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Social networks and renewable energy technology adoption: Empirical evidence from biogas adoption in China

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  • He, Pan
  • Lovo, Stefania
  • Veronesi, Marcella

Abstract

We provide novel empirical evidence on the association between social networks and the adoption of renewable energy technology. We distinguish between two main transmission mechanisms through which social networks can affect renewable energy technology adoption: information diffusion and social influence. Using primarily collected data on biogas adoption in rural China, we find that both mechanisms are at work. In addition, we find that information spreads through trusted network members, such as friends and family, while social influence is mainly exercised by government officials. Government officials are more likely to promote the adoption of technology leading by example rather than by spreading information.

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  • He, Pan & Lovo, Stefania & Veronesi, Marcella, 2022. "Social networks and renewable energy technology adoption: Empirical evidence from biogas adoption in China," Energy Economics, Elsevier, vol. 106(C).
    • Handle: RePEc:eee:eneeco:v:106:y:2022:i:c:s0140988321006277
    DOI: 10.1016/j.eneco.2021.105789
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    as
    1. Clark, Andrew E. & D’Ambrosio, Conchita & Zhu, Rong, 2021. "Job quality and workplace gender diversity in Europe," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 420-432.
    2. Michael Kremer & Edward Miguel, 2007. "The Illusion of Sustainability," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 1007-1065.
    3. Christopher F Baum & Arthur Lewbel, 2019. "Advice on using heteroskedasticity-based identification," Stata Journal, StataCorp LP, vol. 19(4), pages 757-767, December.
    4. Lori Beaman & Ariel BenYishay & Jeremy Magruder & Ahmed Mushfiq Mobarak, 2021. "Can Network Theory-Based Targeting Increase Technology Adoption?," American Economic Review, American Economic Association, vol. 111(6), pages 1918-1943, June.
    5. Timothy Conley & Udry Christopher, 2001. "Social Learning Through Networks: The Adoption of New Agricultural Technologies in Ghana," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 668-673.
    6. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    7. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    8. Emily Oster, 2019. "Unobservable Selection and Coefficient Stability: Theory and Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 187-204, April.
    9. Oriana Bandiera & Imran Rasul, 2006. "Social Networks and Technology Adoption in Northern Mozambique," Economic Journal, Royal Economic Society, vol. 116(514), pages 869-902, October.
    10. Marianne Bertrand & Erzo F. P. Luttmer & Sendhil Mullainathan, 2000. "Network Effects and Welfare Cultures," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(3), pages 1019-1055.
    11. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    12. Wahba, Jackline & Zenou, Yves, 2005. "Density, social networks and job search methods: Theory and application to Egypt," Journal of Development Economics, Elsevier, vol. 78(2), pages 443-473, December.
    13. Davillas, Apostolos & Burlinson, Andrew & Liu, Hui-Hsuan, 2022. "Getting warmer: Fuel poverty, objective and subjective health and well-being," Energy Economics, Elsevier, vol. 106(C).
    14. Jing Cai & Alain De Janvry & Elisabeth Sadoulet, 2015. "Social Networks and the Decision to Insure," American Economic Journal: Applied Economics, American Economic Association, vol. 7(2), pages 81-108, April.
    15. Marcello Graziano & Kenneth Gillingham, 2015. "Spatial patterns of solar photovoltaic system adoption: The influence of neighbors and the built environment," Journal of Economic Geography, Oxford University Press, vol. 15(4), pages 815-839.
    16. Karthik Rajendran & Solmaz Aslanzadeh & Mohammad J. Taherzadeh, 2012. "Household Biogas Digesters—A Review," Energies, MDPI, vol. 5(8), pages 1-32, August.
    17. Andrea Baranzini, Stefano Carattini, Martin Peclat, 2017. "What drives social contagion in the adoption of solar photovoltaic technology," GRI Working Papers 270, Grantham Research Institute on Climate Change and the Environment.
    18. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, vol. 73(1), pages 185-213, February.
    19. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    20. Heidi Hogset & Christopher B. Barrett, 2010. "Social Learning, Social Influence, and Projection Bias: A Caution on Inferences Based on Proxy Reporting of Peer Behavior," Economic Development and Cultural Change, University of Chicago Press, vol. 58(3), pages 563-589, April.
    21. Krekel, Christian & Rechlitz, Julia & Rode, Johannes & Zerrahn, Alexander, 2020. "Quantifying the Externalities of Renewable Energy Plants Using Wellbeing Data: The Case of Biogas," IZA Discussion Papers 13959, Institute of Labor Economics (IZA).
