IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i10p3709-d175946.html
   My bibliography  Save this article

Generating Future-Oriented Energy Policies and Technologies from the Multidisciplinary Group Discussions by Text-Mining-Based Identification of Topics and Experts

Author

Listed:
  • Jong Hwan Suh

    () (Department of Management Information Systems, BERI, Gyeongsang National University, 501 Jinjudae-ro Jinju-si, Gyeongsangnam-do 52828, Korea)

Abstract

With increasing problems and challenging issues for sustainability under climate change, energy research has gained a lot of global attention from citizens, business and government on an important mission to make energy available in sustainable and clean ways. Moreover, as the bigger energy issues get, the more closely they are related to humans, so the multidisciplinary approach in energy research by integrating human sciences in energy domain has been called for and recognized to be of immense importance. However, so far most of the energy research has focused on one side such as economics and technology innovation. In addition, there have been limits to policymakers’ taking multidisciplinary perspectives for agenda-setting and policy-making on energy issues for future society under climate change. In this context, this paper proposes a systematic approach for agenda-setting and policy-making in future-oriented and multidisciplinary perspectives. In particular, it applies text-mining techniques to designing multidisciplinary group discussions and generates energy policies and technologies (EP&Ts) for the future society from the multidisciplinary perspectives. The proposed method was applied to South Korea. To sum up, the core energy-specific future trends in South Korea were identified and subsequently the top-priority future-oriented EP&Ts were generated for South Korea as follows: (i) real-time plan for electricity usage; (ii) purchase system, specialized for green energy products; (iii) cooperation association for sustainability; (iv) donating self-produced energy; (v) social media-based energy policy portal; and (vi) expert system designing the eco-friendly and low-energy indoor and outdoor designs. Thus, this paper has its novelty as the first trial that combines both qualitative and quantitative approaches for building up future-oriented strategies from the balanced and multidisciplinary perspectives. Eventually, it will help deal with bigger problems and grand challenges that our future energy society should overcome to sustain under climate change.

Suggested Citation

  • Jong Hwan Suh, 2018. "Generating Future-Oriented Energy Policies and Technologies from the Multidisciplinary Group Discussions by Text-Mining-Based Identification of Topics and Experts," Sustainability, MDPI, Open Access Journal, vol. 10(10), pages 1-33, October.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3709-:d:175946
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/10/3709/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/10/3709/
    Download Restriction: no

