Informal innovationnetworks are networks which are formed spontaneously, they are not formally assigned relationship groups of economic agents, where the performance or non-performance of informal obligations is punished by exclusion from the network or limitation of informal rights within the network. That is, the stability of an informal innovation network is determined by the nature of the additional rent ratio (Bakhareva, 2012) from participating in the network and the expenses related to avoid the obligations of the informal duties within the network. In contrast to the formal innovation network, which is a legally enforceable set of relationships of the network’s members, which is binding and the violation of which will lead to incurred fixed shape and volume of sanctions. The specificity of the institutional nature of informal institutions leads to the fact that they generate a higher level of creative activity (Shironin, 2010), innovations, which is especially important within innovationnetworks. Higher productivity of informal innovationnetworks is also due to their greater efficiency from the point of view of appearance and changes in the structure and composition, the nature of the relationships, as there are no formal requirements, rules, procedures that take significant time in formal networks. Since informal institutions arise and develop, as a rule, where they are more effective than formal ones, i.e. on their basis specific problems of the institutional environment are solved, they are in a sense contribute to a more efficient allocation of resources and their more productive use, rather than existing in a society formal institutions (Manohina, 2011). This determines the fact that informal innovationnetworks provide a higher efficiency of the innovation process through interoperability “at the right time in the right place.” However, the same property of informal networks gives rise to “anti-institutions,” (Shinkevich and Galimullina, 2012) leveling the problems of functioning of innovationnetworks, or transforming them. An example of such an anti-institution within an informal network can be a discrimination of potential participants not taking into account their potential contribution. At the same time, formal networks are more attractive from the point of view of protection of interests, which is especially important within the innovation process in terms of the need to Table 1: Typology of innovationnetworks according to the criterion of the initiator
The article draws on interviews conducted for a larger study that included biotechnology networks in Chicago (Illinois, USA), Copenhagen (Denmark), Singapore, and Vancouver (British Columbia, Canada). In-person interviews in Chicago were conducted with six stakeholders from academia, govern- ment, and industry that are active in the life science field. The interviewees were selected to include representatives from the three stakeholder groups that contribute to innovationnetworks and reaching some of the key organi- zations that manage and connect the cluster. Furthermore, one follow-up interview was completed over Skype specifically addressing changes in the network. In addition, information on individual biographies was collected linked to key individuals identified by the interviewees. Thereby, the measure of trust is based on the model developed by Ferrin et al. (2006), which out- lines that stakeholders make inferences about trustworthiness based on the history of interaction with a partner and further draw on third parties to inform their trust judgments. This translates into analyzing past interaction of stakeholders, including third-party players—individuals or organizations— as well as the current network setup. Individual biographies were collected through desk research and partial information highlighted in interviews. Special attention was paid to changes over time. The interviews were con- ducted in 2013, the follow-up interview in 2014, and the desk research was largely done in 2015. This is also a time in which Illinois had a change in governor as well as personnel changes in some of the key institutions identi- fied by interviewees. The unit of analysis is the biotechnology network also identified as the “cluster” in the remaining part of the article.
Innovationnetworks and similar phenomenon have been analysed by heterogeneous schools under the title of industrial districts, innovationnetworks, regional innovation systems and innovative mi- lieu. Without emphasising the nuances in the theoretical background and focus, all approaches un- derline the embeddedness and reciprocity of relationships (cf. Granovetter 1973). The social fabric creates trust relationships and constitutes a shared culture. These weak ties facilitate the open ex- change of information leading to interactive learning capabilities, the reduction of uncertainty and increase in flexibility to adopt to market changes (Grabher 1993; Camagni 1991). This rationale is based on the understanding of innovation as an interactive, chain-linked-process with many feed- back loops between different stages and actors of the innovation process (Kline/Rosenberg 1986). Out of this perspective, networks can be seen as a basic institutional arrangement and not just an intermediate stage between market and hierarchy, since they are able to cope with systemic innova- tion (Imai/Baba 1991; Grabher 1993).
