Nominees

With 2.4 billion people suffering from food insecurity globally, this research offers an innovative solution to conventional farming methods through aquaponics. Aquaponics combines aquaculture (raising fish) with hydroponics (soilless plant cultivation) in a closed-loop system, eliminating the need for synthetic fertilizers while simultaneously facilitating resource maximization. This study assessed the economic viability of aquaponics as a model for sustainable agriculture using Python-based analysis of 1,140 vegetable combinations at the NGO Casita Copán in Honduras. By integrating economic modeling with sustainable agriculture, the study highlights aquaponics as a transformative tool for resilient food systems, supporting the SDGs through resource-efficient, community-driven practices.

Combining three Eurostat datasets from 2005 to 2022 for 29 European countries, this thesis

examines how social spending on passive support, activation, and facilitation policies affects the disability employment gap (DEG) in the European Union. The findings suggest that demand-side activation policies, such as wage subsidies, are generally more effective at reducing the DEG compared to supply-side measures like training programs. Work-related facilitation measures, including workplace accommodations, also tend to decrease the DEG. These associations are most pronounced for severely disabled and male job seekers, suggesting the need for targeted approaches considering the type of disability and gender disparities.

This thesis harnesses recent NLP advancements to create sentiment indices that capture public and investor moods through nearly half a million news articles. The novel sentiment measures align closely with established economic indicators, offering actionable insights for investors, businesses, policymakers, and regulators. With minimal cost and near-continuous updates, the approach outlined in this research provides a timely, data-driven alternative to traditional methods, empowering a more responsive, human-centered economic outlook. By rapidly identifying sentiment trends, these measures support informed, sustainable decisions, helping stakeholders understand and adapt to the emotional and social dynamics that shape markets, and possibly other areas.

This study develops actionable design principles for assessing data quality (DQ) when converting National Cancer Registry data to the OMOP Common Data Model, a critical step for improving the utility of Electronic Health Records (EHRs) in cancer research. By applying Action Design Research, the study identifies core data quality issues and addresses them through iterative, stakeholder-informed interventions. These interventions enhance transparency, automation, and interoperability in DQ processes. The design principles derived from these interventions support safer, higher-quality EHR use, contributing to a healthier society with reliable data-driven insights, especially vital for the societal transition toward data-informed healthcare.

This research expands the limited literature on the distributional impact of macroprudential policy (MaPs) on firm credit growth. It builds on it by studying a much larger and granular sample than any of the previous studies. Additionally, this paper is among the first to examine how institutional and financial development, along with banking sector characteristics, influence the effects of MaP actions on firm credit growth. The findings aim to inform targeted policy decisions that address financial imbalances and promote sustainable economic growth, while minimizing unintended consequences.

Prior research on mission-drift in social enterprise focuses on “traditional” structures used
to combat the phenomenon, yet few studies examine the steward-ownership structure as a
viable alternative. The purpose of this study is to gain insights into how social enterprises
use steward-ownership structures to combat mission-drift. Based on the findings from
interviews conducted with 12 employees from the case organisation, and relevant external
persons, three main steward-ownership structures emerge and, under each structure, a
variety of factors that work to ensure mission adherence and fulfillment. Moreover, the
findings reveal that it is a combination of all three structures that works to combat mission-
drift, with emphasis on the specific mechanisms of each structure. These findings contribute
to literature on mission-drift and the legal structuring of social enterprises, and serve as a
practical example for organisations aiming to implement the steward-ownership model.

This research expands the limited literature on the distributional impact of macroprudential policy (MaPs) on firm credit growth. It builds on it by studying a much larger and granular sample than any of the previous studies. Additionally, this paper is among the first to examine how institutional and financial development, along with banking sector characteristics, influence the effects of MaP actions on firm credit growth. The findings aim to inform targeted policy decisions that address financial imbalances and promote sustainable economic growth, while minimizing unintended consequences.

This study develops actionable design principles for assessing data quality (DQ) when converting National Cancer Registry data to the OMOP Common Data Model, a critical step for improving the utility of Electronic Health Records (EHRs) in cancer research. By applying Action Design Research, the study identifies core data quality issues and addresses them through iterative, stakeholder-informed interventions. These interventions enhance transparency, automation, and interoperability in DQ processes. The design principles derived from these interventions support safer, higher-quality EHR use, contributing to a healthier society with reliable data-driven insights, especially vital for the societal transition toward data-informed healthcare.

