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Notions on learning applied to wind turbine development in the Netherlands and Denmark
Abstract
This research investigates how methods of learning influenced the emerging wind power industries in the Netherlands and Denmark. It is found that the manufacturing and implementation successes in Denmark contrast with the relatively poor progress in the Netherlands, and that one of the reasons for this is the contrast in learning mechanisms between the countries. We start from the perspective of innovation systems. Within these systems we place the focus on four types of learning processes: learning by searching, learning by doing, learning by using and learning by interacting. It is concluded that in Denmark, learning by interacting was the most important learning process, while in the Netherlands it was learning by searching. The Dutch wind turbine innovation system was a typical ‘science-push’ innovation system. The aim was to develop large wind turbines at a fast pace, based on the results of scientific research. Because of the lack of contacts between the researchers and the wind turbine producers, the implementation of the research results was problematic. Contrarily, in Denmark the focus was on knowledge transfer between turbine producers, turbine owners and researchers. In this innovation system, conditions for learning by interacting were optimal. In this way, wind turbines were successfully, though slowly, scaled up and improved.
... Another essential TIS building block is a production system that can deliver high quality products in large quantities. Over time, growing experience with the production process and the product itself will increase the product's quality and decrease its production costs (learning by doing) (Kamp et al., 2004). These effects increase the competitiveness of the product Geels (2004). ...
... Customers represent an important TIS building block (Kemp et al., 1998;Malerba, 2002). A customer segment needs to be identified early on (Kamp et al., 2004). Potential customers with a need for the innovation should be identified, for example through a problem solved by the innovation or because they largely benefit by using the innovation. ...
... To become actual customers, the potential customers should be aware of the innovation, see its benefits compared to other products, and have the knowledge, means and willingness to acquire and use it (Ortt et al., 2013). When innovations are developed without involving (future) customers, several customer-related issues may hamper their diffusion (Kamp et al., 2004). Potential customers may want to use a product but may lack the means to acquire it. ...
Pioneering companies of radically new technological innovations often suffer from a slow uptake of their innovations and struggle to find the right introduction strategy. This paper aims to conceptualize a Technological Innovation System framework that can be applied to formulate and study niche introduction strategies from a company perspective. It combines insights from two literatures: the socio-technical systems literature and the innovation & strategic management literature. This results in a framework consisting of seven Technological Innovation System building blocks and seven influencing conditions that can influence the building blocks. The Technological Innovation System building blocks in the framework are: product performance and quality; product price; production system; complementary products and services; network formation and coordination; customers; and innovation-specific institutions. The influencing conditions in the framework are: knowledge and awareness of technology; knowledge and awareness of application and market; natural, human and financial resources; competition; macro-economic and strategic aspects; socio-cultural aspects; and accidents and events. The framework can help explore the context around an innovation during the early stages of Technological Innovation System formation and specify the scope, timing and type of niche introduction strategies that fit this context. This is illustrated with two cases: dual-clutch transmission technology and photovoltaic cells.
... According to [3] it is achievable by the incorporation of foreign innovations across borders directed towards improved domestic innovative techniques. For the purpose of this work, four (4) types of learning as identified by [4] are critical for innovative growth, these include; i. learning by searching-investigative approach, ii. learning by doing-practicalized approach, iii. ...
... A clear instance is seen in the Dutch encounter with the development of wind turbine whereby, the investigative/searching approach was its central learning mode. Hence, as recorded by [4] the traditional innovative approach was primarily tied to R&D subsidies [4]. Another demonstration can be appreciated in Denmark, where using/constructive learning mode was initiated alongside the interactive/knowledge-exchange learning mode between producers of turbines, users of turbines and the Danish Research Institute. ...
... A clear instance is seen in the Dutch encounter with the development of wind turbine whereby, the investigative/searching approach was its central learning mode. Hence, as recorded by [4] the traditional innovative approach was primarily tied to R&D subsidies [4]. Another demonstration can be appreciated in Denmark, where using/constructive learning mode was initiated alongside the interactive/knowledge-exchange learning mode between producers of turbines, users of turbines and the Danish Research Institute. ...
Over the last decade, numerous ideas have insistently emerged and triggered several social, economic and environmental discuss emanating from energy insufficiencies in Africa. A lot around energy poverty are currently argued particularly, on how chiefly Africa's industrialization is prime to its potential sustainability across all facets of growth and development. Sadly, only few member countries since post-colonialism have earnestly attempted innovative approaches towards new alternative energy schemes. Nonetheless, wasteful sums have drowned in projects of less critical nature. For this reason; an innovative bird eye view (IBEV) portrayed how member countries might augment rates of dispensable energy to increase access to electricity. Hence, versatile industrialization via renewable and greener alternative energy sources can be reached. The employed measures herein, extend past industries and research institutes to involve cultural, institutional, economic and political players of key positions in innovative process. Firstly, a conceptual idea of "learning" was conveyed as vital to IBEV, seeing innovation and production as pertinent and dynamic. On a second note, the work featured instances of trials to create renewable energy industries around the continent. Lastly, the possible transformation of research outlets such as the African Network for Solar Energy (ANSOLE) into inventions was highlighted, emphasizing how innovations might be born from inventions. A vital policy suggestion was that divisions of African "innovative force" such as a technological head like South Africa can for example; engage more with member countries involved in production or assembly while creating beneficial agreements with them. Thus, with mixed innovation schemes, more effective knowledge transfer can be groomed across the continent.
... LBD relates to cost reductions achieved due to experience gained during the production process, such as improvements in management and labour knowledge acquired [3]. LBU relates to improvements due to feedback received by users during operational activities [37]. LBI is related to cost reductions achieved due to knowledge exchange through interaction with other actors along the technology value chain such as through benchmarking between industries and research centres (LBI(ind)). ...
... Knowledge can be shared between academic stakeholders and private partners through events, conferences, and joint research projects. Unpublished knowledge can be disseminated, and universities work as knowledge providers for emergent technology developers to improve technology features and bridge the gap towards technology standardization [22,37,56]. Technology spin-offs can arise between different R&D programs leading to the emergence of new advanced technologies [40]. ...
... During this stage some industry players will be crowded out of the market due to the competition between different firms and technology designs [57]. Experience gained in manufacturing leads to improvements in production, operation and management, namely learning by-doing [3,22,36,37,73]. Niche market customers can provide feedback on operational issues to researchers and entrepreneurial producers, namely through learning by-using, usually pushing to improve technology features, and to implement innovation in the production process which will reduce the business-risk for future diffusion [74]. ...
Energy technology cost reductions are the result of many innovation trends in the energy system. The energy technology innovation system is increasingly well understood at an aggregate level and using qualitative concepts. However, the quantification of the multiple drivers of energy technology cost reduction trends remains poorly understood. This paper addresses this knowledge gap by presenting a systematic review of current practices. Despite their simplifications, one-factor learning curves (i.e. using a single driver) remain the most popular method for quantitative modelling of energy technology innovation. The role of multiple drivers on cost reductions has been cited in previous studies. This review enriches our understanding of these multiple drivers by examining their impact along different stages of technology development. The review quantifies the variation in these drivers and shows that the development of multi-factor learning curve models and bottom-up cost models are still in their infancy. With a focus on onshore wind and solar PV technologies, the review finds that most of the published multi-factor learning curve analyses are focused on addressing the impact of drivers related to i) manufacturing process improvements (i.e. learning by-doing) and ii) technology feature improvements (i.e. learning by-researching). This means that the other learning drivers such as market dynamics and learning by-interacting across different stakeholders and geographical areas are still poorly quantified, despite their impact on cost reduction being recognised in the innovation literature. There is a danger that misinformed policies are currently being developed in the absence of a good understanding of these multiple drivers.
... The program enabled Taiwan to develop a policy that further stimulated the country's adoption of this technology. Governmental regulation can function as a framework that sets the boundaries within which organizations need to search for new sustainable energy practices [8]. Not just large and incumbent firms, but also smaller firms need to have access to the demonstration projects that the government uses as a basis for its legislation [48]. ...
... In a sustainable energy demonstration project, there are many situations in which contracts are and remain absent. In these situations, participants have to invest in and develop a basis of mutual trust [8,17,25,53,97,159] and need to rely on an ongoing dialogue about what has been learned [17,25,186], how this is appropriated by each participant in intellectual property and prototyping output, and how this distribution should be agreed upon. For example, Germany's long-term strategy to develop a large national capacity in solar photovoltaics depended heavily on trust relationships between the organizations that collaboratively developed the technologies and prototypes [17]. ...
... For example, Germany's long-term strategy to develop a large national capacity in solar photovoltaics depended heavily on trust relationships between the organizations that collaboratively developed the technologies and prototypes [17]. Sustainable energy technology learning in which trust is the basis is found to be active in various types of sustainable energy demonstration projects, like carbon capture and storage, wind turbines, heat pumps, and solar photovoltaics [8,17,97,159]. This makes the sustainable energy demonstration project an organizational Fig. 4. Learning strategies and facilitating behaviors in sustainable energy demonstration projects. ...
This literature review study presents and discusses the learning strategies of organizations participating in sustainable energy demonstration projects. It finds that academic, commercial, and governmental organizations build on six major learning strategies. The first learning strategy is to capture intellectual property and benefit from knowledge spillovers. The second learning strategy comprises the building of a series of prototypes that are technically and commercially fit for purpose. The third learning strategy aims at operating production plants that produce the prototypes on a large scale. The fourth learning strategy concentrates on exploiting learning curves in these production plants. The fifth learning strategy focuses on creating supply-demand networks that serve increasing markets. Finally, the sixth learning strategy is to develop governmental regulation and funding schemes that support the emergence of an industrial and societal institutional infrastructure for sustainable energy technology, based on the lessons learned from the demonstration projects. This study also finds that the six learning strategies are facilitated by four key behaviors of participants in demonstration projects, which are mutual trust-building, decision-making in favor of sustainable energy technology, learning-network building, and demonstration program development. To academics, this study provides a comprehensive insight into organizations’ learning strategies in sustainable energy demonstration projects, regarding learning directions and outcomes. Its contribution to practice is that it supports academic, commercial, and governmental organizations in managing their portfolio of learning strategies in new sustainable energy demonstration projects.
... From the outset of a pilot project, those implementing the new technology engage with learning-by-searching and learning-by-doing (Kamp, Smits, & Andriesse, 2004). As early adopters, organizations actively search for resources useful for technical implementation. ...
... The development of a robust knowledge sharing network facilitates the diffusion of information on product reliability, performance, sourcing, and operational best practices (Reiner, 2016), including diffusion to actors not participating in the piloting process. By opening knowledge sharing networks to prospective adopters, learning-by-interacting may enable the piloting organizations of a new technology to demonstrate their experiences to a broader set of market participants (Kamp, Smits, & Andriesse, 2004;Von Hippel, 1978;Von Hippel, 1986;Von Hippel, 2010). Policy programs of this nature (i.e., those designed to share the lessons from early investments to facilitate spillovers to other market participants) may be thought of as demonstration projects. ...
... Pilot and demonstration projects create complementary opportunities for increased technology uptake through learning and knowledge transfer. As policy instruments, these projects are often bundled into programs that jointly experiment with an emerging technology as a pilot (Kamp, Smits, & Andriesse, 2004), and seek to generate knowledge spillovers as a demonstration (Bollinger, 2015;Reiner, 2016). For example, solar and wind energy demonstrations often create innovation lessons for participating firms that pilot the technology (Hendry, Harborne, & Brown, 2010). ...
Pilot and demonstration (P&D) projects are commonly deployed to catalyze early adoption of technology but are poorly understood in terms of mechanism and impact. We conceptually distinguish unique functions of pilots and demonstrations, then examine whether they accelerate adoption in the case of green building technology. To identify effects on adoption, we develop a difference‐in‐difference‐in‐differences strategy, exploiting variation in timing, location, and technologies of green building P&Ds. Results indicate local quarterly green building adoption rates double following completion of a P&D project. Further analyses examine mechanisms driving this effect. The results suggest green building demonstration projects create learning externalities, proliferating technology diffusion in local markets and through building owner networks. Together, these results suggest that investments in P&D projects by public and private actors can lower costs for subsequent adoption.