    22. Awaworyi Churchill, Sefa & Smyth, Russell, 2021. "Energy poverty and health: Panel data evidence from Australia," Energy Economics, Elsevier, vol. 97(C).
    23. Rode, Johannes & Weber, Alexander, 2016. "Does localized imitation drive technology adoption? A case study on rooftop photovoltaic systems in Germany," Journal of Environmental Economics and Management, Elsevier, vol. 78(C), pages 38-48.
    24. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    25. Awaworyi Churchill, Sefa & Smyth, Russell, 2020. "Ethnic diversity, energy poverty and the mediating role of trust: Evidence from household panel data for Australia11We thank two referees for constructive comments. This article uses unit record data ," Energy Economics, Elsevier, vol. 86(C).
    26. Andrew D. Foster & Mark R. Rosenzweig, 2010. "Microeconomics of Technology Adoption," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 395-424, September.
    27. Awaworyi Churchill, Sefa & Smyth, Russell, 2021. "Locus of control and energy poverty," Energy Economics, Elsevier, vol. 104(C).
    28. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    29. Arthur Lewbel, 2012. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80.
    30. Antoni Calvó-Armengol & Eleonora Patacchini & Yves Zenou, 2009. "Peer Effects and Social Networks in Education," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(4), pages 1239-1267.
    31. Matthew O. Jackson & Leeat Yariv, 2007. "Diffusion of Behavior and Equilibrium Properties in Network Games," American Economic Review, American Economic Association, vol. 97(2), pages 92-98, May.
    32. Zheng, Y.H. & Li, Z.F. & Feng, S.F. & Lucas, M. & Wu, G.L. & Li, Y. & Li, C.H. & Jiang, G.M., 2010. "Biomass energy utilization in rural areas may contribute to alleviating energy crisis and global warming: A case study in a typical agro-village of Shandong, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3132-3139, December.
    33. Qu, Wei & Tu, Qin & Bluemling, Bettina, 2013. "Which factors are effective for farmers’ biogas use?–Evidence from a large-scale survey in China," Energy Policy, Elsevier, vol. 63(C), pages 26-33.
    34. Aklin, M. & Bayer, P. & Harish, S.P. & Urpelainen, J., 2018. "Economics of household technology adoption in developing countries: Evidence from solar technology adoption in rural India," Energy Economics, Elsevier, vol. 72(C), pages 35-46.
    35. Goolsbee, Austan & Klenow, Peter J, 2002. "Evidence on Learning and Network Externalities in the Diffusion of Home Computers," Journal of Law and Economics, University of Chicago Press, vol. 45(2), pages 317-343, October.
    36. Leonardo Bursztyn & Florian Ederer & Bruno Ferman & Noam Yuchtman, 2014. "Understanding Mechanisms Underlying Peer Effects: Evidence From a Field Experiment on Financial Decisions," Econometrica, Econometric Society, vol. 82(4), pages 1273-1301, July.
    37. Panwar, N.L. & Kaushik, S.C. & Kothari, Surendra, 2011. "Role of renewable energy sources in environmental protection: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1513-1524, April.
    38. Rode, Johannes & Weber, Alexander, 2016. "Does localized imitation drive technology adoption? A case study on rooftop photovoltaic systems in Germany," Journal of Environmental Economics and Management, Elsevier, vol. 78(C), pages 38-48.
    39. Di Falco, Salvatore & Bulte, Erwin, 2013. "The Impact of Kinship Networks on the Adoption of Risk-Mitigating Strategies in Ethiopia," World Development, Elsevier, vol. 43(C), pages 100-110.
    40. Kelebe, Haftu Etsay & Ayimut, Kiros Meles & Berhe, Gebresilasse Hailu & Hintsa, Kidane, 2017. "Determinants for adoption decision of small scale biogas technology by rural households in Tigray, Ethiopia," Energy Economics, Elsevier, vol. 66(C), pages 272-278.
    41. Katuwal, Hari & Bohara, Alok K., 2009. "Biogas: A promising renewable technology and its impact on rural households in Nepal," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2668-2674, December.
    42. Lenis Saweda O. Liverpool-Tasie & Alex Winter-Nelson, 2012. "Social Learning and Farm Technology in Ethiopia: Impacts by Technology, Network Type, and Poverty Status," Journal of Development Studies, Taylor & Francis Journals, vol. 48(10), pages 1505-1521, October.
    43. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    44. He, Pan & Veronesi, Marcella, 2017. "Personality traits and renewable energy technology adoption: A policy case study from China," Energy Policy, Elsevier, vol. 107(C), pages 472-479.
    45. Annemie Maertens, 2017. "Who Cares What Others Think (or Do)? Social Learning and Social Pressures in Cotton Farming in India," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(4), pages 988-1007.
    46. Stephen Eubank & Hasan Guclu & V. S. Anil Kumar & Madhav V. Marathe & Aravind Srinivasan & Zoltán Toroczkai & Nan Wang, 2004. "Modelling disease outbreaks in realistic urban social networks," Nature, Nature, vol. 429(6988), pages 180-184, May.
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    Cited by:

