Newest publications
Perceptions of women entrepreneurs and their impact on opportunities and challenges
(2025) Koch, Laura H.; Kuckertz, Andreas
Women’s entrepreneurship constitutes a critical driver of economic and social progress. Millions of women are entrepreneurs or leaders of ventures and actively contribute to innovation, employment, and economic growth. Moreover, women’s entrepreneurship significantly promotes gender equality by enabling women’s financial independence and enhancing their societal participation.
Despite this central role, women remain vastly underrepresented as entrepreneurs globally. Women entrepreneurs often face restricted access to social, financial, and human resources, which limits their entrepreneurial potential. A key factor driving these resource disparities is societal perceptions of women entrepreneurs. These perceptions shape how key actors recognize, evaluate, and support women entrepreneurs and directly influence their opportunities and challenges within the entrepreneurial ecosystem. Deeply ingrained gender stereotypes frequently frame these perceptions, reflecting traditional role expectations and gender-based attributions. Society has long linked entrepreneurship to traits associated with men, causing many to perceive women entrepreneurs as less competent.
At the same time, research demonstrates that these perceptions vary considerably depending on context. While the venture capital sector often evaluates women entrepreneurs negatively, actors in crowdfunding contexts tend to perceive them as particularly trustworthy. These differences highlight how situational factors influence perceptions of women entrepreneurs. Against this backdrop, the present dissertation investigates how various stakeholders’ perceptions affect women entrepreneurs’ opportunities and challenges. It contributes novel insights into the role of perception in entrepreneurial contexts and advances the academic discourse on gender-specific dynamics in entrepreneurship.
Study 1 examines the scientific perception of women’s entrepreneurship, focusing specifically on growth-oriented ventures. The study analyzed 741 publications from the past two decades using a bibliometric analysis. The findings reveal a significant increase in research activity and a marked thematic diversification since 2014. This trend reflects not only growing scholarly interest but also the rising societal relevance of the field. Simultaneously, the study identifies critical research gaps and provides valuable directions for further advancing the discipline.
Study 2 centers on perceptions of women entrepreneurs among venture capital investors. Women entrepreneurs frequently encounter challenges when seeking venture capital, partly due to gender-specific biases. To quantify the extent of these biases, the study surveyed 361 international venture capital investors using an indirect questioning technique that ensures complete anonymity and reduces social desirability bias. The results reveal that a substantial proportion of respondents hold gender-biased attitudes. These biases occur most strongly among men investors and individuals active in early-stage or corporate venture capital.
Study 3 broadens the perspective by analyzing societal perceptions of women entrepreneurs. This study investigates which gendered narratives of women entrepreneurs inspire readers most effectively. It employed a factorial survey design with a representative sample of 337 participants from the United Kingdom. The results indicate that narratives of women entrepreneurs inspire readers when they emphasize women-associated traits and social goals. Conversely, inspiration decreases when the narratives highlight physical attractiveness. These findings suggest that women-associated characteristics increasingly gain active recognition and appreciation in the traditionally men-dominated entrepreneurial environment, potentially signaling a cultural shift toward a more inclusive image of entrepreneurship where differences are valued and integrated.
Building on the findings of these three studies, this dissertation provides new insights into how perceptions of women entrepreneurs by various stakeholders shape their opportunities and challenges. It concludes with a discussion of how these perceptions shape the challenges women face on their journey to entrepreneurship and the opportunities that exist to create new possibilities for change.
