اخبار و اعلانات

 آمار

تعداد نشریات282
تعداد نشریات سازمان80
تعداد شماره‌ها3,272
تعداد مقالات36,149
تعداد مشاهده مقاله55,713,812
تعداد دریافت فایل اصل مقاله94,492,353
مختاری حصاری, آرزو, نعمتی, علیرضا. (1404). تبیین نقش خودکارآمدی کشاورزان و سهولت کاربرد فناوری بر رفتار به کارگیری سامانه آبیاری کم فشار. سامانه مدیریت نشریات علمی, 26(100), 16-1. doi: 10.22092/idser.2025.370504.1628
آرزو مختاری حصاری; علیرضا نعمتی. "تبیین نقش خودکارآمدی کشاورزان و سهولت کاربرد فناوری بر رفتار به کارگیری سامانه آبیاری کم فشار". سامانه مدیریت نشریات علمی, 26, 100, 1404, 16-1. doi: 10.22092/idser.2025.370504.1628
مختاری حصاری, آرزو, نعمتی, علیرضا. (1404). 'تبیین نقش خودکارآمدی کشاورزان و سهولت کاربرد فناوری بر رفتار به کارگیری سامانه آبیاری کم فشار', سامانه مدیریت نشریات علمی, 26(100), pp. 16-1. doi: 10.22092/idser.2025.370504.1628
مختاری حصاری, آرزو, نعمتی, علیرضا. تبیین نقش خودکارآمدی کشاورزان و سهولت کاربرد فناوری بر رفتار به کارگیری سامانه آبیاری کم فشار. سامانه مدیریت نشریات علمی, 1404; 26(100): 16-1. doi: 10.22092/idser.2025.370504.1628

تبیین نقش خودکارآمدی کشاورزان و سهولت کاربرد فناوری بر رفتار به کارگیری سامانه آبیاری کم فشار

