Abstract
This study analyzes the adoption patterns of sustainability practices among oil palm producers in Colombia using cluster analysis of the Sustainability Index (SI). Employing advanced data mining algorithms, including K-means and Ward’s method, producers were grouped according to their compliance with sustainable practices at national and regional levels. The analysis revealed ten distinct producer typologies, ranging from “Advanced adopters” to “Lagging adopters” in economic, environmental, and social sustainability dimensions. Key factors influencing cluster formation included palm-growing area, producer scale, age, and gender. At the same time, the Palm Nucleus (organizational model for fruit commercialization) emerged as a significant variable at the regional level. Our findings challenge the conventional notion that adoption of sustainability practices is primarily scale-dependent, showing that contextual factors play a crucial role across all producer categories. This research underscores the importance of more nuanced, context-specific technological extension strategies. By providing a comprehensive understanding of adoption patterns, this study contributes to developing tailored interventions that can effectively promote sustainable practices in the Colombian oil palm sector, regardless of producer characteristics.
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Data availability
Data Availability Statement: The datasets analyzed in this study are not publicly available due to confidentiality agreements with participating oil palm producers and the sensitive nature of the data. However, data are available from the corresponding author upon reasonable request and subject to approval by the Colombian Oil Palm Research Center Corporation – Cenipalma.
Abbreviations
- SI:
-
Sustainability Index
References
Garbely, A. & Steiner, E. Understanding compliance with voluntary sustainability standards: A machine learning approach. Environ. Dev. Sustain. 25, 11209–11239 (2023).
Hainmueller, J., Hiscox, M. J. & Sequeira, S. Consumer demand for fair trade: Evidence from a multistore field experiment. Rev. Econ. Stat. 97, 242–256 (2015).
Gagliardi, F., Brogi, L., Betti, G., Riccaboni, A. & Tozzi, C. Italian consumer willingness to pay for agri-food sustainable certification labels: The role of sociodemographic factors. Sustainability https://doi.org/10.3390/su17156792 (2025).
Merbah, N. & Benito-Hernández, S. Consumer willingness-to-pay for sustainable coffee: Evidence from a choice experiment on Fairtrade and UTZ certification. Sustainability https://doi.org/10.3390/su16083222 (2024).
Aminravan, M., Ahmadi Kaliji, S., Mulazzani, L., Rota, C. & Camanzi, L. Surveying consumer preferences for eco-labeled fruits and vegetables in Euro-Mediterranean alternative food systems. Front. Sustain. Food Syst. https://doi.org/10.3389/fsufs.2025.1576321 (2025).
Zhan, Y., Ren, Y. & Xu, J. Willingness to pay a premium for eco-label products in China: A mediation model based on quality value. Sci. Rep. https://doi.org/10.1038/s41598-025-86202-9 (2025).
Omar, A. E., Abu Bakar, H., Mohd, A. & Omar, A. H. The impact of the decentralization and Pluralism policy on agricultural extension services. Journal Agricultural Technology 7, (2011).
Bakar, A. H. Study of role of agricultural extension in the dissemination of sustainable agricultural development. Journal Agricultural Technology (2012).
Nakano, Y., Tsusaka, T. W., Aida, T. & Pede, V. O. Is farmer-to-farmer extension effective? The impact of training on technology adoption and rice farming productivity in Tanzania. World Dev. 105, 336–351 (2018).
Bell, S. & Morse, S. Sustainability indicators past and present: What next?. Sustainability https://doi.org/10.3390/su10051688 (2018).
Liu, Q., Jiang, Y., Lagerkvist, C. J. & Huang, W. Extension services and the technical efficiency of crop-specific farms in China. Agricultural Appl. Economic Association. 1–24 https://doi.org/10.1002/aepp.13209 (2021).
Salehi, M., Abbasi, E., Bijani, M. & Shahpasand, M. R. Evaluation of agricultural extension model sites approach in Iran. J. Saudi Soc. Agric. Sci. 20, 506–518 (2021).
