Building networks to harness innovation synergies: Towards an open systems approach to sustainable development

Rasiah, Rajah Article Building networks to harness innovation synergies: Towards an open systems approach to sustainable development Journal of Open Innovation: Technology, Market, and Complexity Provided in Cooperation with: Society of Open Innovation: Technology, Market, and Complexity (SOItmC) Suggested Citation: Rasiah, Rajah (2019) : Building networks to harness innovation synergies: Towards an open systems approach to sustainable development, Journal of Open Innovation: Technology, Market, and Complexity, ISSN 2199-8531, MDPI, Basel, Vol. 5, Iss. 3, pp. 1-20, https://doi.org/10.3390/joitmc5030070 This Version is available at: https://hdl.handle.net/10419/241329 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Journal of Open Innovation: Technology, Market, and Complexity Article Building Networks to Harness Innovation Synergies: Towards an Open Systems Approach to Sustainable Development Rajah Rasiah Asia-Europe Institute, University of Malaya, Kuala Lumpur 50603, Malaysia; [email protected] Received: 30 July 2019; Accepted: 29 August 2019; Published: 12 September 2019   Abstract: Open innovation has become a popular approach, especially since 2003, as people began purposively managing, evolving and harnessing knowledge flows across organizational boundaries but through increasing connections with systemic knowledge nodes relevant to the innovation process. The creation and appropriation of such knowledge has evolved rapidly with digitalization and the proliferation of broadband networks. Individuals, firms and organizations now connect and coordinate to support innovations openly across innovation systems. This paper proposes an open systems model with institutional underpinnings to not only quicken knowledge flows and expand the networks to a wider range of socioeconomic agents, but also for their inclusive participation in shaping the processes of achieving sustainable development through environmental greening and egalitarian balancing of society. In doing so, using examples, the paper focuses on developments since Schumpeter’s ground-breaking exposition of innovation to explain how individuals, firms, farms and organizations can participate actively in open innovation networks to connect productively with the critical knowledge nodes in society. Keywords: open innovation; systems approach; environmental greening; egalitarian society; sustainable development 1. Introduction The emanation, diffusion and appropriation of knowledge has undergone massive changes over time. Although the term smartification has emerged to explain some aspects of raising intelligence, we use it more broadly to capture all aspects that relate to generation, flow, diffusion and appropriation of knowledge, including the collective production, sharing and appropriation of knowledge. From the rubbing offeffects of systemic knowledge flows in industrial districts, whereby by learning by looking, thinking and doing—all of which evolved interactively [ 1 ], it has subsequently evolved to a profound focus on heavy capital investment that drove R&D activity in large firms [ 2 , 3 ]. Schumpeter [ 3 ] referred to innovations from Marshallian knowledge spillover as incremental and the latter as radical. The argument for registering and protecting intellectual property rights (IPRs) came from Schumpeter’s account for the need to stimulate radical innovations, which he argued were important to initiate new cycles of innovation, as new investments into the production of radically new knowledge was both risky and uncertain. However, since IPRs also block knowledge flows, it can both restrict incremental innovation, as well as cumulatively also slow down investments into radical innovations [ 4 ]. The increasing resort to open innovation systems is one consequence of restrictive IPR regulations. Thus, we recommend short periods for path-dependent innovations, and the use of public ownership where innovations help alleviate poverty and green the environment. Open innovation is defined as the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand markets for external use of innovation, respectively [ 5 , 6 ]. In open J. Open Innov. Technol. Mark. Complex. 2019,5, 70; doi:10.3390/joitmc5030070 www.mdpi.com/journal/joitmc J. Open Innov. Technol. Mark. Complex. 