A Systematic Literature Review: UTAUT Model Research for Green Farmer Adoption

Zaenal Arifin Siregar (1), Sutrisno Anggoro (2), Hari Eko Irianto (3), Hartuti Purnaweni (4)
(1) Department of Environmental Science, School of Doctoral Studies, Diponegoro University Research and Development for Land and Marine Bio Industry, National Research and Innovation Agency
(2) Facultyi ofi Fisheriesi andi Marinei Sciencei, Diponegoroi Universityi, Semarangi, Indonesia
(3) Researchi Centeri andi Developmenti fori Marinei andi Fisheriesi Producti Processingi andi Biotechnologyi (BBP4BKP), Ministryi ofi Marinei Affairsi andi Fisheriesi, Jakarta, Indonesia
(4) Departmenti ofi Environmentali Sciencei, Schooli of Doctorali Studiesi, Diponegoroi Universityi, Semarang, Indonesia
Fulltext View | Download
How to cite (IJASEIT) :
Siregar, Zaenal Arifin, et al. “A Systematic Literature Review: UTAUT Model Research for Green Farmer Adoption”. International Journal on Advanced Science, Engineering and Information Technology, vol. 12, no. 6, Dec. 2022, pp. 2485-90, doi:10.18517/ijaseit.12.6.15834.
Increased food production necessitates technological adoption. Model adoption is a term that refers to the Unified Theory of Acceptance and Use of Technology (UTAUT). The model development research seeks to identify critical variables influencing technology adoption. The development objective is to accelerate the adoption of innovative technology. A literature study is used to develop the UTAUT model and identifies significant factors. SALSA was utilized to conduct this literature review (Secondary Appraisal, Synthesis, and Analysis). The analytical technique employed is a meta-analysis, with the findings shown as a forest plot. Three hundred ten journals were collected for this study evaluation, with 11 selected for further examination. Currently, 13 models are being used in selected journals to modify the UTAUT model. Much of the research in Asia is conducted in research sites. In comparison to the modified UTAUT model, the UTAUT model has the most significant association with technology adoption (0.432). On the other hand, that model exhibits a high degree of heterogeneity (81.5%). Behavioral Intention (0.384) is a component of the UTAUT model, with considerable variability seen in the data (70.3%). Agriculture interventions must be directed at boosting the use of technology. A farmer may engage the services of a mediator following the UTAUT paradigm. Three critical factors to examine are Performance Expectancy, Social Influence, and Facilitating Condition Factors.

M. H. M. Salim, N. M. Ali, and S. A. M. Noah, “Mobile Application on Healthy Diet for Elderly based on Persuasive Design,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 7, no. 1, p. 222, Feb. 2017, doi: 10.18517/ijaseit.7.1.1725.

D. Witarsyah, M. F. MD Fudzee, and M. A. Salamat, “A Conceptual Study on Generic End Users Adoption of e-Government Services,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 7, no. 3, p. 1000, Jun. 2017, doi: 10.18517/ijaseit.7.3.1654.

D. Napitupulu, “A Conceptual Model Of E-Government Adoption in Indonesia,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 7, no. 4, p. 1471, Aug. 2017, doi: 10.18517/ijaseit.7.4.2518.

C. W. Runyan and J. Stehm, “Land Use Change, Deforestation and Competition for Land Due to Food Production,” in Encyclopedia of Food Security and Sustainability, Elsevier, 2019, pp. 21-26.

R. Wohlgemuth, T. Twardowski, and A. Aguilar, “Bioeconomy moving forward step by step - A global journey,” N. Biotechnol., vol. 61, no. November 2020, pp. 22-28, Mar. 2021, doi: 10.1016/j.nbt.2020.11.006.

R. F. Sage, “Global change biology: A primer,” Glob. Chang. Biol., vol. 26, no. 1, pp. 3-30, 2020, doi: 10.1111/gcb.14893.

H. Zhang, L. Wang, S. Yu, J. Zhao, and Z. Shi, “Identifying government’s and farmers’ roles in soil erosion management in a rural area of southern China with social network analysis,” J. Clean. Prod., vol. 278, p. 123499, Jan. 2021, doi: 10.1016/j.jclepro.2020.123499.

D. H. Galeon, P. G. Garcia Jr., and T. D. Palaoag, “SMS-Based ICT Tool for Knowledge Sharing in Agriculture,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 9, no. 1, p. 342, Jan. 2019, doi: 10.18517/ijaseit.9.1.7551.

D. O. Pribadi and S. Pauleit, “The dynamics of peri-urban agriculture during rapid urbanization of Jabodetabek Metropolitan Area,” Land use policy, vol. 48, pp. 13-24, 2015, doi: 10.1016/j.landusepol.2015.05.009.

J. Iskandar, B. S. Iskandar, and R. Partasasmita, “Review: The impact of social and economic change on domesticated plant diversity with special reference to wet rice field and home-garden farming of West Java, Indonesia,” Biodiversitas J. Biol. Divers., vol. 19, no. 2, pp. 515-527, Mar. 2018, doi: 10.13057/biodiv/d190227.