... A cheaper alternative policy approach is the 'science-technology push' strategy, which emphasizes investing in research and development (R&D) to drive innovation, for example through research subsidy programs, specialized institutes and knowledge de- velopment. (Horbach et al., 2012;Kamp et al., 2004;Negro et al., 2012aNegro et al., , 2012b. Countries with this approach assume that market demand follows technology push because R&D lowers the cost of the technology and therefore future demand will pay for the upfront R&D investments (Kavlak et al., 2018;Nemet, 2009). ...
... Countries with this approach assume that market demand follows technology push because R&D lowers the cost of the technology and therefore future demand will pay for the upfront R&D investments (Kavlak et al., 2018;Nemet, 2009). For example, this has been the Dutch approach to the solar sector, leading to internationally competitive firms that produce solar cell machines, but has lagged other countries in new installed solar photovoltaic capacity ( Kamp et al., 2004;Negro et al., 2012aNegro et al., , 2012b. Governments that apply this policy approach wait with commercial home market formation until technologies have gone through the learning curve and become more affordable. ...
... Some argue that the optimal policy strategy is a combination of the science-technology push and market pull for a technology to develop and grow, such as the strategy adopted by Denmark for on-and offshore wind ( Kamp et al., 2004;Nemet, 2009;Wieczorek et al., 2013). In this case, Denmark heavily promoted wind energy as a means to reduce fossil fuel consumption while also strongly supporting the wind industry, leading to the growth of one of the world's largest wind turbine manufacturers, Vestas, and the world's largest offshore wind owner and developer, Ørsted (formerly DONG Energy) (4C Offshore Ltd., 2018c;Wieczorek et al., 2015). ...
This research addresses the challenging question of how to support industry formation policies without relying on expensive domestic market formation strategies. Innovation systems literature classically focuses on the need to support home market development to encourage both technological diffusion and generation of a promising technology. However, it is possible to decouple these notions in a national context under certain conditions. Through in-depth interviews with key stakeholders in the Dutch offshore wind industry, we unearth the conditions for young and established firms to access international markets in the absence of a home market. We determine that established firms can access international markets without significant hinderances or domestic support and can help form the backbone of an emerging industry. Young firms are dependent on a well-functioning innovation system, which facilitates international market access through three pathways: 1) via local incumbents; 2) direct access to international markets; 3) via protected niche-spaces.
... At its core, the literature on innovation systems recognizes that "learning is predominantly an interactive, and therefore, a socially embedded process" (Lundvall, 2010, p. 1), taking place in networks of actors that interact under a particular institutional infrastructure (Binz et al., 2014;Gallagher et al., 2012;Lewis, 2007;Lundvall, 1985). 1 Because of the systemic nature of innovation, the addressal of system failures 2 plays an important role in strengthening key functions of innovation systems (Bergek et al., 2008;Weber and Rohracher, 2012;Negro et al., 2012). In addition, several empirical studies have noted that 'coordination failures' (Aghion et al., 2009), 'network failures' (Keller and Negoita, 2013;Taylor, 2008) or failures in learning-by-interacting (Edquist, 2011) can hinder knowledge development and diffusion in innovation systems (Choi and Anadón, 2014;Garud and Karnøe, 2003;Kamp et al., 2004;Musiolik et al., 2012;Shum and Watanabe, 2008). ...
... 3 In analyses using the TIS framework, the process of knowledge development and diffusion "is normally placed at the heart of a TIS" (Bergek et al., 2008, p. 414). The learning processes that underlie knowledge development and diffusion can be categorized as learning-by-searching, learning-by-producing, learning-by-using, and learning-by-interacting (Kamp et al., 2004;Malerba, 1992;Sagar and van der Zwaan, 2006;Schaeffer et al., 2004). In such analyses, a single technology is the focus of analysis and all actors, networks and institutions contributing to innovation processes (referred to as 'functions' in the TIS literature) pertaining to the technology constitute the TIS. ...
... A. Malhotra, et al. Technological Forecasting & Social Change xxx (xxxx) xxx-xxx learning-by-producing, learning-by-using, and learning-by-interacting (Kamp et al., 2004;Malerba, 1992). Second, the sources of opportunity specify the reliance on certain sources for learning and knowledge development. ...
Innovation is critical for economic growth and addressing societal and environmental problems. Therefore, many policy interventions aim to accelerate and redirect technological change. Most modern technologies have value chains spanning multiple sectors, and thus are likely to require cross-sectoral knowledge spillovers. However, knowledge spillovers between sectors in a technology's value chain have hardly been analyzed. We analyze the role of the sectoral diversity and sectoral distance of knowledge for subsequent knowledge generation within one specific technology. More specifically, we investigate how the sectoral diversity and distance of prior knowledge affect the technological importance, sectoral diversity, and sectoral distance of subsequent knowledge. Our regression analyses of global patent data of lithium-ion batteries show that (1) higher sectoral diversity increases the importance of newly created knowledge, whereas higher sectoral distance does not significantly increase the importance of newly created knowledge; (2) both higher sectoral diversity and distance of prior knowledge increase the sectoral diversity of subsequent knowledge; and (3) higher sectoral distance of prior knowledge increases the sectoral distance of subsequent knowledge, whereas higher sectoral diversity of prior knowledge does not significantly increase the distance of subsequent knowledge. We discuss our findings and derive implications for research, R&D managers and policymakers.
... Instead, it is imperative to also consider the array of other market failures at play. Understanding the complexities 5 The improvements of wind energy and the Danish case are a paradigmatic example of this, where learning by interacting was the most important learning process for wind turbine development (73) and breadth of the energy transition is crucial for developing a robust rationale for policy intervention. This entails recognizing the multifaceted challenges and barriers inherent in the transition to a low-carbon economy, necessitating comprehensive and targeted policy measures beyond simplistic market-based solutions. ...
... In this sense it needs to be adapted by the system integrators and installers based on sitespecific factors ranging from load profiles, national standards for grid connectivity and islanding, building norms, practices, and regulations (126), characterizing this technology as a masscustomized product -rather than mass-produced-, and falling inside the type 2. Continuing into type 2 technologies, but with a higher degree of complexity, we can now put our attention on wind turbines. For this technology, categorized as of the relatively same need for customization as rooftop solar PV given standardized platforms -designed for a certain wind class-and context-specific customized components -as blades or grid connection subsystems- (128), the increase in design complexity is given by the high number (up to 15.000-20.000) of many interdependent components (59), with an increase in electric capacity that has reached up to 5 MW, being the design of the rotor -which increased in size from initially 10 mm to currently more than 150 mm-, the mechanical drivetrain, the electrical generator, and the structural elements carried out by a limited amount of specialized original equipment manufacturers OEMs (as Vestas Wind Systems, Siemens Gamesa Renewable Energy, GE Renewable Energy, Goldwind, and Envision Energy) in close collaboration with the component suppliers (83) (64), requiring the product design high levels of specialized engineering skills and knowledge derived from time-consuming learning by doing and using processes (73), where wind turbines must be designed for very specific physical conditions. Nevertheless, compared to the intensity of the design process, the manufacturing process capabilities -as well as for technologies such as concentrating solar power-are of relatively lower level (123). ...
In order to achieve climate goals, the world must reach net-zero carbon emissions around mid-century, which calls for an urgent energy transition and the acceleration of low-carbon innovation. To this end, I begin by extracting insights from past transitions, exploring the factors influencing transition speed, and highlighting specificities within energy systems. Additionally, I present barriers hindering low-carbon innovation, including the concept of carbon lock-in, path dependency, and the different market failures and externalities associated with the present energy transition. I emphasize the benefits of framing these challenges within the lens of the transitions framework. Next, I delve into innovation theory and technological innovation systems, stressing the significance of understanding the evolution of technologies and knowledge for effective energy innovation policy formulation. I underscore the importance of coordination, inter-sectoral learning, and socio-political factors in technology design and selection. Furthermore, I introduce Wright´s law and the concept of learning rates for measuring innovation and technological competitiveness, presenting corresponding data for different low-carbon energy technologies. Finally, I review academic literature to explain the diverse learning patterns observed in low-carbon technologies. This examination underscores the importance of projecting technologies' competitiveness for the design of technology-specific energy innovation policies, given diverse technology-inherent characteristics.
... In some cases, learning turns universities into spin-o®¯rms and leads to the°ow of knowledge from universities to industry. For instance, research cooperation between universities and¯rms has been one of the reasons behind the success of wind turbine development in Denmark [Kamp et al. (2004)]. Research collaborations with universities have also been considered as a direct mechanism for attracting a skilled workforce [Dantas and Bell (2011)]. ...
... Kamp et al. (2004);Hansen and Ockwell (2014); Lema et al.(2015); Wandera et al. Suurs et al. (2009); Figueiredo and Cohen (2019); Dantas and Bell (2011); Lema et al. (2021)] C 23 Learning by purchase of turnkey plants [Hansen and Lema (2019); Hansen and Ockwell (2014); Lema et al. (2015)] C 24 Learning by strategic alliances with inter-¯rm [Suurs et al. (2009)Kamp et al. (2004); Bell and Figueiredo (2012); Dantas and Bell (2011); Lema et al. ...
In developing countries, firms usually have limited capital, infrastructure, and institutions for technological learning. Hence, knowledge of firms about external and internal learning mechanisms as well as using other firm’s experiences lead to reduced cost and time of technological learning. Present paper contributes to renewable energy firm’s knowledge by analyzing cause and effect relationships of internal and external technological learning mechanisms. For this purpose, internal and external technological learning mechanisms were extracted by literature review. Then, cause and effect relationships of learning mechanisms in Iranian renewable energy firms were investigated by the DEMATEL method. The results indicate that firms should use a combination of internal and external learning mechanisms to enhance their technological capability. Moreover, intramural research and development, trial and error, reverse engineering of competitor’s products, imitation of competitors, and licensing agreement have been the most frequent technological learning mechanisms used by Iranian renewable energy firms. These are the issues that need to be addressed by renewable energy firms and policymakers in developing countries.
... Labour cost component should decrease with the increase of experience in a manufacture, as workers increase their competences and a more efficient lean production and management regime develop (Gustafsson et al., 2016;Linda et al., 2004). Labour costs are also driven by salary price variation (Eq. ...
... Moving to bigger size of turbines requires an investigation into innovative solutions to avoid the increase of delivery costs with device scale. In a long-term view delivery costs vary mainly with company scale and management experience, by the time full commercialization is reached manufacturers tend to move to developing countries to reduce their own costs of production or to delocalize into new demand markets (Linda et al., 2004). Fig. 5 shows that in 2005 Vestas production was mostly concentrated in Europe, during 2008-2017 the wind market expanded globally and in the Americas the capacity delivered almost reached the size of the European market. ...
Wind energy technologies have seen a rapid decline in costs in the last two decades, but the drivers for these cost reductions are poorly understood. This paper addresses this knowledge gap by quantitatively investigating the drivers behind the cost reductions of onshore wind turbines between 2005 and 2017. Starting from a bottom-up cost model, the paper advances the methodology by identifying the techno-economic variables responsible for cost reductions of individual components (in $/kW) and linking them to drivers, specifically: learning by-deployment, learning-by-researching, supply-chain dynamics, and market dynamics. The analysis finds that changes in materials (copper, fiberglass, and iron), labour (employee productivity), legal and financial costs contributed over 30% to the cost reduction of wind turbine prices over the period 2005–2017. Moreover, learning-by-deployment was the most important innovation driver, being responsible for half of the cost reduction. The findings point to the importance of policies tailored to technology's stage of development. For onshore wind energy, which entered a mature phase in the period covered by this analysis, policy support for the needs of a growing industry such as stable support schemes together with appropriate regulatory and investment environments were more important than direct policy support for R&D which played a more important role in earlier periods.
... which emphasizes the importance of R&D to the success of an innovation system [57]. ...
... The learning methods outlined by Kamp et al.[57], are evident in Malaysian academia signifying the development of knowledge development function. The study reveals that numerous research groups are actively engaged in biomass energy technologies for power generation. ...