2019,5, 70 2 of 20 innovation systems, organizational borders are porous, so that individuals, firms and organizations can combine their resources by cooperating with external agents. Because certain types of knowledge are a source of wealth for some and, as such, are registered under IPRs, agents cooperating in such formally defined set ups establish networks to share knowledge among members. However, since knowledge is a public good, which is neither excludable nor rivalrous, government seeking to engender the conditions for stimulating innovations must open it to all active socioeconomic agents to offer extensive synergizing opportunities for both the generators and appropriators of knowledge flows. Although digitalized smart robots are revolutionizing production and service systems, the heart of innovation capabilities has remained the human, and hence, any design of the science, technology and innovation (STI) infrastructure targeted at synergizing knowledge flows (including generation and appropriation), must attempt to link them to knowledge nodes in particular countries. However, an innovation network that is sufficiently open to stimulate knowledge flows—creation and appropriation—on the one hand, and to enable potential generators and appropriators to connect and coordinate with the knowledge nodes on the other hand, is seriously lacking. Aside from this, Chesbrough’s [ 5 ] accounts of open innovation puts too much emphasis on the commercialization of knowledge when the egalitarian needs of society also require a public focus to address climate change mitigation and inequality. This new model of innovation should address the three fundamental tenets of a vibrant ecosystem built on supporting economic growth and structural change, eliminating poverty and inequality, and finally greening the environment. Thus, this paper aims to design a framework for developing an open innovation system to act as an enabler of innovation creation and appropriation for all socioeconomic agents, and one that directs it to achieve environmental greening while improving income distribution. In doing so, this conceptual paper takes on an inductive approach of theorizing based on an evolutionary perspective of institutional changes necessary to induce purposive promotion of open innovation systems [ 7 – 11 ]. The next section discusses the critical developments from past work to anchor the study. The subsequent section discusses the open systems innovation model. The conclusions are presented in the final section. 2. Theoretical Considerations Much of the extant innovation literature has focused on propelling economic growth and structural change from low-to-high value-added activities. It is only since the 1990s, especially after the turn of the millennium, that serious scholarship has emphasized the need to link innovations to support sustainable development issues. We address the three critical pillars of sustainable development, viz., economic development, environmental greening and promotion of an egalitarian society. The broad framework for achieving the three objectives requires emphasis on stimulating innovations that simultaneously drive economic growth while greening the environment and restructuring economies equitably. This section is structured first to establish the importance of developmental rents to stimulate innovations, and their nature [ 2 ]. This is followed by spatial agglomeration of firms and innovation activity since the evolution of industrial districts in Britain, which is arguably the first documented development involving differentiation and division of labour. British industrial districts has been characterized by linkages between socioeconomic agents that connect and coordinate with one-another, including workers, farms and firms [ 1 ]. However, it is the subsequent spatial models that experienced a profound role from knowledge-producing organizations (including science, technology and innovation (STI) infrastructure organizations) and government legislative and policy instruments that stimulate them. While the development of knowledge nodes (STI organizations) is critical for the promotion of knowledge creation and its appropriation, the policy framework must also address environmental greening and achieving an egalitarian society. Also examined in this section is the role of developmental rents to promote innovation. J. Open Innov. Technol. Mark. Complex. 2019,5, 70 3 of 20 3. Developmental Rents Since inventive activities carry risk and uncertainty, rents become necessary to expand the enabling environment for supporting technical change [ 2 ]. However, unproductive rents will misdirect resources to wasteful and destructive activities. Hence, the provision of rents require careful governance in the selection, monitoring and appraisal of socioeconomic agents. The first issue that needs addressing when discussing developmental rents is its incentivizing role in innovations. Rents are associated with transaction value above or below market clearing rates [ 1 ]. Markets refer to relative prices. Instead of taking a strict definition of prices in the presence of perfect information with the assumption of all socioeconomic agents enjoying equal access to resources, we define it as the transaction value in the absence of undue intervention in support of any of the parties involved in the transactions. Neoclassical definitions consider rents that arise from interventions to be distortive, and hence, bad [12,13]. Dirigiste economists take on Schumpeter’s [ 2 , 3 ] argument that interventions are essential to divert resources from less productive activities to