IDEAS home Printed from https://ideas.repec.org/a/spr/ssefpa/v13y2021i5d10.1007_s12571-021-01190-8.html
   My bibliography  Save this article

Spatial dynamics across food systems transformation in IFAD investments: a machine learning approach

Author

Listed:
  • Alessandra Garbero

    (Near East, North Africa, and Europe Division, Programme Management Department, International Fund for Agricultural Development)

  • Giuliano Resce

    (University of Molise)

  • Bia Carneiro

    (University of Coimbra)

Abstract

The food systems approach has gained renewed prominence in recent years, due to its role towards gaining an understanding of food insecurity and malnutrition. A “food systems” lens has therefore become essential to better design development interventions and innovations that can positively impact food systems outcomes. This study provides evidence on the dynamics across food system dimensions within development projects supported by the International Fund for Agricultural Development (IFAD). A custom taxonomy was developed and machine learning techniques primarily focused on supervised text mining, network analysis and LASSO regression were applied to IFAD project documentation to extract analytics about food systems’ spatial and temporal thematic representation over 40 years of project implementation. The paper thus provides insights about the dynamics as well as transformations of food systems within IFAD’s stated activities, providing a historical overview of how the Fund has tackled food systems over four decades of project life cycles. Findings show an overall increase in reporting against food system dimensions and consolidate the applicability of machine learning analytics to uncover trends about international agencies’ activities and accelerate knowledge generation around strategic themes.

Suggested Citation

  • Alessandra Garbero & Giuliano Resce & Bia Carneiro, 2021. "Spatial dynamics across food systems transformation in IFAD investments: a machine learning approach," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(5), pages 1125-1143, October.
  • Handle: RePEc:spr:ssefpa:v:13:y:2021:i:5:d:10.1007_s12571-021-01190-8
    DOI: 10.1007/s12571-021-01190-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12571-021-01190-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12571-021-01190-8?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. F. Picchioni & E. Aurino & L. Aleksandrowicz & M. Bruce & S. Chesterman & P. Dominguez-Salas & Z. Gersten & S. Kalamatianou & C. Turner & J. Yates, 2017. "Roads to interdisciplinarity – working at the nexus among food systems, nutrition and health," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 9(1), pages 181-189, February.
    2. Liran Einav & Jonathan Levin, 2014. "The Data Revolution and Economic Analysis," Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 1-24.
    3. Joe Yates & Swetha Manohar & Shiva Bhandari & Zachary Gersten & Sofia Kalamatianou & Arvin Saleh, 2018. "Building bridges and deconstructing pathways in agriculture, nutrition and health," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 689-700, June.
    4. Hornik, Kurt & Mair, Patrick & Rauch, Johannes & Geiger, Wilhelm & Buchta, Christian & Feinerer, Ingo, 2013. "The textcat Package for n-Gram Based Text Categorization in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i06).
    5. Mequanint B. Melesse & Marrit Berg & Christophe Béné & Alan Brauw & Inge D. Brouwer, 2020. "Metrics to analyze and improve diets through food Systems in low and Middle Income Countries," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(5), pages 1085-1105, October.
    6. Jon Kleinberg & Jens Ludwig & Sendhil Mullainathan & Ziad Obermeyer, 2015. "Prediction Policy Problems," American Economic Review, American Economic Association, vol. 105(5), pages 491-495, May.
    7. Béné, Christophe & Oosterveer, Peter & Lamotte, Lea & Brouwer, Inge D. & de Haan, Stef & Prager, Steve D. & Talsma, Elise F. & Khoury, Colin K., 2019. "When food systems meet sustainability – Current narratives and implications for actions," World Development, Elsevier, vol. 113(C), pages 116-130.
    8. Resce, Giuliano & Maynard, Diana, 2018. "What matters most to people around the world? Retrieving Better Life Index priorities on Twitter," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 61-75.
    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. Fabi, Carola & Gerits, Hannah & Ospina, Christian A. Mongeau & Cullen, Maximo Torero, 2022. "Food System Summit Country Transformation Pathways: What we learned and what is next?," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322752, Agricultural and Applied Economics Association.
    2. Just Dengerink & Florentine Dirks & Eunice Likoko & Joost Guijt, 2021. "One size doesn’t fit all: regional differences in priorities for food system transformation," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(6), pages 1455-1466, December.
    3. Ruerd Ruben & Romina Cavatassi & Leslie Lipper & Eric Smaling & Paul Winters, 2021. "Towards food systems transformation—five paradigm shifts for healthy, inclusive and sustainable food systems," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(6), pages 1423-1430, December.
    4. Similoluwa Felicia Olowo & Abiodun Olusola Omotayo & Ibraheem Oduola Lawal & Adeyemi Oladapo Aremu, 2022. "Improving Rural Livelihood through the Cultivation of Indigenous Fruits and Vegetables: Evidence from Ondo State, Nigeria," Agriculture, MDPI, vol. 12(3), pages 1-20, March.