Malaysia generates significant quantities of Oil Palm Wastes (OPW) which can be potentially valorised into sustainable bioenergy as envisaged by the National Biomass Strategy (NBS-2020). Despite significant investments, policy directives and government support, the valorisation of OPW into bioenergy has remained low exacerbating waste management challenges. Therefore, the strategies and impediments to the rapid bioenergy development and bioelectricity generation from OPW require practical assessment. Therefore, this paper examines the level of development and diffusion of the biomass innovation system in Malaysia based on the Functions of Innovations Systems (FIS) approach developed by Dutch and Swedish researchers. Furthermore, the key factors hindering biomass energy technologies implementation in Malaysia and potential solutions were identified, highlighted and examined. Based on the FIS analysis the functions; entrepreneurial activities, knowledge development, and resources mobilization functions are well established in the Malaysian biomass innovation system (BIS). However, the functions of guidance of search; creation of legitimacy; knowledge diffusion and market formation are underdeveloped resulting in the low penetration of bioenergy in Malaysia. Other factors include; fossil fuel subsidies, numerous or conflicting energy policies and weak collaboration between academia and the industry. The outlined challenges can be addressed by revising fuel subsidies, Feed-in tariffs, RETs implementation, roles of supervisory agencies, and bureaucratic procedures for access to funds for research and development of bioenergy in Malaysia.
... Les panneaux solaires photovoltaïques Dès la fin des années 90, notamment dans le contexte de l'adoption, avec le Protocole de Kyoto (1997), d'objectifs de réduction des émissions de gaz à effet de serre dans les pays industrialisés, des politiques de soutien aux énergies renouvelables ont été mises en oeuvre dans un certain nombre de pays (européens notamment) pour permettre l'atteinte des objectifs de pénétration des énergies renouvelables dans les mix énergétiques. Ces politiques ont à la fois visé la diffusion de ces technologies renouvelables, ce qui a conduit à des effets d'apprentissage ou learning by doing [115], et le soutien à la recherche, ce qui a conduit à de l'innovation dans ces technologies et donc à une décroissance des coûts (learning by searching) [116,117]. La littérature montre ainsi que le taux d'apprentissage moyen pour le photovoltaïque est de 20% [118], c'est-à-dire que le coût du panneau solaire PV diminue de 20% quand la capacité mondiale de production est doublée. Durant la dernière décennie, la Chine a profondément modifié le marché mondial du photovoltaïque, devenant le pays avec la plus forte production d'électricité photovoltaïque et le premier producteur mondial de panneaux solaires. ...
... The 113 present work puts this rule in perspective for the design of MGs. In particular we investigate how a 114 different tilt angle could be beneficial for a specific case, in which the prime objective is not to 115 maximize annual production but to achieve a given QSL and thus maximize day-to-day adequacy 116 between supply and demand. So we also investigate how the tilt angle of solar PV panels can modify 117 the temporal variability and seasonality of local solar production and the QSL for a given PV array size. ...
La réalisation commune de l'objectif du développement durable n°7 des Nations Unies visant à l'accès à une énergie propre et fiable pour tous d'ici 2030 et aux objectifs climatiques de l'accord de Paris nécessite le développement de micro-réseaux (MG), alimentés par des ressources énergétiques renouvelables locales, pour les zones isolées qui ne peuvent pas être connectées au réseau. C'est particulièrement le cas en Afrique subsaharienne où 600 millions de personnes, principalement dans les zones rurales reculées, n'ont pas accès à l'électricité. Cette thèse se concentre sur l'analyse des MG solaires non connectés au réseau (MGSI) pour répondre aux enjeux de la production d'électricité dans les zones isolées du continent africain. La faisabilité technico-économique propre à ces MG repose sur une forte adéquation temporelle entre la ressource solaire et la demande tout en limitant le coût de l'électricité fournie aux consommateurs.Nous explorons d'abord la variabilité temporelle multi-échelle de la ressource solaire en Afrique et son implication sur le dimensionnement des MGSI, en utilisant des données satellitaires à haute résolution de l'irradiance horizontale globale pour une période de 21 ans (1995-2015). La prise en compte des périodes de faibles ressources conduit à surdimensionner la surface photovoltaïque (PV) d'un facteur 1,3 à 4. Avec un tel surdimensionnement, il est possible d'assurer une bonne qualité de service sans dépendre d'un volume de stockage important. Pour certaines zones, une flexibilité de la demande pendant les périodes de faibles ressources permettrait de réduire significativement le dimensionnement.Nous analysons ensuite comment la saisonnalité potentielle de la demande électrique affecte la taille des MGSI, à travers l'analyse de la structure de co-variabilité entre la ressource solaire et la demande. Nous considérons que le MG doit répondre à une demande quotidienne totale d'au moins 95% des jours et à une variation saisonnière de la demande pouvant aller jusqu'à 30%. Alors que dans certaines régions d'Afrique, la taille requise pour répondre à la demande saisonnière est inférieure de 20% à ce qui est nécessaire pour répondre à la demande non saisonnière, elle peut également être supérieure de 20%. Nous explorons également dans quelle mesure l'effet de l'angle d'inclinaison des panneaux PV pourrait réduire l'inadéquation offre-demande et le dimensionnement. Généralement, l'angle d'inclinaison est égal à la latitude. Pour une demande quotidienne constante, le gain de taille obtenu en optimisant l'angle d'inclinaison est inférieur à 4%, mais pour des schémas de demande saisonniers spécifiques, il peut atteindre 9%.Enfin, le coût de l'électricité nécessaire pour assurer une bonne qualité de service est un facteur déterminant du déploiement potentiel des MGSI. Nous évaluons la sensibilité du coût actualisé de l'électricité (LCOE) et de la configuration optimale MG (c'est-à-dire avec le LCOE le plus bas) aux coûts des panneaux PV, des batteries et à d'autres paramètres économiques. Si la sensibilité du LCOE aux coûts actualisés est évidemment importante, la configuration optimale (surface des panneaux PV et capacité de stockage) est très robuste. La configuration optimale est presque uniquement déterminée par la structure de co-variabilité temporelle entre la ressource et la demande. Elle est donc dépendante d'une part du climat régional, et d'autre part de la structure temporelle de la demande. La variable d'ajustement est essentiellement le surdimensionnement des panneaux PV, qui est basé sur les faibles jours de ressource solaire tandis que le stockage a pour fonction principale de gérer l'inadéquation entre demande et ressource au niveau infra-journalier. Un résultat intéressant est que le LCOE est plus faible pour des utilisations productives de l’électricité comparé aux utilisations domestiques uniquement du fait de la capacité de stockage inférieure requise pour les utilisations productives.
... In addition, municipalities can make own specific efforts to promote R&D activities with focus on renewable energy. Examples for such efforts are the search for potential renewable energy project investors or the creation of supportive economic and legal conditions for entrepreneurship in the renewable energy sector (Bergek et al., 2008;Kalkbrenner and Roosen, 2016;Kamp et al., 2004). One example for this kind of positive approach is the Danish government technological innovation program for the support of wind power generation development (Jorgensen, 2005). ...
... Moreover, our results demonstrate that municipalities not only have to concentrate their effort on the development of new knowledge, but also on the efficient exploitation of the knowledge from previous projects. This double effort is necessary for building long-term knowledge-base for renewable energy projects and generation (Kamp et al., 2004;Verbong and Geels, 2007;Smit et al., 2007). ...
Renewable energy systems (RES) are becoming a strong component of local sustainable innovation strategies. Using a policy mix perspective, this paper investigates innovation policy criteria from municipalities’ locational factors, cooperation activities among stakeholders, and local knowledge about RES as antecedents to see how they leverage the development of local RES. We studied these antecedents at a local level by analyzing a sample of 727 middle and large German municipalities using instrumental variables regression. Our results indicate that policymakers should focus on building local knowledge related to RES for local actors and with enhancing public-private cooperation activities. However, we did not find that locational factors such as direct incentives and energy and emissions reductions have a direct impact on RES. We suggest that these locational factors can provide indirect support for RES, as a starting point for the implementation of other policy criteria which we investigated in our study. Our findings also indicate greater RES development potential when policymakers adopt a facilitator role and support local innovation networks among different actors rather than keeping RES development activities within the municipality itself. In such an innovation network, stakeholders from non-municipality public and private institutions offer additional support to develop a local RES.
... The transition studies literature points towards the importance of a technological learning process characterized by different forms of learning that go beyond the R&D-driven learningby-search mechanism found in the breakthrough innovation mode. This involves learning-by-doing, a trial-and-error practice of dealing with the technology, learning-by-using and providing subsequent feedback to technology developers, as well as learning-by-interacting, for example through interactions between producers and consumers (Kamp et al., 2004;van Poeck et al., 2020). This broader mix of learning types characterizes the bricolage innovation mode, as described by Garud and Karnøe (2003), and reflects our observations for the emergent-actor subsystem in HPA: the emergent manufacturers focus on a trial-and-error practice of technology development with an earlier initiation of learning-by-using and learning-by-interacting learning curves through the use of earlier entry-intoservice dates. ...
... Wind turbines are the most glaring incoherence in this study. The Dutch have tried and failed to create a wind turbine manufacturing industry for decades (Agterbosch, Vermeulen, and Glasbergen 2004;Eecen 2011;Kamp, Smits, and Andriesse 2004). Companies such as Lagerwey or Darwind either went bankrupt multiple times and/or were acquired by foreign turbine manufacturers (Kamp 2002). ...
... (2022) høyde for at det å skape nye markeder for ulike transporttjenester nasjonalt også kan bidra til å gi forretningsmuligheter til eksisterende nasjonale teknologileverandører og andre bedrifter, gjøre at nye bedrifter starter, og bidra til å skape nye teknologiske innovasjonssystemer. For eksempel var sannsynligvis Danmarks satsning på vindkraft viktig for at leverandører som Vestas, som er en av verdens største produsenter av vindturbiner, fikk et hjemmemarked å etablere seg i (Kamp et al. 2004). Studien til Grünfeld m.fl. ...
In this report, we investigate the potential societal effects of a battery-electric pilot public service obligation (PSO) route between the two Norwegian cities Førde and Bergen, and what is needed to establish this route. Such a route will yield significant regional political benefits, in particular better cooperation across Western Norway, including faster transport of health sector employees and patients in the region. The passenger base is primarily people on business trips. Prerequisites for success are that the route facilitates daily commuting, offers sufficient departures and that the tickets are reasonably priced. Widerøe wants such a route to be part of a route network. The project’s most important effect in a climate context, is its contribution to phasing in battery-electric aircraft nationally and internationally. In addition, such introduction will contribute to reducing local pollution. To establish such a PSO route, the following is needed: certified electric aircraft, pilots, aircraft engineers and systems around the aircraft, that airlines can achieve commercial operation of them, and that the route receives support for establishment and operation. Different types of state support is therefore essential.
... However, to achieve this, CECs must not only cultivate new knowledge of energy use (and ways of reducing carbon footprint) but also be effective in circulating information about energy among their members and outside their communities (Catney et al., 2013). Thus, the acquisition of knowledge and skills is considered crucial (Kamp et al., 2004). Yet empirical evidence in the literature about the role of learning and knowledge in energy transitions in general and CECs' knowledge circulation and learning in particular is rare (Van Poeck & Ö stman, 2021). ...
Clean energy communities (CEC) represent emerging socio-technical systems that offer a suitable alternative to non-sustainable energy production and consumption. Thus, CECs cultivate new knowledge of clean energy use and diffuse it among their members as well as interested publics outside the CECs. This paper aims to contribute to the rather limited literature on the role of learning and knowledge in energy transitions in general and CECs’ knowledge circulation and learning in particular. The paper presents findings about the knowledge development and
learning settings within CECs that provide the ways of cultivating knowledge within CECs and ways of disseminating this knowledge outside the CECs for potentially influencing wider social change. This research contributes to the energy transition literature by focusing on the overlooked perspective of learning and knowledge dissemination as an important part of a niche innovation setting.
