Backcasting energy futures using industrial ecology

Backcasting has been widely used for developing energy futures. This paper explores the potential for using industrial ecology to guide the development of energy futures within a backcasting framework. Building on the backcasting work of Robinson [1], a seven step method is presented to embed industrial ecology principles within the development and assessment of future scenarios and transition paths toward them. The approach is applied to the case of backcasting regional energy futures in the Latrobe Valley, near Melbourne, Australia. This region has substantial brown coal deposits which are currently mined and used in coal-fired power stations to generate electricity. Bounded by a sustainability vision for the region in a carbon-constrained world, regional industrial ecologies in 2050 were backcast around three themes: bio-industries and renewables (no coal usage); electricity from coal with carbon capture and storage (low to high coal usage); and coal to products such as hydrogen, ammonia, diesel, methanol, plastics and char (demonstrating medium to high overall coal use relative to current levels). Potential environmental, technological, socio-political and economic impacts of each scenario across various life cycle stages were characterised. Results offer a platform for regional policy development to underpin deliberation on a preferred future by the community, industry and other stakeholders. Industrial ecology principles were found to be useful in backcasting for creatively articulating alternative futures featuring industrial symbiosis. However, enabling the approach to guide implementation of sustainable transition pathways requires further development and would benefit from integration within the Strategic Sustainable Development framework of Robèrt et al. [2].     

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.     

Forecasting of electricity costs based on an enhanced gray-based learning model: A case study of renewable energy in Taiwan

This work presents a novel gray-based cost efficiency (GCE) model that integrates the gray forecasting model into a two-factor cost efficiency curve model for renewable energy (RE) technologies and identifies the optimal forecasting model for power generation cost of RE technologies. The analytical framework of proposed GCE model improves short-term prediction of power generation cost, and can be applied during the early developmental stages for RE technologies. Empirical analysis is based on wind power data for Taiwan. Time lag of knowledge stock was simulated to represent the actual relationship between R&D expenditures and cost reductions in power generation by knowledge stock. Analytical results demonstrate the GCE model is a useful tool to quantify the influences of cost reductions in power generation. The implications of analytical results are that institutional policy instruments play an important role in RE technologies achieving cost reductions and market adoption. The proposed GCE model can be applied to all high-technology cases, and particularly to RE technologies. The study concludes by outlining the limitations of the proposed GCE model and directions for further research.     

Patent indicators for monitoring convergence - examples from NFF and ICT

The blurring of boundaries between hitherto distinct scientific disciplines, technologies or markets is a common and powerful phenomenon. Concentrating on monitoring convergence through patent indicators, we discuss convergence with examples from the area of Nutraceuticals and Functional Foods (NFF)/Cosmeceuticals as well as information technologies, consumer electronics, and telecommunications (ICT). We analyze 7455 scientific and patent references on phytosterols with the aid of SciFinder Scholar and 3836 documents employing STN AnaVist. Furthermore, we test an IPC co-classification based approach on 859,469 ICT-related and 341,846 NFF-related patents. Our results show clear indications for convergence and a proof of principle for our monitoring concept. Academics may better evaluate environmental parameters, like cases of convergence, influencing companies' actions. Implications for practitioners are based on a more reliable assessment prior to the forming of strategic alliances or mergers and acquisitions. This could help avoid costly adventures such as the mergers and acquisitions seen in ICT.     

Opinion convergence in location: A spatial version of the Delphi method

This paper proposes a modified version of the Delphi method, starting from the assumption that in many situations the convergence of opinions can be considered in a spatial context. The Spatial Delphi we suggest is based, like the classical Delphi, on the judgments of experts, and it is useful in the consultations for decision and/or forecast purposes, provided that they concern matters of spatial location. The basis for the questionnaire is a map, on which each expert provides, as answer(s), one or more opinion-points, i.e., locations that, according to their opinion, are best for a specific purpose. We propose a method for narrowing the area of convergence along a multi-step procedure so that the final result of the consultation is a small portion of the initial territory with respect to the initial area considered. Besides a simulation study, we report also a prototype application with a panel of twelve experts.     