The open innovation approach (Chesbrough, 2003b) rests on the underlying argument, that the traditional in-house R&D structure is losing ground (Chesbrough, 2003b, Chesbrough et al., 2006) and becoming modularized at each stage of drug discovery and development process (Sampath, 2008, London School of Economics and Political Science, 2005). Increasing costs, complexity and multidisciplinary nature of pharmaceutical innovation, compounded with drug failures, and patent expirations of blockbuster drugs have formed a basis for the emergence of innovationnetworks (Arora and Gambardella, 1990, Cockburn and Henderson, 1996, Hess and Rothaermel, 2011, Melese et al., 2009, Powell et al., 1996). A recent proposal of World Health Organization (WHO) to reformulate the patent based R&D model of pharmaceutical sector to a more open approach, by means of sharing funds, grants to developing countries, milestone based payments, and patent pool, signifies the need for more open innovation in this sector (Correa, 2012). Table 1 summarizes the dimensions of open innovation approach by various authors.
Water Innovation Network (Water I-net), Genomics Innovation Network (Genomics I-net), Regional Accelerator and Innovation Network (Regional Accelerator and I-net), iNnovation Network Liverpool (i-net Liverpool), Food and Drink Innovation Network (Food and Drink I-net), Co-operative Councils Innovation Network (Co-operative Councils I-net), Menu Innovation Network (Menu I-net), Quality Insights is the Quality Innovation Network (Quality I-net), i-net: innovationnetworks Switzerland (I-net Switzerland), Roanoke-Blacksburg Innovation Network (Roanoke-Blacksburg I-net), and European Business and Innovation Network (European Business and I-net)) are set at industry or regional levels for various goals as summarized by Table 1. These, case I-nets were purposefully sampled, as is often the case for qualitative studies , by focusing on innovation motives of organisation and institutions. Data was gathered through secondary sources  (speci ﬁ cally webpages, annual reports, press releases and literature) and examined using content analysis  to present network and innovation orientations due to collaboration in these cases. The study is therefore based on an exploratory approach that generalises at a level of theory as opposed to statistical representativeness or signi ﬁ cance.
objects to develop cognitive-based trust in a temporary knowledge community, which is dependent on the occurrence of everything in a proper order and the attitude of respect for the competence of the other partners to carry out their share of the tasks at hand (Holste & Fields, 2005). Apart from epistemic objects, I also highlight the ability of activity objects to create both extrinsic and intrinsic incentives for crowdsourced digital innovation activities. Specifically, drawing on the attention economy which pointed out that information consumes its recipients’ attention, the newly involved actors, who are attracted to join the innovation network and to con- tribute their knowledge to creating novel innovations, expect to seek attention as their extrinsic reward. In this way, I present how an activity object, through the rep- resentation of zhihu, serves to promote such a doubly distributed innovation network as a marketplace, which connects newcomers’ needs for attention-obtainment, by recognizing, detailing and rewarding newcomers’ differing contributions (Choudhury et al., 2014; Wasko & Faraj, 2005). As extrinsic benefits provide the main motiva- tions for new actors to initiate the behaviour of designing novel components on mul- tiple layers for digital innovation, intrinsic rewards which are involved in social ex- changes that emphasize unspecified obligations, such as social affiliation, feelings of belonging, trust and self-actualization, carry more weight in their motivation for con- tinuous engagement in the process of innovation (Sigala & Chalkiti, 2015). In this way, I demonstrate how an activity object provides a ‘home’ for a ‘family of invisi- ble friends’ (Abrams et al., 2003), intrinsically motivating them to identify them- selves with the communal goal while putting their self-interests aside, thereby fuel- ing the impetus for them to return to the totality. As a result, I highlight the ability of epistemic objects and activity objects to create affective-based & cognitive-based trust and extrinsic & intrinsic activity-related incentives, which serve to foster the information transmission that helps mobilize and aggregate disconnected pieces of knowledge for digital innovation in doubly distributed innovationnetworks. In this way, my research provides a theoretical implication for the coordination of the knowledge discontinuity, complementing the work of Granovetter (1973) who be- lieved the strength of weak ties in accelerating information diffusion within the net- work.
