadnienie nie podejmowano dotychczas próby analizy mechanizmów powiązań pomiędzy przedsiębiorstwami tworzącymi porozumienia klastrowe. Celem tego artykułu jest przedstawienie przykładowego sposobu badania relacji współpracy i przepływów wiedzy pomiędzy przedsiębiorstwami w porozumieniach klastrowych. Badaniem empirycznym objęto przedsiębiorstwa Swarzędzkiego Klastra Producentów Mebli oraz Klastra Spożywczego Leszczyńskie Smaki, w których przeprowadzono wywiady z właścicielami lub osobami na kierowniczych stanowiskach. Do przeanalizowania odpowiedzi wykorzystano ostatnio coraz popularniejszą w badaniach metodę analizy sieciowej, zwaną też analizą sieci społecznych (ang. Social Network Analysis, SNA). Wyniki badania prowadzą do kilku wniosków. Po pierwsze, firmy chętniej współpracowały ze sobą niż dzieliły się wiedzą przydatną w działalności gospodarczej. Po drugie, jakkolwiek w badanych porozumieniach istniał związek pomiędzy intensywnością współpracy i dzieleniem się wiedzą w parach przedsiębiorstw, nie zachodził związek pomiędzy tymi wielkościami a bliskością geograficzną między firmami (gdyż wpływ na badane procesy miały również czynniki pozageograficzne). Wreszcie wykazano, że im bardziej centralna była pozycja przedsiębiorstw w sieciach współpracy i dzielenia się wiedzą (tzn. im bardziej aktywne były przedsiębiorstwa w nawiązywaniu relacji wewnątrz porozumień klastrowych), tym większa była ich innowacyjność. Na podstawie udowodnionych zależności sformułowane zostały rekomendacje dla koordynatorów porozumień klastrowych. Wskazano także propozycje dalszych badań empirycznych procesów zachodzących w klastrach, obejmujące również inne funkcjonalności analiz sieciowyc
... It can make effective classification and unique regression along with high dimensionality. Thus, using PCA is the best choice in this type of data where there are more dimensions (Van Der Valk & Gijsbers, 2010). ...
... In this sense, SNA is useful for understanding structural and positioning patterns, describing the influence on structures and development of innovation networks (Van der Valk & Gijsbers, 2010). This approach provided relevant contributions to innovation studies (DeBresson & Amesse, 1991) in the way the idea of an innovation network is related to the collective nature of the innovation process in contemporary societies (Castells, 2010). ...
Public funding for Small and Medium Enterprises (SMEs) innovation projects in collaboration with Scientific and Technological Institutions is still incipient in less developed Global South regions. Within the context mentioned above, our objective is to show a network analysis of Industry-University-Research Institute (IUR) interactions promoted by a government program, identifying its structure and dynamics and the influences played by these organisational actors. The results point out that the program presents effectiveness in establishing the IUR interaction network. Moreover, the network presents a scale-free structure, strong clustering and short distances between the actors. Universities lead as the most central actors, followed by research institutes. Despite the growth of the network with the significant entry of new SMEs, there is no evidence that this evolution contributes to improving its network metrics. The conclusions suggest that the network structure and dynamics may imply greater redundancy in the innovation process while allowing greater speed in the flow of knowledge and wider dissemination of knowledge among actors. The hubs (four central universities) in the network suggests an influence as generators and disseminators of knowledge and facilitators of interaction, but they can also limit the dynamics of the search for innovation in the network.
... ). Sosyal Ağ analizi ile ağ içerisinde önemli roller üstlenen elamanların tespit edilmesi mümkün olduğu gibi, elamalar arası haritaların görselleştirilmesi de mümkündür(Monaghan vd., 2017;Van Der Valk & Gijsbers, 2010). Bu bilgiler ışığında verilerin analizinde R programlama dili kullanılmıştır. ...
Mucilage (sea saliva) is a thick, sticky substance produced by almost all plants and some microorganisms. It is formed by the combination of many biological and chemical conditions. It plays various roles in plants such as storing water and food, germination of seeds and membrane thickening. Although there are many different reasons, it is possible to talk about three main factors in the formation of Marine Mucilage, which is on the agenda of our country with the situation in the Sea of Marmara recently: Sea temperatures exceeding the average temperatures, increase in the pollution rate in the seas, and the sea being stagnant. It is known that if these three situations occur, Marine Mucilage increases as some plankton species start to multiply rapidly. This study focuses on the general features of scientific research on sea saliva. In the study, the interdisciplinary nature of the research on sea snail is revealed with a data-based analysis. While it was observed that Zoology, Plant Sciences, Oceanography, Marine & Freshwater Biology, Limnology, Fisheries, Environmental Sciences and Ecology carried out joint studies in these studies with a high collaboration pattern, Italy, France, China, Croatia and the USA were among the countries that attracted attention in terms of the number of publications. While the frequency of studies on the northern Adriatic Sea as a geographical area draws attention, Univ Bologna, Univ Gottingen, Univ Melbourne, Univ Genoa and Istanbul University are among the universities that attract attention in terms of institutional publications.
... Furthermore, real-time data analyses and monitoring of machine logs can enable managers to make swifter decisions for quality management (Serrat, 2009). Also, big data analytics can allow for the real-time monitoring of network demand, in addition to the forecasting of bandwidth in response to customer behavior (Vander-Valk, & Gijsbers, 2010). Furthermore, big data can be used for better understanding changes in the location, frequency, and intensity of weather and climate and this can benefit citizens and businesses that rely upon weather, such as farmers, as well as tourism and transportation companies (Herodotou et al., 2011). ...
... W wyjaśnieniu charakterystyk rozwoju technologii wymienionych w tab. 1 zauważyć można ponownie przewijającą się w literaturze istotę faktu współwystępowania technologii. Jak wskazują T. van der Valk i G. Gijsbergs analiza struktur technologicznych ma duże znaczenie w zarządzaniu rozwojem technologii, jak i w obszarze polityki, z uwagi na podejmowane decyzje dotyczące alokacji środków finansowych [12]. Podając za M. W. Pretotiusem i G. de Wet różne technologie mogą współwystępować w czterech różnych relacjach. ...
Dynamika rozwoju technologii jest coraz większa, rośnie również ich poziom skomplikowania. Powoduje to, że ich właściwa identyfikacja oraz selekcja są jednym z warunków bytu rynkowego dla przedsiębiorstw a także rozwoju ekonomicznego dla regionów czy państw. Rzetelna selekcja technologii wymaga obecnie zgromadzenia i przetworzenia coraz obszerniejszego zbioru wiedzy. Często zachodzi również konieczność oceny aspektów jakościowych, których zmierzenie ilościowe jest utrudnione bądź czasem wręcz niemożliwe. Zasadne zatem wydają się prace nad poszukiwaniem i tworzeniem metod i narzędzi badawczych, których wykorzystanie podnosi zasadność podejmowanych decyzji w zakresie wyboru technologii. W artykule omówiono wieloaspektowość decyzji dotyczących wyboru danego rozwiązania technologicznego wskazując na te elementy, których analiza jest istotna podczas przeprowadzania procesu selekcji technologii. Ponadto zwrócono szczególną uwagę na aspekt relacji technologii – ich identyfikację oraz prezentację. Wskazano na sieć jako odpowiednio czytelną formę odzwierciedlającą wspomniane relacje. Zasadniczą część artykułu stanowi przedstawienie wybranych przykładów z zakresu prezentacji graficznej relacji pomiędzy technologiami.
... There are many methods being used to analyze datasets [6].This paper provides a list of some techniques applicable. This result is by no means confined, researchers continue to develop new techniques to enhance existing ones, particularly in need to analyze new combinations of data. ...
Big Data has been developing from few years and created hype. But it is quite normal that 3V's (velocity, volume, and variety) are beyond a more thorough discussion of data approach.'
... Behara et al (2014) shows how co-authorship in research papers is a form of social networking in research collaborations and can be used to understand relational linkages among individuals, organizations, and nations. Research on using co-authorship in publications to understand a social network has been extended to technology and to innovations such as dataset provision (Moody 2004, Van Der Valk andGijsbers 2010). Social networks are an inherent part of organizations, which affect collaborations and decision making, particularly in long-term research which engages with both technology and social decision making, such as in monitoring, reporting and verification of carbon pollution . ...
The NASA Carbon Monitoring System (CMS) and Arctic-Boreal Vulnerability Experiment (ABoVE) have been planned and funded by the NASA Earth Science Division. Both programs have a focus on engaging stakeholders and developing science useful for decision making. The resulting programs have funded significant scientific output and advancements in understanding how satellite remote sensing observations can be used to not just study how the Earth is changing, but also create data products that are of high utility to stakeholders and decisions makers. In this paper we focus on documenting thematic diversity of research themes and methods used, and how the CMS and ABoVE themes are related. We do this through developing a Correlated Topic Model on the 521 papers produced by the two programs and plotting the results in a network diagram. Through analysis of the themes in these papers, we document the relationships between researchers and institutions participating in CMS and ABoVE programs and the benefits from sustained engagement with stakeholders due to recurring funding. We note an absence of policy engagement in the papers and conclude that funded researchers need to be more ambitious and explicit in drawing the connection between their research and carbon policy implications in order to meet the stated goals of the CMS and ABoVE programs.