تحقیقات مهندسی سازه های آبیاری و زهکشی
دوره 26، شماره 100، مهر 1404، صفحه 16-1    اصل مقاله (714.31 K)
نوع مقاله: یادداشت فنی
شناسه دیجیتال (DOI): 10.22092/idser.2025.370504.1628
نویسندگان
آرزو مختاری حصاری* 1؛ علیرضا نعمتی2
1استادیار گروه کشاورزی، دانشگاه پیام نور، تهران، ایران.
2استادیار گروه روانشناسی و علوم تربیتی، دانشگاه پیام نور، تهران، ایران.
چکیده
با توجه به اهمیت عوامل متعدد بر رفتار کشاورزان در به ­کارگیری فناوری­های نوین آبیاری، پژوهش حاضر با هدف تبیین نقش سهولت کاربرد فناوری و خودکارآمدی کشاورزان بر رفتار به ­کارگیری سامانۀ نوین آبیاری کم­فشار اجرا شده است. این پژوهش به لحاظ هدف، کاربردی و از نظر طرح تحقیق، پژوهش­ کمی است. جامعۀ آماری تحقیق، کشاورزان استان آذربایجان ­شرقی به تعداد 112010 نفر بودند که بر اساس فرمول کوکران، نمونه 383 نفری از آن‌ها با استفاده از روش نمونه‌گیری چندمرحله‌ای انتخاب شد. برای تجزیه و تحلیل داده ­ها از نرم ­افزارهای SPSS20 و AMOS21 استفاده شد. نتایج تجربی پژوهش با استفاده از مدل‌سازی معادلات ساختاری نشان داد که متغیرهای سهولت کاربرد فناوری و خودکارآمدی کشاورزان و تمایل به کاربرد فناوری آبیاری کم‌فشار، 60 درصد از واریانس متغیر کاربرد آبیاری کم‌فشار را تبیین کردند. همچنین، متغیر سهولت کاربرد فناوری، پیش‌بینی کننده قوی‌تری برای متغیر تمایل به کاربرد سامانه آبیاری کم‌فشار بوده است.
کلیدواژه‌ها
مدیریت مصرف آب؛ سامانه نوین آبیاری؛ پذیرش فناوری؛ رفتار کشاورزان
عنوان مقاله [English]
Explaining the role of farmers' self-efficacy and ease of technology application on the behavior of using low-pressure irrigation systems
نویسندگان [English]
Arezou Mokhtari hesari1؛ Alireza Nemati2
1Assistant Professor, Department of Agriculture, Payame Noor University, Tehran, Iran.
2Assistant Professor Department of Education Sciences, Payame Noor University, Tehran, Iran.
چکیده [English]
Extended Abstract
Introduction
The majority of agricultural areas worldwide are managed using traditional surface irrigation methods. However, these methods face significant challenges, including inefficient water use and suboptimal productivity. Given their widespread use and low efficiency, improving surface irrigation systems has become essential. In recent decades, numerous initiatives have aimed to enhance the efficiency of irrigation systems and management practices. One such advancement is the development of low-pressure irrigation systems. Studies based on behavioral theories examining farmers’ adoption of irrigation technologies have identified several influential factors. Accordingly, this study aims to explain the role of technology ease of use and farmers’ self-efficacy in influencing their behavior toward adopting and using modern low-pressure irrigation systems.
 Materials and Methods
The method of this research follows a quantitative paradigm. In terms of purpose, it is applied research, and in terms of data collection, it is descriptive research conducted through a survey. In total, 112,010 farmers in East Azerbaijan Province formed the study population, and a sample of 393 was selected using the Cochran formula through multi-stage sampling. The main data collection tool was a researcher-designed questionnaire consisting of three parts: the first part relates to the individual characteristics of the farmers, the second part concerns the characteristics of the exploitation system, and the third part includes items related to the main variables. The face and content validity of the questionnaire were confirmed by professors and subject matter experts. The reliability of the research instrument was determined using Cronbach’s alpha, and construct validity was assessed through convergent validity using confirmatory factor analysis. SPSS 20 and AMOS 21 software were used for data analysis.
Results 
The measurement and structural model analyses indicated that model fit was acceptable across multiple indices and that the hypothesized relationships among the variables were logically consistent. Hypothesis testing revealed that all proposed relationships were statistically significant. Specifically, there was a positive and significant relationship between the perceived ease of use of the low-pressure irrigation system and farmers’ willingness to adopt it. Additionally, farmers’ self-efficacy was found to be significantly associated with their willingness to use the technology. Overall, structural equation modeling showed that ease of use and self-efficacy together explained 60% of the variance in farmers’ willingness to adopt low-pressure irrigation systems, with ease of use emerging as the stronger predictor.
 
Conclusions
This study investigated the factors influencing farmers’ adoption of low-pressure irrigation systems. Specifically, it examined the effects of perceived ease of use of the technology and farmers’ self-efficacy on their willingness to adopt such systems. The findings confirmed that both factors significantly influence adoption, with ease of use playing a particularly strong role. When the equipment, connections, and maintenance of the irrigation system are simple to operate and learn, farmers are more likely to adopt low-pressure irrigation. Additionally, farmers’ confidence in their ability to implement water conservation strategies enhances their conservation behavior. In other words, effective water conservation depends on farmers’ understanding and belief in their own capabilities.
کلیدواژه‌ها [English]
Water consumption management, Modern irrigation system, Technology acceptance, Farmers' behavior
مراجع

 

Abbasi, F., Abbasi, N. (2023). An analysis of irrigation efficiencies over time. Iranian Irrigation and Drainage,. 17(6), 1025-1033. (In Farsi)

Ahmadvand, M., &Sharafipour, L. (2019). Determinants of water conservation behavior of wheat farmers in Orzuieh city using conservation motivation theory. Irrigation and Water Engineering of Iran, 38, 275-259. (In Farsi)

Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.

Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Applied Social Psychology, 32(4), 665-683.

Ataei, P., Karimi, H., Hallaj, Z., Mottaghi, A. (2024). Risks of farmer’s behavior change towards water conservation: a study in the southeast of Iran. Water supply, 24(3), 723.

Behbahani Motlagh, M., Sharifzadeh, M-S., Abdollahzadeh, G-H. & Mahboobi, M-R. (2018). Farmers' Adoption Behavior of Pressurized Irrigation Technology in Dashtestan County.  Agricultural Extension and Education, 13 (1), 89-103. (In Farsi)

Bolliger, D. U., Supanakorn, S., & Boggs, C. (2010). Impact of podcasting on student motivation inthe online learning environment. Computers and Education, 55(2), 714-722.

Chen, M. F. & Tung, P. J. (2014). Developing an extended theory of planned behavior model to predict consumers' intention to visit green hotels. Hospitality Management, 36, 221–230.

Darko R O, Liu J P, Yuan S Q, Sam-Amoah L K, Yan H F.(2020). Irrigated agriculture for food self-sufficiency in the sub-Saharan African region. Int J Agric & Biol Eng, 13(3): 1–12.

East Azerbaijan Jihad-e-Agriculture Organization. (2017). Fifty-seven thousand hectares of land in East Azerbaijan are equipped with modern irrigation. Retrieved from: http://www.irna.ir/eazarbaijan/fa/News/ (In Farsi)

East Azerbaijan Agricultural Jihad Organization. (2023). 96,231 hectares of agricultural lands in East Azerbaijan have been equipped with modern irrigation systems. Available on the website: https://www.irna.ir/news/84743419(In Farsi)

El-Shafie, A.F., Marwa, M.A, & Dewedar, O.M. (2018). Research Article Hydraulic Performance Analysis of Flexible Gated Pipe Irrigation Technique Using GPIMOD Model. Asian Journal of Crop Science, 10(4), 180-189.

Folorunso, O., & Ogunseye, S. (2008). Applying an enhanced technology acceptance model to knowledge management in agricultural extension services. Data Science Journal, 7. 31-45.

Gangwal, N. & Bansal, V. (2016). Application of Decomposed Theory of Planned Behavior for M-commerce Adoption in India. Proceeding of 18th International Conference on Enterprise Information Systems (ICEIS), India, 357-367.

Garcia-Saldana, A., Landeros-Sanchez, C., Castaneda-Chavez, M., Martinez-Davila, J., Perez-Vazquez, A., & Carrillo-Avila, E. (2019). Fertirrigation with Low-Pressure Multi-Gate Irrigation Systems in Sugarcane Agro ecosystems: A Review. Pedosphere, 29(1), 1–11.

Ghorbani piralidehi, F., Alibeigi, A-H. & Simohamadi, S. (2013). Examining the Technology Acceptance Model of IPM among Orchard Farmers of Dalahoo Township, Agricultural Extension and Education Research, 6(4), 107-123. (In Persian).

Hung, S.Y., & Wu, H, L. (2012). Factors Influencing User Acceptance of Web-Based Decision Support Systems. Journal of Computer Information Systems, 52(4), 70-77.

Kakkavou, K., Gemtou, M., Founta, S. (2024). Drivers and barriers to the adoption of precision irrigation technologyes in olive and cotton farming lessons from Messenia and Thessaly regions in Greece.Smart Agricultural Technology. 7, 100401.

Kazemi, A., Nilipour, A. & Kabiry, N. (2013). Factors affecting Isfahanian mobile banking adoption based on the decomposed theory of planned behavior. Academic Research in Business and Social Sciences, 7(3), 230–245. (In Farsi)

Koech, R. Haase, M. Grima, B. Taylor, B. 2021. Barriers and measures to improve adoption of irrigation technologies: A case study from the Bundaberg region in Queensland, Australia. Irrigation and Drainage, 70(5).  