The innovationnetworks formed by firms and ISTs in the energy and biotechnology SFs showed, in general, a higher level of participation of some ISTs, with firms playing a secondary role. Hence, one may say that ISTs were more active, yielded more central nodes, and allowed interconnecting different links in innovation network formation. ISTs also stood out in terms of centrality, which indicates the cohesion of publicly listed company networks in the energy and biotechnology SFs. As few firms had more central nodes in the networks, the structural properties demonstrated, in general, low variability, even with regard to centrality, the property with higher dispersion of results. By comparing the energy and biotechnology SFs, the latter was more fragmented, with lower participation of these same firms in other projects. Fragmentation also indicated some regional characteristics, which are perfectly understandable for a continental country. By and large, it is important that firms select their partners based on their competencies and have access to other ISTs, thereby expanding their access to information, technologies, and funds. The firms that stood out as to the number of projects and total volume of funds allocated to them were mostly public and mixed-capital ones, regarding both the level of participation in
As a result of these criticisms, the linear view is being replaced by systems approaches (e.g., Röling and Engel 1991; Hall et al. 2003; Sumberg and Reece 2004; Knickel et al 2009). As far as agriculture is concerned, the thinking has shifted towards including farmers as important actors in the Agricultural Knowledge and Information Systems (AKIS). The AKIS concept is used to analyse the gradual transformation, involvement of new actors and progression of new initiatives in the AKS (EU SCAR 2012). For specific innovation processes, these actors form flexible and dynamic innovationnetworks which have been referred to as ‘innovation coalitions’ (Biggs & Smith 1998), ‘innovation configurations’ (Engel, 1995), or ‘public-private partnerships’ (Spielman & Von Grebmer 2006; Hall 2006). In these networks, AKS actors are not the dominant providers of knowledge and information, but co-produce knowledge with many other stakeholders (Bruckmeyer and Tovey 2008; Schneider et al., 2009) and joint learning and negotiation takes place to shape an innovation (Leeuwis and Van den Ban 2004).
Foresight or ad hoc management? - 11 - A highly dynamic and therefore very instructive setting for collabora- tive innovation processes is transnational relief. Global disaster manage- ment offers textbook examples of multi-actor collaboration in conditions of great uncertainty. The typical partners in such ad hoc collaboration are as varied as it is possible to be, including: vulnerable local communities, local governments, supranational institutions, foreign state actors, hu- manitarian aid organisations, private companies and private donors. As repeated by observers, actors and crisis researchers (Quarantelli, 2006; Comfort, 2007; Nadarajah, 2011), first and foremost, cooperation in the field needs to be improved. Although we know that sustainable disaster management is more a process than an event (cf. Quarantelli, 1988), the initial stage of crisis management still dominates the media and the aca- demic world. Yet, it takes years to complete a full crisis management cy- cle: from first response, through recovery, to disaster preparedness and mitigation (UNISDR, 2009). The effectiveness, innovativeness and sus- tainability of response depend less on heroic emergency aid than on the collaborative management capabilities of very different actors over time (see, e.g., Donini, 2012; Wamsler & Brink, 2014).
Network process characteristics have previously been deemed important for innovation. The ability to identify common goals and the capacity to handle inter-organizational relationships are important for the network outcomes (Hülsheger, Anderson, and Salgado, 2009; Dhanaraj and Parkhe, 2006; Ritter and Gemünden, 2003). However, whilst professional management is important for all networks, it is probably most crucial for networks composed of partners competing in the same market. Belderbos et al. (2004) found that firms engaged in partnerships with competitors face greater risk of information leakage, which influences the communication flow negatively. Building trust, hindering freeriding and reducing concerns among the partners about undesirable knowledge spill-over may therefore be especially important in homogeneous manufacturer networks (Olsen and Gausdal, 2014). Accordingly, we hypothesise that network process characteristics such as strong network management, stimulating social activities, strong coordination of activities, homework, strong member contribution, support by company and stimulation of team spirit are more relevant for homogeneous manufacturing networks than for heterogeneous manufacturer networks and vertical collaboration networks.
Centrally maintained social network representations can enhance awareness of relationships with those beyond an individual s immediate social circle. They can be invoked step-by-step, as Nardi suggests, to enable indirect contact with an individual, or simply quoted to that person directly as a token of social introduction [Kautz97]. ReferralWeb can identify intensional networks to a named individual, but this requires that the user already know the identity of the specific person that they should contact. ONTOCOPI offers a predicted CoP, but still the user must be able to provide the identity of someone closely associated with the field. As the importance has been stressed of ensuring that CoPs are readily accessible by the wider organisation, a better solution would combine network visualisation with traditional expert finder capability to allow social chains to any individual sharing a particular interest to be identified. Clark, Monk and Dahlbom have argued the importance of common ground and shared practice, but this is not addressed by any of the tools surveyed. A straightforward mechanism should be provided by which the user can be made aware of individuals that share common ground with themselves and have expertise or interest in another specified area.