... The use of social network analysis (SNA) to examine the influence of R&D collaborative networks on knowledge creation and innovation processes is more recent. This methodology is particularly suitable for mapping the mutual 9780367232511_pi-218.indd 68 27-Jan-20 22:10:03 influence of the structure and social connections in innovation studies (Van Der Valk and Gijsbers, 2010;Kolleck, 2013). The use of the SNA approach to investigate FP-related networks has usually focused on the analysis of network characteristics, their structural properties and evolution (Ortega and Aguillo, 2010;Protogerou, Caloghirou and Siokas, 2010, for FP4, FP5 and FP6 in the ICT sector;Heller-Schuh et al., 2011), and on the identification of the position of actors within the network and the strength of their relationships (Breschi and Cusmano, 2004;Wanzenböck, Scherngell and Brenner, 2014). ...
This chapter examines the links between R&D collaborative networks in the ICT field, the regional technological context and the related innovative outputs, for the case of the European Union. First, we consider the links established in these networks to check for the existence of bridging regions, i.e., those which connect isolated groups of regions. Second, we explore the relationships between the regional level of network connectedness and its technological and economic context. Finally, we study the impact of network connectedness on regional technological innovation. We find that the FP7 program has generated complex and unequal collaborative networks, confirming the systematic regional disparities in innovation within the EU. Indeed, the best connected regions show more advanced economic, innovative and digital development.
... Later as ecosystems become established, more stable and with a more consistent lexicon, other approaches become increasingly viable, including structured searches and social network analysis (Van Der Valk and Gijsbers, 2010). ...
The issue of boundary determination in ecosystems remains problematic which is exaggerated in a dynamic, emerging innovation context, with actors joining and leaving. As part of wider research, on how firms innovate in emerging ecosystems, the boundaries of several early innovation ecosystems were explored.
Using evolutionary approaches, with extensive interviews and mapping, the wider ecosystem was initially researched. Then, five in-depth firm-focussed case studies were undertaken, and specific innovation ecosystem boundaries were mapped as they emerged and evolved.
The findings point to ‘identity’, a common early approach, being limited as the ecosystem evolves. The influence of competence and relationships play an increasing role. It is suggested that as the innovation ecosystem develops through its lifecycle, different approaches aligned to Santos and Eisenhardt’s (2005) four foci can be employed, starting with identity, then competence, then power and finally issues of efficiency.
... Paci and Batteta (2003) investigated localized transfer of knowledge and examined technological networks represented by patent citation flows in different sectors. Studies on collaboration networks seek to explain the performance of individual actors by using the attributes of the network where they take part, by describing the structures of the collaboration network or even justifying the network's development and dynamics (Van Der Valk and Gijsbers, 2010). Bazzo (2010) analyzed technological cooperation that resulted in patents in Brazil and found that subsidiaries of foreign firms, universities and research institutes exhibit a low sharing of patent ownership; that is, they do little cooperation, which is an indication of the institutional fragility of local innovation. ...
Purpose
The establishment of partnerships between companies, government and universities aims to enhance innovation and the technological development of institutions. The biotechnology sector has grown in recent years mainly driven by its cooperative business model. Compared to other countries, this sector is slowly advancing in Brazil, with delays in science, technology and innovation, especially in the private sector. This paper aims to examine, through social network analysis, the collaborative networks between institutions that filed patents in biotechnology – medicinal preparations from plants – whose inventions had Brazil as the priority country.
Design/methodology/approach
The study of technological cooperation using patent documents is a reliable approach as they serve as good indicators of the interactions between organizations that focus on innovation and development of new product. Social network analysis of cooperation networks helps to understand the connections between patent assignees, and how they establish relationships.
Findings
Results show that public universities are the institutions that most deposit patents, as well as those that co-operate the most, especially Universidade of Campinas. The study also reveals the critical role of Research Support Agencies in stimulating research and technological development, which result in new technologies.
Originality/value
The study applied the social network analysis to provide an overview of the interactions among Brazilian institutions with the purpose of helping in decision-making and inciting public policies to leverage the biotechnology sector.
... Global actor structures may be visualized and analyzed with social network analysis while the impact of informal institutions may be isolated based on novel forms of comparative discourse analysis (see e.g. Fuenfschilling and Truffer, 2014;Ter Wal and Boschma, 2009;Van der Valk and Gijsbers, 2010). Future research in this field should also actively include emerging and developing economies and find new ways of assessing the agency of powerful incumbents. ...
This paper addresses the question why socio-technical transitions follow similar trajectories in various parts of the world, even though the relevant material preconditions and institutional contexts vary greatly between different regions and countries. It takes a critical stance on the implicit methodological nationalism in transition studies' socio-technical regime concept and proposes an alternative 'global' regime perspective that embraces the increasingly multi-scalar actor networks and institutional rationalities, which influence transition dynamics beyond national or regional borders. By drawing on globalization theories from sociology and human geography, we show that socio-technical systems often develop institutional rationalities that are diffused via international networks and thus become influential in various places around the world. In so doing, we shed light on the multi-scalar interrelatedness of institutional structures and actors in socio-technical systems and elaborate on the implications for the conceptualization of transition dynamics. The paper illustrates this with the case study of an unsuccessful transition in the Chinese wastewater sector. Recent studies indicate that key decisions on wastewater infrastructure expansion were not only influenced by path-dependencies stemming from China's national context, but equally (or even more critically) by the dominant rationality of the water sector's global socio-technical regime. We conclude by discussing the contours of a new research agenda around the notion of global socio-technical regimes.
... The use of network analysis was also applied to study the relationship between common academic inventors in patenting processes, at different technological areas [22]. The studies on collaboration networks seek to explain the performance of individual actors using the characteristics of the network in which they are inserted, to describe the structures of the collaboration network, or even to explain the development and dynamics of the network [23]. ...
Scientific research at universities has a crucial role in leveraging a country’s innovative potential. Sectors that require greater investments in technology for the development of their research, such as biotechnology, need to be aware of the frontier state-of-the-art technology and the knowledge incrusted within it. Although the information available in scientific articles is well explored in academic environment, the patent literature, where much of the technological information is present, is still poorly accessed. This chapter is intended to instruct students and researchers at universities to look at patent document analysis as a source of scientific and technological information and explore its applications. Within this chapter, we use the technological area regarding immunoglobulins inventions (monoclonal and polyclonal antibodies) as example to provide directions on how to develop a patent landscape to get an overview of the inventions in a certain field; how to map a collaborative network of inventors/assignees to help the pursuit and identification of future partnerships; and lastly we describe the steps of how to set up a network of patent citations with the aim of forecasting emerging technologies. We strongly believe that incorporate data from patents in planning phase of research projects at academia, as well as to establish partnerships and join R&D efforts to invest on promising technologies, is of great relevance to leverage the growth of the biotechnology sector.
... In this context, many contributions stressed the importance that the study of networks and social network analysis (Scott, 2012) can play in innovation studies and collaborations for innovation (Capone, 2016;Sciarelli and Tani, 2014;Van der Valk and Gijsbers, 2010). For instance, Yun et al., (2016) apply social network analysis to investigate open innovation practices. ...
Objectives. The aim of this paper is to investigate how firms develop the transition from closed to open innovation and how this process occurs throughout R&D project networks.
Methodology. The work develops a longitudinal case study analysis of 8 Tuscan companies that have developed R&D projects in inter-organizational networks in the period. It investigates the opening of the innovation process departing from the firms’ ego-networks developed over a period of several years.
Findings. Results show that small and medium firms are not lagging behind large firms in the adoption of open innovation practices and that the industry where firms operate is not a discriminating factor for opening up firms innovation process. Besides the technological complexity of the production process that companies adopt results one of the main determinant in the implementation of open innovation practices.
Research limits. The study deals with temporary project networks, that therefore represents only the tip of the iceberg of the relational innovation processes of the analyzed firms.
Practical implications. The work underlines the importance of the opening of the innovation process outside the boundaries of the firms throughout the privileged tools of temporary R&D networks financed by public policies. Managers and entrepreneurs should carefully dedicate resources and competences in this process, according to the increasing relevance of the open innovation paradigm.
Originality of the study. Three network configurations of opening of the innovation process throughout R&D networks are described in order to contribute to our knowledge on the transition from closed to open innovation in small and large firms.
... Within innovation network studies ( Bergenholtz and Waldstrøm, 2011), there is an increasing number of contributions using social network analysis (Van der Valk and Gijsbers, 2010;Sciarelli and Tani, 2014;Zanni and Pucci, 2012) and, in particular, new statistical methods to investigate network structure, thanks to big data and more powerful computers. More recent developments on quantitative analysis (Kastelle and Steen, 2014) consist in the longitudinal analysis of network evolution with simulation investigation for empirical network analysis (SIENA) software (Snijders et al., 2010) and the statistical analysis of large and complex networks with ERGM (Lusher et al. 2013;Contractor et al., 2006). ...
Objectives of the paper. The aim of this study is to measure the impact of various dimensions of proximity to form innovation networks.
Methodology. We use a novel statistical methodology for modelling networks based on a well-studied class of models called exponential-family random graph models.
Findings. Results underline the importance of various forms of proximity in the formation of innovation networks and the potential of the novel methodology to study large and complex networks in innovation studies and R&D management.
Research limits. The research is mainly quantitative and contributes to the debate measuring the role and importance of various forms of proximity in innovation networks. Further analysis of how firms choose their partners is needed. Moreover, the analysis should be expanded to other contexts and industries in order to be able to generalise results.
Practical implications. The work points out managerial implications in innovation studies and R&D management in order to guide firms when choosing their partners and forming a network.
Originality of the paper. The study contributes to the debate on innovation network literature and tests a novel methodology to analyse large and complex inter-organisational networks.
