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.     

New methods of evaluating physical demand at work areas

The manufacturer's requirement of increasing productivity results in the need to design work stations that are increasingly more effective and specialized. However, this procedure can bring about an overloading of the worker, a lack of motivation, and, consequently, a reduction in productivity.Ergonomics adapts the work station to the worker with the object of improving his welfare and satisfaction at his post. One aspect that this science concerns itself with is the evaluation of physical demands connected to productive tasks. Mechanical movements are also studied in order to perform tasks efficiently.We here propose a new method of physical demand analysis that determines the risk factor for muscular skeletal lesion. This method uses, as a base, the system of predetermined times, MTM-UAS. It includes a computer system that allows us to easily analyse the operations at a work station and generates charts similar to those of UAS, but, instead of times, it measures the quantity of mechanical work necessary for each movement.The information that the method provides can be used by different divisions within companies in making decisions about improvements at work stations.     

Foresight analysis of tilapia supply chains (Sistema Producto) in four states in Mexico: Scenarios and strategies for 2018

In order to increase competitiveness among individual producers and to encourage their integration, the federal government of Mexico has pursued the establishment, at both the state and national levels, of supply chains, or Sistema Producto (SP). For fisheries and aquaculture, 33 SPs exist at the state level and 7 at the national level, 1 of them for tilapia. The objective of this study is to carry out a foresight analysis (FA) of 4 tilapia SPs in Mexico—for the States of Colima, Sonora, Tabasco and Yucatán—analyzing their 2018 vision for the development of the tilapia chain. FA provides an integral vision of both the internal and external environments, identifying the key factors for each SP and helping to develop the best strategies in order to compete successfully. Sonora, Tabasco and Yucatán identify marketing aspects as key elements for their 10-year future: adding value to the product by means of new processing technologies, developing their own brand, and identifying and differentiating their product based on sanitary issues. Colima focuses its industry future success on efficiency improvements. Finally, the main technological disruptions identified by the 4 states are the incremental use of information technology, product and process certification, new hatcheries with genetically-improved fry, and new processing methodologies developed and/or applied.     

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.     

Competition and public high school performance

Increasing the level of school competition has been suggested as a way to improve school performance. This study examines one of the most extreme examples of such reform using data from New Zealand public high schools. In the 1990s school zoning was abolished in New Zealand and public schools competed for students, not just with private schools, but also with each other. A categorical Data Envelopment Analysis model using data on school resources and student academic performance, stratified using student socio-economic characteristics, is used to calculate efficiency scores for schools. A regression model is then used to analyse differences in these efficiency scores and their relationship to different levels of competition.