IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i6p2340-d1607322.html
   My bibliography  Save this article

Advancing Sustainable Agriculture Through Digital Technology: The Role of the ‘Agricultural Guide’ App in Improving Olive Farming Practices in Saudi Arabia

Author

Listed:
  • Abdulmalek Naji Alsanhani

    (Department of Agricultural Extension and Rural Society, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia)

  • Mohammad Shayaa Al-Shayaa

    (Department of Agricultural Extension and Rural Society, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia)

  • Abdulaziz Thabet Dabiah

    (Department of Agricultural Extension and Rural Society, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia)

  • Jasser Shaman Alfridi

    (Department of Agricultural Extension and Rural Society, College of Food and Agriculture Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia)

Abstract

The Agricultural Guide application is a crucial component of the digital extension system in Saudi Arabia, providing modern and evidence-based information on sustainable agricultural practices to the farming community. The adoption of digital extension tools has been widely recognized as a key driver in enhancing crop productivity. This study aimed to assess the impact of the Agricultural Guide application on the adoption of sustainable olive farming practices in the Kingdom of Saudi Arabia. The impact was evaluated by analyzing the farming practices of the users and non-users of the application, identifying key determinants of application usage through machine learning techniques. The study also analyzed barriers to its adoption. A structured questionnaire was employed to collect data from 229 olive farmers in the Al-Jouf region. The findings reveal that the majority of respondents were non-users of the application. Significant differences were observed between users and non-users regarding the adoption of sustainable agricultural practices, including irrigation management, soil improvement, pest control, and harvesting techniques. Furthermore, farmers’ productivity, income levels, and digital information sources were significantly influenced by their usage of the application. A random forest analysis, with a predictive accuracy of 94.12%, identified key determinants of the application usage, including digital information sources, soil improvement practices, irrigation management, and education level. The study highlights the need for targeted educational programs under the supervision of the Agricultural Extension Department to enhance farmers’ awareness and knowledge of the Agricultural Guide application. Expanding its adoption within the farming community has the potential to significantly promote sustainable agricultural practices and improve overall agricultural productivity in Saudi Arabia.

Suggested Citation

  • Abdulmalek Naji Alsanhani & Mohammad Shayaa Al-Shayaa & Abdulaziz Thabet Dabiah & Jasser Shaman Alfridi, 2025. "Advancing Sustainable Agriculture Through Digital Technology: The Role of the ‘Agricultural Guide’ App in Improving Olive Farming Practices in Saudi Arabia," Sustainability, MDPI, vol. 17(6), pages 1-22, March.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2340-:d:1607322
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/6/2340/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/6/2340/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aker, Jenny C. & Ksoll, Christopher, 2016. "Can mobile phones improve agricultural outcomes? Evidence from a randomized experiment in Niger," Food Policy, Elsevier, vol. 60(C), pages 44-51.
    2. Aparo, Nathaline Onek & Odongo, Walter & De Steur, Hans, 2022. "Unraveling heterogeneity in farmer's adoption of mobile phone technologies: A systematic review," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    3. Kuhn, Max, 2008. "Building Predictive Models in R Using the caret Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i05).
    4. Wolfert, Sjaak & Ge, Lan & Verdouw, Cor & Bogaardt, Marc-Jeroen, 2017. "Big Data in Smart Farming – A review," Agricultural Systems, Elsevier, vol. 153(C), pages 69-80.
    5. Baozhi Li & Ni Zhuo & Chen Ji & Qibiao Zhu, 2022. "Influence of Smartphone-Based Digital Extension Service on Farmers’ Sustainable Agricultural Technology Adoption in China," IJERPH, MDPI, vol. 19(15), pages 1-14, August.
    6. Dmytro Serebrennikov & Fiona Thorne & Zein Kallas & Sinéad N. McCarthy, 2020. "Factors Influencing Adoption of Sustainable Farming Practices in Europe: A Systemic Review of Empirical Literature," Sustainability, MDPI, vol. 12(22), pages 1-23, November.
    7. Xiaolan Fu & Shaheen Akter, 2016. "The Impact of Mobile Phone Technology on Agricultural Extension Services Delivery: Evidence from India," Journal of Development Studies, Taylor & Francis Journals, vol. 52(11), pages 1561-1576, November.
    Full references (including those not matched with items on IDEAS)