... Universities and research institutions also play their roles in cluster knowledge flows: their knowledge may spillover spontaneously, as well as also offering payable knowledge transfers in the form of consultations, training courses or contract research (Runiewicz-Wardyn, 2013). The extent to which firms can exploit valuable knowledge in clusters depends on their ability to REGIONAL STUDIES, REGIONAL SCIENCE build a relational network position inside a cluster, and their skills to find the best knowledge source inside such networks (van der Valk & Gijsbers, 2010). ...
Knowledge flows are widely believed to be a phenomenon of clusters, and inducing them is one of the chief objectives in establishing and promoting cluster initiatives (CI). However, not many studies discuss how these flows and their effects may differ depending on the mode of CI creation and on the role of public authorities in this process. The main aim of this article is to compare mechanisms of knowledge flows in bottom-up and top-down cluster initiatives. The results of an empirical research involving two case studies in western Poland, obtained through the use of Social Network Analysis (SNA), allowed stating that in bottom-up cluster initiatives firms which were innovation leaders played a prime role in disseminating technological and business knowledge, while in the top-down initiatives the most important were representatives of universities and research centres as well as formal coordinators of cooperation. Policy implications stemming from these results were identified.
... The sources of innovation are more often found rather between firms, universities, research laboratories, suppliers and customers than inside them (Van der Valk and Gijsbers, 2010;Chesbrough, 2003;Von Hippel, 2005). Firms engage in cooperation not only to share the costs and risks of research 1 This study was conducted within the 2014 project 'Tecniche avanzate per la conoscenza materica e la conservazione del patrimonio storico-artistico' (Regione Toscana, POR-CreO/FESR, 2007-2013 coordinated by IFAC-CNR. ...
Purpose of the paper: The aim of this research is to investigate the relationship dynamics of innovation networks in the business of High Technology applied to Cultural Goods (HTCG) in Tuscany, in order to analyze the relevance of the actors’ position and their centrality in the networks. The study contributes to the wide research strand on the importance of network competences and relational capabilities for innovation.
Methodology: Social Network Analysis is applied to 42 R&D projects developed by local actors in Tuscany along fifteen years, funded at regional, national and international levels.
Findings: The results show that the business of HTCG is a complex business, where inter-organizational relationships are developed among Triple Helix actors in public-private partnerships and industry-university relationships.
Research limits: The research adopts a quantitative approach to the study of relationship dynamics in innovation networks and uses the Social Network Analysis. In this context, the analysis of temporary R&D projects is restricted to the results concerning the dynamics of temporary networks and exclusively for formal collaborations. In addition, the research would benefit from some in-depth interviews in order to investigate how and why actors develop relationships and with whom.
Practical implications: It is therefore necessary to underline the importance for managers of relational competences for innovation and the relevance of resources and competences also outside the firm’s boundaries, in particular in a complex business like HTCG.
Originality of the paper: The work is a preliminary, but original study on HTCG and it depicts several figures on network dynamics in this newly emerging business.
... The use of SNA techniques in the management field was introduced and developed by Burt (2001Burt ( , 2007. Their use is related primarily to the study of innovation networks (Cantner & Graf, 2006;Martinez-Torres, 2014;van der Valk & Gijsbers, 2010) and strategic alliances (Gulati, 1998;Gulati et al., 2000). More recently Burgess and Shaw (2010) employed this technique to analyse editorial board membership of management and business journals, while Acedo et al. (2006) used SNA to study the relevance of institutions in relation to their scientific output. ...
The objective of this article is to determine the dynamics of the evolution of management as an academic research discipline in Latin America and the Caribbean (LAC) in the past 25 years. The methodology used in the research comprises a combination of co-word analysis with Social Networks Analysis organized in a six-step procedure. First, the data retrieval was carried out; second, a list of key words related to the management discipline was created; third, a key word co-occurrence matrix and its normalization using Salton’s Cosine was done; fourth, each key word was assigned to the research line it represents, taking into consideration the 25 divisions that make up the Academy of Management Society; fifth, the internal cohesion was calculated for each research line using the density of the words network that makes it up and each line’s centrality degree; and, sixth, a strategic diagram was created representing the stage of development of each research line. The results show how the research lines Strategic Management Process and Innovation & Technology Management have formed the backbone of the development of management as an academic discipline in LAC. We also present how research lines that are necessary for the economic and social development of the region such as Entrepreneurship, Cooperative Strategy and Public Sector Management appear as peripheral underdeveloped lines. Finally, we address possible strategies for future development of the management discipline in LAC.
Objetivo
analizar las redes de transferencia del conocimiento sobre el COVID-19, en los conjuntos acuícolas productores de camarón de la región pacifico norte de México.
Método
. Se realizó un estudio de corte transversal, descriptivo y correlacional, el cual permitió adquirir información de una encuesta de 102 acuacultores de la región del pacifico norte, del estado de Sinaloa. Para el análisis de resultados se probó el Análisis de Redes Sociales (ARS).
Resultados
. Se reportan 4 fuentes de información -Sector Salud, Fuentes Privadas, Sector Gubernamental y Medios de Comunicación- a las cuales los productores acuden para adquirir información sobre el Covid-19 y sus efectos en la actividad acuícola.
In the information era, huge amounts of data have become available to decision-makers. Big data can be referred to as datasets that are not only big but also high in variety and velocity, which makes them tough to handle using traditional tools and techniques. Due to the fast growth of such data, solutions need to be provided to handle and extract value and knowledge from these data. Moreover, decision-makers need to be able to advance the valuable insights from such varied and rapidly changing data, ranging from daily transactions to customer interactions and social network data. Such value can be delivered using big data analytics, which is the application of progressive analytics techniques on big data. This paper's objective is to analyze some of the different analytics methods and tools which can be applied to big data, like the yarn and rack-aware model as well as the opportunities provided by the application of big data analytics in several decision domains.
The concept of big data is spread all over all the sectors of industries. As it is concerning about the most important concept, the data, it need to be managed properly and effectively. By managing the data effectively, it will improve the decision making quality for better business. With the geometrical growth of data, appropriate solutions need to be studied and designed appropriately to handle and extract valuables and knowledge from targeted datasets. The strategic management level needs easy access of valuable insights from such varying and rapidly changing data, which ranges from daily transactions on customer interactions and social network. These values can be extracted using different data mining methods like association rule mining and cluster analysis. This value is provided with big data analytics, which is represented as an application of advanced analytics techniques of big data. The end point use of such finding is supply chain management, risk management fields of different domains.KeywordsBig data analysisSupply chain managementRisk managementQuality managementFraud detectionExperimental analysis
Re-scaling energy systems and governance to the local level is increasingly necessary to transition to a low-carbon society. City region devolution in England enables city regions to develop their own approaches to low-carbon transitions that reflect the context in which they are situated. The approaches associated with these transitions support the localization of the energy system, the involvement of a diverse range of actors and institutions and the establishment of new supporting infrastructures. This paper considers the interactions between, and influence of, different actors, infrastructures and institutions and how these impact the nature of approaches developed by applying a relational perspective. Relational perspectives are increasingly prevalent in research on low-carbon transitions, although they have not been used to consider how different components of the transition influence the approaches developed—which is the focus of this paper. By understanding the influence of the different components, it supports the establishment of appropriate mechanisms to facilitate low-carbon transitions at the localized scale. This paper analyses the approaches to low-carbon transitions developed by three city regions with devolved powers in England. The approach developed by each of the city regions orientates around a different scale of focus—from the whole city region to strategic hubs to individualized, siloed activity. These different scales of focus reflect the influence held by the actors, institutions and infrastructures located within each city region. The context of the city region itself also influences the actors, institutions, and infrastructures present. By adopting a relational perspective, it unpacks the complex interrelations, the multiple points of interaction and influence, and the multi-scalar nature of low-carbon transitions at the city region level. Although the approaches to low-carbon transitions developed by the different city regions suggest a re-scaling of transition processes, the associated actors, infrastructures and institutions associated with these processes are not isolated from broader contexts and particularities of place. There are multi-scalar interactions and influences which impact the nature of approaches developed, demonstrating the value of relational and heterogeneous perspectives when developing localized approaches to low-carbon transitions.
Policy design, aiming to foster innovation in low-density rural areas, shows a grade of complexity and risk that is closely associated with their historical path, often marked by deep impacts in its socioeconomic structure. Despite that, we can observe the emergence of territories that decided to undertake efforts searching for new paths heading their economic and social development, implementing public policies that seek to boost collaboration structures based on very peculiar ways of innovation.
The present study uses social network analysis technics to build a structural representation of the regional innovation system in Idanha-a-Nova, Portugal. We seek to understand how the changes in the network topology and the way in which the interaction dynamics happen interfere in the results of the innovation strategies. The metrics conceptualized by the methodology proved to be indicators capable of showing trends that favor or constrain the evolutionary path of innovation networks.
We also argue that the indicators found are able to help the policy design, as well as guide the implementation of regional action plans, contributing to the improvement of the innovation system and the achievement of its goals.
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A formulação de políticas de fomento à inovação em territórios rurais de baixa densidade apresenta fatores de complexidade e risco que estão intimamente associados à realidades resultantes de um passado histórico marcado por eventos de fragilização de sua estrutura socioeconômica. A despeito deste fato, pode-se observar o surgimento de territórios que decidiram empreender esforços na procura de novos caminhos para seu desenvolvimento econômico
e social, implementando políticas públicas que procuram dinamizar estruturas de colaboração a partir de leituras muito peculiares do conceito de inovação.
O presente estudo, fundamentado por uma análise de rede social quantitativa, apresenta uma caracterização estrutural de um sistema regional de inovação a evoluir no concelho de Idanha-a-Nova em Portugal, onde procuramos perceber de que maneira as mudanças em sua topologia e em suas dinâmicas de interação podem interferir nos resultados esperados pelas estratégias de inovação.
