IDEAS home Printed from https://ideas.repec.org/p/crt/wpaper/2301.html

Factors Shaping Innovative Behavior: A Meta-Analysis of Technology Adoption Studies in Agriculture

Author

Listed:
  • Konstantinos Chatzimichael
  • Charoula Daskalaki

  • Gregory Emvalomatis

  • Michail Tsagris

  • Vangelis Tzouvelekas

    (Department of Economics, University of Crete, Greece)

Abstract

In this paper, we employ a meta-regression analysis approach to synthesize empirical evidence on the average partial effects of eleven adoption determinants that regularly appear in empirical studies examining farmer's adoption behavior worldwide. Our analysis considers a total of 122 studies from the adoption literature using discrete choice models that are published in 24 peer-reviewed journals since 1985, covering farmer's adoption behavior around the world and for a wide variety of agricultural technologies.

Suggested Citation

  • Konstantinos Chatzimichael & Charoula Daskalaki & Gregory Emvalomatis & Michail Tsagris & Vangelis Tzouvelekas, 2023. "Factors Shaping Innovative Behavior: A Meta-Analysis of Technology Adoption Studies in Agriculture," Working Papers 2301, University of Crete, Department of Economics.
  • Handle: RePEc:crt:wpaper:2301
    as

    Download full text from publisher

    File URL: https://economics.soc.uoc.gr/wpa/docs/2301.pdf
    File Function: First version
    Download Restriction: No
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jonathan Skinner & Douglas Staiger, 2005. "Technology adoption from hybrid corn to beta blockers," Proceedings, Federal Reserve Bank of San Francisco.
    2. T. D. Stanley, 2008. "Meta‐Regression Methods for Detecting and Estimating Empirical Effects in the Presence of Publication Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(1), pages 103-127, February.
    3. Nicholas J Pates & Nathan P Hendricks, 2020. "Additionality from Payments for Environmental Services with Technology Diffusion," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 281-299, January.
    4. T. D. Stanley & Stephen B. Jarrell, 2005. "Meta‐Regression Analysis: A Quantitative Method of Literature Surveys," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 299-308, July.
    5. 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.
    6. Di Falco, Salvatore & Feri, Francesco & Pin, Paolo & Vollenweider, Xavier, 2018. "Ties that bind: Network redistributive pressure and economic decisions in village economies," Journal of Development Economics, Elsevier, vol. 131(C), pages 123-131.
    7. Tomáš Havránek & T. D. Stanley & Hristos Doucouliagos & Pedro Bom & Jerome Geyer‐Klingeberg & Ichiro Iwasaki & W. Robert Reed & Katja Rost & R. C. M. van Aert, 2020. "Reporting Guidelines For Meta‐Analysis In Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 469-475, July.
    8. T.D. Stanley & Hristos Doucouliagos & Margaret Giles & Jost H. Heckemeyer & Robert J. Johnston & Patrice Laroche & Jon P. Nelson & Martin Paldam & Jacques Poot & Geoff Pugh & Randall S. Rosenberger & , 2013. "Meta-Analysis Of Economics Research Reporting Guidelines," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 390-394, April.
    9. Dario Schulz & Jan Börner, 2023. "Innovation context and technology traits explain heterogeneity across studies of agricultural technology adoption: A meta‐analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 570-590, June.
    10. Jonathan Skinner & Douglas Staiger, 2007. "Technology Adoption from Hybrid Corn to Beta-Blockers," NBER Chapters, in: Hard-to-Measure Goods and Services: Essays in Honor of Zvi Griliches, pages 545-570, National Bureau of Economic Research, Inc.
    11. Tomas Havranek & Zuzana Irsova & Olesia Zeynalova, 2018. "Tuition Fees and University Enrolment: A Meta‐Regression Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(6), pages 1145-1184, December.
    12. Rita Almeida & Ana Margarida Fernandes, 2008. "Openness and Technological Innovations in Developing Countries: Evidence from Firm-Level Surveys," Journal of Development Studies, Taylor & Francis Journals, vol. 44(5), pages 701-727.
    13. Kazushi Takahashi & Rie Muraoka & Keijiro Otsuka, 2020. "Technology adoption, impact, and extension in developing countries’ agriculture: A review of the recent literature," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 31-45, January.