    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. Resce, Giuliano & Vaquero-Piñeiro, Cristina, 2022. "Predicting agri-food quality across space: A Machine Learning model for the acknowledgment of Geographical Indications," Food Policy, Elsevier, vol. 112(C).
    2. Delogu, Marco & Lagravinese, Raffaele & Paolini, Dimitri & Resce, Giuliano, 2024. "Predicting dropout from higher education: Evidence from Italy," Economic Modelling, Elsevier, vol. 130(C).
    3. Tong Zou & Ayotunde Dawodu & Eugenio Mangi & Ali Cheshmehzangi, 2023. "Exploring Current Trends, Gaps & Challenges in Sustainable Food Systems Studies: The Need of Developing Urban Food Systems Frameworks for Sustainable Cities," Sustainability, MDPI, vol. 15(13), pages 1-32, June.
    4. repec:hal:journl:hal-04662942 is not listed on IDEAS
    5. Jill Nicholls & Adam Drewnowski, 2021. "Toward Sociocultural Indicators of Sustainable Healthy Diets," Sustainability, MDPI, vol. 13(13), pages 1-9, June.
    6. Garbero, Alessandra & Carneiro, Bia & Resce, Giuliano, 2021. "Harnessing the power of machine learning analytics to understand food systems dynamics across development projects," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    7. Fanzo, Jessica & Haddad, Lawrence & Schneider, Kate R. & Béné, Christophe & Covic, Namukolo M. & Guarin, Alejandro & Herforth, Anna W. & Herrero, Mario & Sumaila, U. Rashid & Aburto, Nancy J. & Amuyun, 2021. "Viewpoint: Rigorous monitoring is necessary to guide food system transformation in the countdown to the 2030 global goals," Food Policy, Elsevier, vol. 104(C).
    8. Sophie-Charlotte Klose & Johannes Lederer, 2020. "A Pipeline for Variable Selection and False Discovery Rate Control With an Application in Labor Economics," Papers 2006.12296, arXiv.org, revised Jun 2020.
    9. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
    10. Aiello, Francesco & Albanese, Giuseppe & Piselli, Paolo, 2019. "Good value for public money? The case of R&D policy," Journal of Policy Modeling, Elsevier, vol. 41(6), pages 1057-1076.
    11. Marcel Fafchamps & Julien Labonne, 2017. "Do Politicians’ Relatives Get Better Jobs? Evidence from Municipal Elections," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 33(2), pages 268-300.
    12. Curci, Ylenia & Mongeau Ospina, Christian A., 2016. "Investigating biofuels through network analysis," Energy Policy, Elsevier, vol. 97(C), pages 60-72.
    13. Naguib, Costanza, 2019. "Estimating the Heterogeneous Impact of the Free Movement of Persons on Relative Wage Mobility," Economics Working Paper Series 1903, University of St. Gallen, School of Economics and Political Science.
    14. Nathan, Max & Rosso, Anna, 2014. "Mapping information economy businesses with big data: findings from the UK," LSE Research Online Documents on Economics 60615, London School of Economics and Political Science, LSE Library.
    15. Pedro Carneiro & Sokbae Lee & Daniel Wilhelm, 2020. "Optimal data collection for randomized control trials," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 1-31.
    16. Beulah Pretorius & Jane Ambuko & Effie Papargyropoulou & Hettie C. Schönfeldt, 2021. "Guiding Nutritious Food Choices and Diets along Food Systems," Sustainability, MDPI, vol. 13(17), pages 1-19, August.
    17. de Pedraza, Pablo & Vollbracht, Ian, 2020. "The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve," GLO Discussion Paper Series 515, Global Labor Organization (GLO).
    18. Vogel, Everton & Martinelli, Gabrielli & Artuzo, Felipe Dalzotto, 2021. "Environmental and economic performance of paddy field-based crop-livestock systems in Southern Brazil," Agricultural Systems, Elsevier, vol. 190(C).
    19. Matteo Iacopini & Carlo R.M.A. Santagiustina, 2021. "Filtering the intensity of public concern from social media count data with jumps," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1283-1302, October.
    20. Dengler, Sebastian & Prüfer, Jens, 2021. "Consumers' privacy choices in the era of big data," Games and Economic Behavior, Elsevier, vol. 130(C), pages 499-520.
    21. Erik Heilmann & Janosch Henze & Heike Wetzel, 2021. "Machine learning in energy forecasts with an application to high frequency electricity consumption data," MAGKS Papers on Economics 202135, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

    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:spr:ssefpa:v:13:y:2021:i:5:d:10.1007_s12571-021-01190-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.