... Nevertheless, specialized university cities in more remote regions may also play substantial roles, specifically if they are nearby places of abundant availability of renewable energy resources [33]. Further, being part of a specific country's knowledge economy and institutional system (National Innovation System, NIS) can make a difference between cities in responding to transition challenges, like through national energy research programs, subsidies and tax regimes, and a culture of strong entrepreneurial spirit [34][35][36][37]. ...
This paper pictures several risk-taking strategies of young high-tech firms in bringing energy inventions to market and ways urban policy (municipalities) may provide supporting facilities and help accelerate the energy transition. Derived from a longitudinal study of 100 firms in northwest Europe, two findings contribute to practice. Firstly , a share of almost 40 percent of university spin-off firms fails in the market introduction; if the market introduction is reached, 30 percent is relatively late. This development calls for attention to acceleration and risk-taking concerns. However, risk-taking firm strategies, like targeting radical inventions and new markets, tend to hamper early market introduction. Secondly, urban policy supports filling risk-related needs, particularly in large metropolitan networks. Cities (municipalities) may act as launching customers and provide sites and organizations for practical experimentation (e.g., in living labs) alongside steering on cross-faculty application platforms at the university that also connect with city functions. Cities’ initiatives, however, tend to be fragmented and miss priority. Partnering in Triple Helix networks with local universities and businesses may improve the situation, for example, by priority setting, better alignment, and integration. The urban policy also has a role in improving broader conditions, particularly the attraction of related R&D firms to the city/region and the attraction and retention of top-class researchers.
... The Danish Research Institute has been the main reason for Denmark's success in the innovation system for learning through the interaction between turbine users and turbine producers. The innovation system for education is very important for the success of the scientific and practical innovation process, as innovation is the quality and activity of the network [12]. Several teaching aids, cameral packages , and platforms were created for wind energy systems. ...
... En incitant les acteurs à s'investir dans de nouvelles thématiques et nouvelles technologies de l'énergie, la Région Alsace a réussi le pari de s'imposer dans ce secteur. Si l'on suit les conditions facilitant l'apprentissage par interaction identifiées par Kamp (2002Kamp ( , 2004, le cluster Energivie opère bien en cohérence avec ses ambitions : (condition 1) dans un contexte de proximité au sens large (proximité géographique, culturelle, de langue, de codes de conduite, de confiance mutuelle à l'égard de la technologie…), les personnes adhérant au cluster sont rassemblées pour construire et s'accorder autour d'un intérêt mutuel pour le processus d'apprentissage (condition 2) avec des normes d'ouverture et de divulgation établies (condition 3). Enfin, l'animateur du cluster fait office d'intermédiaire (condition 4) si l'information n'est pas transmise facilement ou si tous les acteurs n'interagissent pas simultanément. ...
... However, to achieve this, CECs must not only cultivate new knowledge of energy use (and ways of reducing carbon footprint) but also be effective in circulating information about energy among their members and outside their communities (Catney et al., 2013). Thus, the acquisition of knowledge and skills is considered crucial (Kamp et al., 2004). Yet empirical evidence in the literature about the role of learning and knowledge in energy transitions in general and CECs' knowledge circulation and learning in particular is rare (Van Poeck & Ö stman, 2021). ...
... An important implication from Stadelmann and Castro is that developing countries are taking cues from developed countries in terms of policy development and TIS's. Further, their results show that empirical models for developing countries and climate technologies should incorporate domestic environmental regulatory stringency as well as learning-by-interacting and collaboration (Kamp et al., 2004). Hence, these TIS related factors are carefully incorporated into the empirical models below. ...
While the Global North is historically responsible for the majority of greenhouse gas emissions in the atmosphere, Newly Industrializing Countries (NICs) are expected to overtake developed country emissions in the coming years. At the same time, NICs are climbing the ladder of the global economy, increasing their competitiveness on the global stage and catching up with technological competencies of developed economies. Against this background, this paper explores innovation and collaboration in Climate Change Mitigation Technologies (CCMTs) in NICs. The research question is whether the propensity to innovate and diffuse CCMTs is impacted by technological collaboration with two highly developed countries, Germany and The United States. The sample of NICs includes the BRICS (Brazil, Russia, India, China, South Africa) plus Israel, Mexico, and Turkey, in a panel from 1995 to 2015. The empirical results suggest that collaboration with both Germany and the U.S. is highly significant for domestic CCMT innovation in NICs. These findings are important because, stepping beyond the literature on the merits and drawbacks of global climate governance tools such as the Clean Development Mechanism (CDM) and related UNFCCC processes, they show that collaboration for climate and environmental technologies could become a key tool to significantly improve the chances to stay in line with the Paris Climate Agreement. Finally, the policy advice for NICs and developing countries is to, above all else, focus on incubating strong technological innovation systems, including strengthening domestic Intellectual Property Rights (IPR), as well as to enhance technological collaboration with developed countries.
... In this respect, the energy technology innovation system, identifies three core, but interlinked features, namely: (1) knowledge and learning; (2) economies of scale, which include standardization and cost reduction; and (3) actors and institutions, which include energy entrepreneurs, energy policies and advocacy coalitions for various types of energy (Gallagher et al., 2012). However, more granular learning (or technological capability building) processes have been comparatively applied to the wind turbine industries in Denmark and Holland (Kamp et al. (2004). These countries emphasized learning by searching (based on subsidies for R&D), learning by doing (manufacturing know-how of turbines), learning by using (user-based learning initially driven by subsidies), and learning by interacting (based on user-producer relations, grassroots entrepreneurs, as well as with the research establishment). ...
Notwithstanding the high levels of renewable energy resources across Sub-Saharan Africa (SSA), modern energy use based on these abundant natural resources remains negligible. Furthermore, the current electrification rates and reliability of available power supply in the region have consistently remained significantly lower than the global average over the last three decades. And of the reasons advanced for this state of affairs, the lack of appropriate financing is said to be a crucial one. Therefore, focusing on a comparative overview of the dominant approaches to financing electrification, we characterize the persistence of this regional gap as a reflection of relative “policy stasis.” We then problematize this condition of stasis by employing the theoretical perspectives of mission-oriented finance in conjunction with those of innovative finance and renewable energy innovation. In addition, we review relevant peer-reviewed articles over the same period, and find evidence that indicates an underappreciation of financing models that stimulate endogenous technological innovation in renewable energy in SSA. Our analysis suggests that the types of innovation, associated configurations of financial actors, levels of capital intensity, and perceived risks in relation to beneficiaries, diverge from those accounted for in the dominant financing models. Consequently, we propose a novel, historically path-dependent conceptual framework that emerges from the intersection among the concepts of mission-oriented finance, endogenous innovation, and innovative financing, which we term “endogenous innovative financing.” This framework ultimately guides our recommendations for more promising financing mechanisms for resolving the interwoven challenges of sustainable universal electrification and renewable energy innovation in SSA.
This article is categorized under:
• Energy Research & Innovation > Economics and Policy
• Energy and Development > Economics and Policy
• Energy and Climate > Economics and Policy
Abstract
Endogenous Innovative Financing of Renewable Energy Technologies
... We use data on spin-off firms (a total of 106) in northwest Europe, established since 1998 [19]. The choice of countries-Denmark, Finland and Sweden-is motivated by favorable small firm and innovation conditions that allowed us to observe market introduction and longer term surviving of young technology firms, while Norway and The Netherlands are included as these have faced some less favorable conditions in (some) past years [28][29][30]. In The Netherlands, for example, the large consumption of natural gas acts as a country-specific barrier to experimentation. ...
Municipalities are increasingly involved in energy transition planning. There are, however, doubts about whether municipalities are an adequate organization and scale level for this. In this context, the article aims to picture developments of local young technology firms in bringing energy inventions to market, in particular, how municipalities have provided support to them. Such aim, in the context of energy transition, is new. Derived from study in Nordic countries and The Netherlands, two findings make a valuable contribution to literature. Firstly, a share of almost 40% of young technology firms fails in market introduction, and if reached the market, a 30% is rather late. Barriers stem from high risk-taking, late (no) collaboration, and limiting circumstances in metropolitan cities. Secondly, municipalities’ initiatives appear useful in filling young technology firms’ needs, but the initiatives are fragmented and miss priority. However, partnering in professional start-up organizations tends to improve the situation, indicating that the municipal level is promising in transitional change with regard to new technology. In contrast, driving energy transition through regional cluster building, includes different levels of functional interdependence, territorial scale, networking and governance, causing manifold complexity and uncertainty. Not all (large) municipalities seem able to act in a promising manner, however, much empirical research needs to be done.
... Qualitative and mixed-method studies describe a wide range of other instruments that were reported to have positively influenced innovation activities by firms, or outcomes of such activities. These include tax incentives for production or investment (Kamp et al 2004, Nemet 2009b, Fevolden and Klitkou 2017; eco-labelling (Ruby 2015, Borghesi et al 2015b; public procurement (Fevolden and Klitkou 2017) and programmes providing tax exemptions in exchange for engagement in a set of eco-innovation related activities (e.g. Scordato et al 2018). ...
We conduct a systematic and interdisciplinary review of empirical literature assessing evidence on induced innovation in energy and related technologies. We explore links between demand-drivers (both market-wide and targeted); indicators of innovation (principally, patents); and outcomes (cost reduction, efficiency, and multi-sector/macro consequences). We build on existing reviews in different fields and assess over 200 papers containing original data analysis.
Papers linking drivers to patents, and indicators of cumulative capacity to cost reductions (experience curves), dominate the literature. The former does not directly link patents to outcomes; the latter does not directly test for the causal impact of on cost reductions). Diverse other literatures provide additional evidence concerning the links between deployment, innovation activities, and outcomes.
We derive three main conclusions. (1) Demand-pull forces enhance patenting; econometric studies find positive impacts in industry, electricity and transport sectors in all but a few specific cases. This applies to all drivers - general energy prices, carbon prices, and targeted interventions that build markets. (2) Technology costs decline with cumulative investment for almost every technology studied across all time periods, when controlled for other factors. Numerous lines of evidence point to dominant causality from at-scale deployment (prior to self-sustaining diffusion) to cost reduction in this relationship. (3) Overall Innovation is cumulative, multi-faceted, and self-reinforcing in its direction (path-dependent). We conclude with brief observations on implications for modeling and policy.
In interpreting these results, we suggest distinguishing the economics of active deployment, from more passive diffusion processes, and draw the following implications. There is a role for policy diversity and experimentation, with evaluation of potential gains from innovation in the broadest sense. Consequently, endogenising innovation in large-scale models is important for deriving policy-relevant conclusions. Finally, seeking to relate quantitative economic evaluation to the qualitative socio-technical transitions literatures could be a fruitful area for future research.
... 6 -In our learning feedback diagram, learning effect represents the effect a combination of economies of scale (the more we produce a technology, the more affordable and attractive that technology becomes) and accumulation of innovation (the more we know about a technology, the more affordable and attractive that technology becomes). Different learning types can be investigated in this case study [119]. ...
In the Paris Agreement, many nations set ambitious global goals to stabilize and reduce carbon emissions to mitigate climate change. A large share of these emissions is caused by electricity production. Scientists have been debating the viability of using natural gas as a transition fuel while renewable energies mature technologically and economically. Although natural gas might help the energy transition by reducing emissions compared to coal, there are other long-term implications of investing in natural gas which can work against reaching climate goals. One concern is that investments in natural gas might crowd out investments in renewable alternatives.
This research reviews the literature on the role of natural gas in reducing carbon emissions to mitigate climate change and to bridge between coal and renewable technologies. We advance the debate by laying out how various positive and negative effects of natural gas interrelate. Our research warns that natural gas’ negative delayed and global effects can easily outweigh the positive immediate and local effects unless precautions are taken.
Existing studies agree that natural gas helps avoid greenhouse gas emissions in the short term, while unintended long term effects might also hinder the transition into renewables. Our review helps to inform the policy-making process by reviewing the systemic effects of using natural gas as a transition fuel and suggests policy actions to avoid the negative long term consequences.