Os resultados obtidos, a partir da interpretação das métricas conceituadas pela metodologia, nos permitiram perceber indicadores capazes de revelar tendências que favorecem ou constrangem o caminho evolutivo de redes de inovação presentes neste tipo de realidade territorial. Observamos também que os indicadores encontrados são capazes de auxiliar decisores políticos na formulação de políticas públicas, bem como orientar a implementação de planos de ação regionais, vindo a contribuir para o
aprimoramento do sistema de inovação e o alcance de seus objetivos.
The present study aims to verify and analyze the leading academic publications related to innovation topics and digital social networks. The research methodology is the co-citation analysis followed by the development of a co-citation map that includes approaches, types of networks and levels of aggregation by these themes. Therefore, this study can promote a better understanding of how the authors studying innovation and digital social networks relate. As a result, 866 articles were identified between 2014 and 2018. Of these, 26,392 were references cited by the analyzed papers in the total of 480 journals. Three main clusters were identified with the references of the articles analyzed.
Este documento está orientado a la construcción de un análisis bibliométrico y una revisión sistemática de la literatura sobre la aplicación del análisis de redes sociales como método de estudio de los sistemas de innovación. La revisión se llevó a cabo en una ventana de observación de 2001 a 2017. Se realizó la búsqueda en los índices bibliográficos Scopus y Web of Science Core Collection. Se obtuvo un conjunto de 1091 registros, con los cuales se realizó un análisis bibliométrico de la actividad, la relación y el
impacto. Por otro lado, se llevó a cabo la selección de 29 artículos recurriendo a criterios de inclusión específicos, permitiendo construir categorías asociadas a patentes, redes de coautoría, información de proyectos conjuntos, combinaciones de fuentes de datos, entre otros.
Palabras clave: Análisis de Redes Sociales; Sistemas de Innovación; Indicadores bibliométricos; Análisis de Contenido; Revisión sistemática de la literatura
This book offers broad evidence on how new information and communication technologies (ICT) impact social development and contribute to social welfare. Its aim is to show how new technological solutions may contribute to society's welfare by encouraging new 'socially responsible' initiatives and practices as the broad adoption of new technologies becomes an integral component of organizations, and of the overall economy. Society and Technology: Opportunities and Challenges is designed to provide deep insight into theoretical and empirical evidence on ICT as socially responsible technologies. More specifically, it puts special focus on examining the following: • how channels of ICT impact on social progress, environmental sustainability and instability • the role of ICT in creating social networks, with positive and negative consequences of networking • how ICT encourages education, skills development, institutional development, etc. • the ethical aspects of technological progress, and • technology management for social corporate responsibility. The book is written primarily for scholars and academic professionals from a wide variety of disciplines that are addressing issues of economic development and growth, social development, and the role of technology progress in broadly defined socioeconomic progress. It is also an invaluable source of knowledge for graduate and postgraduate students, particularly within economic and social development, information and technology, worldwide studies, social policy or comparative economics.
El presente estudio tiene por objetivo “reconstruir” y comparar las redes de flujo de conocimiento e información tecnológica (RFCIT) en la industria acuícola, específicamente en el cultivo de camarón, de dos de las principales regiones productoras de camarón de cultivo en México: el municipio de Ahome, ubicado al norte del Estado de Sinaloa, y la región costera centro-sur del estado de Sonora. La investigación se basa en el enfoque del análisis de redes sociales y la información fue obtenida mediante la aplicación de una encuesta a una muestra de 91 empresas dedicadas al cultivo de camarón en las regiones mencionadas. Las conclusiones del estudio señalan que las características y la configuración de las RFCIT de la acuicultura de Sinaloa le han permitido a esta entidad tener una ventaja de competitividad frente a Sonora, para paliar los efectos de la crisis de los últimos años.
A aplicação de ARS para investigar redes de parcerias para o desenvolvimento de inovações apresenta grande interesse teórico e empírico. Nesse sentido as patentes são reconhecidas como importante indicador de inovação dispondo de informações valiosas, que estão publicamente disponíveis no mundo todo permitindo sua aplicação para investigar essas redes de colaboração para inovação. Entretanto, as informações sobre patentes disponibilizadas pelas autoridades de patentes dos diversos países, geralmente apresentam diferentes tipos de formatos, o que pode comprometer a aplicação de ARS e a interpretação da análise. Para resolver esse problema, esse estudo se propõe a selecionar, desenvolver e apresentar técnicas para organizar e preparar um grande volume de dados sobre patentes, viabilizando a construção e análise dessas redes. Essa pesquisa contribui para difusão de estudos e aplicações de ARS em redes de inovação interorganizacionais, apoiando pesquisadores e profissionais.
This is the era of big data .it refers to large amount of data set whose size is growing at a vast speed and it is collection of dataset that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets. To handle such large amount of data using traditional software tools available. This paper reviews the technologies and challenges related to big data analytics. First introduce general definition of big data second essential technologies related big data analytics like hadoop, map reduce framework etc. and third challenges arising from big data analytics.
This is the era of big data .it refers to large amount of data set whose size is growing at a vast speed and it is collection of dataset that are not only big, but also high in variety and velocity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets. To handle such large amount of data using traditional software tools available. This paper reviews the technologies and challenges related to big data analytics. First introduce general definition of big data second essential technologies related big data analytics like hadoop, map reduce framework etc. and third challenges arising from big data analytics.
Big data analytics is a trending practice that many companies are adopting. The analytics process includes the deployment and use of big data analytics tools, that improves operational efficiency, drive new revenue and gain competitive advantages over business rivals. The descriptive analytics focuses on describing something that has already happened, as well as suggesting its root causes. Descriptive analytics, which remains the lion's share of the analysis performed, typically hinges on basic querying, reporting and visualization of historical data. Alternatively, more complex predictive and prescriptive modeling can help companies anticipate business opportunities and make decisions that affect profits in areas such as targeting marketing campaigns, reducing customer churn and avoiding equipment failures. With predictive analytics, historical data sets are mined for patterns indicative of future situations and behaviors, while prescriptive analytics subsumes the results of predictive analytics to suggest actions that will best take advantage of the predicted scenarios.
Today, peripheral rural areas are indispensable to achieve global and national conservation goals or a post-carbon transition while simultaneously struggling for quality of life and economic development. Biosphere Reserves have the ambition to overcome this dichotomy of environmental protection and regional development by fostering and upscaling (social) innovations within their World Network of Biosphere Reserves (WNBR). This study explores how these innovations resp. innovative firms and projects are stimulated and embedded in practice. A standardized survey and social network analysis (SNA) with these firms in two Biosphere Reserves reveals that innovations in the peripheral regions are multi-level arrangements where the Biosphere Reserves (1) provide platforms for new ideas and needs, (2) foster the development, funding and diffusion of products or services and (3) act as gatekeepers between actors of different areas and spatial scales. We therefore conclude that the role of the Biosphere Reserve in the two regions goes far beyond the protection of nature, providing the ‘institutional thickness’ for successful regional development. Additionally, they are social innovations themselves, which support the co-production of knowledge and learning. However, if UNESCO's Man and Biosphere program truly wants to have an impact on sustainability transitions, the integration of local actors and their projects into their WNBR has to be their top priority for the future.
A inovação figura como aspecto relevante para organizações uma vez que contribui para o melhor desempenho e para os atendimentos às demandas constantes e crescentes da sociedade moderna. O inventário Myers-Briggs Type Indicator (MBTI®) apresenta-se como ferramenta com potencial para a identificação de indivíduos inovadores em organizações. Este estudo tem por objetivo identificar os tipos psicológicos de profissionais com potencial para inovação que trabalham na área da saúde e o posicionamento dos mesmos dentro de suas redes sociais organizacionais. Os dados foram coletados por meio de um questionário estruturado aplicado a 37 profissionais em uma unidade de saúde no município do Rio de Janeiro, e transferidos para dois softwares - Ucinet e MBTI versão Inspiira 1. Os resultados revelaram que alguns dos indivíduos identificados como centrais para o processo de inovação, apresentaram a dimensão Intuição (N), que é apontada pela literatura como indicadora de indivíduos que têm uma maior propensão a gerar ideias inovadoras. O inventário MBTI e sua verificação por meio da análise de redes sociais (ARS) mostraram-se promissores para identificação de indivíduos inovadores e para proporcionar o seu melhor aproveitamento dentro das organizações.
A landscape analysis of the recombinant factor VIII patent sector using network analysis to map the cooperation network among assignees shows emerging technologies that focus on improved methods for rFVIII production and bioactivity performance.
https://rdcu.be/2Aoe
Moving towards more integrative approaches within the invasion sciences has been recognized as a means of improving linkages between science, policy, and practice. Yet despite the recognition that biological invasions pose complex social-ecological challenges, the invasion literature poorly covers social-ecological or distinctly integrative research. Various initiatives and investments have been made towards building research capacity and conducting more integrative research aimed at improving the management of biological invasions. Using a combination of social network and thematic analysis approaches, and the South African Working for Water (WfW) program as a case study for the management of invasive species, we identify and explore the roles of core authors in shaping collaboration networks and research outputs, based on bibliographic records. We found that research produced under the auspices of WfW is authored by a handful of core authors, conducting primarily ecologically-focused research, with social research significantly underrepresented. Core authors identified in this study play an essential role in mediating relationships between researchers, in addition to potentially controlling access to those seeking to form collaborations, maintaining network cohesion and connectivity across institutional and disciplinary boundaries. Research projects should be designed to span disciplines and institutions if they are to adequately address complex challenges.
