IDEAS home Printed from https://ideas.repec.org/p/ags/aesc14/170358.html
   My bibliography  Save this paper

Adoption of greenhouse gas mitigation in agriculture: an analysis of dairy farmers’ preferences and adoption behaviour

Author

Listed:
  • Glenka, Klaus
  • Eorya, Vera
  • Colombo, Sergio
  • Barnes, Andrew Peter

Abstract

Greenhouse gas mitigation in agriculture implies changes in farm management practices. Knowledge on farmers’ current adoption of management practices aimed at reducing emissions, and their preferences regarding these, is important to inform the development of robust climate change mitigation policies in the agricultural sector. In the context of Scottish dairy farms, this study combines information on current adoption of mitigation practices with preference information based on Best-Worst-Scaling to facilitate the choice of mitigation practices to support via policy mechanisms that encourage and incentivise change. We find that current adoption plays an important role in understanding preference rankings of mitigation practices, and identify promising mitigation practices based on their potential for additional emission reduction, their perceived contribution to the farm’s financial and environmental performance and information on their cost-effectiveness.

Suggested Citation

  • Glenka, Klaus & Eorya, Vera & Colombo, Sergio & Barnes, Andrew Peter, 2014. "Adoption of greenhouse gas mitigation in agriculture: an analysis of dairy farmers’ preferences and adoption behaviour," 88th Annual Conference, April 9-11, 2014, AgroParisTech, Paris, France 170358, Agricultural Economics Society.
    • Handle: RePEc:ags:aesc14:170358
    DOI: 10.22004/ag.econ.170358
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/170358/files/Klaus_Glenk_BWS%20AES%20format%202014.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.170358?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
    ---><---

    References listed on IDEAS

    as
    1. Lancsar, Emily & Louviere, Jordan & Donaldson, Cam & Currie, Gillian & Burgess, Leonie, 2013. "Best worst discrete choice experiments in health: Methods and an application," Social Science & Medicine, Elsevier, vol. 76(C), pages 74-82.
    2. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    3. Jayson L. Lusk & Brian C. Briggeman, 2009. "Food Values," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 184-196.
    4. Erdem, Seda & Rigby, Dan & Wossink, Ada, 2012. "Using best–worst scaling to explore perceptions of relative responsibility for ensuring food safety," Food Policy, Elsevier, vol. 37(6), pages 661-670.
    5. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    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. Ashton, Lisa, 2022. "A framework for promoting natural climate solutions in the agriculture sector," Land Use Policy, Elsevier, vol. 122(C).
    2. Worden, David & Hailu, Getu, 2020. "Do genomic innovations enable an economic and environmental win-win in dairy production?," Agricultural Systems, Elsevier, vol. 181(C).
    3. Chen, Jiandong & Cheng, Shulei & Song, Malin, 2018. "Changes in energy-related carbon dioxide emissions of the agricultural sector in China from 2005 to 2013," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 748-761.
    4. Mansaray, B. & Jin, S. & Yuan, R. & Li, H., 2018. "Farmers Preferences for Attributes of Seed Rice in Sierra Leone: A Best-Worst Scaling Approach," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277552, International Association of Agricultural Economists.
    5. O'Donoghue, Cathal & Ryan, Mary & Kilcline, Kevin & Daly, Karen & Fenton, Owen & Heanue, Kevin & Kingston, Suzanne & Sherry, Jenny Mac & Murphy, Pat & O’Hora, Denis, 2018. "The Agri-Environmental Knowledge Innovation System for Water Quality Improvement," 166th Seminar, August 30-31, 2018, Galway, West of Ireland 276232, European Association of Agricultural Economists.
    6. Xuan, Bui Bich & Ngoc, Quach Thi Khanh & Börger, Tobias, 2022. "Fisher preferences for marine litter interventions in Vietnam," Ecological Economics, Elsevier, vol. 200(C).
    7. Kapica, Jacek & Pawlak, Halina & Ścibisz, Marek, 2015. "Carbon dioxide emission reduction by heating poultry houses from renewable energy sources in Central Europe," Agricultural Systems, Elsevier, vol. 139(C), pages 238-249.
    8. Jiake Li & Wei Wang & Meng Li & Qiao Li & Zeming Liu & Wei Chen & Yanan Wang, 2022. "Impact of Land Management Scale on the Carbon Emissions of the Planting Industry in China," Land, MDPI, vol. 11(6), pages 1-15, May.
    9. Traxler, Emilia & Li, Tongzhe, 2020. "Agricultural Best Management Practices, A summary of adoption behaviour," Working Papers 305271, University of Guelph, Institute for the Advanced Study of Food and Agricultural Policy.
    10. Rosanna Salvia & Rosaria Simone & Luca Salvati & Giovanni Quaranta, 2018. "Soil Conservation Practices and Stakeholder’s Participation in Research Projects—Empirical Evidence from Southern Italy," Agriculture, MDPI, vol. 8(6), pages 1-20, June.
    11. Jiaxing Pang & Xiang Li & Xue Li & Xingpeng Chen & Huiyu Wang, 2021. "Research on the Relationship between Prices of Agricultural Production Factors, Food Consumption Prices, and Agricultural Carbon Emissions: Evidence from China’s Provincial Panel Data," Energies, MDPI, vol. 14(11), pages 1-11, May.
    12. Eory, Vera & Topp, Cairistiona F. E. & Butler, Adam & Bond, Clare E., 2018. "Experts’ estimates of future uptake of low-carbon agricultural practices," 92nd Annual Conference, April 16-18, 2018, Warwick University, Coventry, UK 273483, Agricultural Economics Society.
    13. Yixin Nong & Changbin Yin & Xiaoyan Yi & Jing Ren & Hsiaoping Chien, 2020. "Farmers’ Adoption Preferences for Sustainable Agriculture Practices in Northwest China," Sustainability, MDPI, vol. 12(15), pages 1-13, August.
    14. Barnes, A.P. & McMillan, J. & Sutherland, L.-A. & Hopkins, J. & Thomson, S.G., 2022. "Farmer intentional pathways for net zero carbon: Exploring the lock-in effects of forestry and renewables," Land Use Policy, Elsevier, vol. 112(C).

