IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v465y2017icp49-61.html
   My bibliography  Save this article

The rapid bi-level exploration on the evolution of regional solar energy development

Author

Listed:
  • Guan, Qing
  • An, Haizhong
  • Li, Huajiao
  • Hao, Xiaoqing

Abstract

As one of the renewable energy, solar energy is experiencing increased but exploratory development worldwide. The positive or negative influences of regional characteristics, like economy, production capacity and allowance policies, make them have uneven solar energy development. In this paper, we aim at quickly exploring the features of provincial solar energy development, and their concerns about solar energy. We take China as a typical case, and combine text mining and two-actor networks. We find that the classification of levels based on certain nodes and the amount of degree avoids missing meaningful information that may be ignored by global level results. Moreover, eastern provinces are hot focus for the media, western countries are key to bridge the networks and special administrative region has local development features; third, most focus points are more about the application than the improvement of material. The exploration of news provides practical information to adjust researches and development strategies of solar energy. Moreover, the bi-level exploration, which can also be expanded to multi-level, is helpful for governments or researchers to grasp more targeted and precise knowledge.

Suggested Citation

  • Guan, Qing & An, Haizhong & Li, Huajiao & Hao, Xiaoqing, 2017. "The rapid bi-level exploration on the evolution of regional solar energy development," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 49-61.
    • Handle: RePEc:eee:phsmap:v:465:y:2017:i:c:p:49-61
    DOI: 10.1016/j.physa.2016.08.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116305234
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2016.08.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Adil, Ali M. & Ko, Yekang, 2016. "Socio-technical evolution of Decentralized Energy Systems: A critical review and implications for urban planning and policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1025-1037.
    2. Li, Huajiao & An, Haizhong & Gao, Xiangyun & Huang, Jiachen & Xu, Qun, 2014. "On the topological properties of the cross-shareholding networks of listed companies in China: Taking shareholders’ cross-shareholding relationships into account," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 80-88.
    3. Jana Diesner & Kathleen M. Carley & Laurent Tambayong, 2012. "Extracting socio-cultural networks of the Sudan from open-source, large-scale text data," Computational and Mathematical Organization Theory, Springer, vol. 18(3), pages 328-339, September.
    4. Kwan, Calvin Lee, 2012. "Influence of local environmental, social, economic and political variables on the spatial distribution of residential solar PV arrays across the United States," Energy Policy, Elsevier, vol. 47(C), pages 332-344.
    5. Frisari, Gianleo & Stadelmann, Martin, 2015. "De-risking concentrated solar power in emerging markets: The role of policies and international finance institutions," Energy Policy, Elsevier, vol. 82(C), pages 12-22.
    6. Li, Huajiao & Fang, Wei & An, Haizhong & Yan, LiLi, 2014. "The shareholding similarity of the shareholders of the worldwide listed energy companies based on a two-mode primitive network and a one-mode derivative holding-based network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 525-532.
    7. Tracy Holt & Jeffrey C. Johnson & James D. Brinkley & Kathleen M. Carley & Janna Caspersen, 2012. "Structure of ethnic violence in Sudan: a semi-automated network analysis of online news (2003–2010)," Computational and Mathematical Organization Theory, Springer, vol. 18(3), pages 340-355, September.
    8. Lee, Woo Jin & Sohn, So Young, 2014. "Patent analysis to identify shale gas development in China and the United States," Energy Policy, Elsevier, vol. 74(C), pages 111-115.
    9. Algieri, Bernardina & Aquino, Antonio & Succurro, Marianna, 2011. "Going “green”: trade specialisation dynamics in the solar photovoltaic sector," Energy Policy, Elsevier, vol. 39(11), pages 7275-7283.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Dong-xiao & Chen, Zi-yue & Yang, Yong-cong & Nie, Pu-yan, 2019. "Green financial policies and capital flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 135-146.
