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11.
Functions of innovation systems as a framework to understand sustainable technological change: Empirical evidence for earlier claims 总被引:1,自引:0,他引:1
Marko P. Hekkert Author Vitae Simona O. Negro Author Vitae 《Technological Forecasting and Social Change》2009,76(4):584-594
Understanding the emergence of innovation systems is recently put central in research analysing the process of technological change. Especially the key activities that are important for the build up of an innovation system receive much attention. These are labelled ‘functions of innovation systems’. This paper builds on five empirical studies, related to renewable energy technologies, to test whether the functions of innovation systems framework is a valid framework to analyse processes of technological change. We test the claim that a specific set of functions is suitable. We also test the claim made in previous publications that the interactions between system functions accelerate innovation system emergence and growth. Both claims are confirmed. 相似文献
12.
Adrian Monaghan Author Vitae 《Technological Forecasting and Social Change》2009,76(8):1026-1043
The grassroots has recently been identified as an alternative site for the development of innovations that may contribute to shifts towards more sustainable systems of consumption and production. While the characteristics of these innovations have been elaborated, it remains unclear how these alternative ideas and practices can be purposively supported to populate incumbent systems. This is especially so in light of the difficulty the grassroots face in connecting forcefully with the mainstream.This article will address this issue by outlining an adaptation of conceptual niche management - an approach that focuses on the embedding of guiding principles used to fulfill basic societal needs - that is sensitive to grassroots innovation. The framework will be applied to the current UK body disposal system to illustrate how such transformative sustainability ideas may be capitalised on. 相似文献
13.
R. PhaalAuthor Vitae E. O'SullivanAuthor VitaeM. RoutleyAuthor Vitae S. FordAuthor VitaeD. ProbertAuthor Vitae 《Technological Forecasting and Social Change》2011,78(2):217-230
The industrial landscape is becoming increasingly complex and dynamic, with innovative technologies stimulating the emergence of new applications, business models and industries. This paper presents a framework for mapping science and technology-based industrial emergence, in order to better understand the nature and characteristics of such phenomena, as a basis for improved strategy development. A full lifecycle perspective is included, emphasizing early stage phases associated with scientific and technological developments, together with key transitions between phases related to the conversion of scientific knowledge to technological capability, application, industrial activity and economic value. Roadmapping concepts are used to map industrial emergence phenomena from various perspectives that cover value creation and capture activities together with demand and supply-side factors. The framework has been tested by developing more than 25 diverse ‘emergence maps’ of historical industrial evolution, building confidence that the framework might be applicable to current and future emergence. Common characteristics of industrial emergence have been identified, including key events and milestones, focusing on a chain of demonstrators that delineate the various phases and transitions. 相似文献
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Tae Kyung Sung Author Vitae 《Technological Forecasting and Social Change》2009,76(5):700-6498
Recently Korean Government announced ambitious IT strategy to establish Korea as one of leaders in world IT market. To implement this strategy, technology transfer from research lab to market should be successfully performed. This study is to identify factors influencing technology transfer and to examine contribution of these factors on success of technology transfer in Korean IT industry. Survey results show that technology project leaders evaluated “Concreteness of Technology” as the most influential factor for technology transfer, followed by “Communication Channels,” “Collaboration among Participants,” “Management Support,” “Government Support,” and “Incentives for Transfer.” Out of 135 technology transfer projects, respondents rated 33 projects as sustaining (28.44%), 38 as promoting (28.15%), 26 as demonstrating (19.26%), 27 in incubating (20.00%), and the remaining 7 in imaging stage (8.15%). This statistics means that 28.15% of technology transfer projects did not reach production stage. Regression analysis identifies that “Communication Channels,” “Management Support,” “Concreteness of Technology” “Sense of Common Purpose,” and “Awareness of Technology Transfer” were statistically significant in explaining success of technology transfer. 相似文献
16.
Fabio ManziniAuthor Vitae Jorge IslasAuthor VitaePaloma MacíasAuthor Vitae 《Technological Forecasting and Social Change》2011,78(6):931-944
This article focuses on the problem of assessing the environmental sustainability of energy projects. For this purpose an original model, which is based on various indicators that measure the environmental sustainability of energy projects, has been developed. This model, so called index of environmental sustainability of energy projects (IESEP), can be used in scenario comparison, while measuring the effectiveness of the proposed alternatives. Finally, an example of how to use this model is provided by analyzing alternatives to ameliorate the environmental sustainability of a hydroelectric project. In doing so, it is possible to show the usefulness of this model when used as a decision making tool for energy planners. 相似文献
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Kong Chyong Chi Author Vitae William J. Nuttall Author VitaeAuthor Vitae 《Technological Forecasting and Social Change》2009,76(3):339-357
We present a dynamic model of the indigenous natural gas industry in the UK. The model has been built using a system dynamics approach. Using the model several scenarios have been analyzed. We found that management of the supply-side policy alone cannot substantially postpone the discovery, production and consumption peak. We also found that the dynamics of the main variables, namely, exploration, production and consumption, are sensitive to initial demand conditions. Postponing the onset of gas price increases can therefore be achieved more effectively through efforts to reduce demand growth. One might expect that a low taxation policy would encourage more exploration and production of gas and thereby stimulate higher consumption rates. Instead, there was no overall net effect on production and consumption in the long term. The depletion effect on cost of exploration acts as counterbalance to low taxation policy. Depletion effect causes cost and thus price to rise further which depress consumption rate. The advances in exploration and production technology can delay the peak of exploration, production and consumption. Technological improvements mean lower cost of exploration and production which pressure down the long-term pattern of price dynamics. 相似文献
19.
Constantinos S. Hilas Author Vitae Sotirios K. Goudos Author Vitae John N. Sahalos Author Vitae 《Technological Forecasting and Social Change》2006,73(5):495-509
In this paper, forecasting models for the monthly outgoing telephone calls in a University Campus are presented. The data have been separated in the categories of international and national calls as well as calls to mobile phones. The total number of calls has also been analyzed. Three different methods, namely the Seasonal Decomposition, Exponential Smoothing Method and SARIMA Method, have been used. Forecasts with 95% confidence intervals were calculated for each method and compared with the actual data. The outcome of this work can be used to predict future demands for the telecommunications network of the University. 相似文献
20.
Nedaa Mohamed Ezzat Agami Author Vitae Hisham Emad El-Din El-Shishiny Author Vitae 《Technological Forecasting and Social Change》2008,75(9):1439-1450
Decision makers in governments, corporations and institutions all need to forecast the future. Usually, traditional quantitative forecasting techniques are applied for this purpose. But the limitation of such methods is well known since all quantitative methods that are built solely on historical data (whether time-series or causal methods) produce forecasts by extrapolating such data into the future ignoring the effects of unprecedented future events that could cause deviation from the original surprise-free forecast if they were to occur. In the meanwhile, pure qualitative methods that don't utilize historical data miss its sound foundation. In the field of future studies, attempts are often made to combine quantitative and qualitative approaches using various hybrid methods such as Trend Impact Analysis. This paper introduces an advanced algorithm to enhance Trend Impact Analysis that adds another level of sophistication to the current algorithm. This advanced algorithm takes into account not only the impact of unprecedented future events' occurrences on the future trend, but also the different severity degrees with which the event might occur. This idea of severity degrees is novel, and its implementation is the main contribution of this paper. 相似文献