CRED 32: Rwanda GIS Firm for Data Mapping

Scope of Work (SoW) GIS Pilot Study 
The ICRG is seeking GIS and data analysis expertise for a pilot study in Rwanda. This pilot study is intended to explore whether and how GIS data visualization can be cost effectively used in determining the productivity and commercial viability of primary cooperative societies. It will draw on newly generated or derived GIS data and on data sets the OCDC/ICRG has from past studies. The successful bidder will be a well-established entity with a track record of success in econometric analysis and GIS data collection in East Africa. The bidder will define for each variable of the study, the most viable option for data collection (secondary/primary) and lead the data collection process based on the ICRG’s sampling methodology. The bidder will run the regression analysis on the GIS data and prepare a final report that reports on the findings. 

8/18 Amendment to the RFP: The ICRG will share a comprehensive list of agricultural cooperatives in Rwanda with the successful bidder, from which the firm will source the appropriate sample for the study. The deadline for submission to this RFP has also been extended to 8/27/21.

Addition to the SoW: Clarifying scope of work to include the application of Rwandan research permits for the project. The firm’s proposed timeline should take this process into account.

Sampling Methodology 
Stratified random sampling will be conducted using all agricultural cooperatives in Rwanda as the sampling frame. The final sample size will be determined upon receipt of final data sets including a list of all agricultural cooperatives in Rwanda, name, location (province and district), main crop commercialized and contact information, as available. The approximate number of cooperatives to be sampled in this study is 400, which can be used for budgetary purposes. From this figure, cooperatives will be randomly selected from each district to provide statistically robust results that are representative of agricultural cooperatives in Rwanda as a whole. 

To understand the role that certain internal and environmental factors which affect the agricultural value chain might play in the economic performance of cooperatives in Rwanda, this study will collect data on key variables hypothesized to influence the agricultural value chain and thus impact market success. The key variables will be tested against market success of agricultural cooperatives, as measured by the business-membership ratio. The key variables will be measured utilizing a combination of GIS imaging and (primary/secondary) data collection in the field. At present, the study’s design includes an outcome variable (business-membership ratio), eleven key independent variables related to the value chain and production conditions, and four control variables.  

Regression analysis will be run using a linear multivariate regression model that includes the total variables, with particular focus on the key value chain variables and how they impact cooperative market success, or the business-membership ratio (BMR). Further analysis will be done to understand if the impacts of these factors on BMR differs significantly by main value chain. 

 Role of GIS research and analytics firm .The GIS and data analytics firm will carry out key activities, highlighted below, in support of the pilot project as a primary research partner.   

  1. Recommend for each variable included in the study the data collection method proposed, based on available data sets. Define, based on the ~16 variables included in study (see variables above for more details), which will be acceptable for GIS methods. 
  2. Lead data collection in the field and access secondary data sets as mutually decided (in #1 above), based on the ICRG’s sampling methodology. Develop a digital questionnaire for data collection and data collection workplan. 
  3. Run the multivariate regression analysis on the variables included in the study, with a particular focus on the key value chain variables and how they impact cooperatives’ business-membership ratio. 
  4. Run further linear multivariate regression analysis with the same variables, using interaction terms in the model to determine the extent to which the effect of key variables on market success depends upon certain cooperative characteristics, such as geography, main value chain, etc. 
  5. Develop an interactive map and operation dashboard for data collection results visualization and analysis. 
  6. Prepare a report for ICRG detailing the results of the regression analysis. 
  7. Prepare all original data sets for submission to ICRG. 

Participate, as requested, in research dissemination activities, together with ICRG and other research partners.  View and download the complete RFP

5. Deliverables and their dates











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