This paper contributes to the empirical identification of the structural positions in network through an exploration of the interactions between R&D activities (patents) and technological areas of patents (technological classifications). Affiliation network analysis was conducted to study the affiliation between patents and technological classifications. We identified some key patents and explored the differentiated positions of the core and periphery. The results of network analysis was further verified by statistical analysis. We found that the impacts of the centralities in position were significant. Technological implications and foresights are discussed in the conclusion.
The bioeconomy has become a central concept in many strategies for future economic development, emphasising an increasing need for collaboration across industries and sectors for innovation. This paper unpacks aspects of collaboration in the bioeconomy by looking at the development of innovation networks for biorefinery technologies from 2004 to 2014 based on innovation project data from Swedish public funding agencies using a stochastic actor-oriented model for network analysis. The analysis shows that although the network grew significantly during the time period, indicating an increasing interest in biorefinery technology innovation, inter-sectoral collaboration is not favoured over intra-sectoral collaboration. As is known from previous work on social networks trust-building is a key driver for collaboration, as actors tend to form collaborations with previous partners or indirectly connected partners, creating clustered networks.
The literature on “open innovation” so far focuses almost exclusively on strategic issues. In this largely conceptual paper we propose behavioral foundations for knowledge exchange and knowledge sharing to address this gap in the literature. Innovation and knowledge development that result from knowledge transfer, is an uncertain and cumulative process that typically involves a number of parties. Knowledge transfer between people and firms has been fruitfully studied from a structural or network perspective. The social network literature however, faces an “action problem”. Focusing on structural elements such as an agent’s position in a network and the types of relations entertained cannot explain why actors actually do share knowledge. The exchange of knowledge is elusive and is a discretionary act for the people involved, certainly in the case of open innovation (OI). It is argued here that social network analysis is to be complemented by the concept of gift exchange, drawing on social exchange literature. Gift exchange – following Mauss’ dictum to “give, receive and reciprocate”– establishes obligations between people especially under circumstances of ambiguity, which explain why and how knowledge exchange relations are established, persist, and may also end. Relationships in a social network and the social capital that inheres in these cannot be drawn on at will to exchange knowledge. These obligations established by gift exchange between individuals who share a connection explain why agents exchange knowledge with each other even in the absence of markets or hierarchy.
Biofuel policies are motivated by a plethora of political concerns related to energy security, environmental damages, and support of the agricultural sector. In response to this, much scientific work has chiefly focussed on analysing the biofuel domain and on giving policy advice and recommendations. Although innovation has been acknowledged as one of the key factors in sustainable and cost-effective biofuel development, there is an urgent need to investigate technological trajectories in the biofuel sector by starting from consistent data and appropriate methodological tools. To do so, this work proposes a procedure to select patent data unequivocally related to the investigated sector, it uses co-occurrence of technological terms to compute patent similarity and highlights content and interdependencies of biofuels technological trajectories by revealing hidden topics from unstructured patent text fields. The analysis suggests that there is a breaking trend towards modern generation biofuels and that innovators seem to focus increasingly on the ability of alternative energy sources to adapt to the transport/industrial sector.
A Análise de Redes Sociais (ARS) é uma técnica que visa mensurar e mapear conexões entre atores em um coletivo, utilizando-se de conhecimentos da Sociologia, Matemática e Estatística. Com o objetivo de analisar a intensidade da adoção de medidas estruturais, relacionais e posicionais da Análise de Redes Sociais, em estudos na área de Administração, foi realizada uma pesquisa bibliográfica em artigos no período de 1987 a 2011. Entre os resultados, identificaram-se o crescimento no número de publicações e a concentração da utilização das medidas de centralidade e densidade. Apresenta-se uma discussão sobre a utilização de outras medidas de ARS na área da Administração. Palavras-chave: Análise de Redes Sociais. Redes sociais. Relacionamentos interorganizacionais.
The purpose of this paper is to study ties between knowledge based cooperation and innovative development of companies within the framework of external innovation networks, at home and abroad. The paper also presents the network model of the innovative company knowledge management (KM) in a innovation process and describes synergy effects of knowledge based cooperation (i.e. interorganizational KM and knowledge based relationships and learning) of the innovative company within innovation networks. The aim of a questionnaire, which was collected from 64 innovative companies, was to determine the effectiveness of interorganizational knowledge based coopetition (cooperation and/or competition) of companies within the innovation networks and influence of them on innovative development of companies. The key research questions the survey addressed were: How many and which types of outside collaborators did innovative firms cooperate within innovation networks, at home and/or abroad? What internal and external (domestic and foreign) sources of knowledge did the innovative companies use for innovations? How did innovative companies assess effectiveness of their knowledge based cooperation with respectively domestic or foreign collaborators, of various types, within innovation networks? Finally, the paper estimates the results of using chi-square test for independence research of knowledge based cooperation efficiency (which is connected with development) of innovative companies on their adequately home or foreign collaborators within innovation networks.
Using data from co-authorships at the international level in all fields of science in 1990 and 2000, and within six case studies at the sub-field level in 2000, different explanations for the growth of international collaboration in science and technology are explored. We find that few of the explanations within the literature can be supported by a detailed review of the data. To enable further exploration of the role of recognition and rewards as ordering mechanisms within the system, we apply new tools emerging from network science. These enquiries shows that the growth of international co-authorships can be attributed to self-organizing phenomenon based on preferential attachment (searching for recognition and reward) within networks of co-authors. The co-authorship links can be considered as a complex network with sub-dynamics involving features of both competition and cooperation. The analysis suggests that the growth of international collaboration is more likely to emerge from dynamics at the sub-field level operating in all fields of science, albeit under institutional constraints. Implications for the management of global scientific collaborations are explored.
OVERVIEW: R&D support groups make essential contributions to the process of innovation and can help speed time-to-market, yet the role they play is often over-looked or undervalued relative to that of their internal customer groups. When status differences interfere with collaboration and the free flow of knowledge between support groups and their customers, process efficiency and effectiveness can suffer. It is therefore important for organizations to understand the relationships between support groups and their customers, and to determine whether or not they are working as equals in carrying out their shared work process. Social network analysis can be used to describe the relationships between support groups and their customers in terms of the amount and direction of interaction that takes place between them, and can highlight those areas where interactions are out of balance and more collaborative partnerships need to be formed.
Innovatie is meer dan kennis en goede ideeen. Innovatie is ook een kwestie van organisatie en vaardigheden. Een nieuw, open innovatiebeleid met aandacht voor sociale innovatie is nodig. In het rapport Innovatie vernieuwd geeft de WRR aanbevelingen voor verbetering van het innovatieproces in Nederland op micro- en mesoniveau: in bedrijven, tussen bedrijven en in netwerken. Het innovatiebeleid dat de WRR voorstelt, biedt openingen: over grensen heen, voor samenwerking, voor verrassingen en voor uitdagers. Innovatie over grenzen heen van landen, sectoren, technologieen en regio's. Samenwerking en uitwisseling bevorderen in en tussen bedrijven en instellingen. Vormen van organisatie en toezicht die innovatie stimuleren, obstakels wegnemen en ruimte geven aan uitdagers.
This study proposes a quantitative method for investigating the structure of international technology diffusion. By using network analysis, this study defines the structural configuration of each country within the international diffusion network by measuring its degree, closeness, and betweenness centralities. In addition, this study distinguishes between embodied technology diffusion, measured by multilateral trade, and disembodied technology diffusion, measured by patent citations, in individual countries. This study empirically tests a sample data set of international technology diffusion taken from 48 countries. The empirical results show that the structural configuration of countries exhibits similar patterns in both embodied and disembodied diffusion networks. Significant global stratification patterns exist in the capability of national international technology exportation and brokerage advantages. Moreover, this study distinguishes four blocks of countries that play different roles in international technology diffusion: the leading countries provide a source of technological knowledge; an intermediate group diffuses the knowledge acquired from the source; a third group is in the process of initiating the export of technological knowledge; and a final group of countries absorbs technological knowledge without reciprocal exportation. Finally, this study identifies two types of catch-up strategies that newly industrialized or developing countries can use to move up the international technology stratification.
The notion of the knowledge-based economy highlights the strategic importance of inter-industrial knowledge flows. Among others, the crucial role of information and communications technology (ICT) industry is emphasized. The pattern whereby technological knowledge is created, accumulated and disseminated through the interactive learning among industries can be portrayed as a network. Based on the network theory, this empirical study analyses, from the dynamic perspective, inter-industrial technological knowledge structure of Korean industries during the reference period of early 1980s to mid-1990s. Overall, the density of the network increased over time, implying that the knowledge network has expanded and intensified. The role of the ICT industry in the global network has also increased but needs to be further strengthened, especially informatization of non-ICT industries by the outflow of ICT industrial knowledge in the future. The findings in turn render some important policy implications that should be addressed in developing technology policy.
This study presents a quantitative method for investigating the diffusion of e-commerce adoption using social network analysis methodologies. The contagion effects on innovation diffusion are examined by two different social network models: the cohesion model, which is based on diffusion by direct communication, and the structural equivalence model, which is based on diffusion by similarity of network position. This study then empirically examines a sample of e-commerce diffusion taken from the Taiwan's industrial structure in 2001. The analytical results show that e-commerce diffusion among firms in Taiwan exhibits both contagion effects, but that the mimetic behavior is predicted better by network position than by interactions with others.
