Gül Gündüz Mengübaş

• Tuesday 13 May 2025 at 4:00 pm
• Supervisor: Kenneth Sörensen
• The defence will take place at the Promotion Room, Cloister of the Grauwzusters, University of Antwerp, Stadscampus, Lange Sint-Annastraat 7, 2000 Antwerp
• Please contact Gül Gündüz Mengübaş (gul.gunduzmengubas@uantwerpen.be) to inform her whether you wish to attend the PhD defence before Thursday 8 May 2025
  
  

Metaheuristics for Assembly Line Feeding Optimization and Tow Train Routing in the Automotive Industry

The automotive industry, a cornerstone of modern economies, is under increasing pressure to improve production efficiency amidst rising system complexity, sustainability requirements, and the demands of just-in-time (JIT) manufacturing. This dissertation addresses critical optimization problems in this context, focusing on tow train-based assembly line feeding and routing — a key internal logistics function where smart planning can significantly reduce costs and ensure timely, disruption-free operations.
The first part of the dissertation tackles the Assembly Line Feeding Problem (ALFP), where tow trains deliver parts to workstations under strict timing and load constraints. To address this inherently complex and computationally challenging problem, a Variable Neighborhood Search (VNS) algorithm is proposed within the framework of the Split Delivery Vehicle Routing Problem (SDVRP).This method reduces total travel distance and the number of required vehicles while managing trade-offs between cycle times, split deliveries, and transport volume in a multi-objective context.
The second part investigates conflict-free tow train routing in grid-based production environments. In JIT systems, route conflicts lead to delays and safety issues. A novel approach is introduced that models the layout as a grid of “pixels” to detect potential collisions. Paths are computed using the A-star (A*) algorithm, and optimized through a Simulated Annealing (SA) heuristic. A dedicated Conflict Detection Algorithm (CDA) resolves potential collisions using preemptive avoidance strategies, ensuring safe and uninterrupted flow.
The third contribution addresses tow train routing in narrow-aisle environments, where vehicles cannot reverse and risk blocking each other. A pixel-based grid is again employed for spatial modeling, and shortest paths are calculated using Dijkstra’s algorithm. The routing problem is formulated as a Generalized Vehicle Routing Problem (GVRP), and solved using an SA-based heuristic enhanced with problem-specific neighborhood operators. A blocking detection and avoidance algorithm ensures that deadlocks are avoided, maintaining the system’s throughput.
Together, these contributions combine advanced metaheuristic techniques, conflict resolution mechanisms, and routing optimization models. The findings offer scalable and practically implementable strategies to address real-world challenges in modern automotive production environments and contribute to the evolving field of smart manufacturing logistics

Maira Finizola e Silva

• Wednesday 4 June 2025 at 4:00 pm
• Supervisors: Steven Van Passel &  Jan Cools 
• The defence will take place in Room S.M.003, De Meerminne, University of Antwerp, Stadscampus, Sint-Jacobstraat 2, 2000 Antwerp
• Please contact Maira Finizola e Silva (maira.finizolaesilva@uantwerpen.be) to inform her whether you wish to attend the PhD defence before Friday 30 May 2025

Assessing the Willingness of Kenyan Farmers and Consumers to Transition Towards Sustainable Food Systems 

In the face of escalating challenges related to climate change, food security, and environmental sustainability, fostering resilient and sustainable food systems is critical, particularly in Sub-Saharan Africa. This dissertation examines the perspectives and preferences of Kenyan food value chain actors – focusing primarily on farmers and consumers – toward sustainable food systems. First, a systematic literature review highlights the diverse and context-specific factors influencing Sub-Saharan African farmers' adoption of climate-smart agriculture, identifying key barriers (e.g., reliance on off-farm income) and drivers (e.g., education level, training, access to credit, and others). Subsequently, using Q-methodology, four distinct stakeholder perspectives on sustainable food value chains in Kenya are identified, reflecting differing priorities across economic, environmental, and social dimensions. Building on these insights, two Choice Experiments were conducted to quantify the preferences of Kenyan farmers and consumers regarding sustainability-related attributes in the food system. The results reveal overlapping priorities between farmers and consumers, particularly concerning the reduction of pesticide use and the improvement of farmers’ working conditions. By connecting the supply and demand sides of the value chain, this research provides practical recommendations for designing policies and interventions that promote sustainable agricultural practices and resilient food systems in Kenya. Overall, the findings underscore the necessity of context-specific, inclusive strategies that align the motivations of key value chain actors to drive systemic change.