I. Ardiansah, N. Bafdal, E. Suryadi, and A. Bono, “Greenhouse monitoring and automation using arduino: A review on precision farming and Internet of Things (IoT),” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 10, no. 2, pp. 703-709, 2020, doi: 10.18517/ijaseit.10.2.10249.

L. Balaine, E. J. Dillon, D. Lí¤pple, and J. Lynch, “Can technology help achieve sustainable intensification? Evidence from milk recording on Irish dairy farms,” Land use policy, vol. 92, no. January, p. 104437, Mar. 2020, doi: 10.1016/j.landusepol.2019.104437.

S. A. R, D. Salman, A. R. Siregar, and S. Baba, “Modernizing Dairy Farm: A Production Mode Analysis,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 10, no. 2, p. 775, Apr. 2020, doi: 10.18517/ijaseit.10.2.9489.

C. R. Foguesatto, J. A. R. Borges, and J. A. D. Machado, “A review and some reflections on farmers’ adoption of sustainable agricultural practices worldwide,” Sci. Total Environ., vol. 729, p. 138831, Aug. 2020, doi: 10.1016/j.scitotenv.2020.138831.

S. Garcí­a de Jalón, A. Iglesias, and M. B. Neumann, “Responses of sub-Saharan smallholders to climate change: Strategies and drivers of adaptation,” Environ. Sci. Policy, vol. 90, no. September, pp. 38-45, 2018, doi: 10.1016/j.envsci.2018.09.013.

T. Jitmun, J. K. M. Kuwornu, A. Datta, and A. Kumar Anal, “Factors influencing membership of dairy cooperatives: Evidence from dairy farmers in Thailand,” J. Co-op. Organ. Manag., vol. 8, no. 1, p. 100109, Jun. 2020, doi: 10.1016/j.jcom.2020.100109.

F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Q. Manag. Inf. Syst., vol. 13, no. 3, pp. 319-339, Sep. 1989, doi: 10.2307/249008.

V. Venkatesh, “Determinants of Perceived Ease of Use”¯: Integrating Control , Intrinsic Motivation , Acceptance Model,” J. Inf. Syst. Res., vol. 11, no. 4, pp. 342-365, 2000, doi: http://dx.doi.org/10.1287/ isre.11.4.342.11872.

B. Alexandre, E. Reynaud, F. Osiurak, and J. Navarro, “Acceptance and acceptability criteria: a literature review,” Cogn. Technol. Work, vol. 20, no. 2, pp. 165-177, 2018, doi: 10.1007/s10111-018-0459-1.

S. Noordin, N. S. Ashaari, and T. S. M. T. Wook, “A proposed model for Virtual Fitting Room based on usability and profound emotional elements,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 8, no. 6, pp. 2332-2340, 2018, doi: 10.18517/ijaseit.8.6.6440.

V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User Acceptance of Information Technology: Toward a Unified View,” MIS Q. Manag. Inf. Syst., vol. 27, no. 3, pp. 425-478, May 2003, doi: 10.1016/j.inoche.2016.03.015.

O. Calicioglu, A. Flammini, S. Bracco, L. Bellí¹, and R. Sims, “The future challenges of food and agriculture: An integrated analysis of trends and solutions,” Sustain., vol. 11, no. 1, 2019, doi: 10.3390/su11010222.

D. Neuhoff and J. Kwesiga, “Para-organic intensification of future farming as alternative concept to reactor-based staple food production in Africa,” Org. Agric., vol. 11, no. 2, pp. 209-215, Jun. 2021, doi: 10.1007/s13165-020-00326-y.

A. Kaufman and S. Watanasak, “Farmers and Fertilizers: A Socio-ecological Exploration of the Alternative Agriculture Movement in Northeastern Thailand”, Environ Nat Resour J, vol. 9, no. 3, pp. 1-11, Apr. 2017.

J. Rungcharoen, S. Hungspreug, S. Pleumpanya, and N. Insalud, “Improvement of Local Rice Productivity in the Thai Highland Areas”, Environ Nat Resour J, vol. 12, no. 2, pp. 18-23, Dec. 2014.

T. D. Pigott and J. R. Polanin, “Methodological Guidance Paper: High-Quality Meta-Analysis in a Systematic Review,” Rev. Educ. Res., vol. 90, no. 1, pp. 24-46, 2020, doi: 10.3102/0034654319877153.

I. Ferní¡ndez del Amo, J. A. Erkoyuncu, R. Roy, R. Palmarini, and D. Onoufriou, “A systematic review of Augmented Reality content-related techniques for knowledge transfer in maintenance applications,” Comput. Ind., vol. 103, pp. 47-71, Dec. 2018, doi: 10.1016/j.compind.2018.08.007.