Gil, J. et al. Genomic variability of Phytophthora palmivora isolates from different oil palm cultivation regions in Colombia. Phytopathology 110, 1553–1564 (2020).
Rogers, E., Singhal, A. & Quinlan, M. Diffusion of Innovations in An Integrated Approach to Communication Theory and Research Vol. 2 (Routledge, 2014).
Woittiez, L. S., van Wijk, M. T., Slingerland, M., van Noordwijk, M. & Giller, K. E. Yield gaps in oil palm: A quantitative review of contributing factors. European Journal of Agronomy vol. 83 57–77 Preprint at (2017). https://doi.org/10.1016/j.eja.2016.11.002
Ashoori, D., Allahyari, M. S. & Damalas, C. A. Adoption of conservation farming practices for sustainable rice production among small-scale paddy farmers in northern Iran. Paddy Water Environ. 15, 237–248 (2017).
Bernal-Hernandez, P., Ramirez, M. & Mosquera-Montoya, M. Formal rules and its role in centralised-diffusion systems: A study of small-scale producers of oil palm in Colombia. J. Rural Stud. 83, 215–225 (2021).
Gatzweiler, F. W. & Von Braun, J. Technological and Institutional Innovations for Marginalized Smallholders in Agricultural Development (2016). https://doi.org/10.1007/978-3-319-25718-1.
Hazell, P., Poulton, C., Wiggins, S. & Dorward, A. The future of small farms: Trajectories and policy priorities. World Dev. 38, 1349–1361 (2010).
Wiggins, S., Kirsten, J. & Llambí, L. The future of small farms. World Dev. 38, 1341–1348 (2010).
Mwangi, M. R. & Kariuki, S. Factors determining adoption of new agricultural technology by smallholder farmers in developing countries... J. Econ. Sustain. Dev. 6, 208–216 (2015).
Acheampong, P. P., Addison, M., Wongnaa, C. A., Baafi, E. & Opoku, M. Assessment of impacts of adoption of improved sweetpotato varieties in Ghana: accounting for differences in male and female farmers. Gend. Technol. Dev. 1–24. https://doi.org/10.1080/09718524.2023.2289499 (2024).
Loevinsohn, M., Sumberg, J., Diagne, A. & Whitfield, S. Under What Circumstances and Conditions Does Adoption of Technology Result in Increased Agricultural Productivity? A Systematic Review Prepared for the Department for International Development. (2013).
Martínez-Arteaga, D. Determinantes de la adopción de tecnologías para el manejo eficiente del agua por los cultivadores de palma de aceite en la Zona Norte colombiana. Universidad Nac. de Colombia (2022).
Norton, G. W. & Alwang, J. Changes in agricultural extension and implications for farmer adoption of new practices... Appl. Econ. Perspect. Policy 42, 8–20 (2020).
Martínez-Arteaga, D., Arias Arias, N. A., Darghan, A. E. & Barrios, D. Identification of influential factors in the adoption of irrigation technologies through neural network analysis: A case study with oil palm growers. Agriculture https://doi.org/10.3390/agriculture13040827 (2023).
Takahashi, K., Muraoka, R. & Otsuka, K. Technology adoption, impact, and extension in developing countries’ agriculture: A review of the recent literature.. Agric. Econ. 51, 31–45 (2020).
Klerkx, L., Van Mierlo, B. & Leeuwis, C. Evolution of systems approaches to agricultural innovation: concepts, analysis and interventions. In Farming Systems Research into the 21st Century: The New Dynamic 457–483 (2012).
Leeuwis, C. Communication for Rural innovation: Rethinking Agricultural Extension (Blackwell Science, 2005).
Pray, C. E. The Green Revolution as a case study in transfer of technology.... Ann. Am. Acad. Pol. Soc. Sci. 458, 68–80 (1981).
Thompson, J. & Scoones, I. Challenging the populist perspective: Rural people’s knowledge, agricultural research, and extension practice. Agric. Hum. Values 11, 58–76 (1994).