Given the recent accumulation of research on inter-organizational relations and networks and the current fragmentation of the field, it is time to take stock and explore the achievements of, and future challenges for, this field of study. On the basis of a network analysis of the 158 articles on inter-organizational relations and networks that were published in four leading journals from 1980 to 1996, this paper empirically explores the linkages among, and configurations of, core theories and concepts underlying earlier empirical research on inter-organizational relations and networks. We identify core, as well as peripheral, areas of research interest in the field and point out areas of overlap and consolidation. Moreover, our empirical analysis shows that the field segments into four substantive research perspectives, namely social network, power and control, institutional, and institutional economics and strategy clusters. In sum, we suggest an innovative, empirically grounded approach towards a literature review that aims at a synopsis of a field of study and highlights possibly fruitful avenues for future research.
With the advent of the knowledge-based economy, the inter-industrial flow of technological knowledge is reckoned as the principal determinant of national competitiveness. The mode of knowledge flows, however, is intractably complex. Taking it as a network, this paper aims at providing an inductive taxonomy of industries based on the knowledge flow structure and thus identifying the user-supplier relationship among industries in terms of knowledge diffusion. Some proxy indexes are developed first to measure the knowledge flows, then the interactive mechanism among industries is investigated by the network analysis and eventually a taxonomy of industries is presented according to the characteristics of respective industries. The taxonomic approach highlights the importance of inter-industrial knowledge management system that facilitates knowledge flows across industries based on the idiosyncratic features of respective industries.
This paper presents a quantitative method for comparing the structure and performance of intersectoral innovation diffusion in the Taiwanese and Chinese innovation systems. The network of intersectoral innovation diffusion is constructed and proxied by the product-embodied R&D flow matrices calculated by the use of data on input–output tables and sectoral R&D expenditure. The two networks are structurally compared with the help of methodologies derived from the network analysis, which are conducted at the national, cluster and individual levels to thoroughly examine the multi-embededness of the sectors situated in a technological diffusion network.This study shows that the two systems have similar distributions of key sectors, including the cores, i.e. machinery and equipment, electronic parts and components, and the sources, i.e. chemicals and basic metals, of innovation flows. However, significant differences also exist. For example, the Taiwanese system is characterized by higher degrees of systemic connection and hierarchy, while the Chinese system has looser density and less centralization. Additionally, the Taiwanese system appears capable of more efficient innovation diffusion among vertically related industries than the Chinese system due to the former containing more effective clusters. Finally, China’s technological concentration is centered on heavy industry, while Taiwan is focused on high-tech industry.
The purpose of this work is to develop a systematic understanding of embeddedness and organization networks. Drawing on ethnographic fieldwork conducted at 23 entrepreneurial firms, I identify the components of embedded relationships and explicate the devices by which embeddedness shapes organizational and economic outcomes. The findings suggest that embeddedness is a logic of exchange that promotes economies of time, integrative agreements, Pareto improvements in allocative efficiency, and complex adaptation. These positive effects rise up to a threshold, however, after which embeddedness can derail economic performance by making firms vulnerable to exogenous shocks or insulating them from information that exists beyond their network. A framework is proposed that explains how these properties vary with the quality of social ties, the structure of the organization network, and an organization's structural position in the network.
We argue in this paper that when the knowledge base of an industry is both complex and expanding and the sources of expertise are widely dispersed, the locus of innovation will be found in networks of learning, rather than in individual firms. The large-scale reliance on interorganizational collaborations in the biotechnology industry reflects a fundamental and pervasive concern with access to knowledge. We develop a network approach to organizational learning and derive firm-level, longitudinal hypotheses that link research and development alliances, experience with managing interfirm relationships, network position, rates of growth, and portfolios of collaborative activities. We test these hypotheses on a sample of dedicated biotechnology firms in the years 1990-1994. Results from pooled, within-firm, time series analyses support a learning view and have broad implications for future theoretical and empirical research on organizational networks and strategic alliances.•.
This article reviews the support tools available for young biotechnology firms in Israel and points out the need to expand these tools to the area of networks. Such a service would be of specific importance to biotechnology entrepreneurs who have a relatively low starting point in terms of relevant social capital, limited business, and managerial experience. If public support schemes are to support innovation they must broaden their range of services and not focus solely on R&D.
This paper presents an exploratory exercise to characterize the nature of interorganizational networks and the strategic positioning of companies in five industrial sectors: pharmaceuticals, plastics, computers, electronics and instruments. Two types of networks in each sector are analysed: knowledge networks based on patent citations and technology alliance networks based on strategic partnerships. Three sets of results with significant policy and strategy implications underline both the need for better understanding of the social/competitive context within which companies operate and the utility of social network analysis in achieving this goal. First, apparent differences in the networking behaviour in ‘simple technology’ sectors (pharmaceuticals) vis-a-vis networking behaviour in ‘complex technology’ sectors (computers, electronics and instruments) are indicated. Second, a difference between knowledge and alliance networks across all examined sectors is pointed out in terms of their effectiveness as channels of knowledge communication. Third, apparent differences in the competitive positioning of European firms and firms from the United States and Japan in the examined sectoral knowledge networks may reveal significant variance in inter-continental business strategy
We develop and test, using McFadden's discrete choice statistical modeling applied to network dynamics, four alternative logics of attachment - - accumulative advantage, homophily, follow-the-trend, and multiconnectivity - - to account for the development of interorganizational collaboration in the field of biotechnology. The commercial field of the life sciences is characterized by wide dispersion in the sources of basic knowledge and rapid development of the underlying science, fostering collaboration among a broad range of institutionally diverse actors. We map the network dynamics of the field over the period 1988-99. Using multiple novel methods, including analysis of network degree distributions, network visualizations, and multi-probability models to estimate dyadic attachments, we demonstrate how a preference for diversity shapes network evolution. Collaborative strategies pursued by early commercial entrants are supplanted by strategies influenced more by universities, research institutes, venture capital, and small firms. As organizations increase both the number of activities around which they collaborate and the diversity of organizations with which they are linked, cohesive subnetworks form that are characterized by multiple, independent pathways. These structural components, in turn, condition the choices and opportunities available to members of a field, thereby reinforcing an attachment logic based on connection to partners that are diversely and differently linked. The dual analysis of network and institutional evolution offers a compelling explanation for the decentralized structure of this science-based field.
Over the past decade, organisations producing quality goods have been investigating innovative processes to cope with the new quality criteria demanded by consumers, commodity chains and policy-makers. In this paper, we propose to use network sociology to link innovation and learning theories and thus highlight the diverse social practices contributing to changes and underlying learning processes in such contexts. Farmers groups, evolving towards multifunctional agriculture, constitute exemplary cases to study these dynamics. We will be presenting the results of a longitudinal ethnographic case study carried out in a small cooperative implementing environment-friendly viticulture in the Languedoc (South of France). Beyond the diverse strategic positions developed in response to the innovative project, two kinds of networks are highlighted: the first type refers to daily dialogue and service exchange, the second one assumes the contours of knowledge-based strategies required by the management of diverse areas of change. All of these underline the importance of thematic experts that go further than ‘traditional’ leadership. We will conclude by suggesting the management of ‘practices networks’ both integrating these different networks and linking diverse strategic positions to respond to the challenges of the economy of quality.
The intuitive background for measures of structural centrality in social networks is reviewed and existing measures are evaluated in terms of their consistency with intuitions and their interpretability.
To match the global demand and supply of innovation, businesses increasingly internationalise their innovation activities while opening their innovation process by collaborating with external partners (e.g., suppliers, customers, universities). This book examines what drives these global innovation networks across different industries, how they are related to companies' overall strategies, whether they are accessible for small and medium-sized enterprises (SMEs) and what the consequences are.
The increasing syntheses and interactions between various technologies increase the usefulness of cross impact analysis (CIA) as a method for forecasting and analyzing them. Conventional CIA depends on an expert's qualitative judgment or intuition and thus it is difficult to evaluate quantitatively the impact of one technology on another. In this study, we employ patent analysis in CIA to examine such impacts between technologies based on multiple patent classifications. Patent information is used for facilitating quantitative and systematic approach in CIA. The distinctive feature and main contribution of the proposed approach is the overcoming of the limitations of conventional CIA, by employing conditional probabilities based on the patent information. The classification of patents, particularly the multiple classifications, is used to evaluate the relationships between technologies. As an illustration, a patent-based CIA with information and communication technologies (ICTs) was conducted. Firstly, the patent-based cross impact among ICTs was calculated. Secondly, the technology pairs were classified based on the cross impact score between ICTs. Thirdly, a cross impact network was constructed to identify the complex relation among ICTs. Finally, the changes in cross impact scores between technologies over time were analyzed. The results of this research are expected to help practitioners to forecast future trends and to develop better R&D strategies.
Among the many technology forecasting indicators, patents and patent citations are useful and important indicators. The more frequently a certain patent is cited by subsequent patents, the more the related technology can be said to be diffused, implying that the technology is more widely applied and thus more valuable. This paper analyzes the business methods technology which retrieves patents from the USPTO database. There are two purposes of this paper: 1. establish the indicators for finding basic patents and measure the relationship of these basic patents; 2. classify the basic patents and explain the groups of technology diffusion. Finally, this study identifies the two mainstreams in business method technology: one is focused on marketing technology, and the other one stresses on data security. Both are important for Internet data processes or e-commerce activities.