 Kernecker, M, A. Knierim, A. Wurbs, T. Kraus, F. Borges, Experience versus expectation: farmers’ perceptions of smart farming technologies for cropping
systems across Europe, Prec. Agric. 21 (2020) 34–50, https://doi.org/10.1007/
s11119-019-09651-z.

Leejoeiwara, B. (2015). Modeling adoption intention of online education in Thailand using DTPB with self- directed learning. Assumption University. Retrieved from: http://repository.au.edu/handle/6623004553 /3026.

Maranguni, N and A. Grani, A. (2015). Technology acceptance model: a literature review from
1986 to 2013, Universal Access Inf. Soc. 14 (2015) 81–95,
https://doi.org/10.1007/s10209-014-0348-1.

Mokhtari Hesari, A., Rezaei, R. and Shabanali Fami, Hossein. (2019). Opinion of East Azerbaijan Agricultural Jihad experts on the problems of using low-pressure irrigation systems by farmers. Agricultural Education Management Research, 50, 74-90.

Mohseni, A., Mousavi, S. H. & Jamali M. (2013). The role of entrepreneurship training on students’ entrepreneurial attitude and general self-efficiency beliefs. Research and Planning in Higher Education, 19 (3), 63-80. (In Farsi)

Moons, I. & De Pelsmacker, P. (2015). An Extended Decomposed Theory of Planned Behavior to Predict the Usage Intention of the Electric Car: A Multi-Group Comparison. Sustainability, 7, 6212-6245.

Moradhaseli, S., Ataei, P., Van den Broucke, S. & Karimi, H. 2021 the process of farmers’ occupational health behavior by health belief model: Evidence from Iran. Journal of Agromedicine 26 (2), 231–244. doi:10.1080/1059924X.2020.1837316.

Movahedi, R., Izadi, N. & Vahdatadab, R. (2018). Investigating Factors Affecting Farmers’Adoption of Pressurized Irrigation Tchnology in Asadabad County, Hamedan Province. Water Research in Agriculture, 31 (2), 287-300. (In Farsi)

Osama, A. M., Ahmed, A. & Mohammed, S.H. (2015). Performance Evaluation of Gated Pipes Technique for Improving Surface Irrigation Efficiency in Maize Hybrids. Agricultural Sciences, 6, 550-570.

Pathak, H.S, P. Brown, T. Best. (2019). A systematic literature review of the factors affecting the precision agriculture adoption process, Precis. Agric. 20 (2019) 1292–1316, https://doi.org/10.1007/s11119-019-09653-x

Pereira, L.S., Calejo, M.J., Lamaddalena, N., Douteb, A. & Bounoua, R. (2003). Design and performance analysis of low-pressure irrigation distribution systems. Irrigation and Drainage Systems, 17, 305-324.

Rahimi Faizabadi, F., Yazdanpanah, M.,  Forouzani, M., Mohammad Zadeh, S. & Burton, R. (2017). Explanation of Farmers' Water Conservation Behaviors Using Extended Planned Behavior Theory: The Case of Farmers in Aleshtar County. Agricultural Extension and Education, 12(2), 1-17. (In Farsi)

Rezaei, R., Mokhtari Hesari, A. and ُShababali Fami, H. 2021. Analysis of Psychological Factors Affecting Farmers’ Behavior in Using Low-pressure Irrigation System in the East Azarbaijan Province. Iranian Journal of Agricultural Economics and Development Research, 52(3), 469-487. Doi: 10.22059/ijaedr.2021.311867.6689

Sadeghi, A.,  Farhadian, H., & Bijani, B. (2020). The mediating role of farmers' time perspective in water resources exploitation behaviour in the eastern area of Lake Urmia, Iran: An environmental psychological analysis. . Water and Environment, 34(s1), 106-120. (In Farsi)