more productive activities [ 14 ]. However, the pursuit of unproductive rent-seeking will give rise to clientelism [ 15 ]. Economies rife with clientelist activities in the 1980s and 1990s, which include several Sub-Saharan economies [ 16 ], Bangladesh and the Philippines [16,17], have been characterized strongly by unproductive rent-seeking activities. Corruption is linked directly with unproductive rent-seeking activities when resources are wasted or diverted to less productive activities, thereby contributing to economic inefficiency. Also, the diversion of resources through the conduct of socioeconomic agents that create opportunities for officials to exploit unproductive rents can have a negative cascading effect on other segments of society [ 17 – 19 ], which leads to clientelism, whereby the rich and powerful dominate or capture the state machinery to achieve their own ends [ 20 ]. Such relationships tend to be parasitic and unproductive, especially involving collusive transfers between officials and other parties that sap economies of scarce resources [ 17 ]. Developmental rents refer to rents created that succeed in achieving productive outcomes. For that to occur, the state has to enjoy autonomy over interest groups and, at the same time, have the capability and competence to generate productive outcomes [ 16 – 18 , 21 ]. Hence, all rents targeted at supporting innovations must be accompanied by strict selection procedures, monitoring and appraising to not only prevent its misallocation into unproductive activities, but also to ensure that its misdirection is minimized. 4. Schumpeter’s Innovation Initiators Schumpeter [ 3 ] glorified the large firm, as during his time only such firms enjoyed the financial capability to support frontier R&D activities. Two key elements became central for firms’ participation in R&D, which are risky and uncertain. First, Schumpeter called for the provision of protection for first movers of inventive activity. Second, Schumpeter argued that firms make deliberate attempts to raise concentration to ward offlatecomers. He saw such initiation of new cycles of innovation important to stimulate business upswings. The large vertically-integrated firms, such as General Motors and Ford Motors in automobiles, and Fairchild, Intel and Motorola in semiconductors in the United States; Volkswagen, Mercedes, and Bavarian Motor Works (BMW) in automobiles in Germany; Toyota and Honda in Japan; and Siemens, Phillips and Erikson in Europe, fit this framework. The Zaibatsus that dominated industry in Japan before World War II ended, the chaebols in South Korea (e.g., Samsung Semiconductor), and large firms in Brazil (e.g., Embraer) and China (e.g., Huawei) are examples of economies where frontier firms internalize their R&D. Such innovation systems tend to be truncated in large firms, which are fairly closed as innovation systems. 5. Decentralization of Innovation Activity The early shifts towards the decentralization of innovative activity emerged when firms (including start-ups) began clustering around critical knowledge nodes, such as research universities and public J. Open Innov. Technol. Mark. Complex. 2019,5, 70 4 of 20 labs. Strong connectivity and coordination between firms and science, technology and innovation (STI) organizations helped connect small firms to the knowledge nodes. Hence, the Schumpeterian inventor in large firms began to decentralize into a network of firms and organizations that are shaped by institutional change. Latecomers began appropriating, much more than before, incremental innovations from inventions to undertake product proliferation. 5.1. Industrial Districts Arguably the first open innovation system can be traced to the Marshallian industrial district [ 1 ], in which thousands of small firms agglomerated in particular geographical locations but without any significant knowledge-stimulating organizations, such as R&D labs and training centres (Figure 1). Knowledge flowed through interactions between workers without restrictive intellectual property rights (IPRs) regulations. Small firms with clothing and leather goods and their accessories, were located at proximate locations, with the division of labour between firms being high and within firms being low. Firms were specialized on the basis of scope rather than scale, and demonstrated a blend of competition and cooperation in driving productivity [22]. The industrial district became famous following its evolution in Italy as small firms with an employment size of 18 and below evolved to produce some of the most highly value-added furniture, pottery and equipment. A combination of trust and prices have been important in the institutional framework that has held together these firms in Italy (including Emilia Romagna) [ 23 , 24 ]. A major dimension that drove the industrial districts was the differentiation and division of labour, which ensured the constant creation of new firms specializing on the basis of scope economies. While the size of markets