Skip to content
#diffusion models Open access

Donor Transfer of Agricultural Knowledge and Self-Reliant Farming Among Smallholder Farmers: Evidence from Yambio County, South Sudan

Oct 2026 · Journal of Science Innovation and Creativity
Agricultural Innovations and Practices

Abstract

Indigenous knowledge is still firmly linked to farming among smallholder farmers in Yambio County, even though donor programs offer new practices through training, extension services, and demonstration plots and emphasize knowledge transfer as crucial to shifting smallholder farmers away from outside aid. In this study, the degree and direction of the relationship between donor agricultural knowledge transfer and self-reliant farming were ascertained. A cross-sectional correlational survey with a qualitative component was employed, guided by the theories of diffusion of innovations and collective action. The target population was 1,405 registered smallholder farmers, eight extension officers, 30 leaders of farmer groups, 30 group accountants and 30 group secretaries. From the farmers, 180 members were selected by simple random sampling, and 170 returned usable questionnaires (94.4%). All 98 key informants were purposively included (100% participation), giving a targeted sample of 278 and an analytical sample of 268. Perception items used a five-point Likert scale (1 = strongly disagree to 5 = strongly agree), and reliability was assessed with Cronbach's alpha. Descriptive statistics, multiple linear regression, an inferential method with a single dependent variable, and theme analysis were used to analyze the data. Donor transfer of agricultural knowledge was positively and significantly correlated with self-reliant farming after controlling for financial inflows, technical support, and demographic characteristics (B = 0.359, p < .001). Respondents scored low on expert knowledge as their only reliable source (M = 2.188, SD = 1.323, on a five-point scale from 1 = strongly disagree to 5 = strongly agree), while learning from experts (77.1%), group savings (71.8%) and farmer exchange programmes (68.2%) were widely endorsed. Causal claims are precluded by cross-sectional data and a sample below conventional size; clustering within groups was not modeled. Donor programs could combine knowledge transfer with ongoing, peer-led, and participatory learning that builds on indigenous knowledge; this is an interpretation based on qualitative and descriptive data rather than a tested effect.

Read PDF

Similar papers

#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Conference Sep 2010

Exploring the Sources of Waste in Kanban Software Development Projects

The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new an...

Marko Ikonen, Petri Kettunen, Nilay V. Oza et al. · 67 citations · ⚡9

Related blog posts

MIT News · Artificial Intelligence Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.