IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i13p7685-d846230.html
   My bibliography  Save this article

Micro-Irrigation Technology Adoption in the Bekaa Valley of Lebanon: A Behavioural Model

Author

Listed:
  • Maria Sabbagh

    (Department of Agricultural Sciences, University of Sassari, Viale Italia 39/A, 07100 Sassari, Italy)

  • Luciano Gutierrez

    (Department of Agricultural Sciences, University of Sassari, Viale Italia 39/A, 07100 Sassari, Italy
    Desertification Research Centre, University of Sassari, Viale Italia 39/A, 07100 Sassari, Italy)

Abstract

Potato crops are one of the main sources of income for farmers living in the Bekaa Valley of Lebanon. Given the high sensitivity of potatoes to water stress, water shortages can cause considerable losses in terms of potato yield and quality. To overcome this challenge, the use of water-saving technologies such as micro-irrigation systems are very important. However, the adoption of this technique remains quite low among potato farmers in the Bekaa region, who still use ordinary sprinkler systems. In this study, the unified theory of acceptance and use of technology (UTAUT) serves as the conceptual framework for investigating these farmers’ behaviour in adopting a new micro-irrigation system. To achieve this objective, we extended the UTAUT model by considering farmers’ risk perception of the use of a new micro-irrigation technology. The moderators tested were age, previous experience, voluntariness of use, gross unit margin and educational level. Examining the standard regression coefficients, i.e., the β weights, the results indicate that performance expectancy raised behavioural intention for investment in micro-irrigation (β = 0.29) while for effort expectancy the β weight value was 0.24. Overall, an increase of 1 standard deviation of the behavioural intention strongly impacted investment in micro-irrigation systems, β = 0.8 standard deviation of the effective adoption of the technology. Risk perception (β = −0.08) negatively affected farmers’ performance expectancy, i.e., the higher the perceived risk, the lower the perceived performance of the investment, which in turn affected their intention to use micro-irrigation systems. Age (β = 0.11) exerted a significant effect on effort expectancy. Finally in this paper, the policy implications of the results are discussed.