... The current offshore wind turbine dominant design is a threebladed, upwind, horizontal-axis, direct-drive turbine, reaching a power capacity of 8.5-12 MW and projections for even higher capacities [29,[42][43][44], indicating that the unit capacity frontier has not yet been reached [10,42,[46][47][48]. Onshore wind turbines went through a heavy product innovation phase in the 1970s-1980s, allowing for the quick marinization of existing technology [10,29,[49][50][51][52]. Therefore, demonstration farms in the 1990s simply used onshore turbines. ...
A new era of transformative and mission-oriented innovation policy has arisen due to the urgency of grand societal challenges, such as climate change. This new era requires a massive restructuring of societies, industries and consumption and will depend on, in part, new technologies and a high degree of coordination between the industry, civil society and government. These new forms of innovation policy may seriously alter classic innovation dynamics. This is indeed the case in offshore wind, in which a specific institutional architecture has led to a rapidly formed dominant design that emerged early in the technology’s development. Radical experimentation, normally expected at the beginning of technological development, only began to emerge after 20 years of diffusion. This trend reverses classic innovation pathways. This paper empirically demonstrates this reversed innovation trend and then proposes a new innovation dynamic founded in a new era of grand societal challenges. It then proceeds to illustrate how The Netherlands has promoted and embedded a rapidly formed dominant design through an analysis of its offshore wind innovation system based on 31 interviews. It concludes that well-positioned incumbents and a specific innovation system architecture have created this trend, a notion applicable to a broader socio-technical system context. A rapidly formed dominant design and quick diffusion are critical to ensuring countries meet their climate pledges, but may risk early lock-in if there is no room for experimentation. We propose that governments ensure sufficient attention to variety and experimentation in innovation systems while maintaining a focus on rapid diffusion.
... Often, when new innovative and high-tech sustainable technologies are developed, multiple technological options are developed simultaneously by competing (groups of) firms. For example, when the first wind turbines were being developed, both horizontal-axis wind turbines and vertical-axis wind turbines were being developed for about a decade until the horizontal-axis wind turbine became the dominant design (Gipe, 1991;Kamp et al., 2004). Such a process in which more than one option are being developed and ultimately one of them wins is called a 'technology battle', a 'battle for a dominant design' or 'market-based standardization' (Muto, 2017). ...
This paper studies the battle between two types of wind turbines, the gearbox wind turbine and the direct drive wind turbine. Applicable determinants that affect technological dominance for the wind turbine drive trains case are identified. By applying the Best-Worst Method, the relative importance to the determinants to understand which of the two wind turbine drive train types has the highest chance of achieving success are allocated. The results show that energy cost and reliability are the most important determinants, and that at this moment both drive train types still have the potential to become dominant. A contribution is made to the literature on dominant designs by focusing on the energy sector; a sector that has only scarcely been studied before with respect to design dominance. Furthermore, weights for factors for the technology dominance for the case of technology battles for wind turbine technology were established.
... In machine learning approach, algorithms have capability to learn continuously and adapt themselves to the varying situations. Researches often resort to machine learning approach for fault diagnosis of mechanical systems [4]." ...
This study makes an attempt of classifying different fault conditions which occurs on wind turbine blade due to environmental stress and high wind speed. Here three bladed horizontal axis variable wind turbine was used for experimental study and different faults like blade crack, hub-blade loose connection, erosion, pitch angle twist and blade bend was considered. This study had been carried out in three phases namely feature extraction, feature selection and feature classification. Initially vibration signals are noted for different blade conditions and required features are obtained using histogram features. Secondly, from the extracted feature, most dominating feature need to be chosen using J48 decision tree classifier. Later, the selected feature is fed into the classifiers like Nested Dichotomy (ND), Class-Balanced Nested Dichotomies (CBND) and Data near Balanced Nested Dichotomy (DNBND) for classification of the faults. These classifiers are compared with respect to their accuracy to suggest a better model for fault diagnosis on blade. The suggested model can be incorporated in real-time system to monitor the condition of wind turbine blade.
... Tacit knowledge is disseminated between people and is less easy to quantify (Von Hippel, 1998). Less formal knowledge can also flow in a process of interactive learning through a wide variety of mechanisms: networks of scientists and engineers, training, interactions and workshops (Kamp et al., 2004;Jacobsson et al., 2017). ...
A systemic perspective on energy innovation is required to design effective portfolios of directed innovation activity. We contribute a standardised set of technology-specific indicators which describe processes throughout the energy technology innovation system, ranging from patents and publications to policy mixes, collaborative activity, and market share. Using these indicators, we then conceptualise and develop benchmark tests for three portfolio design criteria: balance, consistency, and alignment. Portfolio balance refers to the relative emphasis on specific technologies. Portfolio consistency refers to the relative emphasis on related innovation system processes. Portfolio alignment refers to the relative emphasis on innovation system processes for delivering targeted outcomes. We demonstrate the application of these benchmark tests using data for the EU's Strategic Energy Technology (SET) Plan which spans six technology fields. We find the SET Plan portfolio generally performs well particularly in areas over which portfolio managers have direct influence such as RD&D funding. However we also identify potential areas of imbalance, inconsistency, and misalignment which warrant further attention and potential redress by portfolio managers. Overall, we show how energy innovation portfolios can be analysed from a systemic perspective using a replicable, standardised set of measures of diverse innovation system processes.
... The Netherlands launched a large-scale programme for the development of wind turbines in the 1970s. 54 Although these policies were also promoted to enhance renewable energy deployment, local planning for wind farms 55 revealed to be problematic. 56 Specifically, locals tend to view wind farms with hostility due to environmental concerns, especially noise. ...
... These observations are in stark contrast to research undertaken in a European context, which often emphasises the harmonic, consensual and inclusive processes underlying niche development. For example, this was the case in the development of the wind power niche and the biogas niche in Denmark, which was greatly supported by a longstanding democratic tradition of the formation of cooperatives in the agricultural sector and the appertaining willingness to cooperate and share knowledge across niche actors (Kamp et al., 2004;Raven and Gregersen, 2005). ...
An increasing number of studies have analysed the scope for, and the barriers to, transitions toward sustainability in the context of developing countries building on analytical perspectives from the sustainability transitions literature. This paper introduces a special issue on sustainability transitions in developing countries, which takes stock of this emerging field of research and presents new empirical research that contributes to further advancement of our understanding of the conditions in which sustainability transitions are likely to take place in developing countries and what is involved in these transformative processes. This introductory paper presents the five papers contained in the special issue. The first paper comprises a review of the existing literature on the subject, and the other four papers present new empirical research. The key findings of the papers are discussed in relation to previous research in the field specifically related to four crosscutting themes: (i) global-local linkages and external dependencies; (ii) stability and non-stability of regimes; (iii) undemocratic and non-egalitarian nature of regimes; and (iv) nurturing the development of niches versus the execution of individual projects. The introductory paper concludes by presenting a research agenda, which aims to provide promising avenues for future research on sustainability transitions in developing countries.
In response to global warming issues and access to green energy challenges, wind power is seen as a key source of clean energy which contributes to the reduction of greenhouse gas emissions and air pollution. Nowadays, the technological interest in developing larger and more powerful wind turbines has become a major concern for worldwide wind turbine manufacturers.
Wind forecasting is a typical and fundamental problem in efficient operation of wind power generation systems. Despite of the developed brilliant techniques, current methods for wind forecasting still rely heavily on numerical weather prediction. To investigate the huge amount of meteorological data and to improve the forecasting ability, this paper proposes a temporal dynamic graph convolutional network with learnable coupled adjacent matrix (TCNet), which takes observations of multiple meteorological elements as predictors for wind forecasting. Specifically, for better illustrating the inner property of wind components, a learnable coupled adjacent matrix (CAM) module is introduced. A spatially stable adjacent matrix is built to model the low-frequency part while a temporally dynamic adjacent matrix is developed to extract the high-frequency one. Casting on this mechanism, the CAM can be embedded to vanilla graph convolution network. Apart from that, a simple but effective temporal weights allocating strategy, named temporal dynamic (TED) module, is proposed to depict the cyclicity. By integrating TED with CAM, TCNet can effectively extract the spatio-temporal feature of wind speed and its correlation with other meteorological elements. Using observed datasets of meteorological elements in Denmark and Netherland, we conduct experiments to validate the performance and efficiency of our proposed model. The results indicate the proposed TCNet outperforms the state-of-the-art Graph Convolutional Networks methods and wind forecasting methods.
The mechanisms behind energy efficiency improvement of coal-fired power generation in China have not been well investigated. We proposed new concepts of learning-by-manufacturing (LBM) and learning-by-operating (LBO) to explain the reduced coal consumption rate of coal-fired power generation. The former results in lower initial coal consumption rates for newly commissioned electric generating units (EGUs) as manufacturers produce better equipment through knowledge accumulation, and the latter leads to a continuous decline in fuel intensity as power plant operators gain experiences in energy conservation. The learning rates of LBM and LBO are estimated at 1.1–1.8% and 1.7–2.1% for different EGUs, respectively. They contributed 662 million tonnes of standard coal equivalent (tce) of energy conservation and correspondingly 1.87 billion tonnes of CO2 mitigation (36% by LBM and 64% by LBO) during 2000–2017 in China, and can explain 25.8% of the decrease in the national average coal consumption rate.
Learning curve theory has been adopted for investigating the relationship between technological learning and technology cost developments. The aim of this paper is to explore the impacts of public investment in clean energy research, development, and demonstration (RD&D) on future technology cost developments by using a two-factor learning curve approach. Learning-by-deploying and learning-by-researching were chosen as the main sources of learning. The focus is on onshore wind and solar photovoltaics in the United States of America. By using publicly available data, we estimated learning-by-deploying rates of 31.4% and 27.6%; and learning-by-researching rates of 2.3% and 4.7% for onshore wind and solar PV, respectively. By adopting a logistic curve approach, an additional 819 mil. were forecast to be spent by 2050 in RD&D for onshore wind and solar PV, respectively. We explored the plausible long-term effects of diverse RD&D investment scenarios on electricity generation and greenhouse gas (GHG) emissions using a system dynamics model. The findings reveal that public investment in RD&D for clean energy technologies may play a key role in the pace of capital cost reductions and technology diffusion. However, relatively little long-term effects of RD&D efforts alone were found on market dynamics and GHG emissions.
Only a small number of companies, located in a few countries, have specific technological expertise in wind turbine manufacturing. Such technological expertise is found to be a significant driver of trade in wind turbines. In addition, it is found that countries’ wind power generation efficiency depends on having access to higher quality wind turbines available in international markets. Trade in wind turbines can thus be seen as tantamount to trading (wind) technologies that deliver a level of efficiency that cannot be replicated in importing countries. These results have important policy implications: i) Barriers to trade in wind turbines are also barriers to the dissemination of key environmental technologies needed by countries where they have not been developed; ii) Trade-discriminatory measures can also be a hurdle to non-manufacturing job creation as the latter hinges on the continuous deployment of solar energy, which in turn depends on access to international markets where high quality wind turbines are found; iii) Industrial policies should not focus on the creation of national champions but rather on ensuring that domestic firms can apply their specific capabilities to new opportunities in global industries.
Engineering & Technology, Environment and Sustainability, Social Sciences
Design schools around the world often state that they offer instruction on topics such as sustainability, inclusive design, and responsible design. Fifty years ago, design scholar Victor Papanek had already begun teaching industrial designers that they were contributing to consumerism by designing unnecessary gadgets. Papanek urged them to offer more responsible solutions to the real difficulties that people face daily, difficulties that spanned a range of problems from physical challenges to societal ones. His works were not appreciated—at all—by his American industrial designer contemporaries, but still served as powerful inspiration to European design academics whose efforts comprise some of the first PhD work on design. Here I describe Papanek’s writing and inspiration, and note how long it took before influential design academics would seek to educate and inspire others based on his work. I have served as dean at three universities where his legacy lives on in teaching and research. I will reflect on some of the recent activities taking place under Papanek’s influence at these institutions, and offer a personal perspective of these developments, and some reflections on the progress in light of Papanek’s lessons overall.