    References listed on IDEAS

    as
    1. Haegeman, Karel & Marinelli, Elisabetta & Scapolo, Fabiana & Ricci, Andrea & Sokolov, Alexander, 2013. "Quantitative and qualitative approaches in Future-oriented Technology Analysis (FTA): From combination to integration?," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 386-397.
    2. Schaefer, Manuel S. & Lloyd, Bob & Stephenson, Janet R., 2012. "The suitability of a feed-in tariff for wind energy in New Zealand—A study based on stakeholders' perspectives," Energy Policy, Elsevier, vol. 43(C), pages 80-91.
    3. Marques, António Cardoso & Fuinhas, José Alberto, 2012. "Is renewable energy effective in promoting growth?," Energy Policy, Elsevier, vol. 46(C), pages 434-442.
    4. Kowalski, Katharina & Stagl, Sigrid & Madlener, Reinhard & Omann, Ines, 2009. "Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1063-1074, September.
    5. al Irsyad, M Indra & Nepal, Rabindra, 2016. "A survey based approach to estimating the benefits of energy efficiency improvements in street lighting systems in Indonesia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1569-1577.
    6. Hailu, Yohannes G., 2012. "Measuring and monitoring energy access: Decision-support tools for policymakers in Africa," Energy Policy, Elsevier, vol. 47(S1), pages 56-63.
    7. Calcagnini, Giorgio & Giombini, Germana & Travaglini, Giuseppe, 2016. "Modelling energy intensity, pollution per capita and productivity in Italy: A structural VAR approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1482-1492.
    8. Yingjian, Li & Abakr, Yousif A. & Qi, Qiu & Xinkui, You & Jiping, Zhou, 2016. "Energy efficiency assessment of fixed asset investment projects – A case study of a Shenzhen combined-cycle power plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1195-1208.
    9. Schade, Jutta & Wallström, Peter & Olofsson, Thomas & Lagerqvist, Ove, 2013. "A comparative study of the design and construction process of energy efficient buildings in Germany and Sweden," Energy Policy, Elsevier, vol. 58(C), pages 28-37.
    10. Reichardt, Kristin & Negro, Simona O. & Rogge, Karoline S. & Hekkert, Marko P., 2016. "Analyzing interdependencies between policy mixes and technological innovation systems: The case of offshore wind in Germany," Technological Forecasting and Social Change, Elsevier, vol. 106(C), pages 11-21.
    11. Chuang, Ming Chih & Ma, Hwong Wen, 2013. "An assessment of Taiwan’s energy policy using multi-dimensional energy security indicators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 17(C), pages 301-311.
    12. Nishiguchi, Sho & Tabata, Tomohiro, 2016. "Assessment of social, economic, and environmental aspects of woody biomass energy utilization: Direct burning and wood pellets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1279-1286.
    13. Kumar, Abhishek & Sah, Bikash & Singh, Arvind R. & Deng, Yan & He, Xiangning & Kumar, Praveen & Bansal, R.C., 2017. "A review of multi criteria decision making (MCDM) towards sustainable renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 596-609.
    14. Roshan, Gh.R. & Orosa, J.A & Nasrabadi, T., 2012. "Simulation of climate change impact on energy consumption in buildings, case study of Iran," Energy Policy, Elsevier, vol. 49(C), pages 731-739.
    15. Abbas Mardani & Ahmad Jusoh & Edmundas Kazimieras Zavadskas & Fausto Cavallaro & Zainab Khalifah, 2015. "Sustainable and Renewable Energy: An Overview of the Application of Multiple Criteria Decision Making Techniques and Approaches," Sustainability, MDPI, Open Access Journal, vol. 7(10), pages 1-38, October.
    16. Zhao, Jing & Xin, Yajuan & Tong, Dingding, 2012. "Energy consumption quota of public buildings based on statistical analysis," Energy Policy, Elsevier, vol. 43(C), pages 362-370.
    17. Bauer, Fredric & Coenen, Lars & Hansen, Teis & McCormick, Kes & Palgan, Yuliya Voytenko, 2016. "Technological innovation systems for biorefineries – A review of the literature," Papers in Innovation Studies 2016/27, Lund University, CIRCLE - Center for Innovation, Research and Competences in the Learning Economy.
    18. Yu, Biying & Zhang, Junyi & Fujiwara, Akimasa, 2013. "Evaluating the direct and indirect rebound effects in household energy consumption behavior: A case study of Beijing," Energy Policy, Elsevier, vol. 57(C), pages 441-453.
    19. Azam, Muhammad & Khan, Abdul Qayyum & Zafeiriou, Eleni & Arabatzis, Garyfallos, 2016. "Socio-economic determinants of energy consumption: An empirical survey for Greece," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1556-1567.
    20. Kratochvíl, Petr & Tichý, Lukáš, 2013. "EU and Russian discourse on energy relations," Energy Policy, Elsevier, vol. 56(C), pages 391-406.
    21. Chou, Jui-Sheng & Ngo, Ngoc-Tri, 2016. "Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns," Applied Energy, Elsevier, vol. 177(C), pages 751-770.
    22. Nik, Vahid M., 2016. "Making energy simulation easier for future climate – Synthesizing typical and extreme weather data sets out of regional climate models (RCMs)," Applied Energy, Elsevier, vol. 177(C), pages 204-226.
    23. Van de Velde, Liesbeth & Verbeke, Wim & Popp, Michael & Van Huylenbroeck, Guido, 2010. "The importance of message framing for providing information about sustainability and environmental aspects of energy," Energy Policy, Elsevier, vol. 38(10), pages 5541-5549, October.
    24. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Khalifah, Zainab & Zakuan, Norhayati & Jusoh, Ahmad & Nor, Khalil Md & Khoshnoudi, Masoumeh, 2017. "A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 216-256.
    25. Xuejiao Ma & Dandan Liu, 2016. "Comparative Study of Hybrid Models Based on a Series of Optimization Algorithms and Their Application in Energy System Forecasting," Energies, MDPI, Open Access Journal, vol. 9(8), pages 1-34, August.
    26. Suh, Jong Hwan, 2015. "Forecasting the daily outbreak of topic-level political risk from social media using hidden Markov model-based techniques," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 115-132.
    27. García-Gusano, Diego & Espegren, Kari & Lind, Arne & Kirkengen, Martin, 2016. "The role of the discount rates in energy systems optimisation models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 56-72.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    multidisciplinary group discussion; future-oriented; energy policy; energy technology; climate change; sustainability; text-mining; visualization;

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3709-:d:175946. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (XML Conversion Team). General contact details of provider: https://www.mdpi.com/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.