Noemi Van Meir

• Monday 16 June 2025 at 4:30 pm
• Supervisors: Edwin Van Hassel & Thierry Vanelslander
• The defence will take place at the Promotion Room, Cloister of the Grauwzusters, University of Antwerp, Stadscampus, Lange Sint-Annastraat 7, 2000 Antwerp
• Please contact Noemi Van Meir (noemi.vanmeir@uantwerpen.be) to inform her whether you wish to attend the PhD defence before Wednesday 11 June 2025
  
  

Ports at the crossroads of the energy transition: navigating shifts in energy flows - Scenarios and strategic implications

Daniel Schubert

• Tuesday 17 June 2025 at 4:30 pm
• Supervisors: Christa Sys & Rosario Macario
• The defence will take place at the Promotion Room, Cloister of the Grauwzusters, University of Antwerp, Stadscampus, Lange Sint-Annastraat 7, 2000 Antwerp
• Please contact Daniel Schubert (daniel.schubert@student.uantwerpen.be) to inform him whether you wish to attend the PhD defence before Thursday 12 June 2025

Customized airline offer management: solving the assortment problem through multi-dimensional segmentation

This dissertation develops a novel solution for customized airline offer management with the aim to combine viability, usability, and feasibility. The solution is tested on real data from a major network airline. It expands the existing academic literature and practical applications as it suggests a cost-effective and understandable way for airlines to significantly improve the prediction accuracy of customer choice models without the need for complex models, using existing data and simple forecasts. The research shows that high-dimensional and data-driven segmentation, potentially aided by machine learning to solve data sparsity, can be combined with the traceability of discrete choice models.

This implies airlines do not need complex machine learning models to improve the prediction accuracy of which specific product a specific customer will likely purchase. However, airlines should use information they already have in a customer search. Because the data is already available, this is a cost-effective way for airlines to significantly improve the prediction accuracy of their customer choice models with 99.9% confidence. The proposed offer management system is data-driven, can respond to searches in real-time, and is designed in modules for gradual embedding into existing processes, workflows, and system. Also, it is built in a way that it both works with existing revenue/offer management systems as well as innovations like continuous pricing and new distribution capabilities that are strategic priorities for airlines.

Konstantina Vasilakou

• Monday 30 June 2025 at 4:00 pm
• Supervisors: Steven Van Passel, Philippe Nimmegeers & Pieter Billen​
• The defence will take place at the Promotion Room, Cloister of the Grauwzusters,University of Antwerp, Stadscampus, Lange Sint-Annastraat 7, 2000 Antwerp
• Please contact Konstantina Vasilakou (konstantina.vasilakou@uantwerpen.be) to inform her whether you wish to attend the PhD defence before Wednesday 25 June 2025

Techno-Economic and environmental assessment of new-generation biofuels

Jef Van Cappellen 

• Tuesday 25 March 2025 at 5:00 pm
• Supervisors: Jan Annaert, Marc De Ceuster & Andrew Lepone

Empirical Market Microstructure Essays in Over-the-Counter Markets 

The findings presented in this dissertation significantly enhance our understanding of OTC sovereign bond markets, addressing a crucial gap in academic research due to the scarcity of high-quality publicly available data. Through pioneering trade-level datasets on the UK sovereign bond market, this research offers comprehensive summary statistics that shed light on the overall market and individual participant behaviour. It further delves into the roles of prevalent OTC market frictions—inventory, search, and bargaining—which are instrumental in the liquidity deterioration experienced in the UK sovereign bond market during the COVID-19 pandemic. This analysis clarifies how these frictions impact market resilience and identifies potential vulnerabilities. Further, the dissertation evaluates the effects of post-trade transparency on market quality, systematically exploring how transparency influences transaction costs and contributes to pricing efficiency in sovereign bond markets. These insights have academic and policy implications, offering empirical evidence that can inform future regulatory frameworks and market operations to foster more efficient and resilient financial markets

