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Smart Agriculture Technology Evaluation: A Linguistic-based MCDM Methodology

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  • Uztürk, Deniz
  • Büyüközkan, Gülçin

Abstract

Agricultural operations have been highly affected by all the industrial revolutions. From ancient times to today, agrarian systems have evolved parallel to technological developments. For a decade, we have been facing a new industrial revolution, Industry 4.0. It is for sure that the existing agrarian systems will be affected by this digital transformation. Since agricultural systems are critical production networks for civilizations, their change should be addressed carefully. For that purpose, this paper focuses on the technology evaluation for Smart Agriculture (SA). The SA area is chosen thanks to its importance for sustainable development and production systems. Thus, the expectations from SA are derived from the SA advantages stated in the academic and industrial literature. Afterward, the technologies are assessed according to their ability to meet these expectations. To obtain the most powerful technology, the expectations are first weighted via the 2-Tuple Linguistic (2-TL) DEMATEL technique, then 2-TL-MARCOS is used to calculate the technology prioritization. To overcome the ambiguity about a newly emerged subject as SA, using linguistic variables via the 2-TL approach is one of the essential contributions of this paper. Moreover, this paper suggests a multi-criteria decision-making (MCDM) approach to create a comprehensive understanding of digital technologies and their use and benefits in agricultural systems. A real case study is presented with a sensitivity analysis to test the proposed methodology's applicability and replicability.

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  • Uztürk, Deniz & Büyüközkan, Gülçin, "undated". "Smart Agriculture Technology Evaluation: A Linguistic-based MCDM Methodology," Agri-Tech Economics Papers 337128, Harper Adams University, Land, Farm & Agribusiness Management Department.
    • Handle: RePEc:ags:haaepa:337128
    DOI: 10.22004/ag.econ.337128
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    References listed on IDEAS

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