Extension, Resources and Institutional Support Associated with Oil Palm Farmers’ Adaptive Capacity in Riau, Indonesia

Dyah Retna Puspita; Adi Firmansyah; Anna Fatchiya; Hana Indriana; Meyzi  Heriyanto; Retno  Widihastuti; Masrul  Ikhsan; Elsa  Destriapani

doi:10.48165/IJEE.2026.62432

Authors

Dyah Retna Puspita Study Program of Communication and Community Development, Faculty of Social Sciences and Human Ecology, IPB University, Bogor, Indonesia
Adi Firmansyah Study Program of Communication and Community Development, Faculty of Social Sciences and Human Ecology, IPB University, Bogor, Indonesia
Anna Fatchiya Study Program of Communication and Community Development, Faculty of Social Sciences and Human Ecology, IPB University, Bogor, Indonesia
Hana Indriana Study Program of Communication and Community Development, Faculty of Social Sciences and Human Ecology, IPB University, Bogor, Indonesia
Meyzi Heriyanto Faculty of Social and Political Sciences (FISIP) Riau University
Retno Widihastuti National Agency for Research and Innovation (BRIN)
Masrul Ikhsan Faculty of Social and Political Sciences (FISIP) Riau University
Elsa Destriapani Study Program of Communication and Community Development, Faculty of Social Sciences and Human Ecology, IPB University, Bogor, Indonesia

https://doi.org/10.48165/IJEE.2026.62432

Keywords:

Adaptive Capacity, Advisory Services, Household Income, Indonesia, Institutional Support, Oil Palm, Smallholders

Abstract

Agricultural extension may strengthen farmers’ responses to production, market and information change, but its contribution is rarely separated from supporting institutions. This cross-sectional study examined how extension methods, household resources and institutional support predicted adaptive capacity among oil palm farmers in three villages of Tapung Subdistrict, Indonesia, from December 2023 to April 2024. Of 214 farmers interviewed, 11 incomplete questionnaires were excluded and 203 complete cases were analysed using partial least squares structural equation modelling with 5,000 bootstrap samples, PLSpredict and the cross-validated predictive ability test. Extension methods (β=0.106; p=0.016) and household resources (β=0.492; p<0.001) positively predicted adaptive capacity. Institutional support was positive (β=0.151; p=0.032), but its bias-corrected interval included zero; therefore, H3 was inconclusive. Separating the resource construct showed that household income carried the association (β=0.483; p<0.001), whereas formal education did not (β=0.022; p=0.764). The model explained 37.3% of adaptive-capacity variance. All indicator-level Q²predict values were positive, and PLS-SEM outperformed the linear benchmark for four of six indicators. The findings suggest combining accessible, dialogical extension with financially feasible recommendations, while coordinated public–private support requires further testing.

References

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. https://doi.org/10.1016/j.crm.2021.100304

Atube, F., Malinga, G. M., Nyeko, M., Okello, D. M., Alarakol, S. P., & Okello-Uma, I. (2021). Determinants of smallholder farmers’ adaptation strategies to the effects of climate change: Evidence from northern Uganda. Agriculture & Food Security, 10, 6. https://doi.org/10.1186/s40066-020-00279-1

Bartelet, H. A., Barnes, M. L., Bakti, L. A. A., & Cumming, G. S. (2023). Testing the reliability of adaptive capacity as a proxy for adaptive and transformative responses to climate change. Global Environmental Change, 81, 102700. https://doi.org/10.1016/j.gloenvcha.2023.102700

BPS-Statistics Indonesia. (2023). Indonesian oil palm statistics 2022. BPS-Statistics Indonesia. https://www.bps.go.id/en/publication/2023/11/30/160f211bfc4f91e1b77974e1/indonesian-oil-palm-statistics-2022.html

Dosso, F., Gouroubera, M. W., Idrissou, L., & Moumouni-Mousa, I. (2023). The combination of extension approaches strengthens farmers’ innovativeness in sustainable land management. Environment, Development and Sustainability, 26, 10043–10062. https://doi.org/10.1007/s10668-023-03134-y

Godara S., Bana R. S., Godara S. , Bishnoi, S., Nain M. S., Parsad R.& Marwaha S. (2024a).Data-driven insights for agricultural extension services in Rajasthan: A study of kisan call center queries, Indian Journal of Extension Education, 60(1), 53-58. https://doi.org/10.48165/IJEE.2024.60110

Godara S., Bana R.S., Marwaha S., Parsad R., Nain M.S., Sahu S., Mehta A., Singh D., & Kumar R. (2024b). Uncovering farmers' information need through kisan call centre data analytics of Haryana state. Indian Journal of Extension Education, 60(4), 59-66. https://doi.org/10.48165/IJEE.2024.60411

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.

