Leukel, J., Liu, Z., & Sugumaran, V. (2026). Potential overinterpretation of results in the abstracts of machine learning studies for movie box office revenue prediction: A systematic review. Journal of Revenue and Pricing Management, 25(4), 368-377. https://doi.org/10.1057/s41272-026-00574-9

Oezbek, G., & Leukel, J. (2025). Trust in AI vs. human recommendations among users with AI training: A pilot study. AMCIS 2025 Proceedings. https://aisel.aisnet.org/amcis2025/sig_hci/sig_hci/26

Scheurer, L., Zimpel, T., & Leukel, J. (2025). Predicting tilling and seeding operation times in grain production: A comparison of machine learning and mechanistic models. Smart Agricultural Technology, 11, Article 101043. https://doi.org/10.1016/j.atech.2025

Leukel, J., Scheurer, L., & Zimpel, T. (2025). Overinterpretation of evaluation results in machine learning studies for maize yield prediction: A systematic review. Computers and Electronics in Agriculture, 230, Article 109892, https://doi.org/10.1016/j.compag.2024.109892

Müller, M., Gohl, S., Groll, K., & Leukel, J. (2025). Wie GreenAI-Bauprozesssteuerung und automatisierte CO2-Bilanzierung die CO2-Emissionen senken. In Schäfer, F. (Ed.), 4. Kolloquium Straßenbau in der Praxis: Fachtagung zum Planen, Bauen, Erhalten, Betreiben unter den Aspekten von Nachhaltigkeit und Digitalisierung. Tagungshandbuch 2025 (pp. 381-387). expert.

Scheurer, L., Leukel, J., Zimpel, T., Werner, J., Perdana-Decker, S., & Dickhoefer, U. (2024). Predicting herbage biomass on small-scale farms by combining sward height with different aggregations of weather data. Agronomy Journal, 116(6), 3205-3221. https://doi.org/10.1002/agj2.21705

Leukel, J., Scheurer, L., & Sugumaran, V. (2024). Machine learning models for predicting physical properties in asphalt road construction: A systematic review. Construction and Building Materials, 440, Article 137397. https://doi.org/10.1016/j.conbuildmat.2024.137397

Leukel, J., Özbek, G., & Sugumaran, V. (2024). Application of logistic regression to explain internet use among older adults: A review of the empirical literature. Universal Access in the Information Society, 23, 621-635. https://doi.org/10.1007/s10209-022-00960-1

Stumpe, C., Leukel, J., & Zimpel, T. (2024). Prediction of pasture yield using machine learning-based optical sensing: A systematic review. Precision Agriculture, 25(1), 430-459. https://doi.org/10.1007/s11119-023-10079-9

Zimpel, T., Perdana-Decker, S., Leukel, J., Scheurer, L., Dickhoefer, U., & Werner, J. (2023). P42 Estimating pasture yield using machine learning and weather data: Effect of small and large prediction horizons. Animal-science proceedings, 14(4), 628-629. https://doi.org/10.1016/j.anscip.2023.04.137

Leukel, J., González, J., & Riekert, M. (2023). Machine learning-based failure prediction in industrial maintenance: Improving performance by sliding window selection. International Journal of Quality & Reliability Management, 40(6), 1449-1462. https://doi.org/10.1108/IJQRM-12-2021-0439

Leukel, J., Zimpel, T., & Stumpe, C. (2023). Machine learning technology for early prediction of grain yield at the field scale: A systematic review. Computers and Electronics in Agriculture, 207, Article 107721. https://doi.org/10.1016/j.compag.2023.107721

Leukel, J., Schehl, B., & Sugumaran, V. (2023). Digital inequality among older adults: Explaining differences in the breadth of internet use. Information, Communication & Society, 26(1), 139-154. https://doi.org/10.1080/1369118X.2021.1942951

Leukel, J., & Sugumaran, V. (2022). How novice analysts understand supply chain process models: An experimental study of using diagrams and text. Journal of Enterprise Information Management, 35(3), 757-773. https://doi.org/10.1108/JEIM-11-2020-047