The uptake of electric vehicles supports decarbonization and increasingly interconnects the electricity and transport system. While the integration of electric vehicles could challenge electricity grids, bidirectional power flows between vehicles and grids could support grid operations. Despite the globally increasing number of Vehicle-to-X trials, including Vehicle-to-Grid and Vehicle-to-Customer, an in-depth understanding of trial implementations and expert experiences has largely been overlooked although they are both crucial for technological development and deployment. Based on our analysis of a global Vehicle-to-X trial database and 47 interviews with experts from industry and academia, we (i) provide an overview of the implementation status of Vehicle-to-X and analyze predominate trial configurations, i.e. combinations of characteristics, (ii) identify important technical, social and regulatory challenges for the implementation of Vehicle-to-X and assess and discuss expert evaluations of these challenges and (iii) derive implications for different actors.
The most predominate trial configurations are Vehicle-to-Customer and transmission-level services provided by commercial fleets that charge at work due to current practical advantages of centralized approaches. From a technical standpoint, we find that although Vehicle-to-X can defer or even mitigate grid reinforcement at the distribution level, this potential is highly dependent on local conditions. Regarding social aspects, incentives and Vehicle-to-X operations need to be tailored to different vehicle users. Concerning regulation, it is imperative to avoid double taxation of electricity, simplify market participation for small providers, and further develop Vehicle-to-X standards. Implications for actors include the evaluation and enablement of portfolios with different flexibility assets, and stacking of services to increase revenue streams and reduce risk resulting from variations in driving patterns and charging behavior.
Beijing biopharmaceutical industrial base are currently still in its infancy, innovation network and collaborative innovation system within pharmaceutical industrial clusters still have many problems, and cluster-based technology innovation mechanism and pattern needs further exploration. This study focuses on Beijing pharmaceutical industry clusters, and industry cluster theory, learning theory, and regional innovation system theory apply to the practice of Beijing pharmaceutical industrial bases. The study discusses on the related concepts of technology learning, and establishes a technology learning network among industry clusters, and presents a technological learning system under the cluster network on the basis of existing learning theory. According to characteristics of biopharmaceutical industry, the study develops a basic framework of regional innovation for biopharmaceutical industry clusters, and proposes synergistic development strategies of Beijing north and south pharmaceutical industry clusters.
This article examines the association of location and actors in the invention, development and innovation of power generation and lighting technologies. It is known that niche actors play important roles in knowledge creation and energy innovation. What is not well understood is the association and influence of location for sustainability transition knowledge creation. To understand the association of location and knowledge creation we use a theoretically novel framework which integrates concepts of niches, mode 2 knowledge production, embedded research and socio-spatial embedding. We applied the new framework and comparative case study methods to answer our research question of what locations and actors are associated with knowledge creation. We found that knowledge creation in the cases is positively associated with locations-of-use and the involvement of niche actors. The spacial and temporary variation of our cases limits the generalizability of our framework. Future research directions include examination of other historical and contemporary case studies, and identification of effective practices in embedding energy knowledge creation projects in locations-of-use.
The adoption of the Sustainable Development Goals and the Paris Agreement in 2015 marked a critical landmark in terms of achieving increased alignment between global goals for sustainable development and climate change mitigation. Several scholars have argued that technological change – i.e. the invention, innovation and diffusion of new technologies – particularly in the electricity sector, was one of the key enablers for achieving this increased alignment. Thus, ambitious Nationally Determined Contributions (NDCs) under the Paris Agreement can be seen not only as means to reduce emissions of greenhouse gases, but also as means to achieve development goals such as reducing the cost of energy supply, extending electricity access and developing local industries around low-carbon technologies. However, despite this progress, public policies will continue to play an important role in accelerating technological change and enhancing synergies between development and climate goals in order to scale up ambition for climate change mitigation.
Thus, this dissertation aims to advance our understanding of how policies for technological change in the electricity sector can be designed to incorporate context-specific needs for low-carbon development. To do so, it presents four papers, each aiming to address a gap in the existing literature. Collectively, they contribute to developing a better understanding of how low-carbon development policies can be designed to take into account (i) context-specific policy goals, (ii) technological characteristics, and (iii) technologies’ use environments.
The first paper explores how policy design and sequencing influence synergies and trade-offs between different policy goals and instruments in the electricity sector policy mix. Out of the different policy goals discussed in the first paper, Paper 2 focuses on rural electrification. It analyzes the influence of uncertainties in the use environment on investment risks and cost of energy provision using solar PV mini-grids. Papers 3 and 4 take a value chain perspective to investigate how technological characteristics influence technological learning processes and derive implications for low-carbon industry development.
The papers in this dissertation make four key contributions to the existing literature. First, this dissertation contributes to the literature on policy mixes by using a quantitative ex-ante approach to analyze interactions in a policy mix. Unlike existing qualitative ex-post analyses of policy mixes, using such an approach allows for a better understanding not only of the nature of interactions, but also quantifies the influence of policy interactions and sequencing in a policy mix. Second, it contributes to the literature on rural electrification by demonstrating the importance of aggregation and spatial diversification in derisking investments for off-grid electrification. Third, this dissertation contributes to the literature on technological innovation systems (TIS). By demonstrating that sectoral characteristics are important determinants of the need for learning-by-interacting in a technology’s value chain, this dissertation further contributes to more closely integrating the TIS literature with the literature on sectoral systems of innovation. Fourth, it contributes to the literature on technological catching-up. Taking a value chain perspective, it highlights the influence of technology architecture and associated learning processes (learning-by-interacting and learning-by-using) on opportunities for latecomers to catch up in specific value chain segments.
The findings of the individual papers are used to derive recommendations for policies for low-carbon development. First, the results indicate that better coordination across different policy fields and consideration of the temporal and spatial aspect of interactions between policies can help design more consistent policy mixes. Particularly, an integrated assessment of policy goals and instruments related to renewable energy deployment, financial reform of utilities, and rural electrification can help in highlighting critical interactions. Second, the influence of degree of complexity and the degree of customization of technologies on learning processes has important implications for measures to facilitate technological change, avoid network failures and to support localization of industry value chains. Thus, policymakers should tailor innovation policies to the characteristics of particular technologies, instead of taking a one-size-fits-all approach. Finally, this dissertation concludes with an agenda for future research.
This is the lemma in the Encyclopedia of Sustainability Science and Technology, volume 17. Ed. Robert A Meyers. Springer Reference, 2012.
This lemma gives the most comprehensive overview of social acceptance of wind power so far. It deals with all subjects significant in social acceptance, listed below, including definitions. It provides more than 200 references and some further readings.
The willingness to accept phenomena related to innovation of different parts of society, including all realms beyond “the public,” can be subdivided in two broad categories:
– Acceptance of the creation of new socioeconomic conditions needed for implementation.
– Acceptance of the consequences of the implementation: implementation will affect current practices in society and forcing some to change.
Four Starting Points:
It is not about acceptance of technical systems, but about socio-technical systems; hence institutional factors (structural components of social organization around renewable energy) are key elements.
– All aspects of a new STS featuring a substantial amount of wind power are subject to social acceptance.
– An actor may accept certain aspects, while simultaneously rejecting other aspects, as a result of social, economic, and/or political learning processes.
Existing institutions (existing patterns of behavior as determined by existing societal rules) often impede the development and implementation of new views, approaches, techniques, and practices required for the implementation of wind power.
Some lingering common sense ideas must be abandoned: The objection to any wind power development must be considered as a potentially legitimate, rational, and informed position: All positive, active support as well as passive supporting attitudes, are equally important for obtaining a good understanding of the acceptance of wind power.
Social acceptance of wind power – as other renewables’innovations – contains three main dimesions: Socio-political acceptance, market acceptance, and community acceptance. Public acceptance should not be misinterpreted as a proxy for social acceptance, as it only covers a small part of all three, and it does often not run parallel with social acceptance.
As the first component in the social dimension of the socio-technical system, all relevant social actors involved in the process of acceptance must be considered. Again, this goes far beyond ‘public’ acceptance.
The attributes of acceptance are outlines, emphasizing the large differences between accepptance of general implementation of a technique, such as wind power, from acceptance of concrete projects. In fact these two are only weekly related, as their attributed are very different. Special attention is given to the overly simplistic, and very destructive common sense idea that the ‘gap’ between these two ― in fact the term ‘gap’ is very questionable itself — implies the existence of nimby-attitudes.
Socio-political Acceptance:
The shape and the reliability of the financial procurement system, which is of overwhelming importance for the utilization of 1. the potentially significant willingness to invest in wind developments; 2. The type and amount of effective support generated within the national and regional planning system for policies that develop wind power capacity; 3. The degree to which collaborative decision making on the level of communities is allowed and stimulated by the sociopolitical framework.
Community Acceptance:
Historically, the focus within this issue of social acceptance of renewable energy innovation has been on public acceptance as the cornerstone of community acceptance. Community acceptance refers to the specific acceptance of siting decisions and renewable energy projects by local stakeholders, particularly residents and local authorities.
Market Acceptance:
Social acceptance can also be interpreted as market acceptance or as the process of market adoption of an innovative STS.
Three categories of impact can be distinguished that are discussed in almost any case: landscape, wildlife, and annoyance issues.
The issue of social acceptance of wind power will come to the fore even more prominent in the coming decades, but the character of acceptance issues in the three dimensions will probably change. The current awareness of the required space for sustainable energy supply is still limited and, hence, the consequences in terms of landscape occupation and potential environmental conflicts are neither fully recognized. The main question of social acceptance will remain how to build socio-political and market acceptance for the collaborative way of planning and decision making that is needed. This key to the large number of positive investment and space-making decisions will even become more important because wind power is becoming increasingly part of an all-embracing STS of integrated sustainable energy supply. The new power supply system will have to integrate growing numbers of distributed generation units. The integration of all the components of sustainable power generation, including the mutual fine-tuning and optimization of local supply and demand and possibly with the introduction of local storage capacity must be embedded an intelligent “smart grid”, with many acceptance issues itself — as it runs fully counter to our existing centralized and hierarchically organized power supply system. The social acceptance of wind power will become embedded in the acceptance of all kinds of decisions about this future STS of sustainable energy supply and demand.
Energy technology innovation - improving how we produce and use energy - is critical for a transition towards sustainability. This book presents a rich set of twenty case studies of energy technology innovation embedded within a unifying conceptual framework. It provides insights into why some innovation efforts have been more successful than others, and draws important policy conclusions. The case studies cover a wide range of energy technologies, ranging from energy supply to energy end use, from successes to failures and from industrialized, emerging and developing economies. The case studies are presented by an international group of eminent scholars under the auspices of the Global Energy Assessment (GEA), whose main volume was published in 2012 by Cambridge University Press. Energy Technology Innovation presents new data, new concepts and novel analytical and policy perspectives. It will prove to be invaluable for researchers, policy makers, economists, industrial innovators and entrepreneurs in the field of energy technology.
Kite-based airborne wind energy systems are new high-tech systems that provide sustainable wind energy. Instead of using a wind turbine, these systems use a kite to generate energy. Commercializing such new high-tech systems is a risky strategy, the failure rate is high. This chapter identifies barriers that block large-scale diffusion of kite-based airborne wind energy systems and specific niche strategies to deal with these barriers. The results are based upon literature research and interviews with six academic and industry experts active in the field of airborne wind energy. We identified the most important barriers to large-scale implementation of airborne wind energy. We show how particular barriers, such as the lack of knowledge of the technology and the lack of support and investment opportunities, interact and together block large-scale production and diffusion. The second result is that several niche strategies can be identified to tackle the barriers in this field. The “geographic niche strategy”, the “demo, experiment and develop niche strategy” and the “educate niche strategy” are identified as good strategies to introduce the kite-based systems. The chapter ends with a discussion of these niche strategies and how they relate to previous research into introduction of sustainable energy technologies.
