IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v69y2014icp248-257.html
   My bibliography  Save this article

Diffusion of renewable energy technologies in South Korea on incorporating their competitive interrelationships

Author

Listed:
  • Huh, Sung-Yoon
  • Lee, Chul-Yong

Abstract

Renewable energy technologies (RETs) have attracted significant public attention for several reasons, the most important being that they are clean alternative energy sources that help reduce greenhouse gas emissions. To increase the probability that RETs will be successful, it is essential to reduce the uncertainty about its adoption with accurate long-term demand forecasting. This study develops a diffusion model that incorporates the effect of competitive interrelationships among renewable sources to forecast the growth pattern of five RETs: solar photovoltaic, wind power, and fuel cell in the electric power sector, and solar thermal and geothermal energy in the heating sector. The 2-step forecasting procedure is based on the Bayus, (1993. Manage. Sci. 39, 11, 1319–1333) price function and a diffusion model suggested by Hahn et al. (1994. Marketing Sci. 13, 3, 224–247). In an empirical analysis, the model is applied to the South Korean renewable energy market.

Suggested Citation

  • Huh, Sung-Yoon & Lee, Chul-Yong, 2014. "Diffusion of renewable energy technologies in South Korea on incorporating their competitive interrelationships," Energy Policy, Elsevier, vol. 69(C), pages 248-257.
  • Handle: RePEc:eee:enepol:v:69:y:2014:i:c:p:248-257
    DOI: 10.1016/j.enpol.2014.02.028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421514001177
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2014.02.028?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. Jehoshua Eliashberg & Abel P. Jeuland, 1986. "The Impact of Competitive Entry in a Developing Market Upon Dynamic Pricing Strategies," Marketing Science, INFORMS, vol. 5(1), pages 20-36.
    2. Ibenholt, Karin, 2002. "Explaining learning curves for wind power," Energy Policy, Elsevier, vol. 30(13), pages 1181-1189, October.
    3. Pettersson, Maria & Ek, Kristina & Söderholm, Kristina & Söderholm, Patrik, 2010. "Wind power planning and permitting: Comparative perspectives from the Nordic countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3116-3123, December.
    4. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    5. Cho, Youngsang & Koo, Yoonmo, 2012. "Investigation of the effect of secondary market on the diffusion of innovation," Technological Forecasting and Social Change, Elsevier, vol. 79(7), pages 1362-1371.
    6. Dinica, Valentina, 2006. "Support systems for the diffusion of renewable energy technologies--an investor perspective," Energy Policy, Elsevier, vol. 34(4), pages 461-480, March.
    7. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    8. Han, Jingyi & Mol, Arthur P.J. & Lu, Yonglong & Zhang, Lei, 2009. "Onshore wind power development in China: Challenges behind a successful story," Energy Policy, Elsevier, vol. 37(8), pages 2941-2951, August.
    9. Jacobsson, Staffan & Lauber, Volkmar, 2006. "The politics and policy of energy system transformation--explaining the German diffusion of renewable energy technology," Energy Policy, Elsevier, vol. 34(3), pages 256-276, February.
    10. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601, April.
    11. Harijan, Khanji & Uqaili, Mohammad A. & Memon, Mujeebuddin & Mirza, Umar K., 2011. "Forecasting the diffusion of wind power in Pakistan," Energy, Elsevier, vol. 36(10), pages 6068-6073.
    12. Dan Horsky, 1990. "A Diffusion Model Incorporating Product Benefits, Price, Income and Information," Marketing Science, INFORMS, vol. 9(4), pages 342-365.
    13. Dalla Valle, Alessandra & Furlan, Claudia, 2011. "Forecasting accuracy of wind power technology diffusion models across countries," International Journal of Forecasting, Elsevier, vol. 27(2), pages 592-601.
    14. Patrik Söderholm & Ger Klaassen, 2007. "Wind Power in Europe: A Simultaneous Innovation–Diffusion Model," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 36(2), pages 163-190, February.
    15. Vijay Mahajan & Eitan Muller & Frank M. Bass, 1995. "Diffusion of New Products: Empirical Generalizations and Managerial Uses," Marketing Science, INFORMS, vol. 14(3_supplem), pages 79-88.
    16. Lund, Peter, 2006. "Market penetration rates of new energy technologies," Energy Policy, Elsevier, vol. 34(17), pages 3317-3326, November.
    17. Barry L. Bayus, 1993. "High-Definition Television: Assessing Demand Forecasts for a Next Generation Consumer Durable," Management Science, INFORMS, vol. 39(11), pages 1319-1333, November.
    18. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    19. Dipak Jain & Vijay Mahajan & Eitan Muller, 1991. "Innovation Diffusion in the Presence of Supply Restrictions," Marketing Science, INFORMS, vol. 10(1), pages 83-90.
    20. Geroski, P. A., 2000. "Models of technology diffusion," Research Policy, Elsevier, vol. 29(4-5), pages 603-625, April.
    21. Kumbaroglu, Gürkan & Madlener, Reinhard & Demirel, Mustafa, 2008. "A real options evaluation model for the diffusion prospects of new renewable power generation technologies," Energy Economics, Elsevier, vol. 30(4), pages 1882-1908, July.
    22. Teck-Hua Ho & Sergei Savin & Christian Terwiesch, 2002. "Managing Demand and Sales Dynamics in New Product Diffusion Under Supply Constraint," Management Science, INFORMS, vol. 48(2), pages 187-206, February.
    23. Jacobsson, Staffan & Johnson, Anna, 2000. "The diffusion of renewable energy technology: an analytical framework and key issues for research," Energy Policy, Elsevier, vol. 28(9), pages 625-640, July.
    24. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    25. Usha Rao, K. & Kishore, V.V.N., 2009. "Wind power technology diffusion analysis in selected states of India," Renewable Energy, Elsevier, vol. 34(4), pages 983-988.
