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A Decision Support Method for Choosing an Agricultural Machinery Service Workshop Based on Fuzzy Logic

Author

Listed:
  • Andrzej Osuch

    (Institute of Biosystems Engineering, Poznan University of Life Sciences Wojska Polskiego 50, 60-637 Poznan, Poland)

  • Ewa Osuch

    (Institute of Biosystems Engineering, Poznan University of Life Sciences Wojska Polskiego 50, 60-637 Poznan, Poland)

  • Piotr Rybacki

    (Institute of Biosystems Engineering, Poznan University of Life Sciences Wojska Polskiego 50, 60-637 Poznan, Poland)

  • Przemysław Przygodziński

    (Institute of Biosystems Engineering, Poznan University of Life Sciences Wojska Polskiego 50, 60-637 Poznan, Poland)

  • Radosław Kozłowski

    (Institute of Biosystems Engineering, Poznan University of Life Sciences Wojska Polskiego 50, 60-637 Poznan, Poland)

  • Andrzej Przybylak

    (Institute of Biosystems Engineering, Poznan University of Life Sciences Wojska Polskiego 50, 60-637 Poznan, Poland)

Abstract

The quality of technical services is one of the main criteria for assessing the service processes of agricultural machinery, and it has a significant impact on the decision-making process when choosing a service provider. Technical service quality has a significant role in maintaining agricultural machinery in optimal technical condition, thus ensuring its high reliability and durability. The purpose of this study is to present a decision support method for choosing the right agricultural machinery service facility. The method is based on fuzzy inference. The choice of service workshop is based on decision criteria individually accepted by farmers (experts). The method was checked by way of research carried out among 25 farmers facing the choice of a service facility. The decision-making process allows for ranking the decision criteria and decision-makers. The results of the presented research can be used by farm owners and service companies to plan their development directions.

Suggested Citation

  • Andrzej Osuch & Ewa Osuch & Piotr Rybacki & Przemysław Przygodziński & Radosław Kozłowski & Andrzej Przybylak, 2020. "A Decision Support Method for Choosing an Agricultural Machinery Service Workshop Based on Fuzzy Logic," Agriculture, MDPI, vol. 10(3), pages 1-11, March.
    • Handle: RePEc:gam:jagris:v:10:y:2020:i:3:p:76-:d:332217
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    References listed on IDEAS

    as
    1. Brian Sims & Josef Kienzle, 2017. "Sustainable Agricultural Mechanization for Smallholders: What Is It and How Can We Implement It?," Agriculture, MDPI, vol. 7(6), pages 1-21, June.
    2. Saeid Hamzeh & Marzieh Mokarram & Azadeh Haratian & Harm Bartholomeus & Arend Ligtenberg & Arnold K. Bregt, 2016. "Feature Selection as a Time and Cost-Saving Approach for Land Suitability Classification (Case Study of Shavur Plain, Iran)," Agriculture, MDPI, vol. 6(4), pages 1-13, October.
    3. Marzieh Mokarram & Mahdi Najafi-Ghiri, 2016. "Combination of Fuzzy Logic and Analytical Hierarchy Process Techniques to Assess Potassium Saturation Percentage of Some Calcareous Soils (Case Study: Fars Province, Southern Iran)," Agriculture, MDPI, vol. 6(4), pages 1-12, December.
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    Cited by:

    1. Hiwa Golpira & Rafael R. Sola-Guirado, 2022. "Data-Driven Simulator: Redesign of Chickpea Harvester Reels," Agriculture, MDPI, vol. 12(2), pages 1-11, February.
    2. Wang, Yahua & Huan, Meili, 2023. "The effects of socialized agricultural services on rural collective action in the irrigation commons: Evidence from China," Agricultural Water Management, Elsevier, vol. 289(C).
    3. Liangzhen Zang & Yahua Wang & Jinkai Ke & Yiqing Su, 2022. "What Drives Smallholders to Utilize Socialized Agricultural Services for Farmland Scale Management? Insights from the Perspective of Collective Action," Land, MDPI, vol. 11(6), pages 1-25, June.

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