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Applying analytic hierarchy process (AHP) to identify decision-making in soybean supply chains: a case of Mato Grosso production

Author

Listed:
  • Toloi, Rodrigo Carlo
  • Reis, João Gilberto Mendes dos
  • Toloi, Marley Nunes Vituri
  • Vendrametto, Oduvaldo
  • Cabral, José António Sarsfield Pereira

Abstract

This paper aims to identify and analyze the factors that influence the decision of Mato Grosso’s farmers to produce soybean using the Analytic Hierarchy Process (AHP). We found evidence that decisionmaking of soybean production is related to rural production aspects such as climate, financing, cost of inputs, and soil quality rather than marketing and logistics. The novelty of this paper is the empirical analysis of the decision-making in agricultural production using AHP. The decision model was created and tested considering 21 farmers and 19 experts linked to the soybean production. Three different scenarios were considered: farmers’ view, experts’ view, and combined view. Our findings indicate that farmers and experts agree with rural aspects are predominant in the decision to plant soybean. Moreover, logistics have been used as an important flag of soybean competitiveness on international trade by soybean stakeholders in Brazil. However, our results show that logistics impact in the soybean decision-making process is low. Due to data limitation access, this study focuses only on Mato Grosso. However, this study has an exploratory character and presents empirical results that may help to understand soybean production over the country.

Suggested Citation

  • Toloi, Rodrigo Carlo & Reis, João Gilberto Mendes dos & Toloi, Marley Nunes Vituri & Vendrametto, Oduvaldo & Cabral, José António Sarsfield Pereira, 2022. "Applying analytic hierarchy process (AHP) to identify decision-making in soybean supply chains: a case of Mato Grosso production," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 60(2), January.
    • Handle: RePEc:ags:revi24:340984
    DOI: 10.22004/ag.econ.340984
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    References listed on IDEAS

    as
    1. Goldsmith, Peter D. & Hirsch, Rodolfo, 2006. "The Brazilian Soybean Complex," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 21(2), pages 1-8.
    2. Rose, David C. & Sutherland, William J. & Parker, Caroline & Lobley, Matt & Winter, Michael & Morris, Carol & Twining, Susan & Ffoulkes, Charles & Amano, Tatsuya & Dicks, Lynn V., 2016. "Decision support tools for agriculture: Towards effective design and delivery," Agricultural Systems, Elsevier, vol. 149(C), pages 165-174.
    3. Emerson Rodolfo Abraham & João Gilberto Mendes dos Reis & Oduvaldo Vendrametto & Pedro Luiz de Oliveira Costa Neto & Rodrigo Carlo Toloi & Aguinaldo Eduardo de Souza & Marcos de Oliveira Morais, 2020. "Time Series Prediction with Artificial Neural Networks: An Analysis Using Brazilian Soybean Production," Agriculture, MDPI, vol. 10(10), pages 1-18, October.
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