Maatschappelijke acceptatie van windenergie-Houdingen en oordelen van de bevolking Maarten Wolsink 1990
Thesis publishers Amsterdam
Flaptekst: Na de oliecrisis van 1973 is windenergie in Nederland opnieuw in de belangstelling gekomen. De noodzaak voor het ontwikkelen van nieuwe energiebronnen is daarna met opnieuw twee scherpe stijgingen van de energieprijzen nog duidelijker geworden. Onder de bevolking heeft windenergie als duurzame en relatief schone bron grote voorkeur. Wanneer men ergens windturbines wil plaatsen, blijkt echter dat er plotseling genuanceerd over windenergie wordt gedacht. De initiatiefnemers, zoals energiebedrijven, denken dat er brede steun voor windenergieplannen bestaat, maar ze worden vervolgens met twijfels en bezwaren geconfronteerd. De conclusie is dan al gauw, dat mensen wel windenergie willen, maar geen molens in hun achtertuin. Deze conclusie is maar voor een zeer klein deel van de oppositie tegen windturbines juist. Wat zijn dan wel de achtergronden van het verzet tegen de komst van windturbines? Is er nog iets tegen die oppositie te ondernemen? Of hebben omwonenden van te bouwen windmolens gelijk als ze zich ertegen uitspreken?
This contribution aims to deal with innovation policy from the perspective of the systems of innovation approach. The intention is to address basic principles related to national, regional or local as well as sectoral systems of innovation and the policy implications emerging from these. Hence, there will be a very strong emphasis on policy in what follows. However, it is essential, of course, that any observations should be adapted to the specific conditions in particular sectors, regions or countries to be fully relevant1.
The fact that market experience improves performance and reduces prices is well known and widely exploited in technology-intensive industries, but sparsely used in analysis for energy technology policy. Knowledge of the experience effect can help in the design of efficient programmes for deploying of environment-friendly technologies. The effect must be taken into account when estimating the future costs of achieving targets, including targets for carbon dioxide reduction.
This book discusses issues raised by the experience effect, such as price-cost cycles, competition for learning opportunities in the market, risk of “technology lockout” and the effects of research, development and deployment policies on technology learning.
Case studies illustrate how experience curves can be used to set policy targets and to design policy measures that will encourage both investment in and use of environment-friendly energy technologies. Low-cost paths to stabilising CO2 emissions are explored.
Innovation and technical change play significant roles in both firm and economic growth, resulting in the creation of knowledge and the formation of new products. Due to the competitive aspects of innovation, firms often interact with and share and/or exchange information with other organizations, including other firms and universities, to further their innovative pursuits. Additionally, other factors, such as laws, cultural norms, and social rules, impact a firm's innovative abilities and behaviors. Organizations and institutions, economic infrastructures, sectoral innovation systems, and national imaginations all have a role in innovation systems. This edited work is composed of 17 essays, providing differing perspectives. To better understand the systems of innovation approach to business, this book examines three significant issues: part one dissects conceptual problems related to the theory of the systems of innovation approach; part two discusses the relationship between the systems of innovation approach and other innovation theories; and part three promotes greater understanding of the dynamics of systems of innovation. The various systems of innovation approaches have nine common characteristics: innovations and learning at the center of focus; holistic and interdisciplinary; historical perspective; differences between regional systems (no optimal system); interdependence; encompasses both technological and organizational innovations; institutions are central; conceptual ambiguity; and conceptual frameworks rather than formal theories. The creation and distribution of technological knowledge, including interindustry differences, are also explored. Evolutionary theories of economics and the ways in which they influence the systems of innovation approach are examined. The influence of policy upon technological change is also discussed, as are Technological and institutional change as components in the creation and change of innovation systems. Challenges to the systems approach are examined, including policy-based challenges to firms, paradigmatic shifts in innovation systems, and differences among European systems of innovation. (AKP)
Explores how technological innovation has shaped and been shaped by science, industry, and economics in the twentieth century. Technological change and specific technologies have impacted productivity, the learning process, technology transfer and technology policies. Starting with a summary of historical literature on technical progress, the book goes on to discuss and promote Karl Marx's influential method of studying technology as the result of interrelated social processes -- especially emphasizing the mutual interaction between technology and the economy. Analysis of current empirical studies shows the need for an enlarged framework for understanding the relation between the economy and technical change. Technological interdependence in the American economy is analyzed, and later expanded to encompass international business. High-tech industries are discussed as particularly reliant upon scientific research. The commercial aircraft industry from 1925-75 is also examined, as an exemplary instance in which technological innovation and government support and regulation allowed for economic success. The book concludes that scientific progress is heavily influenced by technological considerations that are, in turn, shaped by industry and economics. Thus, decisions made in the private and public sectors should affect both supply and demand, favoring the creative, mutually advantageous connection between science and technology. (CJC)
This volume offers an exploration of major changes in the way
knowledge is produced in science, technology, social science,
& humanities, arguing that a new mode of knowledge production
promises to replace or radically reform established
institutions, disciplines, practices, & policies. A range of
features - reflexivity, transdisciplinarity, heterogeneity -
associated with the new mode of knowledge production are
identified to illustrate the connections between them & the
changing role of knowledge in social relations.
Methodological difficulties inherent in attempts to describe
a new mode of knowledge production are discussed, &
implications of this mode for science policy & international
economic competitiveness, collaboration, & globalization are
treated. The book is particularly relevant for those
concerned with educational systems, the changing nature of
knowledge, the social study of science, & the connections
between research & development, & social, economic, &
technological development. The book is presented in 7 Chpts
with a Preface & an Introduction. (1) Evolution of Knowledge
Production. (2) The Marketability and Commercialisation of
Knowledge. (3) Massification of Research and Education. (4)
The Case of the Humanities. (5) Competitiveness,
Collaboration and Globalisation. (6) Reconfiguring
Institutions. (7) Towards Managing Socially Distributed
Knowledge. References accompany each Chpt. 2 Tables. W.
Howard (Copyright 1995, Sociological Abstracts, Inc., all
rights reserved.)
Innovation systems can be defined in a variety of ways: they can be national, regional, sectoral, or technological. They all involve the creation, diffusion, and use of knowledge. Systems consist of components, relationships among these, and their characteristics or attributes.The focus of this paper is on the analytical and methodological issues arising from various system concepts. There are three issues that stand out as problematic. First, what is the appropriate level of analysis for the purpose at hand? It matters, for example, whether we are interested in a certain technology, product, set of related products, a competence bloc, a particular cluster of activities or firms, or the science and technology base generally—and for what geographic area, as well as for what time period. The choice of components and system boundaries depends on this, as does the type of interaction among components to be analyzed. The attributes or features of the system components that come into focus also depend on the choice of level of analysis.The second and closely related issue is how to determine the population, i.e. delineate the system and identify the actors and/or components. What are the key relationships that need to be captured so that the important interaction takes place within the system rather than outside?The third issue is how to measure the performance of the system. What is to be measured, and how can performance be measured at the system level rather than at component level?
During the last two decades there has been a great deal of research on renewable energy technologies. It is commonly thought that very little has come out of this research in terms of commercially interesting technologies. The first objective of this paper is to demonstrate that this perception is no longer entirely correct; in the 1990s there has been a double-digit growth rate in the market for some renewable energy technologies. The consequent alteration in the energy system, is, however, a slow, painful and highly uncertain process. This process, we argue, needs to be studied using an innovation system perspective where the focus is on networks, institutions and firms’ perceptions, competencies and strategies. The second objective of the paper is therefore to present the bare bones of such an analytical framework. A third objective is to identify a set of key issues related to the speed and direction of that transformation process which needs to be studied further.
In this paper we discuss some limitations that selection mechanisms face when the entities subject to selection are complex systems of interdependent elements. We briefly present Kauffman’s NK model which addresses this problem in biological systems. It is argued that, contrary to the myopic search behaviour, underlying biological fitness landscapes, social organisations are not bound in their search dynamics. This amounts to say that the problem of finding optima on a fitness landscape can be decomposed in many different ways. Following work by Page (1996), we present some measures of the complexity of a fitness landscape in terms of the complexity (size) of the algorithm that decomposes the problem most accurately, while still being able to locate the global optima with full certainty. We then extend this measures to allow for nearly-decomposability in a sense close to Simon (1969). Finally we study some evolutionary properties of populations of agents characterised by different decompositions of the same given problem.
This essay presents an overview of selected aspects of prevailing theoretical understanding of innovation, and attempts to sketch some directions that would seem fruitful to follow if we are to achieve a theoretical structure that can be helpful in guiding thinking about policy. We are using the term innovation as a portmanteau to cover the wide range of variegated processes by which man’s technologies evolve over time. By a theory we mean a reasonable coherent intellectual framework which integrates existing knowledge, and enables predictions to go beyond the particulars of what actually has been observed. It seems apparent that if scholarly knowledge is to be helpful to deliberation about policy directions, theory must be wide enough to encompass and link the relevant variables and their effects, and strong enough to give guidance as to what would happen if some of these variables changed.
The procedures and the nature of “technologies” are suggested to be broadly similar to those which characterize “science”. In particular, there appear to be “technological paradigms” (or research programmes) performing a similar role to “scientific paradigms” (or research programmes). The model tries to account for both continuous changes and discontinuities in technological innovation. Continuous changes are often related to progress along a technological trajectory defined by a technological paradigm, while discontinuities are associated with the emergence of a new paradigm. One-directional explanations of the innovative process, and in particular those assuming “the market” as the prime mover, are inadequate to explain the emergence of new technological paradigms. The origin of the latter stems from the interplay between scientific advances, economic factors, institutional variables, and unsolved difficulties on established technological paths. The model tries to establish a sufficiently general framework which accounts for all these factors and to define the process of selection of new technological paradigms among a greater set of notionally possible ones.
Collateral impacts of LULUCF projects, especially those concerning social and environmental aspects, have been recognised as important by the Marrakech Accords. The same applies to the necessity of assessing and, if possible, of quantifying the magnitude of these impacts. This article aims to define, clarify and structure the relevant social, economic and environmental issues to be addressed and to give examples of indicators that ought to be included in the planning, design, implementation, monitoring, and ex post evaluation of LULUCF projects. This is being done by providing a conceptual framework for the assessment of the sustainability of such projects that can be used as a checklist when dealing with concrete projects, and that in principle is applicable to both Annex I and non-Annex I countries. Finally, a set of recommendations is provided to further develop and promote the proposed framework.
This article addresses the question of how policymakers could deliberately influence processes of technology development. Using the development of wind turbines in Denmark as an example, the article describes the frames of meaning guiding the actions of those involved in the three subprocesses of policymaking, the generation of new technologies, and the management of the firms that bring new artifacts to the market. The three types of actors share an interest in one notion: the meaning of a technological artifact. This notion, however plays a different role in the respective frames of meaning of the actors. For policymakers and managers, it is an instrumental notion. For technologists, it provides guidance to their activities. The shared interest affords the possibility of reaching common action with only congruent (not necessarily shared) meanings. Interactive forms of technology assessment can play a central role in bringing about such congruent meanings and thus in influencing the generation of new technologies.
1. Purpose and Scope PART I: BUILDING-BLOCKS 2. Management and Organization 3. Innovation, Entrepreneurship, and Competence 4. Evolution 5. Institutions 6. Knowledge 7. Language PART II: CONSTRUCTION 8. A Theory of Interactive Learning 9. A Heuristic of Discovery 10. An Elaboration with Scripts 11. Integration and Disintegration PART III: APPLICATION 12. Innovation Systems 13. Organizational Learning 14. Conclusions and Further Research 15. Summary
Technology and Culture 39.4 (1998) 641-670
A huge body of scholarship in recent decades has convincingly demonstrated the contingent and contextual character of technological development. Technologies are shaped by social factors and thus "mirror our societies." Regional and national characteristics of technological developments can often be explained by their embedment in different cultures and environments. To describe or explain technological differences, historians of technology have employed the loosely defined concept of "technological style," which in recent years has received growing attention. Drawing extensively on this concept, John Staudenmaier has raised the possibility of a "link between technological style and national character."
The development of wind technology from 1940 to 1990 in Germany, Denmark, and the United States does at first glance appear to corroborate Staudenmaier's hypothesis. Wind technology in these countries differs in conspicuous ways. The renaissance of wind power technology in California and Denmark in the 1980s contained several notable surprises. California produced scores of unsuccessful turbine designs, poorly performing turbines, and disastrous turbine failures, especially when compared to the clearly superior Danish wind technology. The American failure looks even worse when one considers that between 1975 and 1988 the United States government spent twenty times (and Germany five times) as much for wind power research and development as did Denmark, yet Danish manufacturers made better turbines -- have, indeed, since the early 1980s been the most successful wind turbine producers. Danish wind turbines supplied about 45 percent of the total worldwide wind turbine capacity in 1990. Most U.S. manufacturers failed in the 1980s, and by 1990 only one major manufacturer of commercial turbines (US Windpower) remained. Producers from other countries had little impact on the total wind turbine capacity in the 1980s.
