These files include the dataset and code used in the paper titled “Consumer Preferences for Genetically Engineered Foods in Nigeria: Does Process Information Matter?”. The study examines consumer preferences for genetically engineered biofortified cassava processed into Gari, a staple food in Nigeria.
The data were collected through a cross-sectional survey and a discrete choice experiment involving 235 households in Nigeria between April and June 2022. In the experiment, each respondent completed eight choice tasks, resulting in a panel dataset with eight observations per respondent. The dataset, labelled biofortification_data, contains individual-level sociodemographic and background variables that capture respondents’ characteristics, awareness, knowledge, and purchasing behaviour. It also includes the outcome variable, which records each respondent’s choice of Gari in every choice task. Additionally, the dataset provides treatment variables and their interactions with product attributes, based on an experimental design in which respondents were assigned to different information groups prior to making their choices. One group received nutrition information only, while the second group received both nutrition information and scientific information on the three biofortification methods, conventional breeding, genetic modification, and gene editing, used in producing the cassava for Gari.
The data were analyzed using mixed logit models in R, including models that assume full attribute attendance as well as models that account for stated attribute non-attendance across the two information treatment groups.
The README file provides detailed descriptions of the variables included in biofortification_data. The files 4_code_full_attendance_mixl_nutrition and 5_code_full_attendance_mixl_nutrition+method contain the R code used to estimate the full attendance mixed logit models for the nutrition information group and the group that received both nutrition and scientific information, respectively. Similarly, the files 8_code_stated_ana_nutrition and 9_code_stated_ana_nutrition+method include the R code for estimating mixed logit models that incorporate stated attribute non-attendance for the nutrition information group and the combined nutrition and scientific information group, respectively.
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