drove the division of labour, the division of labour drove the market size [ 10 , 25 , 26 ]. In this context, trust has been a key element in holding firms, in particular industrial districts, including in R&D activities in Norway and Taiwan [27,28]. While knowledge flows are open in industrial districts in that they are systemic, the specific distinguishing tacit elements are often embodied in humans and retained in firms so that they flow through families and relatives inter-generationally. However, while the Italian industrials have organizational support from government agencies, utility firms and training centres (including access to universities) and industrial districts, linkages with important knowledge nodes, such as R&D labs, incubators and venture capitalists, are not pronounced. 5.2. Silicon Valley and Route 128 Silicon Valley and Route 128 are two major examples where connectivity and coordination between firms, public R&D labs, universities and other intermediaries (including funding) have forged a strong network of knowledge flow to support firm-level innovations (Figure 1). Both Silicon Valley and Route 128 provide what industrial districts lacked, i.e., world-class frontier organizations undertaking R&D and incubator support. The proliferation of technology funding firms, such as venture capital, has stimulated the scaling up of start-ups in Silicon Valley and Route 128 [ 26 , 29 ]. Silicon Valley and Route 128 have also evolved a strong capacity to speciate new firms through differentiation and division of labour. While Best [ 26 ] discussed the evolution of new industries from the relocation of dissimilar but complementary demand from old firms to new firms, Saxenian [ 30 ] documented the movement of human capital from old firms to start new firms. Innovation networks in Silicon Valley and Route 128 received a massive boost when government regulations helped the diffusion of innovations to a broader spectrum of society (which opened the way for private appropriation of it) when the U.S. government enacted the Bayh–Dole Act in 1980. The government of the U.S. attempted to tackle the lack of commercialization of knowledge from federally-funded projects when Congress passed the Bayh–Dole act to give control to universities to grant licenses for their use by small businesses and non-profit establishments. It overcame one major barrier that restricted university–industry linkages [ 31 ]. Also, if in the past large firms that had the capacity to undertake R&D and to scale up products created closed innovation systems, the Bayh–Dole J. Open Innov. Technol. Mark. Complex. 2019,5, 70 5 of 20 act opened this to individuals, firms, farms and organizations to appropriate such knowledge for a small fee. Such publicly-held knowledge can also be better amortized as the same IPRs can be accessed by several agents depending on the nature of rights defined. However, the innovation openness of Silicon Valley and Route 128 is also limited by IPRs opened by holders. For example, IBM opened its computer architecture, which saw the development of several clones, such as Compaq [ 5 ]. However, of the three technologies that have defined the PC industry in the 1980s, i.e., IBM’s architecture, Microsoft’s operating system and Intel’s microprocessors, the latter two share their knowhow to support computer processing products but Microsoft and Intel IPRs remain closed for non-collaborators. Consequently, such a sub-system of openness cannot be accessed by society as a whole. Also, the Bayh–Dole Act focused only on giving control to universities to appropriate innovations from federally-funded research projects. While this legislation expanded the reach of knowledge to a wider set of socioeconomic agents, thereby by casting the net of incremental innovations beyond the closed boundaries of R&D laboratories in large firms, government (including military) and universities, it did not purposively target the appropriation of innovations by individuals and organizations that function wholly to achieve social goals, as well as those unable to afford the small licensing fees. Aside from this, the Bayh–Dole act did not place any priority for supporting innovations specifically targeted at assisting the poor and for greening the environment. To ensure sustainability, a mechanism is necessary to prioritize innovations to assist the poor and to green the environment. 