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PurposeThis paper aims to present a forecast for renewable energy production in the USA. Growth curves are used to conduct the forecasts.Design/methodology/approachThe analysis is based upon a literature review, supplemented by collection of secondary data. The study then focuses on applying the Pearl growth curve.FindingsThe authors' results show that biomass energy production is growing the fastest followed by geothermal and wind. Additionally, the forecast for solar energy production shows little to no growth over the next two decades.Research limitations/implicationsIf the US government hopes to achieve its goals in renewable energy, considerable funding and incentives will have to be put forth to accelerate the growth of renewable energy. Since the biomass technology is already growing nicely it makes sense to put the additional resources behind the other three technologies to close the 10.3 percent gap being forecasted. The government also needs to put more funding into dual renewable plants such as wind or solar combines with pumped hydro, this will ensure environmental and reliability are both maintained. Finally, for renewable energies to be competitive in the long term, considerable research needs to go into driving down the cost so there is not a need for subsidies.Originality/valueThis study provides value in providing a forecast for expected future growth for renewable energy sources.

PurposeThis paper aims to propose a method for forecasting product returns based on reason codes. The methodology uses two approaches, namely central tendency approach and extreme point approach, and is developed for the consumer electronics industry.Design/methodology/approachThe methodology presented here is based on the return reason codes (RC). The incoming returns are split into different categories using reason codes. These reason codes are further analyzed to forecast returns. The computation part of this model uses a combination of two approaches, namely extreme point approach and central tendency approach. Both the approaches are used separately for separate types of reason codes and then results are added together. The extreme point approach is based on data envelopment analysis (DEA) as a first step combined with a linear regression while central tendency approach uses a moving average. For certain type of returns, DEA evaluates relative ranks of products using single input and multiple outputs. Once this is completed, linear regression defines a correlation between relative rank (predictor variable) and return quantity (response variable). For the remaining type of returns the authors use a moving average of percent returns to estimate the central tendency.FindingsReason codes and consumer behavior in combination with statistical methods can be used to forecast product returns.Practical implicationsConsumer electronics retailers and manufacturers can effectively use this methodology to forecast product returns. This methodology effectively addresses and covers different product return scenarios.Originality/valueThis research paper shows the new way of forecasting product returns i.e. reason codes based forecasting by combining two approaches, namely extreme point approach and central tendency approach. Also, it shows a new way of translating the consumer behavior into meaningful data; that data can be fed to a model to forecast product returns.

This book introduces readers to essential technology assessment and forecasting tools, demonstrating their use on the basis of multiple cases. As organizations in the high-tech industry need to be able to assess emerging technologies, the book presents cases in which formal decision-making models are developed, providing a framework for decision-making in the context of technology acquisition and development. Applications of different technology forecasting tools are also discussed for a range of technologies and sectors, providing a guide to keep R & D organizations abreast of technological trends that affect their business. As such, the book offers a valuable the theoretical and practical reference guide for R & D managers responsible for emerging and future technologies.

Across industries, firms vary broadly on how they operate with respect to their Research & Development (R & D) activities. This volume presents a holistic approach to evaluating the critical elements of R & D management, including planning, organization, portfolio management, project management, and knowledge transfer by assessing R & D management from different sectors. Featuring empirical research and in-depth case studies from industries as diverse as medical imaging, electric vehicles, and cyber security, the authors identify common features of successful R & D management, despite fundamental differences, such as company size, number of employees, industry sector, and the R & D budget. In particular, they consider the implications for decision making with respect to resource allocation and investments, such as site selection, purchasing, and cross-departmental communication.

Economic development or economic growth is a continuous change in the economic conditions of a community group towards a better state. The purpose of this research is to find out how the economic development in Medan city is based on the results of the internship analysis that the researchers did. The research method used in this study uses qualitative methods. To improve regional development, especially in developing areas, the regional government seeks to improve the welfare of the community by exploring and developing the potentials that exist in the region through Economic Development.

This article seeks to undertake a critical assessment of the changing position of public science in the entrepreneurial ecosystem of the countries on the periphery of Euro- pean research. These countries are driven by new innovation paradigm based on entrepreneurship, which are implemented within the European Smart specialization strategy (S3). This article argues that S3 is widely implemented in the cohesion coun- tries and, while it provides substantial resources for science, technology, and innova- tion, it fails to provide sustainability in the public research sector. This has direct implications for policies concerning innovation and entrepreneurial ecosystems. In order to prove the thesis, the article provides theoretical argumentation for emer- gence of a new innovation paradigm, driven by the rise of the entrepreneurial ecosys- tem, its incorporation into S3, and a consequent retreat of science policy in favor of entrepreneurial policy. The empirical analysis is focused on the funding trends seen in the business and public research sectors over the last decade (2008–2017), which have clearly shown that S3 has not contributed, despite expectations, to an increase in public expenditure for science. This signifies S3's neglect of public research within entrepreneurial ecosystems and challenges the ability of S3 to reduce wide dispar- ities in research and innovation performance across the European Union. This ulti- mately endangers the innovation potential of the entrepreneurial ecosystem itself.

Purpose
– The purpose of this study is to investigate whether news media as a form of social communication regarding pressing, important, and contemporary issues could be used as a leading indicator of technology adoption. For technology foresight, monitoring and analyzing energy technologies is in the spotlight due to their strategic importance to the agenda of competitive and sustainable economic growth.



Design/methodology/approach
– The trends in renewable energy production and news media are determined and compared to draw inferences in foresight concerning the use of renewable energy technologies in energy production. Consequently, the data concern wind and solar energy production and their representation in news media in Germany and the UK. The analysis proceeds as a quasi-experiment treating each yearly observation of energy production as a function of news media data with lagged variables.



Findings
– The study reveals consistent dynamics in the lag in the primary production of energy in related technologies compared to the media visibility of the respective technologies.



Originality/value
– This study explores the prospects of using news media data in foresight analysis concerning renewable energy production and provides many fruitful avenues for foresight research in investigating relationships between technology adoption and media exposure.

PurposeThe purpose of this paper is to forecast the performance and adoption of residential energy management technology (REMT).Design/methodology/approachThe paper integrates scenarios, analogy and Bass diffusion model.FindingsFour different scenarios were identified. Bass curve parameters were extracted through many different existing devices, and then fit into each scenario subjectively to produce four different kinds of diffusion curves.Originality/valueThe approach and the model provide decision and policy makers to evaluate how they should position new energy management innovations based on the desired type of diffusion.