    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. Glenk, Klaus & Eory, Vera & Colombo, Sergio & Barnes, Andrew, 2014. "Adoption of greenhouse gas mitigation in agriculture: An analysis of dairy farmers' perceptions and adoption behaviour," Ecological Economics, Elsevier, vol. 108(C), pages 49-58.
    2. Yangui, Ahmed & Akaichi, Faical & Costa-Font, Montserrat & Gil, Jose Maria, 2019. "Comparing results of ranking conjoint analyses, best–worst scaling and discrete choice experiments in a nonhypothetical context," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(2), April.
    3. Erdem, Seda & Rigby, Dan & Wossink, Ada, 2012. "Using best–worst scaling to explore perceptions of relative responsibility for ensuring food safety," Food Policy, Elsevier, vol. 37(6), pages 661-670.
    4. Kaambwa, Billingsley & Lancsar, Emily & McCaffrey, Nicola & Chen, Gang & Gill, Liz & Cameron, Ian D. & Crotty, Maria & Ratcliffe, Julie, 2015. "Investigating consumers' and informal carers' views and preferences for consumer directed care: A discrete choice experiment," Social Science & Medicine, Elsevier, vol. 140(C), pages 81-94.
    5. Zaffou, Madiha & Campbell, Benjamin L. & Martin, Jennifer, 2014. "Using a Randomized Choice Experiment to Test Willingness to Pay for Multiple Differentiated Products," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 176910, Agricultural and Applied Economics Association.
    6. Seda Erdem & Dan Rigby, 2013. "Investigating Heterogeneity in the Characterization of Risks Using Best Worst Scaling," Risk Analysis, John Wiley & Sons, vol. 33(9), pages 1728-1748, September.
    7. Genie, Mesfin G. & Ryan, Mandy & Krucien, Nicolas, 2021. "To pay or not to pay? Cost information processing in the valuation of publicly funded healthcare," Social Science & Medicine, Elsevier, vol. 276(C).
    8. Yoo, Hong Il & Doiron, Denise, 2013. "The use of alternative preference elicitation methods in complex discrete choice experiments," Journal of Health Economics, Elsevier, vol. 32(6), pages 1166-1179.
    9. Fitzsimmons, Jill & Cicia, Gianni, 2018. "Different Tubers for Different Consumers: Heterogeneity in Human Values and Willingness to Pay for Social Outcomes of Potato Credence Attributes," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 9(4), August.
    10. Ortega, David L. & Wang, H. Holly & Wu, Laping & Hong, Soo Jeong, 2015. "Retail channel and consumer demand for food quality in China," China Economic Review, Elsevier, vol. 36(C), pages 359-366.
    11. Pereira, Pedro & Ribeiro, Tiago, 2011. "The impact on broadband access to the Internet of the dual ownership of telephone and cable networks," International Journal of Industrial Organization, Elsevier, vol. 29(2), pages 283-293, March.
    12. Choi, Andy S., 2013. "Nonmarket values of major resources in the Korean DMZ areas: A test of distance decay," Ecological Economics, Elsevier, vol. 88(C), pages 97-107.
    13. Doherty, Edel & Campbell, Danny, 2011. "Demand for improved food safety and quality: a cross-regional comparison," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108791, Agricultural Economics Society.
    14. Abdurrahman B. Aydemir & Erkan Duman, 2021. "Migrant Networks and Destination Choice: Evidence from Moves across Turkish Provinces," Koç University-TUSIAD Economic Research Forum Working Papers 2109, Koc University-TUSIAD Economic Research Forum.
    15. Lai, John & Olynk Widmar, Nicole J. & Gunderson, Michael A. & Widmar, David A. & Ortega, David L., 2018. "Prioritization of farm success factors by commercial farm managers," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(6), July.
    16. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    17. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    18. Veneziani, Mario & Sckokai, Paolo & Moro, Daniele, 2012. "Consumers’ willingness to pay for a functional food," 2012 First Congress, June 4-5, 2012, Trento, Italy 124101, Italian Association of Agricultural and Applied Economics (AIEAA).
    19. Kesternich, Iris & Heiss, Florian & McFadden, Daniel & Winter, Joachim, 2013. "Suit the action to the word, the word to the action: Hypothetical choices and real decisions in Medicare Part D," Journal of Health Economics, Elsevier, vol. 32(6), pages 1313-1324.
    20. Jianhua Wang & Jiaye Ge & Yuting Ma, 2018. "Urban Chinese Consumers’ Willingness to Pay for Pork with Certified Labels: A Discrete Choice Experiment," Sustainability, MDPI, vol. 10(3), pages 1-14, February.

    More about this item

    Keywords

    Agribusiness; Environmental Economics and Policy; Livestock Production/Industries; Research and Development/Tech Change/Emerging Technologies;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:aesc14:170358. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aesukea.html .

    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.