A review of experience curve analyses for energy demand technologies

Transitioning towards a sustainable energy system requires the large-scale introduction of novel energy demand and supply technologies. Such novel technologies are often expensive at the point of their market introduction but eventually become cheaper due to technological learning. In order to quantify potentials for price and cost decline, the experience curve approach has been extensively applied to renewable and non-renewable energy supply technologies. However, its application to energy demand technologies is far less frequent. Here, we provide the first comprehensive review of experience curve analyses for energy demand technologies. We find a widespread trend towards declining prices and costs at an average learning rate of 18 ± 9%. This finding is consistent with the results for energy supply technologies and for manufacturing in general. Learning rates for individual energy demand technologies are symmetrically distributed around the arithmetic mean of the data sample. Absolute variation of learning rates within individual technology clusters of 7 ± 4%-points and between technology clusters of 7 ± 5%-points both contribute to the overall variability of learning rates. Our results show that technological learning is as important for energy demand technologies as it is for energy supply technologies. Applying the experience curve approach to forecast technology costs involves, however, unresolved uncertainties, as we demonstrate in a case study for the micro-cogeneration technology.     

The UK technology foresight programme: An assessment of expert estimates

Since the early 1990s, ‘Technology Foresight’ exercises with special emphasis on the use of Delphi surveys have played an important role in science and technology (S + T) policy across Europe in an effort to focus resource allocation. Yet, none of the estimates made in the European Delphi surveys have been formally assessed in retrospect, while this process has been incorporated into the Japanese surveys since 1996. Taking the UK Technology Foresight Programme, this research sets out to assess the estimates of three of the fifteen panel Delphi surveys. Whilst on average 2/3 of Delphi statements were predicted to be realised by 2004, it will be shown that only a fraction of these statements had been realised by 2006. Based on the evidence collected from the published panel reports, the ‘Hindsight on Foresight’ survey conducted by OST in 1995 and interviews with panel members, it will be argued that the overwhelming majority of estimates were overly optimistic. While optimism and strategic gaming of experts is the most convincing explanation for these results, process factors were also explored, including the quality of expert panels used, the Delphi statements and the respondents of the Delphi questionnaire. It is argued that at least the issue of short-range optimism and strategic gaming of experts should be addressed in future Delphi exercises, as decision makers relying on expert advice cannot deal with this issue alone.     

How does a cluster relocate across the border? The case of information technology cluster in the Taiwan-Suzhou region

Since the end of the Cold War, cross-border regions have proliferated at the borders of formal socialist countries, especially in China. Existing accounts of these emergences treat them either at the macro-level, focusing on political initiatives, or at the micro-level, with emphasis on social and economic relations. This paper uses the Taiwan-Suzhou cross-border region as a case study for suggesting a meso-level approach, arguing that as a result of continuous interactions between individual Taiwanese information technology firms and opportunity structures generated by the selective opening of the Chinese border, the formation of cross-border high-tech regions is shaped and determined at the level of the industrial system. The industrial system acts as a platform for coordination and cooperation between local elites and foreign investors and among individual firms within this system. The formation of the cross-border high-tech region thus involves the relocation and institutional re-embedding of industrial systems across the border, which has been accompanied by the systemic building of Taiwanese firms on the one hand, and the institutional innovation of Chinese local states on the other.     

An information-based adaptive strategy for resource exploitation in competitive scenarios

Given an exploitation problem, in which a number of agents compete for a limited renewable resource, the optimal harvesting strategy depends on the ratio between resource availability and exploitation effort. For scarce resource a purely competitive, greedy strategy outperforms a more collaborative approach based on the Collective Intelligence, while for more abundant resource the opposite holds. The rationale for this behaviour lies in the amount of information each strategy is able to provide and a combined strategy is possible according to which agents choose dynamically the most informative strategy according to a minimum entropy criterion. This approach, which provides best performance for both under and over-exploited scenarios, can be used to monitor the resource status for management purposes and is effective in both centralised and decentralised decision making.     

Technology transfer in the IT industry: A Korean perspective

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.     

Dynamics of the UK natural gas industry: System dynamics modelling and long-term energy policy analysis

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.     

A sensemaking perspective on network pictures

This paper examines the concept of network pictures through the lens of the organizational sensemaking perspective. Essentially it develops the concept of network pictures by suggesting we think of them as exercises in sensemaking. It does so by providing an introduction to organizational sensemaking before establishing a degree of commensurability between network pictures and sensemaking. It suggests that what we may then see more clearly is that the concept of network pictures needlessly gets involved in reification when talking of ‘the’ network picture whereas a more dynamic approach leads to ideas of network picturing in which the complete discrediting or collapse of extant sensemaking and network pictures provides a research opportunity that could be jointly explored by both perspectives. The paper concludes that paradoxically ‘finding’ this new sense or new network picture appropriate to radically changed times is facilitated by a process that involves first ‘becoming lost’.     

The contingent value of marketing strategy innovativeness for product development performance in Chinese new technology ventures

This study extends research on entrepreneurial behavior by investigating the relationship between the marketing strategy innovativeness (MSI) and new product performance in technology-based new ventures in China. Specifically, premised on contingent resource-based view we argue that MSI is a firm capability that must be bundled with external managerial relationships and be deployed in the appropriate environment to ensure its success. We found that the team's extra industry relationships and market dynamism enhanced the impact of MSI on new product performance. In contrast, top management team's intraindustry relationships, financial relationships, and technology dynamism hindered the impact of MSI on new product performance.     

Context matters: How existing sectors and competing technologies affect the prospects of the Swiss Bio-SNG innovation system

Emerging technological fields are affected by developments in their broader context. This article proposes a differentiation of context structures as a crucial step in the analysis of technological innovation systems. A thorough context analysis, so the argument, is essential for understanding the pace and direction of technology development and the prospects of an emerging technological innovation system. Empirical insights are provided for Bio-SNG, a technology in an early stage of development. The article discusses the conditions under which actors from different sectors (forestry, wood industry, and energy supply) may play a role in the emerging field. It is shown that Bio-SNG is likely to become a victim of the recent boom in wood-to-energy technologies that has favored investments in more mature but technologically inferior alternatives. The case provides lessons for policy making as it highlights how effective support schemes might foster a lock-in into technologies that are readily available.     

The state of research on technological uncertainties, social uncertainties and emerging markets: A multidisciplinary literature review

The objective of this research work is to study the progress of research on technological uncertainties, social uncertainties and emerging markets and outline and identify the key disciplines, journals, articles and authors. For this the author studied the existing literature from the various fields in which technological uncertainties, social uncertainties and emerging markets research work have been published using ISI Web of Knowledge database. The paper finds that there is increasing research work on technological uncertainties, social uncertainties and emerging markets and the bibliographical search resulted in ninety-one documents written by one-hundred-sixty-one authors in eighty-four journals in seventy-two disciplines. The five major disciplines and their underlying journals are business and economics, agriculture, psychology, public administration, and environmental sciences and ecology accounting for majority of publications. In journals the most prolific, measured by number of articles published are Harvard Business Review, Social Science and Medicine, World Development, and Higher Education; and most influential, measured by the global citation received, are Harvard Business Review, Social Science and Medicine and Sociological Review. The top 10% of the journals are responsible for 23% of all publications but 85% of all global citations received. This highlights that despite the high, diverse and increasing number of journals; only few are dominating and shaping the research arena of technological uncertainties, social uncertainties and emerging markets. Further, in the ten most cited articles, no author appears more than once.