Suggested Citation

  • Maria Sabbagh & Luciano Gutierrez, 2022. "Micro-Irrigation Technology Adoption in the Bekaa Valley of Lebanon: A Behavioural Model," Sustainability, MDPI, vol. 14(13), pages 1-19, June.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7685-:d:846230
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/13/7685/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/13/7685/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sara Trærup & Jean Stephan, 2015. "Technologies for adaptation to climate change. Examples from the agricultural and water sectors in Lebanon," Climatic Change, Springer, vol. 131(3), pages 435-449, August.
    2. Marra, Michele & Pannell, David J. & Abadi Ghadim, Amir, 2003. "The economics of risk, uncertainty and learning in the adoption of new agricultural technologies: where are we on the learning curve?," Agricultural Systems, Elsevier, vol. 75(2-3), pages 215-234.
    3. Darwish, T.M. & Atallah, T.W. & Hajhasan, S. & Haidar, A., 2006. "Nitrogen and water use efficiency of fertigated processing potato," Agricultural Water Management, Elsevier, vol. 85(1-2), pages 95-104, September.
    4. Namara, Regassa E. & Upadhyay, Bhawana & Nagar, Rashmi K., 2005. "Adoption and impacts of microirrigation technologies: Empirical results from selected localities of Maharashtra and Gujarat states of India," IWMI Research Reports 44543, International Water Management Institute.
    5. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    6. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    7. Shirley Taylor & Peter A. Todd, 1995. "Understanding Information Technology Usage: A Test of Competing Models," Information Systems Research, INFORMS, vol. 6(2), pages 144-176, June.
    8. Said S. Al-Gahtani, 2004. "Computer Technology Acceptance Success Factors in Saudi Arabia: An Exploratory Study," Journal of Global Information Technology Management, Taylor & Francis Journals, vol. 7(1), pages 5-29, January.
    9. Castillo, Gracia Maria Lanza & Engler, Alejandra & Wollni, Meike, 2021. "Planned behavior and social capital: Understanding farmers’ behavior toward pressurized irrigation technologies," Agricultural Water Management, Elsevier, vol. 243(C).
    10. Laurie Houston & Susan Capalbo & Clark Seavert & Meghan Dalton & David Bryla & Ramesh Sagili, 2018. "Erratum to: Specialty fruit production in the Pacific Northwest: adaptation strategies for a changing climate," Climatic Change, Springer, vol. 146(1), pages 173-173, January.
    11. J. Arbuckle & Linda Prokopy & Tonya Haigh & Jon Hobbs & Tricia Knoot & Cody Knutson & Adam Loy & Amber Mase & Jean McGuire & Lois Morton & John Tyndall & Melissa Widhalm, 2013. "Climate change beliefs, concerns, and attitudes toward adaptation and mitigation among farmers in the Midwestern United States," Climatic Change, Springer, vol. 117(4), pages 943-950, April.
    12. John Knight & Sharada Weir & Tassew Woldehanna, 2003. "The role of education in facilitating risk-taking and innovation in agriculture," Journal of Development Studies, Taylor & Francis Journals, vol. 39(6), pages 1-22.
    13. Ronaghi, Mohammad Hossein & Forouharfar, Amir, 2020. "A contextualized study of the usage of the Internet of things (IoTs) in smart farming in a typical Middle Eastern country within the context of Unified Theory of Acceptance and Use of Technology model," Technology in Society, Elsevier, vol. 63(C).
    14. Luisa De Amicis & Silvia Binenti & Felipe Maciel Cardoso & Carlos Gracia-Lázaro & Ángel Sánchez & Yamir Moreno, 2020. "Understanding drivers when investing for impact: an experimental study," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-9, December.
    15. Laurie Houston & Susan Capalbo & Clark Seavert & Meghan Dalton & David Bryla & Ramesh Sagili, 2018. "Specialty fruit production in the Pacific Northwest: adaptation strategies for a changing climate," Climatic Change, Springer, vol. 146(1), pages 159-171, January.
    16. Scoville-Simonds, Morgan & Jamali, Hameed & Hufty, Marc, 2020. "The Hazards of Mainstreaming: Climate change adaptation politics in three dimensions," World Development, Elsevier, vol. 125(C).
    17. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    18. Namara, Regassa & Upadhyay, Bhawana & Nagar, R. K., 2005. "Adoption and impacts of microirrigation technologies: empirical results from selected localities of Maharashtra and Gujarat states of India," IWMI Research Reports H037307, International Water Management Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ding Xiuling & Lu Qian & Li Lipeng & Apurbo Sarkar, 2023. "The Impact of Technical Training on Farmers Adopting Water-Saving Irrigation Technology: An Empirical Evidence from China," Agriculture, MDPI, vol. 13(5), pages 1-20, April.