Investigation of the spatial and temporal variations of weather conditions in a mesoscale vineyard
(2021) Pfisterer, Philipp; Schock, Steffen; Ramaj, Iris; Müller, Joachim
Climatological conditions and weather variability have a momentous impact on viticulture and vineyard management and can be detrimental for grapevine growth and its yield. Humid weather conditions contribute to the spread of fungal pathogens and diseases, which afterwards degrade the quality of the grapevine and risk the longevity of orchards and vineyards in the tropical and subtropical regions. Therefore, it is critical to monitor the spatial and temporal variations of weather conditions in the vineyards. Despite numerous sensor systems developed in academia and industry to address this problem, a scalable and dense sensor system that guarantees low maintenance, fast and reliable data acquisition is still lacking. Thus, in this study, a low-cost wireless networked system was developed for real-time monitoring of weather parameters namely, temperature, relative humidity and dew point temperature. A capacitive-type sensor SHT31 integrated into an STM32L0 microcontroller was employed as a measuring unit. Data transmittance was empowered via a functional radio network. The sensor housings were designed and manufactured in-house via a 3D printer. The accuracy of data readings was validated by a climatic test chamber CTS-20/1000 under a wide-ranging set of temperatures and relative humidities. As an evasive experimental site, a mesoscale 30-ha vineyard located in Hessigheim, Germany was used to test the monitoring system. A number of 30 sensors were installed irregularly in this area. For the graphical analysis, data collected during the summer and winter periods were compared. From the results, substantial differences in temperature were observed between vineyard sites at p ≤ 0.05. The spatial temperature gradients altered up to 8°C, which was mainly attributed to the heterogeneous and steeply sloping terrain of the vineyard. These gradients increased over the summer and decreased during the winter. This behaviour was accredited to the diurnal solar orientation, shaded conditions as well as wind direction imposed by a bend in the river. Likewise, significant differences were observed for dew point and relative humidity. In conclusion, the developed network system demonstrated a high capability to track the variability of weather conditions and should be used as a tool for the prediction of infection hotpots in vineyards.
Improvement of the drying performance of pre-cooked beans (Phaseolus vulgaris) through ultrasonic-assisted hulling
(2022) Ramaj, Iris; Schock, Steffen; Ayetigbo, Oluwatoyin; Ntwali, Janvier; Müller, Joachim
Beans are among the most versatile and widely consumed staple foods worldwide. They are highly nutritious and contain high levels of dietary fibers, complex carbohydrates, proteins, essential vitamins, and minerals that are indispensable to human wellbeing. Due to their given importance, the development of processing methods for hard-to-cook beans for the preparation of instant end-products is of great interest, especially in developing countries. Thus, this study focused on investigating the influence of ultrasonic-assisted dehulling on the drying behaviour of pre-cooked beans as a viable alternative to the present drying approaches. Red kidney beans (Phaseolus vulgaris), unhulled (UHB) and dehulled via ultrasonication (HB/UT), were used for the experimental analysis. The cooking time of beans was determined based on sensory evaluation, with 50 and 25 min proving to be optimal for UHB and HB/UT, respectively. Afterwards, the pre-cooked samples were dried in a high-precision through-flow laboratory dryer (HPD-TF3+) at 30, 50, and 70° C with an air velocity of 0.20 ms-1 and specific humidity of 10 g kg-1. Results revealed a faster moisture transfer of the HB/UT beans compared to UHB beans at p < 0.05, which was attributed to the lower resistance to moisture diffusion induced by the hull removal. Henceforth, a reduction of drying time up to 73.3% was ascertained experimentally. A generalised semi-empirical model was developed from the analysis of the drying data, which was capable of predicting the drying behaviour of beans with R2 ≥ 0.990 and MAPE ≤ 10.0%. In terms of colour, UHB and HB/UT beans differed significantly at p < 0.05 for redness a*, yellowness b*, hue angle H*, and chroma c* across all drying conditions, while no significant differences were observed for luminosity L*. Microstructural analysis revealed comparable structures after drying at 30 and 50° C, with beans exhibiting an intact cellular structure. Temperatures of 70° C, on the other hand, degraded the cellular integrity of beans by breaking down the cell wall boundaries, especially in HB/UT beans. In conclusion, ultrasonic-assisted hulling has demonstrated a great potential for improving the drying performance of beans, thereby making it a viable alternative for practical applications.
