Competency development through empowerment: A model for millennial vegetable farmers in West Java Highlands
Main Article Content
Abstract
The decreasing interest in agriculture among younger generations threatens Indonesia’s food security, particularly as food demand rises. Enhancing millennial farmers’ competencies is essential due to their limited experience and formal education. This study develops an empowerment model aimed at increasing competencies among millennial vegetable farmers in West Java. Using a cross-sectional survey and Structural Equation Modeling (SEM) with AMOS, this research examined how factors such as environmental and institutional support, participation, and motivation influence competencies. Model fit was confirmed with indices including Comparative Fit Index (CFI) = 0.936, Goodness-of-Fit Index (GFI) = 0.920, Adjusted Goodness-of-Fit Index (AGFI) = 0.900, Tucker-Lewis Index (TLI) = 0.921, and Root Mean Square Error of Approximation (RMSEA) = 0.047. Findings highlight that nearest environment support and intrinsic motivation are key factors shaping farmers’ perceptions and competencies, while institutional support significantly affects perceptions but has a less direct influence on competence. Active participation and motivation were positively correlated with enhanced competence. This empowerment model underscores the importance of combining institutional support with strategies to increase motivation and engagement, offering actionable insights for policymakers and practitioners to improve the effectiveness and sustainability of millennial farmers in vegetable farming.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
You are free to: Share — copy and redistribute the material in any medium or format. Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
How to Cite
Share
References
Agboola, A., Adekunle, I., & Ogunjimi, S. (2015). Assessment of youth participation in indigenous farm practices of vegetable production in Oyo State, Nigeria. Journal of Agricultural Extension and Rural Development, 7, 73–79. https://doi.org/10.5897/JAERD2014.0590
Ahaibwe, G., Mbowa, S., & Lwanga, M. M. (2013). Youth engagement in agriculture in Uganda: Challenges and prospects.
Antwi-Agyei, P., & Stringer, L. C. (2021). Improving the effectiveness of agricultural extension services in supporting farmers to adapt to climate change: Insights from northeastern Ghana. Climate Risk Management, 32, 100304.
Barghusen, R., Sattler, C., Deijl, L., Weebers, C., & Matzdorf, B. (2021). Motivations of farmers to participate in collective agri-environmental schemes: The case of Dutch agricultural collectives. Ecosystems and People, 17, 539–555. https://doi.org/10.1080/26395916.2021.1979098
Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258.
Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. routledge.
Casadevall, A., & Fang, F. C. (2016). Rigorous Science: A How-To Guide. mBio, 7(6), 10.1128/mbio.01902-16. https://doi.org/10.1128/mbio.01902-16
Chambers, R. (1995). Poverty and livelihoods: Whose reality counts? Environment and Urbanization, 7(1), 173–204.
Charatsari, C., Lioutas, E. D., & Koutsouris, A. (2017). Farmers’ motivational orientation toward participation in competence development projects: A self-determination theory perspective. The Journal of Agricultural Education and Extension, 23, 105–120. https://doi.org/10.1080/1389224X.2016.1261717
Chinsinga, B., Matita, M., Chimombo, M., Msofi, L., Kaiyatsa, S., & Mazalale, J. (2021). Agricultural commercialisation and rural livelihoods in Malawi: A historical and contemporary agrarian inquiry. APRA Working Paper, 75.
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
de Janvry, A., & Sadoulet, E. (2020). Using agriculture for development: Supply-and demand-side approaches. World Development, 133, 105003.
DeVon, H. A., Block, M. E., Moyle-Wright, P., Ernst, D. M., Hayden, S. J., Lazzara, D. J., Savoy, S. M., & Kostas-Polston, E. (2007). A psychometric toolbox for testing validity and reliability. Journal of Nursing Scholarship, 39(2), 155–164.
Diana, A. (2022). Motivation, competence and empowerment in farming group productivity at uptd fisheries and livestock. 1(2). https://doi.org/10.58468/ijmeba.v1i2.19
Geza, W., Ngidi, M. S. C., Ojo, T., Adetoro, A., Slotow, R., & Mabhaudhi, T. (2021). Youth Participation in Agriculture: A Scoping Review. Sustainability, 13, 9120–9120. https://doi.org/10.3390/su13169120
Glover, D., Mausch, K., Conti, C., & Hall, A. (2021). Unplanned but well prepared: A reinterpreted success story of international agricultural research, and its implications. Outlook on Agriculture, 50(3), 247–258.