The failure of numerous turbine designs and the remarkable contrast between R&D expenditures and commercial success raise important questions. Why did so many designs fail? What made Danish turbines superior? How could small Danish companies outclass large American and German high-tech concerns? Forrest Stoddard, an American engineer, identified characteristic technical differences of Danish and American turbines that he considered responsible for Danish success and American failures. Peter Karnøe, a Danish political scientist, has explained the superiority of Danish wind turbines as a result of Danish manufacturers' "bottom-up" strategy for development: a slow, crafts-oriented, step-by-step process including incremental learning through practical experience. This strategy, Karnøe argues, proved superior to the "top-down" approaches of science-oriented German and American researchers and manufacturers, which aimed at both quick and ambitious full-scale developments. Karnøe has shown that many striking wind turbine failures may be attributed to the disadvantages of top-down development.
Stoddard's and Karnøe's interpretations offer interesting explanations for the remarkable Danish success, but they do not answer all the questions posed. Why did the Danish bottom-up strategy prove more successful than American and German top-down approaches, and why did this strategy evolve in Denmark, and only there? Historical analysis shows that technical and conceptual differences in wind turbine development had important roots in the 1940s and 1950s. Individual and collective ideas and working styles can be attributed to individual actors and particular communities, both of which have characteristic patterns of knowledge, actions, and artifacts. These patterns may be called technological styles. The failure of a top-down approach to the development of wind technology reveals the limits of science-oriented technological development, or engineering science, and hints at technological hubris. Big-science and high-tech approaches were in this case mistakenly considered powerful enough to support gigantism, extreme technical sophistication, and immediate full-scale development.
Wind power's long and rich history reached its zenith in industrializing western Europe and North America in the late nineteenth century. In the twentieth century the use of wind power declined, and thousands of windmills and wind turbines disappeared within a few decades. By the 1980s, however, oil crises, growing concern over environmental degradation, and nuclear-power protests were contributing to a revival of wind technology. Supported by government subsidies, California and Denmark became by far the biggest markets for wind turbines. By the late 1980s, California accounted for 79 percent...
Experience curves are used to analyse the prospects for diffusion and adoption of renewable energy technologies, with special emphasis on wind turbines and photovoltaic (PV) modules. The analysis shows that the possibility of cost reductions of renewable energy technologies is greater than for conventional energy technologies, However, large investments are necessary to make wind turbines and PV modules economically competitive with conventional power plants. The results indicate that the prospects for diffusion and adoption of wind turbines and PV modules will increase if policy instruments are used to bring about diffusion.
Expert case studies This book is about national systems of technological innovation. The heart of the book consists of studies of 17 countries, including the large market-oriented industrialized countries, several smaller high-income countries, and a number of newly industrialized states. The studies have been carefully designed, developed and written to illuminate the institutions and mechanisms supporting technological innovation in the various countries, the similarities and differences across countries, and how these came to be.
The use of the learning curve has been receiving increasing attention in recent years. Much of this increase has been due to learning curve applications other than in the traditional learning curve areas. A comprehensive survey of developments in the learning curve area has never been published. The closest thing to a survey was by Asher in 1956. His study focused exclusively on military applications during and immediately after World War II. This paper summarizes the learning curve literature from World War II to the present, emphasizing developments since the study by Asher. Particular emphasis is given to identifying the new directions into which the learning curve has made recent inroads and identifying fruitful areas for future research.
This paper describes an analysis of the prospects of reducing the cost of wind-generated electricity. Special attention has been paid to the dynamic development of wind turbines, i.e. development based on experience gained in the production and use of wind turbines. Historical and future cost reductions associated with wind turbines are described using experience curves. The results of the analysis show that although the experience curve for wind turbines indicates relatively moderate cost reductions there is potential for considerable cost reductions in wind-generated electricity. This is due to the fact that the cost of wind-generated electricity will be affected by improved performance and reduced operating and maintenance costs, in addition to the reduction in cost of wind turbines. The results show that the average cost of wind-generated electricity will almost be reduced by half by the year 2020, assuming an annual market growth of 15–20%.
Science-based innovations have played an important role in our society for centuries. In this paper, after a discussion of the concept of innovation, changes in three major developments in the context of innovation processes are analysed: structural changes in our economy, the broadening of decision-making processes and the emergence of the network society, and changes in the knowledge infrastructure. On the basis of this analysis, questions and challenges confronting the players involved in innovation processes and the management of them are identified and topics for a research agenda for innovation researchers that take into account the needs of these players are formulated. The focus is on the macro and meso level, and the broadening of decision-making on innovation processes acts as an important guiding principle. Three lines of research are distinguished on the research agenda: (1) empirical studies of innovation processes and systems, (2) critical reflection on innovation theory, and (3) analysis and support of decision-making processes. With regard to the first line, case studies of innovation in services, life sciences, the relationship between ICT and sustainability and the identification of (intangible) throughput and output indicators are on the agenda. The reflection on theory (line 2) focuses primarily on innovation in chains and clusters, the role of (knowledge intensive) intermediaries and the interaction between processes and systems. Furthermore, innovation studies should also try to contribute towards endogenisation of innovation in other scientific disciplines. With regard to the analysis and support of decision-making processes (line 3), strategic intelligence providing insight into the potential, application and implementation of new technologies and the development of instruments to support players in innovation processes are addressed. An important basic assumption of this paper is that innovation studies should not only strive to deepen the insight into innovation processes and systems, but also to contribute to the development of insights, concepts, methods, techniques and instruments to support various players involved in innovation processes. The major conclusion of this paper is that shifts in the context of innovation processes, more particularly the emergence of the ‘porous society’, will lead to a radical transformation of innovation systems in which (knowledge intensive) intermediaries and the quality of the interface between users and producers play an increasingly important role.
This study develops an evolutionary theory of the capabilities and behavior of business firms operating in a market environment. It includes both general discussion and the manipulation of specific simulation models consistent with that theory. The analysis outlines the differences between an evolutionary theory of organizational and industrial change and a neoclassical microeconomic theory. The antecedents to the former are studies by economists like Schumpeter (1934) and Alchian (1950). It is contrasted with the orthodox theory in the following aspects: while the evolutionary theory views firms as motivated by profit, their actions are not assumed to be profit maximizing, as in orthodox theory; the evolutionary theory stresses the tendency of most profitable firms to drive other firms out of business, but, in contrast to orthodox theory, does not concentrate on the state of industry equilibrium; and evolutionary theory is related to behavioral theory: it views firms, at any given time, as having certain capabilities and decision rules, as well as engaging in various ‘search' operations, which determines their behavior; while orthodox theory views firm behavior as relying on the use of the usual calculus maximization techniques. The theory is then made operational by the use of simulation methods. These models use Markov processes and analyze selection equilibrium, responses to changing factor prices, economic growth with endogenous technical change, Schumpeterian competition, and Schumpeterian tradeoff between static Pareto-efficiency and innovation. The study's discussion of search behavior complicates the evolutionary theory. With search, the decision making process in a firm relies as much on past experience as on innovative alternatives to past behavior. This view combines Darwinian and Lamarkian views on evolution; firms are seen as both passive with regard to their environment, and actively seeking alternatives that affect their environment. The simulation techniques used to model Schumpeterian competition reveal that there are usually winners and losers in industries, and that the high productivity and profitability of winners confer advantages that make further success more likely, while decline breeds further decline. This process creates a tendency for concentration to develop even in an industry initially composed of many equal-sized firms. However, the experiments conducted reveal that the growth of concentration is not inevitable; for example, it tends to be smaller when firms focus their searches on imitating rather than innovating. At the same time, industries with rapid technological change tend to grow more concentrated than those with slower progress. The abstract model of Schumpeterian competition presented in the study also allows to see more clearly the public policy issues concerning the relationship between technical progress and market structure. The analysis addresses the pervasive question of whether industry concentration, with its associated monopoly profits and reduced social welfare, is a necessary cost if societies are to obtain the benefits of technological innovation. (AT)
Standard transaction cost economics (TCE) considers transactions from the perspective of static efficiency. Increasingly, attention is required to dynamic efficiency; to capabilities to exploit transaction relations for innovation. Since innovation is dependent on knowledge and learning, the step from the statics to the dynamics of exchange requires an understanding of the development and acquisition of knowledge, preferences, and meaning, and the role in that of interaction between transaction partners. As a step towards this, the article provides an exploration of theories of knowledge and knowledge development, the relation to language, the role of intersubjective relations, the connection with evolutionary theory and the implications for transaction cost theory.
This paper suggests that the economic growth of countries reflects their developmental potential which, in turn, is a function of the technological systems in which various economic agents participate. The boundaries of technological systems may or may not coincide with national borders and may vary from one techno-industrial area to another. The central features of technological systems are economic competence (the ability to develop and exploit new business opportunities), clustering of resources, and institutional infrastructure. A technological system is defined as a dynamic network of agents interacting in a specific economic/industrial area under a particular institutional infrastructure and involved in the generation, diffusion, and utilization of technology. Technological systems are defined in terms of knowledge/competence flows rather than flows of ordinary goods and services. In the presence of an entrepreneur and sufficient critical mass, such networks can be transformed into development blocks, i.e. synergistic clusters of firms and technologies which give rise to new business opportunities.
In the following paragraphs we will discuss the ‘mapping of innovative clusters in national innovation systems’. For this we have used a data set of almost 3.000 firms that participated in the first and fifth survey of the Mannheimer Innovation Survey (which is comparable with CIS data). The Community Innovation Survey (CIS) is an initiative of the EU Commission and a joint survey of DG XIII/SPRINT/EIMS and Eurostat. To begin with we will, in the context of a definition of innovation systems, highlight the outline conditions for innovations in Germany, focusing above all on the basis of innovations, science and engineering. This is followed by a step-by-step empirical analysis of the mapping of innovative clusters at the company level which is based on the Community Innovation Survey set of data; and finally the structural influences (size-effect, effects of sectors/industries) on the innovative behaviour or innovative styles are presented. The explanatory power of structural influences on the innovative behaviour will also be analysed as well as the influence of other variables such as information flows and cooperation patterns within the innovation system of Germany. In the summary at the end of this paper we will suggest starting points for potential implications for innovation policy in order to be able to develop generic and specific policies for the different industry clusters. As far as we know from firms innovating at a certain level of organisation, they use a special portfolio of information and knowledge transfer strategies that can not simply be transferred to firms which are not (yet) innovative. While accepting that innovative inhouse activities are necessary to keep track with international developments and competition, a highly innovative atmosphere within the economy which supports innovative activities should be among the main goals of innovation policy. Furthermore, firms need to have an absorptive capacity to transform knowledge into innovations that bring economic success.
This essay presents an overview of the prevailing theoretical literature on innovation, probes the adequacy of existing theory to guide policy regarding innovation, and sketches some directions for more fruitful theorizing. The focus is on the vast interindustry differences in rates of productivity growth, and other manifestations of differential rates of technological progress across industries. It is argued that the most important policy issues involve finding ways to make the currently lagging sectors more progressive, if in fact that can be done. Theory, to be useful, therefore must organize knowledge and guide research regarding what lies behind the uneven performance of the different economic sectors. In fact prevailing theory cannot do this, for two basic reasons. One is that theory is fragmented, and knowledge and research fall into a number of disjoint intellectual traditions. The second is that the strongest of the research traditions that bear on the differential innovation puzzle, research by economists organized around trying to ‘fit’ production functions and explain how production functions ‘shift’, neglects two central aspects of the problem; that innovation involves uncertainty in an essential way, and that the institutional structure supporting innovation varies greatly from sector to sector. The bulk of the paper is concerned with sketching a theoretical structure that appears to bridge a number of presently separate subfields of study of innovation, and which treats uncertainty and institutional diversity centrally.
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