    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. Paul Juinn Bing Tan, 2013. "Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan," SAGE Open, , vol. 3(4), pages 21582440135, October.
    2. Sanjeev Verma, 2015. "Harnessing the Benefit of Social Networking Sites for Intentional Social Action: Determinants and Challenges," Vision, , vol. 19(2), pages 104-111, June.
    3. Guych Nuryyev & Yu-Ping Wang & Jennet Achyldurdyyeva & Bih-Shiaw Jaw & Yi-Shien Yeh & Hsien-Tang Lin & Li-Fan Wu, 2020. "Blockchain Technology Adoption Behavior and Sustainability of the Business in Tourism and Hospitality SMEs: An Empirical Study," Sustainability, MDPI, vol. 12(3), pages 1-21, February.
    4. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    5. Kexiao Xie & Yuerui Zhu & Yongqiang Ma & Youcheng Chen & Shuiji Chen & Zhidan Chen, 2022. "Willingness of Tea Farmers to Adopt Ecological Agriculture Techniques Based on the UTAUT Extended Model," IJERPH, MDPI, vol. 19(22), pages 1-14, November.
    6. Masud Rana & Gazi Md. Shakhawat Hossain & Maruf Hasan, 2020. "Effectiveness of entrepreneurship skill development training – A case study at RUDSETI in Chitradurga District, Karnataka," Indian Journal of Commerce and Management Studies, Educational Research Multimedia & Publications,India, vol. 11(3), pages 30-44, September.
    7. Jaydeep Mukherjee, 2016. "A comprehensive framework for adoption of mobile broadband services in Indian cities," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 6(1), pages 9-25, January.
    8. Nripendra P. Rana & Yogesh K. Dwivedi & Banita Lal & Michael D. Williams & Marc Clement, 2017. "Citizens’ adoption of an electronic government system: towards a unified view," Information Systems Frontiers, Springer, vol. 19(3), pages 549-568, June.
    9. Lorenz Graf-Vlachy & Katharina Buhtz & Andreas König, 2018. "Social influence in technology adoption: taking stock and moving forward," Management Review Quarterly, Springer, vol. 68(1), pages 37-76, February.
    10. Türker, Cansu & Altay, Burak Can & Okumuş, Abdullah, 2022. "Understanding user acceptance of QR code mobile payment systems in Turkey: An extended TAM," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    11. Andrei OGREZEANU, 2015. "Models Of Technology Adoption: An Integrative Approach," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 5, pages 55-67, June.
    12. Allam, Hesham & Bliemel, Michael & Spiteri, Louise & Blustein, James & Ali-Hassan, Hossam, 2019. "Applying a multi-dimensional hedonic concept of intrinsic motivation on social tagging tools: A theoretical model and empirical validation," International Journal of Information Management, Elsevier, vol. 45(C), pages 211-222.
    13. Iviane Ramos-de-Luna & Francisco Montoro-Ríos & Francisco Liébana-Cabanillas, 2016. "Determinants of the intention to use NFC technology as a payment system: an acceptance model approach," Information Systems and e-Business Management, Springer, vol. 14(2), pages 293-314, May.
    14. Wajeeha Aslam & Marija Ham & Imtiaz Arif, 2017. "Consumer Behavioral Intentions towards Mobile Payment Services: An Empirical Analysis in Pakistan," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 29(2), pages 161-176.
    15. Cansu TÜRKER & Abdullah OKUMUŞ, 2019. "Mobil Ödeme Kullanımına Yönelik Niyet ve Algıların SosyoDemografik Özelliklere Göre Farklılıklarının İncelenmesi," Istanbul Management Journal, Istanbul University Business School, vol. 0(87), pages 111-139, December.
    16. repec:dau:papers:123456789/13000 is not listed on IDEAS
    17. Christopher R. Plouffe & John S. Hulland & Mark Vandenbosch, 2001. "Research Report: Richness Versus Parsimony in Modeling Technology Adoption Decisions—Understanding Merchant Adoption of a Smart Card-Based Payment System," Information Systems Research, INFORMS, vol. 12(2), pages 208-222, June.
    18. Chanchai Phonthanukitithaworn & Carmine Sellitto & Michelle W. L. Fong, 2016. "A Comparative Study of Current and Potential Users of Mobile Payment Services," SAGE Open, , vol. 6(4), pages 21582440166, November.
    19. Marzieh Zendehdel & Laily Hj Paim & Syuhaily Bint Osman, 2015. "Students’ online purchasing behavior in Malaysia: Understanding online shopping attitude," Cogent Business & Management, Taylor & Francis Journals, vol. 2(1), pages 1078428-107, December.
    20. Jozé Braz de Araújo & Silvia Novaes Zilber, 2016. "What Factors Lead Companies to Adopt Social Media in their processes: Proposal and Test of a Measurement Model," Brazilian Business Review, Fucape Business School, vol. 13(6), pages 260-290, November.
    21. Sung S. Kim & Naresh K. Malhotra, 2005. "A Longitudinal Model of Continued IS Use: An Integrative View of Four Mechanisms Underlying Postadoption Phenomena," Management Science, INFORMS, vol. 51(5), pages 741-755, May.

    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:14:y:2022:i:13:p:7685-:d:846230. 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.