For policy-makers, there are also clear implications, in seeking to improve the openness of the knowledge community to local partners and to increase their benefits from the KCP in order to stimulate “Cambridge effect” style benefits. Success or failure in the regional engagement of KCPs has serious implications for the regions in terms of increasing their smart specialization in innovation based economic development. There is already a good understanding of how to encourage firms to improve their innovation performance, taking them along an innovation journey through raising their awareness of the value of innovation. This typically involves introducing them to those in similar situations and/ or able to help them, and to take the first steps in innovative investments with innovation vouchers, proof-of-concept funds and ultimately venture capital. We argue that policy-makers, investing substantially in these new-style
Traditional financial institutions rarely reluctant to lend to the poor, for ex- ample, but in BOP networks, companies can provide guarantees for the BOP producers, while association or cooperation will select qualified applicants and through the internal constraints to supervise the use of funds, to a large extent solve the problem of adverse selection and moral hazard in lending. In the case of the ducks, the enterprise, aquaculture association and the government also negotiated the establishment of the “Linwu duck breeding insurance fund” to provide compensation for the farmers who suffered losses due to natural disas- ters, epidemics and accidents. All three of these mechanisms can be in network conditions to form a hybrid system arrangement, the core members more closely relates in together, is not only a simple market contractual relationship, also in- cludes informal trust and mutually beneficial relationship, eventually formed in continuous trial and error and adjust the Shared norms, rules and agreements. But it should be pointed out that, although the enterprise is the core of the BOP network, but not to directly control the establishment and development of all relationships, more is by providing cooperation framework, communication mechanism and knowledge to guide the way to the role of the member func- tions. Relationship interwoven with different properties can form a kind of beneficial to CSV system environment, to make up for the deficiency of the for- mal system, and for the production and business activities within the BOP mar- ket support. Table 3 gives six cases to make up for the specific performance of the system.
At the early 1980s, when the mass production and consumption model reached its limits, innovation has become the engine of competition between firms implementing global strategies. This period is also characterized by the development of the ‘ open innovation ’ paradigm which means that ‘ valuable ideas can come from inside or outside the company and can go to market from inside or outside the company as well’ (Chesbrough 2003, p. 47). According to the author, the development of this model is linked to several changes: a growing mobility of highly skilled workers, the growing presence of venture companies, new possibilities offered to market internal ideas and the increasing capabilities of external suppliers. In this model of open innovation, the creation of knowledge and the whole innovation process proceeds through feedbacks between R&D, design, production and commercialization. In this chain-linked model (Kline and Rosenberg 1986), the genesis of innovation results from systemic links be- tween knowledge and the market. The open innovation strategies put forward the growing importance of networks, within which the knowledge-capital is built.
The English government was pleased with these better than expected PISA results, in contrast with the dismay and alarm felt by Germany to their unexpected lower ranking. In Norway the education minister is following a top-down, centralist intervention not unlike that which has taken place in England over recent years and which has been interpreted as the cause of the improvement in student performance. At the same time, those at the top of such league tables, notably Japan and other East Asian countries, are far from complacent and are ready to innovate, not merely to maintain their position but to forge further ahead. All education systems now look on innovation more favourably; this explains why in England ministers have established an innovation unit in the Department for Education and Skills (DfES). In East Asia it is known that radical innovation in the way organisations work can transform an industry. They are now thinking hard about how educational organisations might engage in innovation to nurture the creativity on which their future success as a nation may well depend. The PISA-induced complacency has been short-lived in England, where ministers have become used, with some justification, to proclaiming internationally the success of reforms such as the literacy and numeracy strategies. The recent failure to maintain the upward curve of improvement has come as a shock. Is there something wrong with the strategies, ask ministers and their officials? Are some people, such as school principals or headteachers, or teacher trainers, not doing what they are supposed to do? Or is something more innovative required? Do we need a transformation rather than just improvement if we are to maintain our position in the PISA league table, let alone improve it?
