Background:

Digital Green, in collaboration with local partners, is piloting an AI-powered mobile application (Farmer.Chat) developed to enhance the speed and efficiency of agricultural extension services. The application aims at empowering extension workers and farmers with personalized advisory services that can be accessed through voice, text, images or videos in local languages. The platform delivers location and crop-specific data, such as weather, enabling farmers to make faster, smarter decisions while promoting climate-smart agricultural practices. IFPRI is undertaking a baseline evaluation that will capture the status of key outcome and impact indicators before the expansion phase to systematically gauge the impact of Farmer.Chat.

The baseline study will rely on an experimental design, in which about 1,850 sample households will be surveyed in-person from 185 wards in 5 counties. The baseline survey will mainly consist of sample households background characteristics, farmers’ use of digital tools, adoption of agricultural practices, yield, income, and food security. The survey will be administered on tablets using survey application. In addition, the baseline study includes a ward level survey, aimed at capturing background information about the ward demographics, services, and infrastructure. IFPRI is seeking a qualified survey firm based in Kenya to conduct the baseline data collection.

Scope of work:

The selected firm will coordinate and implement a face-to-face quantitative survey with farming households across the five target counties in Kenya (Nakuru, Meru, Kirinyaga, Murang’a, and Uasin Gishu). As mentioned above, the survey will consist of in-person interviews with both male and female farmers, using computer-assisted personal interviewing (CAPI), and will involve approximately 1,850 households and 185 ward level surveys. All data should be collected by mid-January 2025. The survey instrument and specific study locations will be determined by IFPRI.

The activities for the survey firm are detailed below:

  • Translate the survey instrument and interview guide into local languages (as needed).
  • Obtain ethics clearance, research permits, and/or other local approvals.
  • Obtain enough tablets for CAPI data collection.
  • Develop, test, and finalize the CAPI data entry program that will be used to conduct the interviews in the field.
  • With assistance from the IFPRI, prepare the field implementation manual prior to enumerator training. The field manual will be the basis for quality assurance of the data collection process.
  • Organize the selection, hiring, and payment of enumerators to conduct the required data collection work. This will include hiring both male and female interviewers with the necessary language skills to ensure respondents for the individual interviews are matched on sex.
  • Facilitate and ensure the smooth operation of the enumerator training and survey pretest in collaboration with IFPRI staff. It is expected that there will be a 5-day training course, followed by a 2-day pretest and debrief, for the quantitative survey.
  • Develop a field schedule for the quantitative data collection teams and provide regular status updates during fieldwork.
  • Develop spot- and back-check protocols and share these with IFPRI for feedback prior to the start of data collection.
  • Participate in weekly meetings with IFPRI throughout data collection.
  • Share the data generated from the spot and back-checks and additional data collection concerns with IFPRI in a timely manner so that issues can be promptly resolved.
  • Share the data generated from CAPI (in Stata format) with IFPRI during data collection, as and when the data is uploaded to the servers. These data will not be the cleaned data sets (except for variable and value labels, checking and correcting skip patterns, and formatting the data in long format as required), but the raw data sets as sent to the firm from their survey teams.
  • Conduct data cleaning to ensure consistency and range-checks; share the error check do-files with IFPRI.
  • Provide responses to queries from IFPRI in relation to data cleaning (as needed).
  • Deliver cleaned data sets (in Stata format) from the 1,850 households in long format. The dataset should include translation of any open-ended questions from local languages to English if necessary.
  • Provide a brief report covering the quantitative survey fieldwork, as well as any issues related to data management and cleaning.

    Required qualifications of the consultant / survey firm:

Recommended for you