Methodical approach to foresight-research at definition of trends in Green IT development
Abstract
The problem of determining the Green IT development strategy using decision support tools is described in the article. Technology Green IT is a typical result of the advanced technologies convergence, especially information and knowledge. The expediency of the foresight technology applying for the Green IT development perspective directions evaluating is shown. It is indicated that the most critical, in this case, is the stage of forming the initial list of directions. The technology of retrospective analysis of the Green IT development based on the parametric synthesis of the predictive model of exponential smoothing under the conditions of data uncertainty is presented. For the implementation of the parametric analysis of Brown’s predictive model, or exponential smoothing, is used the exponential average value of the stationary time series to evaluate its value at the next time point. The applying of the developed technology provides experts with additional volumes of information about the perspectives for the Green IT development. An example of a retrospective analysis of the Green IT development directions is given. The initial data for the retrospective analysis used the number of scientific publications for the period from 2010 to 2015 in Ukraine, which characterizes the Green IT direction development. The following directions were assessed: green software engineering, software ecosystem, energy-saving green software and green telecommunications. As a result, the most promising direction is green software engineering. The results of the analysis are one of the sources of information for assessing the perspectives for the Green IT development directions by experts
Downloads
References
Kharchenko, V., Illiashenko, O. (2016). Concepts of Green IT Engineering: Taxonomy, Principles and Implementation. Studies in Systems, Decision and Control, 3–19. doi: https://doi.org/10.1007/978-3-319-44162-7_1
Sadi, M. H., Yu, E. (2014). Analyzing the evolution of software development: From creative chaos to software ecosystems. 2014 IEEE Eighth International Conference on Research Challenges in Information Science (RCIS). doi: https://doi.org/10.1109/rcis.2014.6861055
Murugesan, S. (2008). Harnessing Green IT: Principles and Practices. IT Professional, 10 (1), 24–33. doi: https://doi.org/10.1109/mitp.2008.10
Brooks, S., Wang, X., Sarker, S. (2012). Unpacking Green IS: A Review of the Existing Literature and Directions for the Future. Green Business Process Management, 15–37. doi: https://doi.org/10.1007/978-3-642-27488-6_2
Feng, W. (2014). The Green Computing Book: Tackling Energy Efficiency at Large Scale. CRC Press, 353. Available at: http://www.crcpress.com/product/isbn/9781439819876?source=crcpress.com&utm_source=productpage&utm_medium=website&utm_campaign=RelatedTitles
Adegbile, A., Sarpong, D., Meissner, D. (2017). Strategic Foresight for Innovation Management: A Review and Research Agenda. International Journal of Innovation and Technology Management, 14 (04), 1750019. doi: https://doi.org/10.1142/s0219877017500195
Shostak, I., Danova, M., Kuznetsova, Y. (2016). Foresight-Research for Green IT Engineering Development. Studies in Systems, Decision and Control, 21–41. doi: https://doi.org/10.1007/978-3-319-44162-7_2
Dolhikh, A. O., Baybuz, O. H. (2018). Analysis of methods, models and software tools forecasting time series. Open information and computer integrated technologies, 79, 74–87.
Romanenkov, Yu. (2015). Analysis of the predictive properties of Brown's model in the extended domain of the internal parameter. MOTROL. Commission of Motorization and Energetics in Agriculture, 17 (8), 27–34.
Romanenkov, Yu. A. (2015). Parametric synthesis of Brown's predictive model based on phase portraits of time series. In Information and modeling technologies, 54.
Copyright (c) 2018 Yuri Romanenkov, Mariia Danova
This work is licensed under a Creative Commons Attribution 4.0 International License.
Our journal abides by the Creative Commons CC BY copyright rights and permissions for open access journals.
Authors, who are published in this journal, agree to the following conditions:
1. The authors reserve the right to authorship of the work and pass the first publication right of this work to the journal under the terms of a Creative Commons CC BY, which allows others to freely distribute the published research with the obligatory reference to the authors of the original work and the first publication of the work in this journal.
2. The authors have the right to conclude separate supplement agreements that relate to non-exclusive work distribution in the form in which it has been published by the journal (for example, to upload the work to the online storage of the journal or publish it as part of a monograph), provided that the reference to the first publication of the work in this journal is included.