Wigboldus, S. et al. Systemic perspectives on scaling agricultural innovations. A review. Agronomy for Sustainable Development vol. 36 Preprint at (2016). https://doi.org/10.1007/s13593-016-0380-z
Fedepalma. La palma de aceite en Colombia. https: (2023). //web.fedepalma.org/la-palma-de-aceite-en-colombia-departamentos https://web.fedepalma.org/la-palma-de-aceite-en-colombia-departamentos
Mahecha, X. Sustainable Palm Oil of Colombia (APSColombia): Aiming to position our origin. in (ed. Fedepalma) (Fedepalma, Bogotá, (2024).
Fedepalma, S. I. S. P. A., SIFF & DANE & DIAN. La palma de aceite en Colombia. (2023). https://repositorio.fedepalma.org/bitstream/handle/123456789/142819/Colombia%202022.pdf?sequence=1&isAllowed=y
Solidaridad Network. Extension solution. Extension solution - Solidaridad https://solidaridadlatam.org/extension-solution/#:~:text=Extension%20Solution%20permite%20hacer%20un,de%20manera%20precisa%20y%20confiable. (2020).
Murcia, J. D. La palma de aceite, un sector agroindustrial que aporta 17% al PIB agrícola nacional. (2023). https://www.larepublica.co/especiales/la-palma-que-transforma-el-agro/la-palma-de-aceite-un-sector-agroindustrial-que-aporta-17-al-pib-agricola-nacional-3631992
Rincón-Romero, V. O., Molina-Villarreal, A., Zabala-Quimbayo, A., Barrera-Agudelo, O. R. & Torres-León, J. L. The oil palm cadastre in Colombia. Agron Colomb 40, (2022).
UPRA & Colombia 16 millones de hectáreas aptas para palma de aceite. Ministerio de Agricultura y Desarrollo Rural (2022). https://www.upra.gov.co/sala-de-prensa/noticias/-/asset_publisher/GEKyUuxHYSXZ/content/colombia-16-millones-de-hectareas-aptas-para-palma-de-aceite
Becerra-Encinales, J. F. et al. Definition of technological extension strategies based on exploratory analysis of the Sustainability Index using Artificial Intelligence: the case of oil palm producers in Colombia. (2023). https://repositorio.fedepalma.org/handle/123456789/142851#page=1
Fedepalma Manual para la Administración de la Información de los Grupos de Interés de la Federación de Cultivadores de Palma de Aceite de Colombia de 2018. (2018). https://fedepalma.org/fede_content/uploads/2023/05/manual-administracion.pdf
El Congreso de la República de Colombia. LEY ESTATUTARIA 1581 DE 2012, Por La Cual Se Dictan Disposiciones Generales Para La Protección de Datos Personales. Colombia, (2012). https://www.funcionpublica.gov.co/eva/gestornormativo/norma.php?i=49981
Garbely, A. & Steiner, E. Understanding compliance with voluntary sustainability standards: A machine learning approach. Environ. Dev. Sustain. https://doi.org/10.1007/s10668-022-02524-y (2022).
Cherkassky, V. & Mulier, F. ‘Introduction,’ in Learning from Data: Concepts. Theory, and Methods, IEEE 1–18 (2007).
Morgenthaler, S. Exploratory data analysis., 1(1), 33–44.. Wiley Interdiscip. Rev. Comput. Stat. 1, 33–34 (2009).
Yang, A. et al. Review on the Application of Machine Learning Algorithms in the Sequence Data Mining of DNA. Frontiers in Bioengineering and Biotechnology vol. 8 Preprint at (2020). https://doi.org/10.3389/fbioe.2020.01032
Xu, D. & Tian, Y. A comprehensive survey of clustering algorithms.... Ann. Data Sci. 2, 165–193 (2015).
Xu, R. & Wunsch, D. Survey of clustering algorithms.. IEEE Trans. Neural Netw. 16, 654–678 (2005).
