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Informational Cascades and Technology Adoption: Evidence from Greek and German Organic Growers

Author

Listed:
  • Konstantinos Chatzimichael
  • Margarita Genius

    (Department of Economics, University of Crete, Greece)

  • Vangelis Tzouvelekas

    (Department of Economics, University of Crete, Greece)

Abstract

The present study aims to empirically analyze the effect of social interactions and conversion subsidies on the adoption rates of organic farming practices in two samples of olive and cereal growers in Greece and Germany, respectively. To this end we construct two alternative indicators to capture informational cascades created in rural areas. The first indicator is based on demographic characteristics while the other one on profitability considerations since farmers are likely to imitate the behavior of more successful farmers. Building upon the theoretical findings of Foster and Rosenweig (1995), Munshi (2004), Bandiera and Rasul (2006) and Weber (2012), we find that informational cascades are indeed important in revising farmers’ perceptions and adoption behavior in both rural areas of Europe. Our results show that conversion subsidies can enhance social network effects internalizing informational externalities even in areas where adoption rates are considerable. This finding is independent of the crop and the country under consideration underlying the importance of informational cascades for technology adoption.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Konstantinos Chatzimichael & Margarita Genius & Vangelis Tzouvelekas, 2011. "Informational Cascades and Technology Adoption: Evidence from Greek and German Organic Growers," Working Papers 1102, University of Crete, Department of Economics, revised 12 Mar 2013.
    • Handle: RePEc:crt:wpaper:1102
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    Cited by:

    1. Marios Zachariou & Adewale Henry Adenuga & Claire Jack, 2025. "Education and Farmers’ Environmental Performance: A Systematic Literature Review," Sustainability, MDPI, vol. 17(2), pages 1-26, January.
    2. Hai Hu & Andi Cao & Si Chen & Houjian Li, 2022. "Effects of Risk Perception of Pests and Diseases on Tea Famers’ Green Control Techniques Adoption," IJERPH, MDPI, vol. 19(14), pages 1-15, July.
    3. Xiaojuan Luo & Qingqing Ye & Xinzao Huang & Bo Zhao & Hongbin Liu, 2025. "How Do Multidimensional Relational Networks Affect Large-Scale Grain Producers’ Adoption of Low-Carbon Fertilization Technology?," Sustainability, MDPI, vol. 17(1), pages 1-22, January.
    4. Mingyang Han & Ruifeng Liu & Hengyun Ma & Kaiyang Zhong & Jian Wang & Yifan Xu, 2022. "The Impact of Social Capital on Farmers’ Willingness to Adopt New Agricultural Technologies: Empirical Evidence from China," Agriculture, MDPI, vol. 12(9), pages 1-19, September.
    5. Parra-López, Carlos & Reina-Usuga, Liliana & Carmona-Torres, Carmen & Sayadi, Samir & Klerkx, Laurens, 2021. "Digital transformation of the agrifood system: Quantifying the conditioning factors to inform policy planning in the olive sector," Land Use Policy, Elsevier, vol. 108(C).
    6. Wen Xiang & Jianzhong Gao, 2023. "From Agricultural Green Production to Farmers’ Happiness: A Case Study of Kiwi Growers in China," IJERPH, MDPI, vol. 20(4), pages 1-25, February.
    7. Xinqiang Chen & Xiu-e Zhang & Jiangjie Chen, 2024. "TAM-Based Study of Farmers’ Live Streaming E-Commerce Adoption Intentions," Agriculture, MDPI, vol. 14(4), pages 1-22, March.
    8. Kexiao Xie & Yuerui Zhu & Yongqiang Ma & Youcheng Chen & Shuiji Chen & Zhidan Chen, 2022. "Willingness of Tea Farmers to Adopt Ecological Agriculture Techniques Based on the UTAUT Extended Model," IJERPH, MDPI, vol. 19(22), pages 1-14, November.
    9. Unay Gailhard, Ilkay & Bavorova, Miroslava & Pirscher, Frauke, "undated". "The Influence of Communication Frequency with Social Network Actors on the Continuous Innovation Adoption: Organic Farmers in Germany," 131st Seminar, September 18-19, 2012, Prague, Czech Republic 135786, European Association of Agricultural Economists.
    10. Ning Geng & Shanyao Wang & Xibing Han, 2025. "Efficacy of Social Networks in Promoting the Green Production Behaviors of Chinese Farmers: An Empirical Study," Agriculture, MDPI, vol. 15(6), pages 1-21, March.
    11. Wen Xiang & Jianzhong Gao, 2023. "Do Not Be Anticlimactic: Farmers’ Behavior in the Sustainable Application of Green Agricultural Technology—A Perceived Value and Government Support Perspective," Agriculture, MDPI, vol. 13(2), pages 1-24, January.
    12. Marilena Gemtou & Konstantina Kakkavou & Evangelos Anastasiou & Spyros Fountas & Soren Marcus Pedersen & Gohar Isakhanyan & Kassa Tarekegn Erekalo & Serafin Pazos-Vidal, 2024. "Farmers’ Transition to Climate-Smart Agriculture: A Systematic Review of the Decision-Making Factors Affecting Adoption," Sustainability, MDPI, vol. 16(7), pages 1-34, March.
    13. Weihong Huang & Caiyan Yang & Ke Liu & Rui Min, 2023. "Information Acquisition Ability and Farmers’ Herd Behavior in Rice–Crayfish Coculture System Adoption," Agriculture, MDPI, vol. 13(10), pages 1-15, September.
    14. Dmytro Serebrennikov & Fiona Thorne & Zein Kallas & Sinéad N. McCarthy, 2020. "Factors Influencing Adoption of Sustainable Farming Practices in Europe: A Systemic Review of Empirical Literature," Sustainability, MDPI, vol. 12(22), pages 1-23, November.
    15. Mohamed Ghali & Maha Ben Jaballah & Nejla Ben Arfa & Annie Sigwalt, 2022. "Analysis of factors that influence adoption of agroecological practices in viticulture," Review of Agricultural, Food and Environmental Studies, Springer, vol. 103(3), pages 179-209, September.

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    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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