David Stuer

• Monday 24 March 2025 - 4:00 PM
• Supervisor: Ans De Vos

As above, so below? A multilevel approach to the Job-Demands Resources Model

The dissertation extends the Job Demands-Resources (JDR) model in two key directions: the intra-individual level (how job demands and resources fluctuate over time) and the supra-individual level (how they are distributed within teams).
At the intra-individual level, a dynamic systems perspective is introduced, differentiating between trait and state job demands and resources and incorporating patterns of change over time, such as variability and attractor strength. At the team level, the research explores disparities in job demands and resources, analyzing how unequal distributions influence employee outcomes.
Conceptually, the dissertation advances the JDR model by integrating emergent properties across different levels of measurement and incorporating configural constructs, drawing on diversity research to examine how disparities in job characteristics shape workplace experiences. Methodologically, the research applies multilevel modeling to simultaneously assess job demands and resources across different levels (intra-individual, individual, and team level). It introduces novel measures for emergent concepts and investigates interactions, ensuring a systemic and integrated approach to understanding job demands, resources, and their organizational impact.
By combining conceptual advancements with rigorous methodological approaches, this dissertation provides a deeper and more dynamic perspective on job demands and resources.

Jehangir Khan

• Wednesday 19 March 2025 - 2:00 pm 
• Supervisors: Roel Gevaers & Alessio Ishizaka​

Risk assessment of supply chain management during COVID19 pandemic and inventory classification using MCDM tools

This dissertation focuses on the risk assessment of supply chain management during the COVID-19 pandemic and inventory classification using Multi-Criteria Decision Making (MCDM) tools. It comprises three research articles. In the first article, we introduce a novel MCDM approach called Fuzzy VIKORSort. This method is utilized to classify various economic sectors into predefined groups (High, Moderate, Low) based on the disruptions in the global and regional supply chains due to the COVID-19 pandemic. We validate our methodology using the case of Pakistan. In the second article, we propose an enhanced visualization method based on MCDM called VIKOR-GAIA. To implement this visualization approach, we use a case study of supply chain disruptions in perishable food items. Additionally, we conduct a comparative analysis with an existing visualization based on the MCDM approach to demonstrate the effectiveness of our proposed method. In the third article, a new method called VIKOR Fuzzy Sort is proposed to address the Multi-Criteria Inventory Classification (MCIC) problem. This methodology facilitates the classification of different inventory items based on their inherent characteristics' resemblance to neighboring classes during the sorting process. The proposed methodologies in this dissertation will assist policymakers and practitioners in addressing various complex decision problems. Additionally, they will make a meaningful contribution to scholarly work.

Babette Jansen

• Friday 14 February 2025 at 4:00 pm
• Supervisors: Sunčica Vujić & Roland Winkler

Macroeconomic Policy, Household Heterogeneity, and the Labor Market

This dissertation contributes to the understanding of fiscal and monetary policy aimed at stimulating economic activity during recessions and maintaining price stability.  With the resurgence of fiscal policy as a crucial stabilization tool post-Great Recession and the recent shift to higher interest rates following an extended period of historically low rates, a deep understanding of fiscal and monetary policy is vital. Empirical research of labor markets and the development of theoretical macroeconomic models that analyze fiscal and monetary policy contribute to this understanding. The results reveal significant changes in labor market conditions, with increased employer market power and heterogeneous labor supply elasticities, and underscore the need to consider these factors in policy decisions. Additionally, a novel fiscal policy transmission channel can be observed through countercyclical monopsony power. Finally, the analysis of New Keynesian models discovers new insights into the Taylor principle and determinacy issues depending on household heterogeneity and households’ labor supply preferences. Overall, this thesis underscores the necessity of current empirical analysis of the labor market and updated models for macroeconomic policy analysis.