Zhao, X., Liang, J. & Dang, C. A stratified sampling based clustering algorithm for large-scale data. Knowl. Based Syst. 163, 416–428 (2019).
Cramér, H. Mathematical Methods of Statistics (PMS-9) (Princeton University Press, 1999).
López-Roldán, P. & Fachelli, S. Metodología de La Investigación Social Cuantitativa. (2015). https://ddd.uab.cat/pub/caplli/2015/131469/metinvsoccuan_cap3-6a2015.pdf
Python Visualization Project & Folium Preprint at (2024). https://python-visualization.github.io/folium/latest/
Mills, J. et al. Engaging farmers in environmental management through a better understanding of behaviour. Agric. Hum. Values 34, 283–299 (2017).
Rogers, E. Diffusion and Innovations. Simon and Shuster (2010).
Wejnert, B. Integrating models of diffusion of innovations: A conceptual framework. Annu. Rev. Sociol. 28, 297–326 (2002).
Pannell, D. & Zilberman, D. Understanding adoption of innovations and behavior change to improve agricultural policy. Appl. Econ. Perspect. Policy 42, 3–7 (2020).
Aguilar, G. N., Muñoz, R. M. & Santoyo, C. V. & Aguilar, Á. J. Influencia del perfil de los productores en la adopción de innovaciones en tres cultivos tropicales. Teuken Bidikay 207–228 (2013).
Bernet, T., Ortiz, O., Estrada, R. D., Quiroz, R. & Swinton, S. M. Tailoring agricultural extension to different production contexts: A user-friendly farm-household model to improve decision-making for participatory research. Agric. Syst. 69, 183–198 (2001).
Cook, B. R., Satizábal, P. & Curnow, J. Humanising agricultural extension: A review.. World Dev. https://doi.org/10.1016/j.worlddev.2020.105337 (2021).
Acknowledgements
The authors thank the Colombian Oil Palm Research Center Corporation—Cenipalma, the Colombian Fondo de Fomento Palmero, and the Los Andes University in Colombia, which made this research possible.
Funding
This research was funded by the Colombian Oil Palm Research Center Corporation (Cenipalma) with the support of the Colombian Fondo de Fomento Palmero (FFP). The project was financed through the FFP’s investment program in technological extension for the oil palm sector, under funding codes EXT-2023 and EXT-2024.
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Conceptualization, J.F.B-E., J.C.C. and L.H.R.; methodology, J.F.B-E., E.M-F., B.R.; software, J.F.B-E., B.R., E.M-F.; validation, J.C.C., L.H.R., and A.P.C; formal analysis, J.F.B-E.; investigation, J.F.B-E., J.C.C., L.H.R., P.B-H., and A.P.C; resources, J.F.B-E.; data curation, J.F.B-E., B.R.; writing—original draft preparation, J.F.B-E.; writing—review and editing, J.F.B-E., P.B-H., B.R., J.C.C., L.H.R.; visualization, J.F.B-E.; supervision, J.C.C., L.H.R., E.M-F., P.B-H., and A.P.C.; project administration, J.F.B-E.; funding acquisition, J.F.B-E., and A.P.C. All authors have read and agreed to the published version of the manuscript.
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Ethics Statement
This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Research Committee of the Colombian Oil Palm Research Center – Cenipalma (protocol code 2024019000475 H, approved on 8 May 2024). The ethical review was conducted in accordance with Cenipalma’s internal research governance procedures and national guidelines for non-clinical research involving human participants in Colombia. Written informed consent was obtained from all participating producers.
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The form kept the Personal Data Treatment Policy, which is published on the official websites of Fedepalma and Cenipalma (articles 4 and 11 of Decree 1377 of 2013).
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Becerra-Encinales, J.F., Rodríguez, B., Mesa-Fuquen, E. et al. Compliance patterns in adopting sustainability practices: A cluster analysis of oil palm producers in Colombia. Sci Rep (2026). https://doi.org/10.1038/s41598-026-43888-9
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DOI: https://doi.org/10.1038/s41598-026-43888-9