Experimental analysis and CFD-based modeling of grain bulk drying dynamics
(2021) Ramaj, Iris; Schock, Steffen; Müller, Joachim
Drying is of great importance in the postharvest processing of agricultural commodities. It refers to the removal of the surplus moisture responsible for biochemical, microbiological, and other moisture-related deteriorative reactions, thereby ensuring quality preservation. However, drying is an intricate process comprising simultaneous heat and moisture transfers, which depends on product and drying air conditions. Therefore, drying practices are oftentimes misused, resulting in serious degradation of product quality. For this reason, modeling can be used to provide a deeper understanding of air-product interactions and to gain insights into drying process. Thus, this study focused on developing a CFD systematic approach to model the drying dynamics of wheat bulk (Pionier A, DSV AG) under controlled conditions. Within the model framework, a porous medium approach with tailored user-defined functions was utilized to represent the grain bulk characteristics. The drying experiments were performed using a high-precision and automated through-flow laboratory dryer. A coherent set of drying air temperatures T = 10 - 50°C, relative humidity RH = 20 - 60% and airflow velocity v = 0.15 - 1.00 ms-1 were employed for model validation. Afterwards, the validated computational model was used to predict the drying performance at T = 40°C, RH = 40% and v = 0.15 ms-1, where the simulated temperature and moisture content agreed very well with the experimental results (R2 ≥ 0.98 and MAPE ≤ 14.93%). The proposed model proved to be an efficient tool capable of simulating temperature and moisture dynamics inside the grain bulk with high spatial and temporal resolution, providing rapid and in-depth information compared to laborious physical experiments. In conclusion, the CFD-based approach has demonstrated a great potential for simulating drying processes. Its capabilities should be further assessed across various drying technologies, operating conditions, and agricultural commodities.
Improved prediction of wheat quality and functionality using near-infrared spectroscopy and novel approaches involving flour fractionation and data fusion
(2025) Ziegler, Denise; Buck, Lukas; Scherf, Katharina Anne; Popper, Lutz; Schaum, Alexander; Hitzmann, Bernd; Ziegler, Denise; Department of Process Analytics, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany; Buck, Lukas; Department of Bioactive and Functional Food Chemistry, Institute of Applied Biosciences, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; Scherf, Katharina Anne; Department of Bioactive and Functional Food Chemistry, Institute of Applied Biosciences, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany; Popper, Lutz; Mühlenchemie GmbH & Co. KG, Ahrensburg, Germany; Schaum, Alexander; Department of Process Analytics, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany; Hitzmann, Bernd; Department of Process Analytics, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany
The accurate and rapid determination of wheat quality is of great importance for the wheat supply chain. Near-infrared (NIR) spectroscopy has become an established method for this purpose. So far, however, predictions for most wheat quality characteristics are not accurate enough to replace reference measurements, with the exception of protein content. This study investigates the potential to improve the prediction of 41 wheat quality parameters (protein- and starch-related parameters, solvent retention capacity, farinograph, extensograph, alveograph) based on a flour fractionation approach (sieve fractionation, dough preparation, gluten washing) and data fusion using the established techniques of NIR spectroscopy and chemometrics. Results show that preprocessing of flour significantly altered the composition of the samples, which reflected in spectral differences of their NIR spectra. This also led to a change in the prediction accuracy for many wheat quality parameters. Compared to the prediction using flour spectra, flour fractionation with or without data fusion improved the RMSECV between 5.6 and 28.6% for 35 out of the 41 quality parameters tested, leading to R2CV between 0.80 and 0.96 for many of them. Gluten, dough, and the 50–75 µm and the 75–100 µm fractions were particularly important for the improved predictions. The best predictions were often based on data fusion of spectra from different sample types, demonstrating the importance of using complementary information from different data sources to improve predictions. The results underline the potential of this novel approach to be established in the industry as an extension of conventional NIR spectroscopy to improve wheat quality prediction.