IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v134y2019ics0301421519304938.html
   My bibliography  Save this article

Transitions between technological generations of alternative fuel vehicles in Brazil

Author

Listed:
  • Brito, Thiago Luis Felipe
  • Islam, Towhidul
  • Stettler, Marc
  • Mouette, Dominique
  • Meade, Nigel
  • Moutinho dos Santos, Edmilson

Abstract

The transportation sector is responsible for nearly a quarter of greenhouse gases emissions (GHG); thus, incisive policies are necessary to mitigate the sector’s effect on climate change. Promoting alternative fuel vehicles (AFV) is an essential strategy to reduce GHG emissions in the short term. Here, we study the effects of governmental incentives on the diffusion of ethanol and flex-fuel vehicle technologies in Brazil. We use a multi-generation diffusion model which assumes that new technologies introduce fresh market potential for adopters as well as upgraders from established technologies. Our analysis indicates that tax rates affected the adoption of both gasoline and ethanol technology, but for flex vehicles, the effect of taxation is not significant. The effect of fuel price shocks during the 1990s meant that the introduction of ethanol technology made no significant impact on market potential and a negative word-of-mouth effect contributed to the technology’s failure. In contrast, the introduction of flex technology led to almost a doubling of total market potential. As policy suggestions, we emphasise the importance of tax reduction in addition to promoting versatile technologies, which insulate consumers against price fluctuations.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:enepol:v:134:y:2019:i:c:s0301421519304938
    DOI: 10.1016/j.enpol.2019.110915
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421519304938
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2019.110915?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. Bodas Freitas, Isabel Maria & Dantas, Eva & Iizuka, Michiko, 2012. "The Kyoto mechanisms and the diffusion of renewable energy technologies in the BRICS," Energy Policy, Elsevier, vol. 42(C), pages 118-128.
    2. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    3. Negro, Simona O. & Alkemade, Floortje & Hekkert, Marko P., 2012. "Why does renewable energy diffuse so slowly? A review of innovation system problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3836-3846.
    4. Baran, Renato & Legey, Luiz Fernando Loureiro, 2013. "The introduction of electric vehicles in Brazil: Impacts on oil and electricity consumption," Technological Forecasting and Social Change, Elsevier, vol. 80(5), pages 907-917.
    5. Egbue, Ona & Long, Suzanna, 2012. "Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions," Energy Policy, Elsevier, vol. 48(C), pages 717-729.
    6. Ibenholt, Karin, 2002. "Explaining learning curves for wind power," Energy Policy, Elsevier, vol. 30(13), pages 1181-1189, October.
    7. 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.
    8. Nastari, Plinio Mario, 1983. "The role of sugar cane in Brazil's history and economy," ISU General Staff Papers 198301010800009947, Iowa State University, Department of Economics.
    9. Brito, Thiago Luis Felipe & Moutinho dos Santos, Edmilson & Galbieri, Rodrigo & Costa, Hirdan Katarina de Medeiros, 2017. "Qualitative Comparative Analysis of cities that introduced compressed natural gas to their urban bus fleet," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 502-508.
    10. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    11. Aguirre, Mariana & Ibikunle, Gbenga, 2014. "Determinants of renewable energy growth: A global sample analysis," Energy Policy, Elsevier, vol. 69(C), pages 374-384.
    12. Jeroen Struben & John D Sterman, 2008. "Transition Challenges for Alternative Fuel Vehicle and Transportation Systems," Environment and Planning B, , vol. 35(6), pages 1070-1097, December.
    13. Furtado, André Tosi & Scandiffio, Mirna Ivonne Gaya & Cortez, Luis Augusto Barbosa, 2011. "The Brazilian sugarcane innovation system," Energy Policy, Elsevier, vol. 39(1), pages 156-166, January.
    14. Stefan Stremersch & Eitan Muller & Renana Peres, 2010. "Does new product growth accelerate across technology generations?," Marketing Letters, Springer, vol. 21(2), pages 103-120, June.
    15. Jeroen Struben & John D. Sterman, 2008. "Transition Challenges for Alternative Fuel Vehicle and Transportation Systems," Post-Print hal-02312277, HAL.
    16. Bastin, Cristina & Szklo, Alexandre & Rosa, Luiz Pinguelli, 2010. "Diffusion of new automotive technologies for improving energy efficiency in Brazil's light vehicle fleet," Energy Policy, Elsevier, vol. 38(7), pages 3586-3597, July.
    17. Nardon, Luciara & Aten, Kathryn, 2008. "Beyond a better mousetrap: A cultural analysis of the adoption of ethanol in Brazil," Journal of World Business, Elsevier, vol. 43(3), pages 261-273, July.
    18. Collantes, Gustavo O, 2007. "Incorporating stakeholders' perspectives into models of new technology diffusion: The case of fuel-cell vehicles," Institute of Transportation Studies, Working Paper Series qt9bm1w968, Institute of Transportation Studies, UC Davis.
    19. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    20. Carlos Bastian-Pinto & Luiz Brandão & Mariana Lemos Alves, 2010. "Valuing the switching flexibility of the ethanol-gas flex fuel car," Annals of Operations Research, Springer, vol. 176(1), pages 333-348, April.
    21. 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.
    22. Sierzchula, William & Bakker, Sjoerd & Maat, Kees & van Wee, Bert, 2014. "The influence of financial incentives and other socio-economic factors on electric vehicle adoption," Energy Policy, Elsevier, vol. 68(C), pages 183-194.