    14. Edward Oczkowski & Hristos Doucouliagos, 2015. "Wine Prices and Quality Ratings: A Meta-regression Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 103-121.
    15. James G. MacKinnon & Matthew D. Webb, 2017. "Wild Bootstrap Inference for Wildly Different Cluster Sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 233-254, March.
    16. Kolawole Ogundari & Olufemi D. Bolarinwa, 2018. "Impact of agricultural innovation adoption: a meta†analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), pages 217-236, April.
    17. Leslie Lipper & Philip Thornton & Bruce M. Campbell & Tobias Baedeker & Ademola Braimoh & Martin Bwalya & Patrick Caron & Andrea Cattaneo & Dennis Garrity & Kevin Henry & Ryan Hottle & Louise Jackson , 2014. "Climate-smart agriculture for food security," Nature Climate Change, Nature, vol. 4(12), pages 1068-1072, December.
    18. T.D. Stanley & Hristos Doucouliagos & Margaret Giles & Jost Heckemeyer & Robert Johnston & Patrice Laroche & Jon Nelson & Martin Paldam & Jacques Poot & Geoff Pugh & Randall Rosenberger & Katja Rost, 2013. "Meta-analysis of economics research reporting guidelines," Post-Print hal-02137661, HAL.
    19. Andrew D. Foster & Mark R. Rosenzweig, 2010. "Microeconomics of Technology Adoption," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 395-424, September.
    20. Ogundari, Kolawole & Bolarinwa, Olufemi D., 2018. "Impact of agricultural innovation adoption: a meta-analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), April.
    21. Staal, S. J. & Baltenweck, I. & Waithaka, M. M. & deWolff, T. & Njoroge, L., 2002. "Location and uptake: integrated household and GIS analysis of technology adoption and land use, with application to smallholder dairy farms in Kenya," Agricultural Economics, Blackwell, vol. 27(3), pages 295-315, November.
    22. Buddhini Ranjika Walisinghe & Shyama Ratnasiri & Nicholas Rohde & Ross Guest, 2017. "Does agricultural extension promote technology adoption in Sri Lanka," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 44(12), pages 2173-2186, December.
    23. Balima, Hippolyte W. & Kilama, Eric G. & Tapsoba, René, 2020. "Inflation targeting: Genuine effects or publication selection bias?," European Economic Review, Elsevier, vol. 128(C).
    24. Erwin Wauters & Erik Mathijs, 2014. "The adoption of farm level soil conservation practices in developed countries: a meta-analytic review," International Journal of Agricultural Resources, Governance and Ecology, Inderscience Enterprises Ltd, vol. 10(1), pages 78-102.
    25. Wallace E. Huffman, 1977. "Allocative Efficiency: The Role of Human Capital," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 91(1), pages 59-79.
    26. Dasgupta, Susmita & Meisner, Craig & Wheeler, David & Jin, Yanhong, 2002. "Agricultural Trade, Development and Toxic Risk," World Development, Elsevier, vol. 30(8), pages 1401-1412, August.
    27. Shang, Linmei & Heckelei, Thomas & Gerullis, Maria K. & Börner, Jan & Rasch, Sebastian, 2021. "Adoption and diffusion of digital farming technologies - integrating farm-level evidence and system interaction," Agricultural Systems, Elsevier, vol. 190(C).
    28. Evenson, Robert E. & Westphal, Larry E., 1995. "Technological change and technology strategy," Handbook of Development Economics, in: Hollis Chenery & T.N. Srinivasan (ed.), Handbook of Development Economics, edition 1, volume 3, chapter 37, pages 2209-2299, Elsevier.
    29. Knowler, Duncan & Bradshaw, Ben, 2007. "Farmers' adoption of conservation agriculture: A review and synthesis of recent research," Food Policy, Elsevier, vol. 32(1), pages 25-48, February.
    30. T. D. Stanley, 2005. "Beyond Publication Bias," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 309-345, July.
    31. Ruzzante, Sacha & Labarta, Ricardo & Bilton, Amy, 2021. "Adoption of agricultural technology in the developing world: A meta-analysis of the empirical literature," World Development, Elsevier, vol. 146(C).
    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. is not listed on IDEAS
    2. Olha Aleksandrova & Annika Tienhaara & Omid Zamani & Jo Bijttebier & Anne Põder & Eija Pouta, 2026. "Farmers’ adoption of environmental soil management practices across four European regions: willingness to accept analysis," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 14(1), pages 1-27, December.

