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Driving Agricultural Transformation: Unraveling Key Factors Shaping IoT Adoption in Smart Farming with Empirical Insights

Author

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  • Mahadi Bahari

    (Department of Information Systems, Faculty of Management, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia)

  • Ibrahim Arpaci

    (Department of Information Systems, Faculty of Management, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
    Department of Software Engineering, Faculty of Engineering and Natural Sciences, Bandırma Onyedi Eylul University, Bandırma 10200, Türkiye)

  • Oguzhan Der

    (Department of Maritime Vehicles Management Engineering, Maritime Faculty, Bandırma Onyedi Eylul University, Bandırma 10200, Türkiye)

  • Fatih Akkoyun

    (Department of Mechanical Engineering, Faculty of Engineering, İzmir Demokrasi University, İzmir 35140, Türkiye)

  • Ali Ercetin

    (Department of Naval Architecture and Marine Engineering, Maritime Faculty, Bandırma Onyedi Eylul University, Bandırma 10200, Türkiye)

Abstract

The Internet of Things (IoT) holds immense potential for the social and economic development of developing countries, as recognized by academia and professionals. However, there is a notable lack of theoretical research on IoT adoption within agricultural settings. To address this gap, this study introduces a model focusing on nine critical “Technology-Organization-Environment” (TOE) factors. Empirical validation was conducted using data from 179 managers in diverse agricultural organizations. The research model was evaluated by using “Partial Least Squares Structural Equation Modeling” (PLS-SEM). The results underscored the significance of governmental support and technological compatibility in driving IoT adoption. Moreover, financial considerations within organizations and the evolving digital landscape were identified as key influencers of smart farm adoption. This study offers valuable insights with significant implications for sustainable IoT adoption in research and practical applications.

Suggested Citation

  • Mahadi Bahari & Ibrahim Arpaci & Oguzhan Der & Fatih Akkoyun & Ali Ercetin, 2024. "Driving Agricultural Transformation: Unraveling Key Factors Shaping IoT Adoption in Smart Farming with Empirical Insights," Sustainability, MDPI, vol. 16(5), pages 1-22, March.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:5:p:2129-:d:1351064
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    References listed on IDEAS

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    Cited by:

    1. Huwei Wen & Yulin Huang & Jiayi Shi, 2024. "Revitalizing Agricultural Economy Through Rural E-Commerce? Experience from China’s Revolutionary Old Areas," Agriculture, MDPI, vol. 14(11), pages 1-19, November.
    2. Junhyeok Hyoung & Youngsoo Lee & Sunlee Han, 2024. "Development of Machine Learning-Based Production Forecasting for Offshore Gas Fields Using a Dynamic Material Balance Equation," Energies, MDPI, vol. 17(21), pages 1-21, October.

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