    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. Ni Zhuo & Baozhi Li & Qibiao Zhu & Chen Ji, 2023. "Smartphone‐based agricultural extension services and farm incomes: Evidence from Zhejiang Province in China," Review of Development Economics, Wiley Blackwell, vol. 27(3), pages 1383-1402, August.
    2. Osrof, Hazem Yusuf & Tan, Cheng Ling & Angappa, Gunasekaran & Yeo, Sook Fern & Tan, Kim Hua, 2023. "Adoption of smart farming technologies in field operations: A systematic review and future research agenda," Technology in Society, Elsevier, vol. 75(C).
    3. Pallavi Rajkhowa & Heike Baumüller, 2024. "Assessing the potential of ICT to increase land and labour productivity in agriculture: Global and regional perspectives," Journal of Agricultural Economics, Wiley Blackwell, vol. 75(2), pages 477-503, June.
    4. Lin Tang & Xiaofeng Luo & Yanzhong Huang & Sanxia Du & Aqian Yan, 2023. "Can smartphone use increase farmers’ willingness to participate in the centralized treatment of rural domestic sewage? Evidence from rural China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(4), pages 3379-3403, April.
    5. Zou, Baoling & Mishra, Ashok K., 2022. "Engaging Information Technology in Farmland Rental Market: An Empirical Study from Rural China," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322265, Agricultural and Applied Economics Association.
    6. Dzanku, F.M. & Osei, R.D., 2018. "Impact of pre– and post-harvest training reminders on crop losses and food poverty in Mali," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275924, International Association of Agricultural Economists.
    7. Peng Nie & Wanglin Ma & Alfonso Sousa-Poza, 2021. "The relationship between smartphone use and subjective well-being in rural China," Electronic Commerce Research, Springer, vol. 21(4), pages 983-1009, December.
    8. Joël Cariolle & David A Carroll, 2022. "The Use of Digital for Public Service Provision in Sub-Saharan Africa," Working Papers hal-03004535, HAL.
    9. Ma, W. & Grafton, Q. & Renwick, A., 2018. "Gender and Income Effects of Smartphone Use: The Case of Rural China," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277310, International Association of Agricultural Economists.
    10. Yi Cai & Wene Qi & Famin Yi, 2023. "Smartphone use and willingness to adopt digital pest and disease management: Evidence from litchi growers in rural China," Agribusiness, John Wiley & Sons, Ltd., vol. 39(1), pages 131-147, January.
    11. Pallavi Rajkhowa & Matin Qaim, 2022. "Mobile phones, off‐farm employment and household income in rural India," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 789-805, September.
    12. Adane Tufa & Arega Alene & Hambulo Ngoma & Paswel Marenya & Julius Manda & Md Abdul Matin & Christian Thierfelder & David Chikoye, 2024. "Willingness to pay for agricultural mechanization services by smallholder farmers in Malawi," Agribusiness, John Wiley & Sons, Ltd., vol. 40(1), pages 248-276, January.
    13. Wanglin Ma & R. Quentin Grafton & Alan Renwick, 2020. "Smartphone use and income growth in rural China: empirical results and policy implications," Electronic Commerce Research, Springer, vol. 20(4), pages 713-736, December.
    14. Lin Xie & Biliang Luo & Wenjing Zhong, 2021. "How Are Smallholder Farmers Involved in Digital Agriculture in Developing Countries: A Case Study from China," Land, MDPI, vol. 10(3), pages 1-16, March.
    15. Oliver Falck & Johannes Koenen, 2020. "Rohstoff „Daten“: Volkswirtschaflicher Nutzen von Datenbereitstellung – eine Bestandsaufnahme," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 113.
    16. Hrosul, Viktoriia & Kruhlova, Olena & Kolesnyk, Alina, 2023. "Digitalization of the agricultural sector: the impact of ICT on the development of enterprises in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(4), December.
    17. Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.
    18. Jie Zhao & Ji Chen & Damien Beillouin & Hans Lambers & Yadong Yang & Pete Smith & Zhaohai Zeng & Jørgen E. Olesen & Huadong Zang, 2022. "Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    19. Ascui, Francisco & Ball, Alex & Kahn, Lewis & Rowe, James, 2021. "Is operationalising natural capital risk assessment practicable?," Ecosystem Services, Elsevier, vol. 52(C).
    20. Huo, Dongyang & Malik, Asad Waqar & Ravana, Sri Devi & Rahman, Anis Ur & Ahmedy, Ismail, 2024. "Mapping smart farming: Addressing agricultural challenges in data-driven era," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).

    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:gam:jsusta:v:17:y:2025:i:6:p:2340-:d:1607322. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.