    23. Pfeiffer, Birte & Mulder, Peter, 2013. "Explaining the diffusion of renewable energy technology in developing countries," Energy Economics, Elsevier, vol. 40(C), pages 285-296.
    24. Goldemberg, José & Schaeffer, Roberto & Szklo, Alexandre & Lucchesi, Rodrigo, 2014. "Oil and natural gas prospects in South America: Can the petroleum industry pave the way for renewables in Brazil?," Energy Policy, Elsevier, vol. 64(C), pages 58-70.
    25. Gnann, Till & Plötz, Patrick, 2015. "A review of combined models for market diffusion of alternative fuel vehicles and their refueling infrastructure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 783-793.
    26. Kloess, Maximilian & Müller, Andreas, 2011. "Simulating the impact of policy, energy prices and technological progress on the passenger car fleet in Austria--A model based analysis 2010-2050," Energy Policy, Elsevier, vol. 39(9), pages 5045-5062, September.
    27. Vijay Mahajan & Eitan Muller & Roger A. Kerin, 1984. "Introduction Strategy for New Products with Positive and Negative Word-of-Mouth," Management Science, INFORMS, vol. 30(12), pages 1389-1404, December.
    28. Langbroek, Joram H.M. & Franklin, Joel P. & Susilo, Yusak O., 2016. "The effect of policy incentives on electric vehicle adoption," Energy Policy, Elsevier, vol. 94(C), pages 94-103.
    29. Frits M. Andersen & Helge V. Larsen & Mette Skovgaard, 2007. "A European model for the number of End-of-Life Vehicles," International Journal of Automotive Technology and Management, Inderscience Enterprises Ltd, vol. 7(4), pages 343-355.
    30. Munoz, Miquel & Oschmann, Volker & David Tabara, J., 2007. "Harmonization of renewable electricity feed-in laws in the European Union," Energy Policy, Elsevier, vol. 35(5), pages 3104-3114, May.
    31. John Leslie King & Vijay Gurbaxani & Kenneth L. Kraemer & F. Warren McFarlan & K. S. Raman & C. S. Yap, 1994. "Institutional Factors in Information Technology Innovation," Information Systems Research, INFORMS, vol. 5(2), pages 139-169, June.
    32. Zhengrui Jiang & Dipak C. Jain, 2012. "A Generalized Norton-Bass Model for Multigeneration Diffusion," Management Science, INFORMS, vol. 58(10), pages 1887-1897, October.
    33. 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.
    34. 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.
    35. Moreira, Jose R. & Goldemberg, Jose, 1999. "The alcohol program," Energy Policy, Elsevier, vol. 27(4), pages 229-245, April.
    36. Ferreira, Agmar & Kunh, Sheila S. & Fagnani, Kátia C. & De Souza, Tiago A. & Tonezer, Camila & Dos Santos, Geocris Rodrigues & Coimbra-Araújo, Carlos H., 2018. "Economic overview of the use and production of photovoltaic solar energy in brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 181-191.
    37. Leibowicz, Benjamin D., 2018. "Policy recommendations for a transition to sustainable mobility based on historical diffusion dynamics of transport systems," Energy Policy, Elsevier, vol. 119(C), pages 357-366.
    38. Goldemberg, José & Coelho, Suani Teixeira & Guardabassi, Patricia, 2008. "The sustainability of ethanol production from sugarcane," Energy Policy, Elsevier, vol. 36(6), pages 2086-2097, June.
    39. Guidolin, Mariangela & Guseo, Renato, 2016. "The German energy transition: Modeling competition and substitution between nuclear power and Renewable Energy Technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1498-1504.
    40. Gerard J. Tellis & Stefan Stremersch & Eden Yin, 2003. "The International Takeoff of New Products: The Role of Economics, Culture, and Country Innovativeness," Marketing Science, INFORMS, vol. 22(2), pages 188-208, October.
    41. Massiani, Jérôme & Gohs, Andreas, 2015. "The choice of Bass model coefficients to forecast diffusion for innovative products: An empirical investigation for new automotive technologies," Research in Transportation Economics, Elsevier, vol. 50(C), pages 17-28.
    42. Peter, Raja & Ramaseshan, B & Nayar, C.V, 2002. "Conceptual model for marketing solar based technology to developing countries," Renewable Energy, Elsevier, vol. 25(4), pages 511-524.
    43. Meade, Nigel & Islam, Towhidul, 2015. "Modelling European usage of renewable energy technologies for electricity generation," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 497-509.
    44. Jenn, Alan & Springel, Katalin & Gopal, Anand R., 2018. "Effectiveness of electric vehicle incentives in the United States," Energy Policy, Elsevier, vol. 119(C), pages 349-356.
    45. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    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. Rodrigues Teixeira, Ana Carolina & Machado, Pedro Gerber & Borges, Raquel Rocha & Felipe Brito, Thiago Luis & Moutinho dos Santos, Edmilson & Mouette, Dominique, 2021. "The use of liquefied natural gas as an alternative fuel in freight transport – Evidence from a driver's point of view," Energy Policy, Elsevier, vol. 149(C).
    2. Nilsa Duarte da Silva Lima & Irenilza de Alencar Nääs & João Gilberto Mendes dos Reis & Raquel Baracat Tosi Rodrigues da Silva, 2020. "Classifying the Level of Energy-Environmental Efficiency Rating of Brazilian Ethanol," Energies, MDPI, vol. 13(8), pages 1-16, April.
    3. Anna Brdulak & Grażyna Chaberek & Jacek Jagodziński, 2020. "Development Forecasts for the Zero-Emission Bus Fleet in Servicing Public Transport in Chosen EU Member Countries," Energies, MDPI, vol. 13(16), pages 1-20, August.
    4. Ioana Ancuta Iancu & Patrick Hendrick & Dan Doru Micu & Denisa Stet & Levente Czumbil & Stefan Dragos Cirstea, 2023. "The Influence of Cultural Factors on Choosing Low-Emission Passenger Cars," Sustainability, MDPI, vol. 15(8), pages 1-18, April.

