Professur für Marktlehre der Agrar- und Ernährungswirtschaft
Professur für Marktlehre der Agrar- und Ernährungswirtschaft an der JLU Giessen
Willkommen auf der Homepage der Professur für Marktlehre der Agrar- und Ernährungswirtschaft am Fachbereich 09 der JLU!
Sie finden auf den folgenden Seiten Informationen zu unseren Forschungsschwerpunkten, Lehrinhalten und Projekten.
Falls Sie Interesse an einer möglichen Kooperation mit uns haben oder weitergehende Informationen zu bestimmten Punkten benötigen, zögern Sie bitte nicht, uns telefonisch oder per E-Mail zu kontaktieren.
Wir sind zudem eng mit dem Zentrum für Nachhaltige Ernährungssysteme (ZNE) verbunden. Die Website des ZNEs finden Sie hier:
https://www.uni-giessen.de/de/fbz/zentren/zne/index
Food (In)security and Food Choice Motives in Kigali, Rwanda
We offer a Master’s thesis opportunity based on an existing dataset from a study on the 🍄 mushroom value chain and consumption in Rwanda. The dataset includes 👥 402 participants and contains rich data from the Food Insecurity Experience Scale (FIES) and the Food Choice Questionnaire (FCQ).
🔎 The thesis will:
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Assess the prevalence and severity of food insecurity using FIES
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Examine how food insecurity relates to food choice motives (e.g., 💰 cost, ❤️ health, ⏱️ convenience, 😋 taste)
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Identify consumer motivation patterns (e.g., price-oriented, health-oriented) using factor or cluster analysis
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Explore links with socio-demographic characteristics
🌍 Impact:
The project will contribute to understanding food choice behaviour in food-insecure contexts and may inform nutrition-sensitive agricultural interventions, including mushroom promotion in Rwanda.
In case you are interested please send your CV + transcript (single PDF) to ramona.teuber@agrar.uni‑giessen.de and felix.ndayisaba@uni-giessen.de. We are also also happy to answer pending questions.
We are hiring
We are looking for a student assistant to support us in data management. The position requires good proficiency in Excel and R. Stata skills are an asset. Tasks may include, but are not limited to:
Data Coding and Recoding
- Standardizing variable formats (e.g., dates, numeric responses, and categorical codings) to ensure compatibility with Stata.
- Assigning numerical codes to categorical variables.
- Recategorizing or combining responses where necessary to meet analytical requirements.
- Organizing datasets into structured formats with clear variable names and labels.
Data Cleaning
- Identifying and correcting anomalies, inconsistencies, and missing values in exported datasets.
- Anonymizing and exporting cleaned and organized datasets in various formats for open access (e.g., CSV, .dta).
- Assisting with the submission of the dataset to a data repository.
Preliminary Data Analysis
- Generating preliminary descriptive statistics and frequency tables.
In case you are interested, please send an email with your CV and transcript of records to Prof. Dr. Ramona Teuber (ramona.teuber@agrar.uni-giessen.de) and Dieu-Merci Akonkwa Nyamuhirwa (dieu-merci.akonkwa@uni-giessen.de).