    1. Davillas, Apostolos & Burlinson, Andrew & Liu, Hui-Hsuan, 2022. "Getting warmer: Fuel poverty, objective and subjective health and well-being," Energy Economics, Elsevier, vol. 106(C).
    2. Foroughi, Behzad & Nhan, Pham Viet & Iranmanesh, Mohammad & Ghobakhloo, Morteza & Nilashi, Mehrbakhsh & Yadegaridehkordi, Elaheh, 2023. "Determinants of intention to use autonomous vehicles: Findings from PLS-SEM and ANFIS," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    3. Zhao Xin-gang & Wang Wei & Hu Shuran & Lu Wenjie, 2023. "How to Promote the Application of Biogas Power Technology: A Perspective of Incentive Policy," Energies, MDPI, vol. 16(4), pages 1-11, February.
    4. Li, He & Fang, Debin & Zhao, Chaoyang, 2024. "Retail competition among multi-type retail electric providers in social networks," Energy Economics, Elsevier, vol. 132(C).
    5. Meles, Tensay Hadush & Ryan, Lisa, 2022. "Adoption of renewable home heating systems: An agent-based model of heat pumps in Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    6. Lili Geng & Yongji Xue, 2023. "Promoting ICT adoption in rural entrepreneurship: more neighbourhood effect or more institutional incentives?—Empirical evidence from China," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(6), pages 1530-1548, August.
    7. Ahmad, Munir & Jabeen, Gul, 2023. "Biogas technology adoption and household welfare perspectives for sustainable development," Energy Policy, Elsevier, vol. 181(C).
    8. Ma, Xiaoyue & Huo, Yudi, 2023. "Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework," Technology in Society, Elsevier, vol. 75(C).
    9. Xiaojing Li & Xianli Xia & Jiazhen Ren, 2022. "Can the Participation in Quality Certification of Agricultural Products Drive the Green Production Transition?," IJERPH, MDPI, vol. 19(17), pages 1-16, September.
    10. Li, Hui & Mu, Wenyu & Chen, Tianqi & Wu, Jingwen, 2024. "A social network perspective on household cooking fuel transition: Evidence from China," Energy Economics, Elsevier, vol. 131(C).
    11. Jinxing Wang & Wanming Li & Shamsheer ul Haq & Pomi Shahbaz, 2023. "Adoption of Renewable Energy Technology on Farms for Sustainable and Efficient Production: Exploring the Role of Entrepreneurial Orientation, Farmer Perception and Government Policies," Sustainability, MDPI, vol. 15(7), pages 1-20, March.

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    More about this item

    Keywords

    Social networks; Social influence; Information diffusion; Renewable energy; Biogas; China;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • 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

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