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This paper investigates the role of intellectual property rights (IPRs) in shaping the GSM (global system for mobile communications) industry. This industry is an example of a high-tech industry in which standards play a large role. In the process of designing the GSM standard, a lot of attention has been given to IPRs, mainly to avoid a situation in which a single IPR holder could hamper or even totally block the development of the standard. Nevertheless, the ultimate GSM standard contains a large amount of so-called ‘essential IPRs’, i.e. IPRs without which the implementation of GSM products is impossible.The GSM case provides an interesting example of how (essential) IPRs ownership and alliance networks influence each other, and how both of them affect market structure and market shares. The play with the essential GSM IPRs, and the strategy of Motorola in particular, is found to have dramatically changed the standardization processes in the telecommunications industry. Where IPR was considered a non-issue in this sector for many decades, it is now among the main issues to be resolved for any new standard, as has recently been shown with the standardization of third-generation mobile networks. Our findings with respect to alliances reveal that timing of the emergence of strong network positions is in line with the findings on essential IPRs. We found for three of the four dominant network players that their position in the network is based on ownership of essential IPRs. The relationship between market power (inclusion in the top-5 equipment suppliers) and the two variables of our main interest (essential IPRs and network centrality) is found to be a positive one with some notable exceptions.
In the early 21st century, Korean government issued a policy recommendation that Korean public research institutes should select strategic research fields to concentrate their resources, based on a careful review of the various strategic R&D factors. The government has emphasized the “selection and concentration” strategy for the efficient use of R&D resources and as a way to increase the national competitiveness of Korea. This paper suggests a method, a “Technology Cluster Analysis,” for selecting the strategic research areas, mainly targeting large, multi-disciplinary and long-term programs. The technology cluster analysis groups near technologies together based on key indicators. In this study, the method is applied to national R&D programs in the nano-technology field. Fifty-six nano-technologies are analyzed and grouped into three main clusters based on the survey data from 180 experts. Technological distances and correlations among individual technologies are depicted by hierarchical dendrogram. Three main clusters in nano-technology field are found and termed nano-materials, nano-devices, and nano-bio. These three clusters are expected to be the core technology clusters in nano-technology field in South Korea.
Science and technology for renewable and sustainable energy are indispensable for our future society and economics. To meet the goal of sustainable energy development, there is a growing body of research efforts world wide. The planner of energy research has to grasp the broader coverage of scientific and technological research, and make decisions on effective investment in promising and emerging technologies especially under circumstances of limited resources. In this paper, we track emerging research domains in energy research by using citation network analysis. Our analysis confirms that the fuel cell and solar cell are rapidly growing domains in energy research. We further investigate the detailed structure of these two domains by clustering publications in these domains. Each citation cluster has characteristic research topics, and there is a variety of growth trends among the clusters. By using citation network analysis, we can track emerging research domains among a pile of publications efficiently and effectively.
Biomass and bio-fuels have gained a growing interest as sustainable and renewable energy. In this paper, we perform a citation network analysis of scientific publications to know the current structure of biomass and bio-fuel research. By clustering and visualizing the network, we revealed their taxonomic structure. Emerging technologies are detected by analyzing the average publication year of clusters. According to the results, bio-diesel and hydrogen production are the most rapidly developing domains among biomass bio-fuel researches. We also analyzed the position of each cluster in the global structure of research. By using citation counts within and out of the cluster, we categorized each cluster into the following four categories: (I) topic specific; (II) domain specific; (III) global link; and (IV) specific & global. For research domains of category (III) or (IV), it is difficult that single technology overcomes the current limitation of bio-energy productions. Research on lignocellulose feedstock is a typical case where knowledge from other scientific disciplines is necessary.
In a regional innovation system, a dense inter-organizational network within the region is recognized as a key factor in enhancing knowledge diffusion, regional learning, and effective resource transfers. Therefore, understanding the network structure and physical proximity of organizations is essential. In this paper, we investigated the industrial structure of Yamagata prefecture in Japan as a case study. Because Yamagata is a representative industrial region, the analysis can also provide an insight into other industrial regions. Initially, we investigated the geographical dispersion of firms and found them to be agglomerated along Route 13 and the Tohoku Shinkansen railroad, indicating that infrastructures for transportation still have a decisive role in terms of site location. Subsequently, we analyzed the modular structure of the inter-firm network. The results showed that hub firms construct a different type of network and play different roles within the inter-firm network, reflecting their strategic choice. The results also showed that there is a tendency for firms to transact with those in close proximity, and that firm location is also affected by the location of the hub firm in the module in addition to the infrastructures.
We apply social network analysis methods to describe the evolution of the innovator network of Jena, Germany in the period from 1995 to 2001. We find this evolution to be directed towards an increasing focus on core competencies of the network. Further we analyse the network resulting from R&D cooperations and explain – by means of network regression techniques – that the job mobility of scientists and the technological overlap between the actors, rather than past cooperations, can best predict the resulting structure.
The formation of a network is determined by the opposition of two forces. The first is the reproduction of network structure as a general social resource for network members. The second is the alteration of network structure by entrepreneurs for their own benefit. The idea of reproduction is a conventional one in organizational sociology but has taken on increased importance due to the work of Bourdieu and Coleman. In contrast, Burt stresses the entrepreneurship of individual agents in exploiting structural holes that lie between constrained positions. Though complementary, the theories of social capital and structural holes have fundamentally different implications for network formation.
This paper investigates these theories by examining empirically the formation of the interorganizational network among biotechnology firms. We propose that network structure determines the frequency with which a new biotechnology firm (or startup) establishes new relationships. Network structure indicates both where social capital is distributed in the industry and where opportunities for entrepreneurial action are located. The reproduction of network structure depends on how startups value social capital compared to these opportunities. The critical test is, consequently, whether new relationships reproduce or alter the inherited network structure. We find strong support for the power of social capital in reproducing the network over time.
R&D support groups make essential contributions to the process of innovation and can help speed time-to-market, yet the role they play is often overlooked or undervalued relative to that of their internal customer groups. When status differences interfere with collaboration and the free flow of knowledge between support groups and their customers, process efficiency and effectiveness can suffer. It is therefore important for organizations to understand the relationships between support groups and their customers, and to determine whether or not they are working as equals in carrying out their shared work process. Social network analysis can be used to describe the relationships between support groups and their customers in terms of the amount and direction of interaction that takes place between them, and can highlight those areas where interactions are out of balance and more collaborative partnerships need to be formed.
This study considers the role of social networktheory in unveiling the hidden value in Internet networks in the Swedishbiotechnology industry. To value informal internet-based networks, socialnetwork analysis is used to identify key nodes in the network on the Internetfor small- to medium-sized enterprises (SMEs), using data from the Swedishbiotech industry. Data concerning the online networks of Swedish biotech SMEs (defined asenterprises with fewer than 100 employees) were gathered through: (1)identifying three different biotech SME company websites as the starting point;(2) recording all the hyperlinks referring to external websites; (3) visitingthose links back to the originating links; and (4) constructing a sociogram ofthis network. Prominence and structural hole analyses were used to determinethe most important networks and actors in the system. The findings show that networks can be constructed from the links betweenthe websites of actor firms. The findings also suggest the possibility of usingsocial network theory to identify the most prominent actors and to outline theentrepreneurial opportunities in whichthese identified actors can engage.(CBS)
The formation of organisational tacit knowledge has been studied in the most part using only qualitative explanations such as case studies including those on the workings of communities of practice. From this perspective, tacit knowledge is submersed and consequently it is difficult to quantify. In our community of communities of practice case study we use quantitative social network analysis techniques to explore the process of tacit knowledge exchange among expert knowledge workers forensic scientists. Conceptually, we search for more structured relational mechanisms that shape tacit knowledge flows occurring between participant actors in communities of practice, in their day-to-day knowledge intensive environments.
In the context of the emergence of new modular organizational forms, especially in high-tech sectors such as the biotechnology sector, this article proposes that while a firm observes benefits from direct alliances, it also benefits from indirect linkages. First, a theoretical framework revolving around indirect ties is built on the basis of social network and innovation management literature. It ends with the proposition of two research hypotheses linking the indirect network position of a firm to its innovation capacities. To test those hypotheses, data on strategic partnerships and collaborations were collected through 40 interviews with biotech firms from the nutrition sector in the biotech clusters of Quebec (Canada). Using network analysis, centrality measures and hierarchical regressions, results of this study indicate that by occupying a central position in a network of indirect ties, a firm is more likely to access useful knowledge from its direct partners and increase innovation. We suggest, as a conclusion, that indirect network position could be considered as an intangible strategic resource for biotech firms.
The existence of informal social networks within organizations has long been recognized as important and the unique working relationships among scientific and technical personnel have been well documented by both academics and practitioners. The growing interest in knowledge management practices has led to increased attention being paid to social network analysis as a tool for mapping the nature and membership of informal networks. However, despite the knowledge-intensive nature of research and development (R&D) activities, social network analyses of the R&D function remain relatively rare. This paper discusses the role of informal networks in the development, exchange and dissemination of knowledge within the R&D function. A case study using social network analysis is used to compare and contrast formal and informal knowledge networks within ICI. Marked differences between the informal organization and ICI's formal structures for knowledge exchange are revealed and a series of insights into the working habits of technical staff are presented. The implications for managers are clear: through a better understanding of the informal organization of R&D staff, they can more successfully capture and exploit new ideas; more efficiently disseminate information throughout the function; and more effectively understand the working habits and activities of employees.
This paper is concerned with the mechanisms through which medical knowledge emerges, grows and transforms itself. It is a large-scale empirical analysis of the development of treatments for coronary artery disease, which is the most common cause of death in developed countries. We uncover the structure of medical understanding of the disease and the path-dependent co-evolution of scientific and technical knowledge in the search for solutions to the relevant set of problems. After reviewing a broad range of secondary sources and a number of interviews with leading clinicians, we use new tools recently developed for the longitudinal analysis of large citation networks. We apply them to a bibliographic database of 11,240 papers published in the area of coronary artery disease between 1979 and 2003 and to a patent dataset of 5136 US patents documents granted between 1976 and 2003 for angioplasty-related devices. The results are consistent maps, which we critically discuss, of the major scientific and technological trajectories associated with one of the most important medical procedures of the last 30 years.