    26. Söderholm, Patrik & Ek, Kristina & Pettersson, Maria, 2007. "Wind power development in Sweden: Global policies and local obstacles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(3), pages 365-400, April.
    27. Dinica, Valentina, 2008. "Initiating a sustained diffusion of wind power: The role of public-private partnerships in Spain," Energy Policy, Elsevier, vol. 36(9), pages 3562-3571, September.
    28. Isoard, Stephane & Soria, Antonio, 2001. "Technical change dynamics: evidence from the emerging renewable energy technologies," Energy Economics, Elsevier, vol. 23(6), pages 619-636, November.
    29. Purohit, Pallav & Michaelowa, Axel, 2007. "CDM potential of bagasse cogeneration in India," Energy Policy, Elsevier, vol. 35(10), pages 4779-4798, October.
    30. Jain, Dipak C & Rao, Ram C, 1990. "Effect of Price on the Demand for Durables: Modeling, Estimation, and Findings," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 163-170, April.
    31. Purohit, Pallav, 2008. "Small hydro power projects under clean development mechanism in India: A preliminary assessment," Energy Policy, Elsevier, vol. 36(6), pages 2000-2015, June.
    32. Purohit, Pallav & Kandpal, Tara C., 2005. "Renewable energy technologies for irrigation water pumping in India: projected levels of dissemination, energy delivery and investment requirements using available diffusion models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 9(6), pages 592-607, December.
    33. Maya Sopha, Bertha & Klöckner, Christian A. & Hertwich, Edgar G., 2011. "Exploring policy options for a transition to sustainable heating system diffusion using an agent-based simulation," Energy Policy, Elsevier, vol. 39(5), pages 2722-2729, May.
    34. Haehnlein, Stefanie & Bayer, Peter & Blum, Philipp, 2010. "International legal status of the use of shallow geothermal energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 2611-2625, December.
    35. Minhi Hahn & Sehoon Park & Lakshman Krishnamurthi & Andris A. Zoltners, 1994. "Analysis of New Product Diffusion Using a Four-Segment Trial-Repeat Model," Marketing Science, INFORMS, vol. 13(3), pages 224-247.
    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, Chunmeng & Bu, Siqi & Fan, Yi & Wan, Wayne Xinwei & Wang, Ruoheng & Foley, Aoife, 2023. "Data-driven prediction and evaluation on future impact of energy transition policies in smart regions," Applied Energy, Elsevier, vol. 332(C).
    2. Heshmati, Almas & Kumbhakar, Subal C. & Sun, Kai, 2014. "Estimation of productivity in Korean electric power plants: A semiparametric smooth coefficient model," Energy Economics, Elsevier, vol. 45(C), pages 491-500.
    3. Reddy, B. Sudhakara, 2018. "Economic dynamics and technology diffusion in indian power sector," Energy Policy, Elsevier, vol. 120(C), pages 425-435.
    4. Seoin Baek & Heetae Kim & Hyun Joon Chang, 2016. "Optimal Hybrid Renewable Airport Power System: Empirical Study on Incheon International Airport, South Korea," Sustainability, MDPI, vol. 8(6), pages 1-13, June.
    5. Lee, Boreum & Park, Junhyung & Lee, Hyunjun & Byun, Manhee & Yoon, Chang Won & Lim, Hankwon, 2019. "Assessment of the economic potential: COx-free hydrogen production from renewables via ammonia decomposition for small-sized H2 refueling stations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    6. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting the diffusion of renewable electricity considering the impact of policy and oil prices: The case of South Korea," Applied Energy, Elsevier, vol. 197(C), pages 29-39.
    7. Shin, Jungwoo & Lee, Chul-Yong & Kim, Hongbum, 2016. "Technology and demand forecasting for carbon capture and storage technology in South Korea," Energy Policy, Elsevier, vol. 98(C), pages 1-11.
    8. Furlan, Claudia & Mortarino, Cinzia, 2018. "Forecasting the impact of renewable energies in competition with non-renewable sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1879-1886.
    9. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    10. Kyeongsik Yoo & Eunil Park & Heetae Kim & Jay Y. Ohm & Taeyong Yang & Ki Joon Kim & Hyun Joon Chang & Angel P. Del Pobil, 2014. "Optimized Renewable and Sustainable Electricity Generation Systems for Ulleungdo Island in South Korea," Sustainability, MDPI, vol. 6(11), pages 1-11, November.
    11. Mukisa, Nicholas & Zamora, Ramon & Lie, Tek Tjing, 2021. "Diffusion forecast for grid-tied rooftop solar photovoltaic technology under store-on grid scheme model in Sub-Saharan Africa: Government role assessment," Renewable Energy, Elsevier, vol. 180(C), pages 516-535.
    12. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting new and renewable energy supply through a bottom-up approach: The case of South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 207-217.
    13. Chul-Yong Lee & Sung-Yoon Huh, 2017. "Technology Forecasting Using a Diffusion Model Incorporating Replacement Purchases," Sustainability, MDPI, vol. 9(6), pages 1-14, June.
    14. Park, Sang Yong & Yun, Bo-Yeong & Yun, Chang Yeol & Lee, Duk Hee & Choi, Dong Gu, 2016. "An analysis of the optimum renewable energy portfolio using the bottom–up model: Focusing on the electricity generation sector in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 319-329.
    15. Bodo, Peter, 2016. "MADness in the method: On the volatility and irregularity of technology diffusion," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 2-11.
    16. Xin-gang, Zhao & Wei, Wang & Jieying, Wang, 2022. "The policy effects of demand-pull and technology-push on the diffusion of wind power: A scenario analysis based on system dynamics approach," Energy, Elsevier, vol. 261(PA).
    17. Xu, Jiuping & Li, Li & Zheng, Bobo, 2016. "Wind energy generation technological paradigm diffusion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 436-449.

