Case Study: Green Revolution in Sub Saharan Africa and the Implications of Imposed Innovation for the Wellbeing of Rural Smallholders

This case study was conducted by Neil Dawson, Adrian Martin, and Thomas Sikor in 2015. The paper is an excellent example of how mixed methods can be used to provide holistic research in order to effectively come to a conclusion. In this blog post, we will have a closer look at the methodologies used and how interdisciplinarity helped inform the research.

The case study was focused on how Green Revolution policies were implemented in Sub-Saharan Africa, and how imposed innovation impacted smallholders. It focused on rural areas in mountainous western Rwanda, and therefore looked at two significant policies that were implemented in Rwanda in line with the Green Revolution. Green Revolution policies in Africa target agricultural growth and reducing poverty. In order to be able to provide a critical analysis of these policies and the impact they had on a local level, they adopted a mixed-methods multidimensional wellbeing approach. The mixed methods study was used to assess wellbeing and policy impacts on rural households, and the multidimensional wellbeing approach was utilized to assess the impacts of agricultural modernization policies.

Roos de Raadt, 2014

Footprints to Africa 2016

The implemented policies resulted in the transformation from a traditional polyculture system to the specialization in marketable crops with modern seed varieties and inputs in order to increase productivity and income. This is justified by the Malthusian approach. However, where these policies were seemingly successful in raising yields and reducing poverty rates, they seemed to be incongruous with local experiences. The majority of households were negatively impacted by this transformation as it disrupted local knowledge, trade and labor systems and worsened landlessness and inequality. Results showed that only a wealthy minority could sustain the enforced modernization, whereas the poorer rural inhabitants were disadvantaged. However, before we get to the conclusion of the study we will have a look at the methodology used.

An Analysis of the Methodology

The study was conducted in 8 different villages that were laid out across 3 sites in mountainous western Rwanda. This was purposely done in order to provide a better representation of the various social and ethnic groups in the country.

The image below outlines the 3 regions Rutsiro, Nyamasheke and Nyamagabe, where the study sites were located

(Dawson, Martin and Sikor, 2016)


The interviews also collected a large array of quantitative data from each household to support analysis in more objective terms. Data included the demographic and socio-economic characteristics of people within each household, their resources, education, occupation, land practices, their ability to meet specific basic needs, and the ways in which each had changed over the past ten years. These objective indicators were then averaged among different social groups (see Table 2).

In order to differentiate between groups of households based on socio-economic status, a hierarchical cluster analysis was conducted to create meaningful groups of households based on the main material and human resources put forward by participants. This allows for seeing the impact of policies on different socio-economic groups.


This allows the researchers to better analyze differences in wellbeing between different socio-economic groups, socio-ethnic groups and sites (see Table 3). This is important, because other studies have shown that overall agricultural growth can in fact lead to increased poverty or marginalization among disadvantaged groups, when the data is disaggregated. It also enables the researchers to more clearly show temporal developments, such as changes in wellbeing over the previous ten years (see Table 4). Using these objective criteria, the agricultural policies are shown to be clearly successful in raising yields and lowering conventionally measured poverty rates.


However, this hard data is less suitable for other research objectives that require more qualitative methods. For example, to explore how rural people define wellbeing. Hard data by itself is also not able to explain why the apparent positive results of the agricultural policies were found to be incongruous with local experiences. Qualitative methods shed light on micro-level experiences, which is important in complementing macro-surveys. Furthermore, a qualitative methods such as semi-structured interviews are capable to generate objective data as well.


Qualitative data collection included several methods. Participants were randomly selected by the researchers, who received lists of households from local administrators. The goal was to explore how rural people define wellbeing, and examine how these policies affect wellbeing outcomes. The methods consisted of:

  • Focus groups in each village with 5-7 participants
    • Male & female household members were alternately asked to take part to gather a broad range of participants (gender, age, and ethnic group)
    • They were asked what, according to them, is required to live a good life in that village.
    • Ongoing discussion until no new answers were provided

  • Semi-structured interviews
    • Participants from more than 10% of households per village (overall representing 12-17% of all households in each village)
    • Participants were adult male or female
    • Pro: open questions in this interview format allowed space to explore the topics the participant found important, and their subjective meaning applied to different domains of life.


This study takes an interdisciplinary approach, combining different perspectives to create an integrated and comprehensive model of wellbeing. Insights are used from:

Social science: The study has a human-centered approach, focusing on the wellbeing of individuals. How do certain policies affect different groups? Do these policies actually strengthen the position of marginalized groups? How are these experienced on the micro-level?

Environmental science: The researchers focus on Green Revolution policies, aimed at boosting agricultural productivity and sustainability. Are these policies successful in boosting farmer’s yield?

Political science: The study considers changes in political economies of rural development in sub-Saharan Africa. The political context and narratives of civil society are important for the outcome of agricultural policies. Which groups in society win, and which ones lose?

Economics: A major part of increasing well-being is to boost farmer’s income. Can the policies be considered to be pro-poor? Does the overall increase in agricultural productivity ‘trickle down’ to smallholder farms on the lower parts of the value chain?


Studies on measuring wellbeing are a good example of why some assessments should be based not only on consistent, objective indicators, but also link these to more interpretive approaches associated with detailed testimonies of individual interview respondents. Reliance on objective indicators alone may overlook subjective, locally meaningful values and definitions of wellbeing and poverty. Incorporating these plural perspectives can account for these differences.


  1. Dawson, N., Martin, A. and Sikor, T., 2016. Green Revolution in Sub-Saharan Africa: Implications of Imposed Innovation for the Wellbeing of Rural Smallholders. World Development, 78, pp.204-218.
  2. Footprints to Africa, 2016. [image] Available at: [Accessed 28 September 2021].