5.3. Vinnova Model The Vinnova model launched by the Swedish government in 2001 has elements of the triple helix, which supports government, industry and university collaboration, but one that also brings together the different stakeholders to stimulate innovative activities (see Figure 1) [ 32 – 34 ]. Funding is allocated to qualifying firms and other critical members, such as universities. Extensive attention is given by the management of Vinnova to connect universities to firms, and to prioritize research on greening the environment, natural resources and agriculture. Elements of Etkowitz’s [ 35 ] triple helix framework is visible here as industry, government and universities work together to stimulate innovation to drive the economy. As a concept, the triple helix of university–industry–government relationships was popularized largely by Etzkowitz [ 36 , 37 ], who expounded it as a triadic relationship between university–industry–government [ 38 ]. This model uses stringent criteria for selecting, monitoring and appraising the loans provided, the research undertaken and the system as a whole. The main responsibility of Vinnova is to stimulate collaboration between higher education institutions (HEIs) and the society around them, although the focus is on firms. The Swedish Research Council is a key stakeholder in this network that attempts to lead Swedish research strategically while collaborating with other funding bodies. Forma, Forte, HEIs and companies complete the main stakeholders in the Vinnova model. Forte is a Swedish research council agency under the Ministry of Environment and Energy, while Forme is a Swedish research council agency under the Ministry of Health and Social Affairs. Although Edquist et al. [ 39 ] argued that the Swedish framework produced a low innovation return to R&D output, McKelvey [ 40 ] provided evidence to show the successful translation of funding into commercialization under the Swedish model when compared to other countries. Deiaco et al. [ 41 ] discuss how over time and across countries, universities exhibit a wide range and forms of public and private ownership, profit and not-for-profit objectives, and the degree of dependence on state funding to support innovative activity varies. Also, as Chaminade et al. [ 42 ] show, the Swedish innovation system is also internationally open, though it is strongly integrated regionally. The Vinnova model offers room for stakeholders to organize the creation and appropriation of knowledge that focuses on commercialization and environmental greening. The stringently evaluated funding system provides scarce capital to support collaborative innovations in firms, universities and public laboratories. However, it is not sufficiently open to synergize, as well as absorb all socioeconomic J. Open Innov. Technol. Mark. Complex. 2019,5, 70 6 of 20 agents’ prospective participation in the innovation system, especially to enable the innovative faculties of individuals unconnected to farms, firms and organizations. 5.4. Taiwan’s Science Parks The R&D consortia evolved in Taiwan to support collaborative innovations is another example of innovation networks that penetrate firm and organization boundaries (Figure 1) [ 43 ]. The major contribution of Taiwan’s framework of collaboration between science parks, universities and firms to a systems framework of innovation is the use of the consortia to share research, as well as to appropriate collaborative synergies. Indeed, the location of several different incubators that share common support machinery and equipment (e.g., for instrumentation and standards testing), and proximity for interactions has stimulated the proliferation of new products [ 28 , 44 ]. Science parks launched by the Industrial Technical Research Institutes (ITRI) in 1974 have been organized by broad sectoral categories—for example, micro-chip and micro-chip-driven products, biotechnology-based products and metaland machinery-based products—to take account of the special structures associated with each. Each of them have a strong infrastructure to support innovation using specialized incubators. Taiwan’s STI is open to extensive adaptive learning from foreign sources of knowledge. In addition to technology acquired through manuals, imported machinery, licensing and mergers and acquisitions, institutions and interactions between experts were evolved to attract tacit knowledge embodied in human capital from across the globe to solve problems and to lead technological catch up [ 28 , 45 , 46 ]. The institutionalization of knowledge flows and continuous adaptations made Taiwan’s knowledge networks innovative in providing the capabilities for developing new products and process, as well as fertilizing innovation across different industries. The open nature of Taiwan’s science parks also stimulated the coevolution of innovation activity, which allowed individuals and firms to connect with the knowledge nodes. While government-funded high-tech firms emerged through initial mergers and acquisitions—such as the United Microelectronics Company and Taiwan Semiconductor Corporation [ 28 ]—small firms, such as Phison, started by five graduates and an equity of $0.9 million USD in 2003, managed to generate sales exceeding $1 billion USD in 2009 with 200 design engineers). In an interview with the chief executive officer of Phison on 15 September 2009 by the author showed that the firm successfully used the universities and science park incubators to scale up and commercialise innovations. The Taiwan model offers considerable room for socioeconomic agents in firms and organizations to organize the creation and appropriation of knowledge that focuses on commercialization. The matching grant funding system offers scarce capital to support collaborative innovations in firms, universities and public laboratories in Taiwan. However, like the Vinnova model, it is not sufficiently open to synergize, as well as absorb, all socioeconomic agents’ prospective participation in the innovation system, especially in enabling the innovative faculties of individuals unconnected to farms, firms and organizations (Figure 1). J. Open Innov. Technol. Mark. Complex. 