were especially drawn to Peter GloorÕs work on collaborative innovationnetworks (COINs). The COIN model has been applied in fields as wide-ranging as medical research (Gloor et al., 2011) and collaborative editing of wiki sites (Iba et al., 2011). While the concept is often applied to larger-scale collaborations such as these, when introducing the model, Gloor (2006, p. 23) also uses the example of a trio of collaborative musical composer-performers to illustrate the functions of COINs, indicating how the COIN construct can be applicable to musicians (and others) working in networks of various sizes. Gloor (2006, p. 3Ð4) observes that groups of people have behaved in ways framed in his research for hundreds years Ð Òmany of us have already collaborated in COINs without even knowing it.Ó The Eruptšrs can be seen as a quintessential example of a functioning ÒCOIN,Ó for the model captures much of what is termed by punk and other musicians as a ÒDIYÓ approach, explored further below. Gloor tells us that Òin a COIN, knowledge workers collaborate and share in internal transparency. They communicate directly rather than through hierarchies. And they innovate and work toward common goals in self- organization instead of being ordered to do soÓ (Gloor, 2006, p. 4). This is certainly true of the Eruptšrs.
Innovation activities usually take place under a framework of cooperative links between agents. Some innovators still operate in an isolated way, but nowadays innovative companies, universities and research centers increasingly share information and resources in cooperative R&D projects, aiming to obtain collective synergies and individual advantages from strategic collaborations (Wuchty et al., 2007; Jones et al., 2008). Previous research in various disciplines has shown that collaboration patterns represent a crucial aspect of innovation processes and determine the success of individual agents and territories (see, e.g. Allen, 1983; Saxenian, 1994; Brusco, 1999). Applying social network analysis, more recent literature characterizes the particular structural properties of innovationnetworks that enhance or inhibit both present and future R&D outcomes (see e.g. Fleming et al. (2007) for analysis of regional performance and Schilling and Phelps (2007) for firm-level analysis; see also Section 2). Therefore, companies willing to improve their innovation outcomes should take into account the structure of their collaboration patterns while performing research activities with other agents. At the same time, policymakers who seek to encourage innovation should consider how to enhance or inhibit certain features of collaboration networks within and across regions to maximize the knowledge spillovers.
Nuvolari’s findings to the ones presented here as there are both parallels and differences between the two. Firstly, steam engine patents were relatively spread out across the country and very few were issued to residents of Cornwall, perhaps a result of the increased usage of steam power for numerous purposes in industrialising areas. Pottery patents, on the other hand, were concentrated in Staffordshire and London’s surrounding area which between them accounted for two thirds of patents. Secondly, Cornwall had an extremely low number of patents for steam engines relative to the ‘major contribution’ of the region to steam power. 36 This shows that the geography of patenting activity in the pottery industry was somewhat more complex. Whilst Staffordshire did command the largest share of pottery patents for a single county, the absolute number was relatively low given the extreme concentration of the industry, and the majority of patents were located outside of the county. Moreover, when we look away from the producer side, outsiders to the industry, shown in Figure 7.4, who held patents were spread far more widely across England and located in regions heavily involved in other industries such as Yorkshire, Lancashire, Cornwall and Devon. This shows, therefore, that the low propensity to patent a pottery innovation was exhibited within the industry rather than at the regional level, and did not extend to outsiders. This reinforces the notion that the types of innovations being awarded patents in each of these industries were very different. This is of course a somewhat obvious distinction to make but it is an important one nevertheless as it will lead us to an examination of the patent specifications themselves. Was there something specific about the pottery industry in England which made it difficult or precluded the need for innovations to be patented? The short answer to this question is yes. The long answer will become
According to a study by Market Research Future, the telemedicine market is expected to grow at a compound annual growth rate of 16.5% from 2017 to 2023. The study determined that the reason for the predicted increase is demand in rural areas for healthcare, as well as a rise in government initiatives. Telemedicine requires a network that can support real- time high- quality video, which often means wired networks. With 5G, healthcare systems can enable mobile networks to handle telemedicine appointments, which can greatly increase the reach of the program.