    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. Xu, Jiuping & Li, Li & Zheng, Bobo, 2016. "Wind energy generation technological paradigm diffusion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 436-449.
    2. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting the diffusion of renewable electricity considering the impact of policy and oil prices: The case of South Korea," Applied Energy, Elsevier, vol. 197(C), pages 29-39.
    3. Barnes, Belinda & Southwell, Darren & Bruce, Sarah & Woodhams, Felicity, 2014. "Additionality, common practice and incentive schemes for the uptake of innovations," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 43-61.
    4. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    5. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    6. Cong, Rong-Gang, 2013. "An optimization model for renewable energy generation and its application in China: A perspective of maximum utilization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 17(C), pages 94-103.
    7. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    8. Ramírez-Hassan, Andrés & Montoya-Blandón, Santiago, 2020. "Forecasting from others’ experience: Bayesian estimation of the generalized Bass model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 442-465.
    9. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    10. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    11. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    12. Harijan, Khanji & Uqaili, Mohammad A. & Memon, Mujeebuddin & Mirza, Umar K., 2011. "Forecasting the diffusion of wind power in Pakistan," Energy, Elsevier, vol. 36(10), pages 6068-6073.
    13. Xu, Mei & Xie, Pu & Xie, Bai-Chen, 2020. "Study of China's optimal solar photovoltaic power development path to 2050," Resources Policy, Elsevier, vol. 65(C).
    14. Lu, Ze-Yu & Li, Wen-Hua & Xie, Bai-Chen & Shang, Li-Feng, 2015. "Study on China’s wind power development path—Based on the target for 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 197-208.
    15. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    16. Radpour, S. & Gemechu, E. & Ahiduzzaman, Md & Kumar, A., 2021. "Developing a framework to assess the long-term adoption of renewable energy technologies in the electric power sector: The effects of carbon price and economic incentives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    17. Furlan, Claudia & Guidolin, Mariangela & Guseo, Renato, 2016. "Has the Fukushima accident influenced short-term consumption in the evolution of nuclear energy? An analysis of the world and seven leading countries," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 37-49.
    18. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    19. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    20. Duan, Hong-Bo & Zhu, Lei & Fan, Ying, 2014. "A cross-country study on the relationship between diffusion of wind and photovoltaic solar technology," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 156-169.

    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:enepol:v:69:y:2014:i:c:p:248-257. 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.elsevier.com/locate/enpol .

    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.