Sandoghi, A. & Raheli, H. (2017). Extending the model of planned behavior to predict the intention of producing organic products among Isfahan cucumber greenhouse owners by Moral norm variable. Iranian Journal of Agricultural Economics and Development Research, 47-2(4), 961-974. (In Farsi)

Sarlak, M-A., GHolpaygani, Z, & Yamani, M. (2015). Investigating the effective factors on the acceptance of e-government by those who refer to the judiciary of Tehran province based on the DTPB model. Management and Development Process, 27(1), 27-42. (In Farsi)

Shen, C.C., and Chiou, J.S. (2010). The impact of perceived ease of use on internet service adoption: the moderating effects of temporal distance and perceived risk. Computers in Human. Behavior, 23(1), 42-50.

Singh, A., Jhorar, R.K., Kumar, S. and Kumar, N. (2018). Performance Evaluation of Surface Irrigation Method under Cotton-Wheat Rotation. Current Microbiology and Applied Sciences. 7(5), 1014-1026.

Statistical Center of Iran (2014). Detailed results of the general agricultural census of 2014, East Azerbaijan Province. Management and Planning Organization

 Tao, C.C., & Fan, C.C. (2017). A Modified Decomposed Theory of Planned Behavior Model to Analyze User Intention towards Distance-Based Electronic Toll Collection Services. Promet – Traffic and Transportation, 29 (1), 85-97.

Taylor, S., & Todd, P.A. (1995). Understanding information technology usage, a test of competing modeles. Information Systems Research, 6 (2), 144-176.

Thompson, E.J., Merkley, G.P., Keller, A.A. & Barfuss, S.L. (2010). Experimental determination of the hydraulic properties of low-pressure, lay-flat drip irrigation systems. Irrigation and Drainage Engineering. 137 (1), 37-48.

Tognetti, R., Palladino, M., Delfine, S. & Alvino, A. (2003). The response of sugar beet to drip and low-pressure sprinkler irrigation in southern Italy. Agricultural Water Management. 60 (2), 135-155.

Valizadeh, N., & Karimi Goghari, H. (2018). Psychological and social analysis of water resources protection: a solution to reduce vulnerability to water shortage. The Second National Conference on Meteorology of Iran, Mashhad. (In Farsi)

Venkatesh, V., and Davis, F.D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Journal of Management Science, 46(2) 186 -204.

Verma, P., & Sinha, N. (2018). Integrating perceived economic wellbeing to technology acceptance model: The case of mobile based agricultural extension service. Technological Forecasting and Social Change, 126, 207-216.

Warner, L. A., Lamm, A. J. & Silvert, C. (2020). Diffusion of water-saving irrigation innovations in Florida’s urban residential
landscapes. Urban Forestry & Urban Greening 47, 126540. https://doi.org/10.1016/j.ufug.2019.126540.

Wang, Y., Wang, Z., Zhao, M., Li, B. (2024). The influence of thechnology perceptions on farmer’s water saving irrigation technology adoption behavior in the north china plain. Water policy, 26(2), and 170.

Woltering, L., Ibrahim, A., Pasternak, D. & Ndjeunga, J. (2011). The economics of low pressure drip irrigation and hand watering for vegetable production in the Sahel. Agricultural Water Management, 99 (1), 67-73.  

Yadavar, H., Nami, M. & Zarifiyan, SH. (2018). Applying the Analysis of Planned Behavior Theory on Adoption of Organic Farming. Agricultural Science and Sustainable Production, 28 (1), 169-183. (In Farsi)

Zeweld, W., Huylenbroeck, G.V., Tesfay, G. & Speelman, S. (2017). Smallholder farmers' behavioral intentions towards sustainable agricultural practices. Environmental Management, 187, 71-81.

آمار
تعداد مشاهده مقاله: 215
تعداد دریافت فایل اصل مقاله: 199


counter
سامانه مدیریت نشریات علمی. طراحی و پیاده سازی از سیناوب