Managing academic innovation in Taiwan: Towards a ‘scientific-economic’ framework

Since the passage of the Science and Technology Basic Law in 1999, Taiwanese universities have taken a more “scientific-economic” approach to protect and commercialize their research. This research mainly examines innovation activities such as patenting, licensing, and incubated startups in the context of Taiwanese higher education institutions (HEIs). The “scientific-economic” framework used to analyze the strategic aspects influencing these academic innovations includes (1) intellectual property managerial capabilities, (2) the strength of external industrial partnerships, (3) the university entrepreneurial orientation, and (4) government research policy. Four hypotheses were developed. Data were collected via a questionnaire with all 122 HEIs in Taiwan surveyed.The research reveals that the aspects of intellectual property managerial capability, HEI-industry partnerships, and academic entrepreneurial orientation are useful to distinguish the university's innovation performance on patent grants, licensing incomes, and firm incubation. Also, government support on research plays a moderating role in academic innovation. Managerial and policy implications for managing innovation effectively in universities were drawn.     

Assessing French nursing home efficiency: An indirect approach via budget-constrained DEA models

In this paper, data envelopment analysis (DEA) techniques are applied to the French nursing home industry in order to address two policy issues. The first involves nursing home size and returns to scale, while the second deals with the potential effects of a change in nursing home reimbursement from a flat rate to one based on the severity of case-mix. To accomplish this, our analysis expands on the existing nursing home literature to analyze technical and allocative efficiency along with budget-constrained models rather than the more common direct input-based distance function. Technical efficiency is evaluated via an indirect output distance function while allocative output efficiency is computed with a cost indirect revenue function. The findings suggest that system-wide efficiency and equity may result from coming reforms since payments would more accurately reflect resource use.     

Terrorism and its impact on economic growth and technological innovation

Recent terrorist acts, in particular the 9-11 attacks in 2001, have created disruptions in the global economy. The short-term impact had been felt in the global tourism, airline industries, as well as the financial markets. While the global economy has recovered and is adjusting to the new global realities, the longer-term impact of heightened security risk across the world can be felt in the form of higher risk premiums in asset markets, as well as a shift of resources towards dealing with terrorism. Just as World War II had accelerated the development of nuclear energy as well as a major contributing factor in the genesis of Silicon Valley, the current war against terrorism will affect both the pace and trajectory of technology trends, as efforts are focused on developing technologies to combat terrorism. In this paper, we review the effects of the current war on terrorism in terms of its impact on the economy, the allocation of resources to R&D, and the trajectory of future R&D.     

Governance structures in R&D networks: An analysis in the European context

This paper analyses governance structures used to organize partnerships in R&D networks using two approaches: transaction costs theory and social capital theory. We argue that these theories are complementary; this explains forms of governance through the degrees of administrative (structural and safeguard mechanism) and social factors (cohesion and openness) they embody. Data was obtained from European R&D networks created through Framework Programmes which include a great number of universities, non profit institutions and firms. Findings show the variables that characterize and explain the governance forms based on the applicability of R&D networks. This study not only provides a theoretical model for analysing governance structures of these networks, but is also useful for both improving the management of networks and for fostering collaboration at an international level.     

On the forecasting of the challenging world future scenarios

Logistic and power law methodologies for both retrospective and prospective analyses of extended time series describing evolutionary growth processes, in environments with finite resources, are confronted. While power laws may eventually apply only to the early stages of said growth process, the Allee logistic model seems applicable over the entire span of a long range process. On applying the Allee logistic model to both the world population and the world gross domestic product time series, from 1 to 2008 AD, a projection was obtained that along the next few decades the world should experience a new economic boom phase with the world GDP peaking around the year 2020 and proceeding from then on towards a saturation value of about 142 trillion international dollars, while the world population should reach 8.9 billion people by 2050. These results were then used to forecast the behavior of the supply and consumption of energy and food, two of the main commodities that drive the world system. Our findings suggest that unless the currently prevailing focus on economic growth is changed into that of sustainable prosperity, human society may run into a period of serious economical and social struggles with unpredictable political consequences.