Kamruzzaman, M., Daniell, K. A., Chowdhury, A., & Crimp, S. (2021). The role of extension and advisory services in strengthening farmers’ innovation networks to adapt to climate extremes. Sustainability, 13(4), 1941. https://doi.org/10.3390/su13041941

Kangogo, D., Dentoni, D., & Bijman, J. (2020). Determinants of farm resilience to climate change: The role of farmer entrepreneurship and value chain collaborations. Sustainability, 12(3), 868. https://doi.org/10.3390/su12030868

Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1–10. https://doi.org/10.4018/ijec.2015100101

Liengaard, B. D., Sharma, P. N., Hult, G. T. M., Jensen, M. B., Sarstedt, M., Hair, J. F., & Ringle, C. M. (2021). Prediction: Coveted, yet forsaken? Introducing a cross-validated predictive ability test in partial least squares path modeling. Decision Sciences, 52(2), 362–392. https://doi.org/10.1111/deci.12445

Ma, W., & Rahut, D. B. (2024). Climate-smart agriculture: Adoption, impacts, and implications for sustainable development. Mitigation and Adaptation Strategies for Global Change, 29, 44. https://doi.org/10.1007/s11027-024-10139-z

Maguire-Rajpaul, V. A., Khatun, K., & Hirons, M. A. (2020). Agricultural information’s impact on the adaptive capacity of Ghana’s smallholder cocoa farmers. Frontiers in Sustainable Food Systems, 4, 28. https://doi.org/10.3389/fsufs.2020.00028

Manevska-Tasevska, G., Petitt, A., Larsson, S., Bimbilovski, I., Meuwissen, M. P. M., Feindt, P. H., & Urquhart, J. (2021). Adaptive governance and resilience capacity of farms: The fit between farmers’ decisions and agricultural policies. Frontiers in Environmental Science, 9, 668836. https://doi.org/10.3389/fenvs.2021.668836

Maurya, A. S., Yadav, B., Patel, S., Kumar, R., & Kumar, A. (2026). Assessing the role of digital platforms in strengthening agricultural extension services: Advisory to empowerment. Indian Journal of Extension Education, 62(2), 47–53. https://doi.org/10.48165/IJEE.2026.62208

Nain M. S., Singh R., Mishra J.R., & Singh A. K. (2024). Developing model for diffusion of farmers’ innovations for maximizing farm income: Indian Agricultural Research Institute Experiences, Indian Journal of Extension Education, 60(1), 105-110. https://doi.org/10.48165/IJEE.2024.60120.

Niranjan S., Singh D.R., Kumar N.R., Jha G.K., Venkatesh P., Nain M.S, & Krishnakumare B.(2023). Do information networks enhance adoption of sustainable agricultural practices? Evidence from northern dry zone of Karnataka, India, Indian Journal of Extension Education 59 (1), 86-91 http://doi.org/10.48165/IJEE.2023.59118

Novira, N. (2023). The vulnerability of Indonesian smallholder oil palm farmers in the times of global crisis. IOP Conference Series: Earth and Environmental Science, 1190, 012044. https://doi.org/10.1088/1755-1315/1190/1/012044

Ogundeji, A. A., Danso-Abbeam, G., & Jooste, A. (2022). Climate information pathways and farmers’ adaptive capacity: Insights from South Africa. Environmental Development, 44, 100743. https://doi.org/10.1016/j.envdev.2022.100743

Osumba, J. J. L., Recha, J. W., & Oroma, G. W. (2021). Transforming agricultural extension service delivery through innovative bottom–up climate-resilient agribusiness farmer field schools. Sustainability, 13(7), 3938. https://doi.org/10.3390/su13073938

Paterson, R. R. M. (2023). Future climate effects on yield and mortality of conventional versus modified oil palm in Southeast Asia. Plants, 12(12), 2236. https://doi.org/10.3390/plants12122236

Reich, C.-E., Ölkers, T., Bonke, V., & Musshoff, O. (2025). Beyond the ban: Shedding light on smallholders’ price vulnerability in Indonesia’s palm oil industry. Applied Economic Perspectives and Policy, 48(3), 653–678. https://doi.org/10.1002/aepp.70040

Ringle, C. M., Wende, S., & Becker, J.-M. (2024). SmartPLS 4. SmartPLS GmbH. https://www.smartpls.com

Shitu, A. G., Ojo, D. T., Shitu, M. V., & Nain, M. S. (2026). Small-scale farmers’ willingness to pay for extension services: Evidence from Nigeria. Indian Journal of Extension Education, 62(1), 86–91. https://doi.org/10.48165/IJEE.2026.62114

Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. https://doi.org/10.1108/EJM-02-2019-0189

Sibhatu, K. T., Tabe-Ojong, M. P., Jr., & Siregar, H. (2025). Nature-based land management practices and yield dynamics in oil palm production: Insights from Indonesian smallholder growers. Agricultural Economics, 56(5), 713–727. https://doi.org/10.1111/agec.70018

Sthitaprajna, S., & Shasani, S. (2026). Factors influencing farmers’ adaptive capacity to climate change. Indian Journal of Extension Education, 62(1), 195–199. https://doi.org/10.48165/IJEE.2026.621RN02

van den Berg, H., Ketelaar, J. W., Dicke, M., & Fredrix, M. (2020). Is the farmer field school still relevant? Case studies from Malawi and Indonesia. NJAS: Wageningen Journal of Life Sciences, 92(1), 100329. https://doi.org/10.1016/j.njas.2020.100329

Vijayabhinandana, B., Asha, R., & Gowtham Kumar, B. S. N. S. (2022). Adaptation methods practiced by farmers in response to perceived climate change in Andhra Pradesh. Indian Journal of Extension Education, 58(2), 81–85. https://doi.org/10.48165/IJEE.2022.58216

Yadav, P. K., & Ghosh, S. (2023). Effectiveness of adaptation mechanisms of farmers and its determinants in flood-prone areas of Bihar. Indian Journal of Extension Education, 59(3), 32–37. https://doi.org/10.48165/IJEE.2023.59306