    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. 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.
    2. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    3. 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).
    4. Brozynski, Max T. & Leibowicz, Benjamin D., 2022. "A multi-level optimization model of infrastructure-dependent technology adoption: Overcoming the chicken-and-egg problem," European Journal of Operational Research, Elsevier, vol. 300(2), pages 755-770.
    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. 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.
    7. 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.
    8. Guidolin, Mariangela & Guseo, Renato, 2016. "The German energy transition: Modeling competition and substitution between nuclear power and Renewable Energy Technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1498-1504.
    9. Dong, Changgui & Sigrin, Benjamin & Brinkman, Gregory, 2017. "Forecasting residential solar photovoltaic deployment in California," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 251-265.
    10. Shi, Xiaohui & Chumnumpan, Pattarin, 2019. "Modelling market dynamics of multi-brand and multi-generational products," European Journal of Operational Research, Elsevier, vol. 279(1), pages 199-210.
    11. 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.
    12. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    13. 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.
    14. 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.
    15. Laciana, Carlos E. & Rovere, Santiago L. & Podestá, Guillermo P., 2013. "Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1873-1884.
    16. 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).
    17. Singhal, Shakshi & Anand, Adarsh & Singh, Ompal, 2020. "Studying dynamic market size-based adoption modeling & product diffusion under stochastic environment," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    18. Shepherd, Simon & Bonsall, Peter & Harrison, Gillian, 2012. "Factors affecting future demand for electric vehicles: A model based study," Transport Policy, Elsevier, vol. 20(C), pages 62-74.
    19. Martin Zsifkovits & Markus Günther, 2015. "Simulating resistances in innovation diffusion over multiple generations: an agent-based approach for fuel-cell vehicles," 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. 23(2), pages 501-522, June.
    20. Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.

    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:134:y:2019:i:c:s0301421519304938. 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.