Die chronologische Liste zeigt aktuelle Veröffentlichungen aus dem Forschungsbetrieb der Hochschule Weihenstephan-Triesdorf. Zuständig ist das Zentrum für Forschung und Wissenstransfer (ZFW).
8 Ergebnisse
M.Sc. Andreas Niedermeier,
Christian Mergel,
Dr. Agnes Emberger-Klein,
Prof. Dr. Klaus Menrad
Predictive models are increasingly crucial in navigating heterogeneous markets. This study develops a predictive model approach to forecast consumer cluster membership in the green fast-moving consumer goods sector, focusing on bio-based products like adhesives and plasters. Through two online surveys in Germany, we identified key factors acting as drivers and barriers, demonstrating their effectiveness in distinguishing similar consumer segments across both product categories. Utilizing multinomial logistic regression, we crafted a prediction model that accurately forecasts cluster membership, providing novel insights into consumer behavior towards non-food bio-based products. This facilitates the development of targeted business and marketing strategies, optimizing resource allocation in market research activities. Our findings offer significant contributions to understanding the dynamics influencing consumer choices in the bio-based product market.
Melanie Hohner ist Gartenbauingenieurin mit internationaler Erfahrung – und nun Chefin des Tropenhauses mit großen Plänen. Unter anderem will sie die Produktion ausbauen.
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Prof. Dr. Dominikus Gregor Kittemann,
Prof. Dr. Michael Beck,
Johannes Werth,
Anna Lena Haug,
Konni Biegert,
Annika Killer,
Alexander Zimmermann,
Thomas Kuster
Prof. Dr. Dominikus Gregor Kittemann,
Prof. Dr. Michael Beck,
Johannes Werth,
Anna Lena Haug,
Konni Biegert,
Annika Killer,
Alexander Zimmermann,
Thomas Kuster
BackgroundNatural health products (NHP) are an important part of the healthcare system. They are mainly non-prescription and sold over the counter, which requires active decision making by the consumer. Within the framework of the Complementary and Alternative Healthcare Model, this study aims to identify factors that influence NHP usage, in particular related to concentration and cognition (CC), a topic that concerns all ages and social classes within the population.MethodsData were collected by means of a representative online survey (n = 1,707) in Germany in April 2022. Three user groups were defined: NHPCC users, who used NHP for CC (12 month prevalence); nCC-NHP users, who used NHP but not for CC indications (12 month prevalence); and past NHP users, who have used NHP but not within the previous 12 months. Independent influencing variables were categorized into predisposing, enabling, need, and health service use factors. Data were analyzed with descriptive statistics, inferential statistics, and binary logistic regression models to compare NHPCC users to nCC-NHP users (model 1) and to past NHP users (model 2).ResultsA higher share of NHPCC and nCC-NHP users compared to past NHP users were women, self-medicated with NHP, and used information about NHP provided by health professionals or on product. Their openness-to-change value orientation was more pronounced than of past users. Compared to nCC-NHP and past NHP users, the probability of being an NHPCC user increased if an individual had more difficulties in daily attention and memory performance, made use of health professionals and literature to seek information about NHP, and used NHP for health support and illness prevention. Additionally, a female gender, NHP self-medication, and having higher values of self-transcendence were significant indicators for NHPCC usage compared to past NHP usage.ConclusionNHP manufacturers, health professionals, and policymakers should be aware of the factors that lead to NHP consumption decisions and consider them in the development and optimization of healthcare strategies as well as in the marketing and communication strategies of companies producing NHP, in particular for CC. The current study can contribute to characterizing the target groups and to defining the aims and communication channels of such campaigns.
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Prof. Dr. Dominikus Gregor Kittemann,
Prof. Dr. Michael Beck,
Johannes Werth,
Anna Lena Haug,
Konni Biegert,
Annika Killer,
Alexander Zimmermann,
Thomas Kuster
Josef Eiglsperger,
Prof. Dr. Florian Haselbeck,
Viola Stiele,
Claudia Guadarrama Serrano,
Kelly Lim-Trinh,
Prof. Dr. Klaus Menrad,
Prof. Dr. Thomas Hannus,
Prof. Dr. Dominik Grimm
Accurately forecasting demand is a potential competitive advantage, especially when dealing with perishable products. The multi-billion dollar horticultural industry is highly affected by perishability, but has received limited attention in forecasting research. In this paper, we analyze the applicability of general compared to dataset-specific predictors, as well as the influence of external information and online model update schemes. We employ a heterogeneous set of horticultural data, three classical, and twelve machine learning-based forecasting approaches. Our results show a superiority of multivariate machine learning methods, in particular the ensemble learner XGBoost. These advantages highlight the importance of external factors, with the feature set containing statistical, calendrical, and weather-related features leading to the most robust performance. We further observe that a general model is unable to capture the heterogeneity of the data and is outperformed by dataset-specific predictors. Moreover, frequent model updates have a negligible impact on forecasting quality, allowing long-term forecasting without significant performance degradation.
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Julia Ruf,
Prof. Dr. Klaus Menrad,
Dr. Agnes Emberger-Klein
Using bio-based building products for renovation and refurbishment contributes to a bioeconomy. As private consumers mainly buy building products at local hardware stores, it is essential to consider the local supply situation. This qualitative study analyzes the local range of bio-based building products for renovation and refurbishment and related consumer perceptions and assessments in two case cities in Germany. The study results reveal that consumers face high search costs, the range of products is primarily narrow, and their placement and presentation are unfavorable. Manufacturers can use the study results and invest in classical marketing strategies, and initiate pull strategies with consumers for bio-based building products. This could motivate retailers to increase the range and improve the placement and presentation of such products. Finally, policymakers can apply the insights from this study to educational campaigns and the promotion of quality labels in this field.
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