M. K. Alqudah and R. Razali, “Key Factors for Selecting an Agile Method: A Systematic Literature Review,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 7, no. 2, p. 526, Apr. 2017, doi: 10.18517/ijaseit.7.2.1830.

L. Malinauskaite, D. Cook, B. Daví­í°sdóttir, H. í–gmundardóttir, and J. Roman, “Ecosystem services in the Arctic: a thematic review,” Ecosyst. Serv., vol. 36, 2019, doi: 10.1016/j.ecoser.2019.100898.

C. Camargo, J. Goní§alves, M. í. Conde, F. J. Rodrí­guez-sedano, P. Costa, and F. J. Garcí­a-peñalvo, “Educational Robotics Context,” pp. 1-25, 2021.

W. Mengist, T. Soromessa, and G. Legese, “Ecosystem services research in mountainous regions: A systematic literature review on current knowledge and research gaps,” Sci. Total Environ., vol. 702, p. 134581, Feb. 2020, doi: 10.1016/j.scitotenv.2019.134581.

J. Mantua et al., “A systematic review and meta-analysis of sleep architecture and chronic traumatic brain injury,” Sleep Med. Rev., vol. 41, pp. 61-77, 2018, doi: 10.1016/j.smrv.2018.01.004.

H. Borgeraas, L. K. Johnson, J. Skattebu, J. K. Hertel, and J. Hjelmesí¦th, “Effects of probiotics on body weight, body mass index, fat mass and fat percentage in subjects with overweight or obesity: a systematic review and meta-analysis of randomized controlled trials,” Obes. Rev., vol. 19, no. 2, pp. 219-232, 2018, doi: 10.1111/obr.12626.

M. U. Khan and T. U. Rehman, “Early trends, current status and future prospects of farm mechanization in Asia,” Agric. Eng. Int. CIGR J., vol. 21, no. 3, pp. 76-87, 2019.

F. T. S. Chan, A. Yee-Loong Chong, and L. Zhou, “An empirical investigation of factors affecting e-collaboration diffusion in SMEs,” Int. J. Prod. Econ., vol. 138, no. 2, pp. 329-344, 2012, doi: 10.1016/j.ijpe.2012.04.004.

A. A. Faridi, M. Kavoosi-Kalashami, and H. El Bilali, “Attitude components affecting adoption of soil and water conservation measures by paddy farmers in Rasht County, Northern Iran,” Land use policy, vol. 99, no. April, p. 104885, 2020, doi: 10.1016/j.landusepol.2020.104885.

E. Beza, P. Reidsma, P. M. Poortvliet, M. M. Belay, B. S. Bijen, and L. Kooistra, “Exploring farmers’ intentions to adopt mobile Short Message Service (SMS) for citizen science in agriculture,” Comput. Electron. Agric., vol. 151, no. May, pp. 295-310, 2018, doi: 10.1016/j.compag.2018.06.015.

N. Nejadrezaei, M. S. Allahyari, M. Sadeghzadeh, A. Michailidis, and H. El Bilali, “Factors affecting adoption of pressurized irrigation technology among olive farmers in Northern Iran,” Appl. Water Sci., vol. 8, no. 6, pp. 1-9, 2018, doi: 10.1007/s13201-018-0819-2.

J. Silva et al., “Factors affecting the big data adoption as a marketing tool in SMEs,” Commun. Comput. Inf. Sci., vol. 1071, pp. 34-43, 2019, doi: 10.1007/978-981-32-9563-6_4.

J. A. Krishnan, ICT Unbounded, Social Impact of Bright ICT Adoption, vol. 558. Springer International Publishing, 2019.

K. E. Trozzo, J. F. Munsell, and J. L. Chamberlain, “Landowner interest in multifunctional agroforestry Riparian buffers,” Agrofor. Syst., vol. 88, no. 4, pp. 619-629, 2014, doi: 10.1007/s10457-014-9678-5.

M. Diekmann and L. Theuvsen, “Non-participants interest in CSA - Insights from Germany,” J. Rural Stud., vol. 69, no. May 2018, pp. 1-10, 2019, doi: 10.1016/j.jrurstud.2019.04.006.

R. Rezaei and M. Ghofranfarid, “Rural households’ renewable energy usage intention in Iran: Extending the unified theory of acceptance and use of technology,” Renew. Energy, vol. 122, pp. 382-391, 2018, doi: 10.1016/j.renene.2018.02.011.

G. Fox, J. Mooney, P. Rosati, V. Paulsson, and T. Lynn, “Towards an understanding of farmers’ mobile technology adoption: A comparison of adoption and continuance intentions,” Am. Conf. Inf. Syst. 2018 Digit. Disruption, AMCIS 2018, pp. 1-10, 2018.

M. Michels, V. Bonke, and O. Musshoff, “Understanding the adoption of smartphone apps in crop protection,” Precis. Agric., no. 0123456789, 2020, doi: 10.1007/s11119-020-09715-5.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).