2019,5, 70 7 of 20 J. Open Innov. Technol. Mark. Complex. 2019, 5, x FOR PEER REVIEW 7 of 20 Figure 1. Evolution towards open systems knowledge flows. IPRs: intellectual property rights. 6. Innovation Systems Framework We now turn to review the extant literature on innovation systems. From the heuristic concept of innovations systems, a range of works emerged to offer governments a framework to organize policy for promoting innovations. The broadest classification took on a loose model of national innovation systems (NIS) [47], which focused on critical instruments and organizations that deal with innovations. The use of the concept to denote links between knowledge nodes and appropriators can be traced to Freeman [48], though its crude version was articulated earlier by List [49]. However, much of the empirical works that came out of it deal with R&D, intellectual property rights, universities and R&D labs, and how firms connect to such organizations and instruments. Not only have subsequent works been overly loose, they do not take advantage of the fact that humans are the only socioeconomic agents capable of generating new stocks of knowledge, albeit other animals are known to have the capacity to evolve through adapting their routines with changes in time. Some elements of clustering and differentiation and division of labour have been captured by Lundvall [50], who discussed the critical role of user–producer relationships, which has its antecedents to Vernon’s [51] scanning–coordinating relationships between R&D engineers and scientists, and consumers. Consequently, members of NIS then went on to develop the sectoral innovation systems (SIS) concept by arguing that industries are different [9,52]. The focus was on identifying the different drivers of each of these industries, taking account of the institutional changes that are specific to locations and time [9,53,54]. The sectoral focus also allowed Chang et al. [55] to capture the nature of radical innovations in the construction sector. In contrast to the arguments of Pavitt [52], they provide evidence to show how a myriad of existing and new knowledge in areas such as seismic movements are adapted and fused together to transform construction. In fact, the construction of smart tunnels through mountains to handle both flash floods and jams, and the construction of tall buildings using construction beams, have radicalized the sector. These changes were welcome addition to our understanding of innovation systems, though much of the works on sectoral innovation systems have hardly mapped the innovation nodes and their drivers effectively. Also, unlike in manufacturing, where much of the NIS and SIS literature has focused, the governance or institutional structures that have stimulated innovation in construction, agriculture Figure 1. Evolution towards open systems knowledge flows. IPRs: intellectual property rights. 6. Innovation Systems Framework We now turn to review the extant literature on innovation systems. From the heuristic concept of innovations systems, a range of works emerged to offer governments a framework to organize policy for promoting innovations. The broadest classification took on a loose model of national innovation systems (NIS) [ 47 ], which focused on critical instruments and organizations that deal with innovations. The use of the concept to denote links between knowledge nodes and appropriators can be traced to Freeman [ 48 ], though its crude version was articulated earlier by List [ 49 ]. However, much of the empirical works that came out of it deal with R&D, intellectual property rights, universities and R&D labs, and how firms connect to such organizations and instruments. Not only have subsequent works been overly loose, they do not take advantage of the fact that humans are the only socioeconomic agents capable of generating new stocks of knowledge, albeit other animals are known to have the capacity to evolve through adapting their routines with changes in time. Some elements of clustering and differentiation and division of labour have been captured by Lundvall [ 50 ], who discussed the critical role of user–producer relationships, which has its antecedents to Vernon’s [ 51 ] scanning–coordinating relationships between R&D engineers and scientists, and consumers. Consequently, members of NIS then went on to develop the sectoral innovation systems (SIS) concept by arguing that industries are different [ 9 , 52 ]. The