    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. Fernau, Erik & Hirsch, Stefan, 2019. "What drives dividend smoothing? A meta regression analysis of the Lintner model," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 255-273.
    2. Klomp, Jeroen, 2023. "Political budget cycles in military expenditures: A meta-analysis," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 1083-1102.
    3. Masagus M. Ridhwan & Affandi Ismail & Peter Nijkamp, 2023. "The real exchange rate and economic growth: a meta-analysis," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 51(2), pages 287-318, June.
    4. Mattia Filomena & Matteo Picchio, 2023. "Retirement and health outcomes in a meta‐analytical framework," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1120-1155, September.
    5. Dario Schulz & Jan Börner, 2023. "Innovation context and technology traits explain heterogeneity across studies of agricultural technology adoption: A meta‐analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 570-590, June.
    6. Iryna Printezis & Carola Grebitus & Stefan Hirsch, 2019. "The price is right!? A meta-regression analysis on willingness to pay for local food," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-23, May.
    7. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    8. Zhuanlan Sun & Demi Zhu, 2023. "Investigating environmental regulation effects on technological innovation: A meta-regression analysis," Energy & Environment, , vol. 34(3), pages 463-492, May.
    9. Stanley, T. D. & Doucouliagos, Chris, 2019. "Practical Significance, Meta-Analysis and the Credibility of Economics," IZA Discussion Papers 12458, IZA Network @ LISER.
    10. Germà Bel & Mildred E. Warner, 2016. "Factors explaining inter-municipal cooperation in service delivery: a meta-regression analysis," Journal of Economic Policy Reform, Taylor and Francis Journals, vol. 19(2), pages 91-115, April.
    11. Ruzzante, Sacha & Labarta, Ricardo & Bilton, Amy, 2021. "Adoption of agricultural technology in the developing world: A meta-analysis of the empirical literature," World Development, Elsevier, vol. 146(C).
    12. Demena, B.A., 2021. "Effectiveness of export promotion programmes," ISS Working Papers - General Series 688, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    13. Geyer-Klingeberg, Jerome & Hang, Markus & Rathgeber, Andreas, 2020. "Meta-analysis in finance research: Opportunities, challenges, and contemporary applications," International Review of Financial Analysis, Elsevier, vol. 71(C).
    14. Matteo Picchio & Michele Ubaldi, 2024. "Unemployment and health: A meta‐analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1437-1472, September.
    15. Stefan Hirsch, 2018. "Successful In The Long Run: A Meta†Regression Analysis Of Persistent Firm Profits," Journal of Economic Surveys, Wiley Blackwell, vol. 32(1), pages 23-49, February.
    16. Sebastian Gechert & Bianka Mey & Matej Opatrny & Tomas Havranek & T. D. Stanley & Pedro R. D. Bom & Hristos Doucouliagos & Philipp Heimberger & Zuzana Irsova & Heiko J. Rachinger, 2025. "Conventional wisdom, meta‐analysis, and research revision in economics," Journal of Economic Surveys, Wiley Blackwell, vol. 39(3), pages 980-999, July.
    17. Petra Valickova & Tomas Havranek & Roman Horvath, 2015. "Financial Development And Economic Growth: A Meta-Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 506-526, July.
    18. Anton Astakhov & Tomas Havranek & Jiri Novak, 2019. "Firm Size And Stock Returns: A Quantitative Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 33(5), pages 1463-1492, December.
    19. Schulz, Dario & Börner, Jan, 2021. "Context and Technology Traits Explain Heterogeneity Across Adoption Studies of Agricultural Innovations: A Global Meta-Analysis," 2021 Conference, August 17-31, 2021, Virtual 315003, International Association of Agricultural Economists.
    20. Sebri, Maamar & Dachraoui, Hajer, 2021. "Natural resources and income inequality: A meta-analytic review," Resources Policy, Elsevier, vol. 74(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy

    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:crt:wpaper:2301. 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: Kostis Pigounakis (email available below). General contact details of provider: https://edirc.repec.org/data/deuchgr.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.