The demand for and complexity of youth care have increased, resulting in long waiting lists with serious consequences. Individual cases often exceed expertise of single care providers, making network collaboration essential but challenging. Municipal procurement decisions shape the youth care system, offering opportunities to enhance this collaboration. Through an archival study of procurement documents and a multiple casestudy with policymakers and care providers, this research identifies twelve policy incentives stimulating network collaboration within the system. Findings show that effective collaboration relies on well-designed procurement procedures and policy incentives across different levels, offering solutions to improve youth care in the Netherlands.

This thesis harnesses recent NLP advancements to create sentiment indices that capture public and investor moods through nearly half a million news articles. The novel sentiment measures align closely with established economic indicators, offering actionable insights for investors, businesses, policymakers, and regulators. With minimal cost and near-continuous updates, the approach outlined in this research provides a timely, data-driven alternative to traditional methods, empowering a more responsive, human-centered economic outlook. By rapidly identifying sentiment trends, these measures support informed, sustainable decisions, helping stakeholders understand and adapt to the emotional and social dynamics that shape markets, and possibly other areas.

This thesis critically explores the European Union’s pursuit of technological advancement for border security, focusing on artificial intelligence (AI) within securitization practices. Using discursive analysis of text and images, it examines how migration is framed as a primary security issue, positioning AI as an essential solution. Analyzing three Horizon 2020 projects (ROBORDER, NESTOR, and TRESSPASS), it scrutinizes the ideological assumptions and values in research discourse. Highlighting tensions between technological neutrality and ethical concerns, it raises potential risks to fundamental rights, especially data privacy, and advocates for informed, ethically aware AI policy within the EU’s border and migration management strategies.

My thesis aims to assess the validity of the ‘sin stock anomaly’ by observing whether sin stocks are traded on a sin premium and whether they are recession-resilient. Integrating quantitative data analysis, I compared the monthly returns of sin stocks to stocks to comparable stocks in the consumer industry over 60 years to determine whether a unique sin component drives their performance. The results indicate that sin stocks exhibit significant premiums during expansions but do not consistently outperform during recessions. However, the research also reveals different characteristics of stocks in the gambling, tobacco, and alcohol industries.

The thesis investigates the impact of the EU Carbon Border Adjustment Mechanism (CBAM) on African countries’ exports to the European Economic Area (EEA). The methodology involves a partial equilibrium analysis of a gravity model of bilateral trade, combined with input-output analysis to derive CO2 intensities along the value chain of African-produced goods. The results indicate a significant reduction in exports from African countries to the EEA under full product coverage. The study demonstrates that CBAM has the potential to shift the burden of emission reduction onto vulnerable EEA trading partners, underscoring the need for a carefully considered application of the policy in its final stage.

Combining three Eurostat datasets from 2005 to 2022 for 29 European countries, this thesis

examines how social spending on passive support, activation, and facilitation policies affects the disability employment gap (DEG) in the European Union. The findings suggest that demand-side activation policies, such as wage subsidies, are generally more effective at reducing the DEG compared to supply-side measures like training programs. Work-related facilitation measures, including workplace accommodations, also tend to decrease the DEG. These associations are most pronounced for severely disabled and male job seekers, suggesting the need for targeted approaches considering the type of disability and gender disparities.

Several governments are considering a food carbon tax to tackle climate change. However, this could invertedly increase animal suffering. If consumers substitute carbon-intensive beef with meat from smaller animals (like chicken), producers will slaughter more animals to produce the same amount of meat. This is called the Small Animal Replacement Problem. This thesis develops a market model of substitution between animal products after a carbon tax and calibrates it with data for the United States. While it predicts a slight decrease in slaughtered animals, a slaughter or meat tax is a better option when society even slightly values animal welfare.

With 2.4 billion people suffering from food insecurity globally, this research offers an innovative solution to conventional farming methods through aquaponics. Aquaponics combines aquaculture (raising fish) with hydroponics (soilless plant cultivation) in a closed-loop system, eliminating the need for synthetic fertilizers while simultaneously facilitating resource maximization. This study assessed the economic viability of aquaponics as a model for sustainable agriculture using Python-based analysis of 1,140 vegetable combinations at the NGO Casita Copán in Honduras. By integrating economic modeling with sustainable agriculture, the study highlights aquaponics as a transformative tool for resilient food systems, supporting the SDGs through resource-efficient, community-driven practices.