focus was on identifying the different drivers of each of these industries, taking account of the institutional changes that are specific to locations and time [ 9 , 53 , 54 ]. The sectoral focus also allowed Chang et al. [ 55 ] to capture the nature of radical innovations in the construction sector. In contrast to the arguments of Pavitt [ 52 ], they provide evidence to show how a myriad of existing and new knowledge in areas such as seismic movements are adapted and fused together to transform construction. In fact, the construction of smart tunnels through mountains to handle both flash floods and jams, and the construction of tall buildings using construction beams, have radicalized the sector. These changes were welcome addition to our understanding of innovation systems, though much of the works on sectoral innovation systems have hardly mapped the innovation nodes and their drivers effectively. J. Open Innov. Technol. Mark. Complex. 2019,5, 70 8 of 20 Also, unlike in manufacturing, where much of the NIS and SIS literature has focused, the governance or institutional structures that have stimulated innovation in construction, agriculture and services have been inadequately studied. The developmental focus on agriculture, services and construction received a strong impetus when the systems of innovation literature evolved to undertake research on how adaptive learning and R&D have progressed to stimulate productivity growth in the sectors [ 35 , 53 , 55 ]. However, these works have shown little focus on how individual farms, units and firms moved up the technology ladder through a profound empirical assessment of how rents were created and translated productively. What is lacking is a direct approach to see how technological transformation has evolved in these sectors, and how the evolution of knowledge nodes has radicalized the sectors from the perspective of both generators/adaptors, as well as users. Such developments can not only stimulate structural transformation that address greening, but also support egalitarian accumulation. Aside from this, existing NIS and SIS works have not taken advantage of advancements in systemic technological instruments, such as digitalization and Industry 4.0 tools, to conjecture the likely future institutional paths that will evolve innovation agglomerations and would enable all socioeconomic agents to participate actively in such systems, as well as embrace critical developmental measures to strengthen human societies by greening the environment and shifting the world to an egalitarian system. Rural Innovation Systems Since the majority of the poor among developing economies are associated with rural farming, this sub-section examines innovations that are devoted to rural developments that demonstrate how participative open innovation systems can alleviate poverty and green the environment. Socioeconomic agents’ participation in innovation networks have already evolved in agriculture to address poverty and inequality and the environment. There exist considerable accounts of the state’s role in poverty alleviation through land reforms, and integration of farmers and fishermen with markets (both domestically and export markets), connecting and coordinating parastatals with farmers and markets, as well as with price stabilization, in Malaysia, South Korea, Taiwan and Chile [ 56 – 59 ]. To check the spread of communism to South Korea and Taiwan, land confiscated from the Japanese colonial government was distributed to the poor in the late 1940s and early 1950s [ 57 , 60 ]. The state of Malaysia also introduced land and fisheries reforms through the launching of the Federal Land Development Authority, Rubber Industry Smallholders Development Authority (RISDA), Federal Land Consolidation and Rehabilitation Authority (FELCRA) and the Malaysian Fisheries Development Authority (MAJUIKAN) [ 59 ]. To prevent a return to socialism in Chile, the United States’ government supported the Pinochet government to alleviate poverty in the country by funding the development of economic activity in locations where the poor lived [61]. While land reforms were important, two major channels of innovation were critical in the catch up experienced by poor farmers in South Korea, Taiwan, Chile and Malaysia. In the first channel, adaptive innovations were developed using largely foreign sources of knowledge (such as in the use of fertilizers, double-cropping paddy seeds and plant and fish species from abroad). Farms in all four countries raised productivity rapidly by raising yields. Whereas parastatals in Sub-Saharan Africa failed [ 62 ], effective institutional change made them a success in South Korea, Taiwan, Chile and in Malaysia until the 1980s [56,59]. Secondly, the evolution of the STI infrastructure through the development of STI infrastructure helped raise agricultural productivity in South Korea, Taiwan, Chile and Malaysia [ 63 ]. Innovation in agriculture deepened a lot more in South Korea, Taiwan and Chile than in Malaysia, owing to the three former nations’ continuously evolve domestic innovation capabilities to stimulate technological upgrading. Rural farming in Malaysia, associated with the poor, began to face a decline, owing to a combination of reduced focus from the government, as well as the debilitating Dutch disease effects of an overvalued ringgit over the period of 1989 to 1997 [ 59 ]. In addition, the science and technology J. Open Innov. Technol. Mark. Complex. 