Gosnell, H., Gill, N., & Voyer, M. (2019). Transformational adaptation on the farm: Processes of change and persistence in transitions to ‘climate-smart’regenerative agriculture. Global Environmental Change, 59, 101965.
Grando, S., Bartolini, F., Bonjean, I., Brunori, G., Mathijs, E., Prosperi, P., & Vergamini, D. (2020). Small farms’ behaviour: Conditions, strategies and performances. In Innovation for sustainability: Small farmers facing new challenges in the evolving food systems (pp. 125– 169). Emerald Publishing Limited.
Hair, J. F. (2009). Multivariate data analysis.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., Tatham, R. L., & others. (2006). Multivariate data analysis 6th Edition. Pearson Prentice Hall. New Jersey. humans: Critique and reformulation.
Haryati, N., Lasitya, D. S., Nurirrozak, M. Z., Herdianti, D. F., Fibrianingtyas, A., & Hidayat, A. R. T. (2024). Demographics and course choices: Impact on youth farming intention in Indonesia. International Journal of Adolescence and Youth, 29(1), 2358088.
Hietkamp, F. (1994). Urban food production in Bandung, Indonesia [PhD Thesis]. University of British Columbia.
Howard-Grenville, J., Nash, J., & Coglianese, C. (2008). Constructing the license to operate: Internal factors and their influence on corporate environmental decisions. Law & Policy, 30(1), 73– 107.
Humphreys, R. K., Puth, M.-T., Neuhäuser, M., & Ruxton, G. D. (2019). Underestimation of Pearson’s product moment correlation statistic. Oecologia, 189, 1–7.
Jabarprov. (2022). Transformasi Pertanian Jawa Barat Melalui Petani Milenial. https://jabarprov.go.id/berita/transformasi-pertanian-jawa-barat-melalui-petani-milenial-2574
Keputusan Menteri Pertanian Republik Indonesia. (2021). Nomor 434/KPTS/SM.020/M/2021 tentang Duta Petani Milenial dan Duta Petani Andalan Pembangunan Pertanian.
Khoshmaram, M., Shiri, N., Shinnar, R. S., & Savari, M. (2020). Environmental support and entrepreneurial behavior among Iranian farmers: The mediating roles of social and human capital. Journal of Small Business Management, 58, 1064–1088. https://doi.org/10.1111/JSBM.12501
Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford publications.
Knook, J., & Turner, J. (2020). Reshaping a farming culture through participatory extension: An institutional logics perspective. Journal of Rural Studies, 78, 411–425. https://doi.org/10.1016/j.jrurstud.2020.06.037
Li, M., Wang, J., Zhao, P., Chen, K., & Wu, L.-F. (2020). Factors affecting the willingness of agricultural green production from the perspective of farmers’ perceptions. The Science of the Total Environment, 738, 140289. https://doi.org/10.1016/j.scitotenv.2020.140289
Liu, T., Bruins, R. J., & Heberling, M. T. (2018). Factors influencing farmers’ adoption of best management practices: A review and synthesis. Sustainability, 10(2), 432.
Menconi, M., Grohmann, D., & Mancinelli, C. (2017). European farmers and participatory rural appraisal: A systematic literature review on experiences to optimize rural development. Land Use Policy, 60, 1–11. https://doi.org/10.1016/J.LANDUSEPOL.2016.10.007
Mohajan, H. K. (2020). Quantitative research: A successful investigation in natural and social sciences. Journal of Economic Development, Environment and People, 9(4), 50–79.
Moschitz, H., Roep, D., Brunori, G., & Tisenkopfs, T. (2015). Learning and Innovation Networks for Sustainable Agriculture: Processes of Co-evolution, Joint Reflection and Facilitation. The Journal of Agricultural Education and Extension, 21, 1–11. https://doi.org/10.1080/1389224X.2014.991111
Muhie, S. H. (2022). Novel approaches and practices to sustainable agriculture. Journal of Agriculture and Food Research, 10, 100446.
Piñeiro, V., Arias, J., Dürr, J., Elverdin, P., Ibáñez, A. M., Kinengyere, A., Opazo, C. M., Owoo, N., Page, J. R., Prager, S. D., & others. (2020). A scoping review on incentives for adoption of sustainable agricultural practices and their outcomes. Nature Sustainability, 3(10), 809–820.
Prudon, P. (2015). Confirmatory factor analysis as a tool in research using questionnaires: A critique. Comprehensive Psychology, 4, 03-CP.