    2. Samuel Zanferdini Oliva & Livia Oliveira-Ciabati & Denise Gazotto Dezembro & Mário Sérgio Adolfi Júnior & Maísa Carvalho Silva & Hugo Cesar Pessotti & Juliana Tarossi Pollettini, 2021. "Text structuring methods based on complex network: a systematic review," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1471-1493, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. An, Feng & Gao, Xiangyun & Guan, Jianhe & Huang, Shupei & Liu, Qian, 2017. "Modeling the interdependent network based on two-mode networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 57-67.
    2. Sun, Bowen & Li, Huajiao & An, Pengli & Wang, Ze, 2020. "Dynamic energy stock selection based on shareholders’ coholding network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    3. Xi, Xian & An, Haizhong, 2018. "Research on energy stock market associated network structure based on financial indicators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1309-1323.
    4. Sun, Qingru & Gao, Xiangyun & Zhong, Weiqiong & Liu, Nairong, 2017. "The stability of the international oil trade network from short-term and long-term perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 345-356.
    5. Li, Huajiao & An, Haizhong & Wang, Yue & Huang, Jiachen & Gao, Xiangyun, 2016. "Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 657-669.
    6. An, Qier & An, Haizhong & Wang, Lang & Gao, Xiangyun & Lv, Na, 2015. "Analysis of embodied exergy flow between Chinese industries based on network theory," Ecological Modelling, Elsevier, vol. 318(C), pages 26-35.
    7. An, Pengli & Li, Huajiao & Zhou, Jinsheng & Chen, Fan, 2017. "The evolution analysis of listed companies co-holding non-listed financial companies based on two-mode heterogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 558-568.
    8. Qing Guan & Haizhong An & Xiaoqing Hao & Xiaoliang Jia, 2016. "The Impact of Countries’ Roles on the International Photovoltaic Trade Pattern: The Complex Networks Analysis," Sustainability, MDPI, vol. 8(4), pages 1-16, March.
    9. Li, Huajiao & An, Haizhong & Huang, Jiachen & Huang, Xuan & Mou, Songtao & Shi, Yanli, 2016. "The evolutionary stability of shareholders’ co-holding behavior for China’s listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks," Applied Energy, Elsevier, vol. 162(C), pages 1601-1607.
    10. Hossein Dastkhan & Naser Shams Gharneh, 2016. "Determination of Systemically Important Companies with Cross-Shareholding Network Analysis: A Case Study from an Emerging Market," IJFS, MDPI, vol. 4(3), pages 1-17, June.
    11. Li, Huajiao & Fang, Wei & An, Haizhong & Gao, Xiangyun & Yan, Lili, 2016. "Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 224-232.
    12. Li, Huajiao & An, Haizhong & Fang, Wei & Wang, Yue & Zhong, Weiqiong & Yan, Lili, 2017. "Global energy investment structure from the energy stock market perspective based on a Heterogeneous Complex Network Model," Applied Energy, Elsevier, vol. 194(C), pages 648-657.
    13. Antoine Boche & Clément Foucher & Luiz Fernando Lavado Villa, 2022. "Understanding Microgrid Sustainability: A Systemic and Comprehensive Review," Energies, MDPI, vol. 15(8), pages 1-29, April.
    14. Moroni, Stefano & Antoniucci, Valentina & Bisello, Adriano, 2016. "Energy sprawl, land taking and distributed generation: towards a multi-layered density," Energy Policy, Elsevier, vol. 98(C), pages 266-273.
    15. Klein, Martin & Deissenroth, Marc, 2017. "When do households invest in solar photovoltaics? An application of prospect theory," Energy Policy, Elsevier, vol. 109(C), pages 270-278.
    16. Li, Huajiao & An, Haizhong & Liu, Xueyong & Gao, Xiangyun & Fang, Wei & An, Feng, 2016. "Price fluctuation in the energy stock market based on fluctuation and co-fluctuation matrix transmission networks," Energy, Elsevier, vol. 117(P1), pages 73-83.
    17. Fonseca, Juan D. & Commenge, Jean-Marc & Camargo, Mauricio & Falk, Laurent & Gil, Iván D., 2021. "Sustainability analysis for the design of distributed energy systems: A multi-objective optimization approach," Applied Energy, Elsevier, vol. 290(C).
    18. Kim, Dong Ha & Lee, Bo Kyeong & Sohn, So Young, 2016. "Quantifying technology–industry spillover effects based on patent citation network analysis of unmanned aerial vehicle (UAV)," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 140-157.
    19. Gottschamer, L. & Zhang, Q., 2016. "Interactions of factors impacting implementation and sustainability of renewable energy sourced electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 164-174.
    20. Liu, Shen & Colson, Gregory & Hao, Na & Wetzstein, Michael, 2018. "Toward an optimal household solar subsidy: A social-technical approach," Energy, Elsevier, vol. 147(C), pages 377-387.

    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:eee:phsmap:v:465:y:2017:i:c:p:49-61. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.