2019,5, 70 15 of 20 Overall, the four pillars of the systemic quad should be evolved simultaneously to appropriate maximum knowledge creation, flow and appropriation synergies. Institutional change should not only focus on quickening the development of these four pillars, but also on strengthening elements of greening and equitable distribution of income. 9. Conclusions Despite corporate motives to protect new knowledge, constituencies calling for opening it to appropriate its public goods characteristics have been snowballing. While scientific knowledge has largely been generated in developed countries, sustaining humankind requires increased emphasis on greening and access for all socioeconomic agents, as well as ensuring that its financing takes care of the interests of both the haves and have-nots. Consequently, it is pertinent that policies to stimulate growth and structural change are integrated with environmental greening and poverty alleviation initiatives. Technological advancement has enabled the development of STI infrastructure that offers connectivity to individuals, firms, farms and organizations with the critical knowledge nodes. This paper developed an open innovation model that took account of evolving knowledge networks to offer socioeconomic agents the opportunity to participate in knowledge networks—both as generators and appropriators. In doing so, the paper traced the evolution of open systems networks from the industrial districts of Britain and Italy, and subsequently the unique developments in the United States, Sweden and Taiwan. The specific rural experiences of Chile, Malaysia, South Korea and Taiwan were also included to construct an open innovation model that extends knowledge creation and appropriation to embrace environmental greening and egalitarian societal balance as equally important national targets as growth and structural change. For the inclusive participation of all socioeconomic agents, we extended access from firms, farms and organizations to include all socioeconomic agents. The evolution of technology (including digitalization, big data analytics and smart machines) has raised the potential for attracting the participation of all socioeconomic agents in innovation networks. While the incentive system should continue to finance economic growth and structural change, we call for a review of the IPR system to shorten protective periods to remove undue impediments to path-dependent innovation routes, and for the financing of greening and societal goods and services through public support and public ownership of IPRs. Two important stylized models were built through the extensive adaptation and development of previous models to show how institutional, macroeconomic and innovation policies should be formulated to promote the evolution of an open innovation network that is geared towards driving both incremental and radical innovations, as well as its links to individuals, firms, farms and organizations. The open innovation system with an institutional framework that is geared towards stimulating innovations to power economic growth, environmental greening and balancing income distribution should enable the participation of entire societies in knowledge adaptation, creation and appropriation. However, given that the future is always uncertain, and that policies can fail, the governance of such a system must be subjected to stringent and accountable appraisal with a view towards recalibration to ensure that the direction of its steering is right. Funding: This paper was presented as a keynote speech of SOItmC 2019, and the publishing fee was supported by SOItmC. The research was supported by Distinguished Professor Special Grant (WBS Ac.: UM.0000098/HME.OM; Project No.: MO004-2018). Acknowledgments: I wish to acknowledge the generous support by the organizing committee of SOItmC 2019, including JinHyo Joseph Yun, Yuri Sadoi and Xiaofei Zhao, and the constructive comments by the anonymous referees. The usual disclaimed applies. Conflicts of Interest: The author declares no conflict of interest. J. Open Innov. Technol. Mark. Complex. 2019,5, 70 16 of 20 Appendix A J. Open Innov. Technol. Mark. Complex. 2019, 5, x FOR PEER REVIEW 16 of 20 Appendix A Figure A1. Upgrading action plan. Source: Adapted from Rasiah [54]. Figure A1. Upgrading action plan. Source: Adapted from Rasiah [54]. J. Open Innov. Technol. Mark. Complex. 2019,5, 70 17 of 20 References 1. Marshall, A. Principles of Economics; Macmillan: London, UK, 1890. 2. 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