The paper compares the innovative structure and performance of Italy and Germany by using the concept of the technological system which is defined as the result of the interaction of four different components: the industrial, the innovative, the commercial (domestic and foreign markets) and the institutional sub-systems. The analysis of the intersectoral innovation flows within the two national technological systems is based on an input-output database rearranged in vertically integrated sectors. Specific hypotheses have been formulated and valid proxies for the variables studied have been used.The final results have been obtained by using network analysis methodology and indicators. This called for a dicotornisation of the original matrices.These results take into account separately the existing differences between Italy and Germany in both absolute terms (dimension effect) and relative terms (proportion effect).The paper shows that Germany is characterised by a higher level of systemic connection both in absolute and (generally) in relative terms. The Italian technological system seems to be segmented in a dualistic structure where few high-tech sectors co-exist along with a pool of traditional ones, rather peripheral in the innovation flow network. The German system, on the contrary, appears to be homogeneous with a more evenly distributed structure of intersectoral innovation flows. The paper concludes by considering the effects of the introduction of other sub-systems: namely foreign market and public intervention. While the former introduces further elements of differentiation between Italy and Germany, the latter seems to perform a similar role in both systems.
In this paper, we performed a comparative study in two research domains in order to develop a method of detecting emerging knowledge domains. The selected domains are research on gallium nitride (GaN) and research on complex networks, which represent recent examples of innovative research. We divided citation networks into clusters using the topological clustering method, tracked the positions of papers in each cluster, and visualized citation networks with characteristic terms for each cluster. Analyzing the clustering results with the average age and parent–children relationship of each cluster may be helpful in detecting emergence. In addition, topological measures, within-cluster degree z and participation coefficient P, succeeded in determining whether there are emerging knowledge clusters. There were at least two types of development of knowledge domains. One is incremental innovation as in GaN and the other is branching innovation as in complex networks. In the domains where incremental innovation occurs, papers changed their position to large z and large P. On the other hand, in the case of branching innovation, they moved to a position with large z and small P, because there is a new emerging cluster, and active research centers shift rapidly. Our results showed that topological measures are beneficial in detecting branching innovation in the citation network of scientific publications.
This paper explores the persistence of research organizations in their efforts to participate in the development of an emerging field of science and technology. Persistence is operationalized as the ongoing contribution of a research organization to knowledge creation and diffusion. In particular, we relate the position of a research organization in a network of R & D collaborations to its ongoing contribution to knowledge development, using data on 991 research organizations in the field of hepatitis C over the period 1979–1992/3. Event-history modeling is used to explore the influence of sociometric time-varying covariates on organizational contribution-spans. The analytical results support the hypothesis that network embeddedness is a significant determinant of organizational persistence in an emerging field. More specifically, the position of a research organization in a network of collaborative R & D activities (rather than the number of network partners or collaborative relationships) has a significant and positive influence on its ongoing contribution to the field.
Regional governments around the world hope to become significant players in the world biotechnology industry through their support for local clusters. This article explores whether or not this is a realistic ambition. It does so through network analysis of biotechnology firms located in Melbourne, Australia, the leading biotechnology cluster in the Asia-Pacific. The article finds that the Melbourne cluster is characterized by both intensive regionalism and precocious internationalism, fuelled by ‘the tyranny of distance’ [Blainey, G., 1966. The Tyranny of Distance: How Distance Shaped Australia's History. Sun, Melbourne]. The regional ties are partial; the international ties are precarious. Support from venture capital and deals with big pharma are especially problematic. ‘The tyranny of distance’ is exacerbated by cultural dynamics, favouring ties with the US and UK rather than Japan and Korea, for example. In this context, making the cluster viable is an immense challenge, calling for imaginative and finely-directed public policy measures.
Geographical clusters are significant drivers of regional economic growth and competitiveness in today's economy. Recent studies have shown that geographically limited knowledge diffusion which results from inventor movements within clusters is a facilitating factor to regional innovation output and therefore to the development of clusters. However, it remains unclear whether the dynamics of inventor movements can be used as an indicator for different stages of cluster progression. In this study, using patent co-authorship data, we construct inventor networks for two telecom clusters, New Jersey and Texas. Based on the longitudinal analysis of inventor network properties and interviews with the key inventors maintaining the networks, we seek to gain a better understanding of 1) how the properties of inventor networks across the two clusters reflect their difference in fundamental “typology” of clusters; and 2) are the patterns of inventor network structures and properties over time indicative of the change in viability of the clusters. Our findings suggest that the cluster “typology” is a key factor determining the structure of the inventor networks in a geographical cluster. Over time, as the economic and social conditions of a cluster change, the regional inventor networks change their performance accordingly. Importantly, the cluster “typology” may be a significant moderating factor for the relationship between the inventor network performance and the cluster's development.
We study the large-scale topology and dynamics of maps of alliances in a major segment of the biotechnology industry. The results point to the joint dynamics of network and innovation. The study demonstrates that the network is scale-free. Competition for links translates into a dynamic exponent that seems to follow the fitter-get-richer model of network growth, with preferential attachment to firms holding key technologies. This network also shows a small-world effect. This work highlights the strategic importance of understanding the growth dynamics and structure of collaboration networks for the building of leading positions in industries led by sustained radical change.
This paper develops a theoretical framework for an explanation of how exploitation and exploration build on each other, in a ‘cycle of discovery’, developed in earlier research. The framework is tested empirically, in the sense of seeing whether it can help to reconstruct and understand the emergence of the pharmaceutical industry. One of the conclusions is that whereas recent literature stresses the idiosyncratic nature of the biotechnological revolution, our analysis seems to reveal that this does not seem to be as unique as suggested. From this, we conclude that the theoretical framework we propose, serves its purpose of explanation. But there are also some lessons for improving it.
The paper addresses the question of what constitutes an appropriate evaluation strategy for national foresight activities in different situations. The variety of rationales for foresight is explored, ranging from a desire to set priorities through to participation-oriented goals and building new networks around common visions and strategies. A generational model of foresight is used to show the evolution of key evaluation issues. The generic motivations for evaluation of accountability, justification and learning are discussed in the context of foresight. Evaluation grounded in the concept of behavioural additionality and the systems failure rationale is shown to be more suited as a rationale for foresight as public policy.Assessing the effects of foresight requires an understanding that it is only one of several influences on public policy. To be effective it needs to be tuned into the strategic behaviour and cycles of policy and economic actors. Cases are presented of evaluation of foresight programmes in the United Kingdom, Germany and Hungary. It is concluded that there is no “one-size-fits-all” evaluation approach and that the method selected is conditioned by motivation, timing and the level of aggregation. Foresight cannot be fully evaluated independently from its context. Foresight is being strengthened by the emergence of rigorous and systematic knowledge to assist learning and improvement.
The development and diffusion of innovations involves groups of organizations with many different roles, who interact with each other (suppliers, adopters, third parties, etc.). This paper examines the nature of the communication networks that exist between adopting organizations, and from third parties and suppliers to adopters. Quantitative models of diffusion often assume that information about innovations flows along pre-existing links, that this information flows from adopters to non-adopters directly, and that there is perfect mixing in the population (i.e. every actor has an equal chance of communicating with every other actor). These are strong assumptions which should be subject to testing. We investigate the impact of differing network topologies of communications and alternative models of social contagion on observed adoption patterns. Network topologies are also extended beyond the focal industry to include suppliers, consultants and other customers. We use a simulation model to test the effect of departures from traditional assumptions on the diffusion pattern and undertake an empirical field study to examine the prevalence of those departures in one specific industry. Our simulation findings suggest that network structure can have a substantial effect on the manner in which innovations diffuse, while innovation-specific communication links, and communication through third parties does not change the shape of the penetration trajectory as much as it alters the places in the process where salesforce effort can offer the most leverage. The empirical study shows strong evidence of imperfect mixing, that both pre-existing and innovation-specific communication links are used, and that communication through third parties may be as important to the diffusion process as direct links from adopters to potential adopters.
Studies of technological change constitute a field of growing importance and sophistication. In this paper we contribute to the discussion with a methodological reflection and application of multi-stage patent citation analysis for the measurement of inventive progress. Investigating specific patterns of patent citation data, we conclude that single-stage citation analysis cannot reveal technological paths or lineages. Therefore, one should also make use of indirect citations and bibliographical coupling. To measure aspects of cumulative inventive progress, we develop a “shared specialization measure” of patent families. We relate this measure to an expert rating of the technological value added in the field of variable valve actuation for internal combustion engines. In sum, the study presents promising evidence for multi-stage patent citation analysis in order to explain aspects of technological change.
The main goal of the research presented in this paper is to provide an overview of the available insights concerning radical changes in inter-organizational network structures. The following research question has been formulated: what is known about the way organizations in networks deal with, and are affected by, radical changes in inter-organizational network structures?In order to answer this question, a review of the most relevant literature dealing with changes in network structure over time is presented. The literature reviewed has been analyzed by comparing the role of change in the analysis (independent vs. dependent variable) as well as the manner in which change is conceptualized (incremental vs. radical change and dyadic vs. network change).It is found that studies that observe networks changing over time are scarce. Nevertheless, the available studies provide some interesting insights concerning the formation, evolution and termination of dyadic ties, network evolution, and the effects of (radical) changes in network structure. However, more research on several specific topics seems necessar