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Mehran Farzadmehr

• Monday 10 February 2025 at 4:30 pm
• Supervisors: Thierry Vanelslander & Valentin Carlan
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AI-powered solutions assessment in port and maritime sector

The digitalization of port and maritime, particularly through the adoption of AI-powered solutions, is a major trend these days. However, this research identifies gaps in the literature, including the lack of a consistent approach to distinguishing AI initiatives and quantifying their costs and benefits. To address these gaps, this PhD thesis employs a mixed-method approach, combining both desk and empirical research. This study develops two assessment models: an AI typology to differentiate AI solutions and a cost-benefit framework to conduct economic analyses of AI solutions. Furthermore, the research identifies a typology of 30 AI initiatives and ranks them based on deployment complexity, considering their application domains. Secondly, three detailed economic analyses are conducted at two implementation levels: micro and macro. The first analysis explores the use of AI to predict truck ETAs for a trucking company. The findings indicate that the truck ETA prediction project offers comparable profitability under two conditions: trucking companies with legacy systems but with potential for revenue growth through AI adoption or trucking companies without the chance for revenue growth but can avoid technical integration costs. However, the project becomes highly cost-effective when revenue increases, and technical integration is not required. The second analysis assesses the benefits of AI-assisted data entry for logistics companies when processing transport orders. The economic analysis reveals that modifying IT system architecture to incorporate AI-assisted data entry is not cost-effective for companies with low transaction volumes. However, horizontal collaboration can reduce organizational integration costs, typically 1% to 7% of total solution implementation costs. The third analysis evaluates an AI-powered solution to optimize the scheduling of tugboats and dock pilots within the lock. It highlights the trade-offs between incorporating fairness in task allocation and achieving cost savings through AI-driven optimization. Including fairness as a goal reduces cost savings, reflecting the social integration costs, which account for 31% and 23% of cost savings for tugboat and pilotage companies, respectively. Additionally, a gain-sharing scenario minimizes benefit losses among port stakeholders, reducing overall losses by 3.5% to promote vertical collaboration. Overall, this dissertation offers valuable insights into AI assessment in the port and maritime sectors, contributing to scholars and industry.

Katrien Storms

• Friday 7 February 2025 at 4:30 pm
• Supervisors: Thierry Vanelslander & Edwin Van Hassel
  
  

Unravelling D&D within the maritime ecosystem and its influence on IWT in port-hinterland supply chains

The use of intermodal inland waterway transport (IWT) is a key European strategy to move towards climate-neutral transport. However, challenges such as COVID-19, extreme Rhine water levels, and geopolitical disruptions complicate the shift from road to IWT. These disruptions often result in additional costs, known as demurrage and detention (D&D).

This dissertation researches the impact of D&D practices on IWT within Europe’s port-hinterland supply chain. Using a SARIMAX modeling, it forecasts IWT container volumes on the Rhine and highlights the potential impact of disruptions on IWT recovery. Findings from surveys, discussions, and legal analyses reveal inefficiencies in D&D practices and propose solutions such as extended free time for IWT, digitalization, and improved negotiation strategies. Cost analyses show that D&D fees can exceed the shipping lines’ opportunity costs as time passes, suggesting their role as a revenue stream. Nevertheless, shippers can leverage D&D into their storage strategies to optimize costs. Furthermore, D&D and terminal dwell times significantly influence IWT's modal share. Consequently, addressing D&D is important in making a shift towards more sustainable and efficient hinterland transport.

Elke Godden

• Tuesday 21 January  2025 at 5.00 pm
• Supervisors: Nathalie Dens & Lukar Thornton 

How the Nutri-Score affects consumers and manufacturers: A focus on consumers’ choices and manufacturers’ reformulation efforts

Imagine you are standing in the supermarket. As you gaze at the rack of breakfast cereals, you might feel overwhelmed by the numerous alternatives presented to you. How do you choose what to buy? The Nutri-Score was developed to simplify this decision by aiding consumers to compare products’ healthiness. As previous research demonstrates its understandability, attention-grabbing properties, and mostly positive effects on purchase intention and choice, the European Union has considered adopting it as the official European label as part of their Farm-To-Fork strategy.
Nevertheless, not all countries are unequivocally in favour of this label; the same holds true for companies, and even experts and researchers, who cite mixed findings and several evidence gaps. This has complicated the decision of the European Commission and led to postponing their harmonized labelling efforts.
Against this backdrop, this dissertation focusses on strengthening the available evidence by addressing five key gaps. It explores the Nutri-Score’s effect outside of controlled environments, its impact on multi-attribute product choices, the heterogeneity in consumers’ preferences for the label, its implementation in online supermarkets, and the efforts undertaken by food manufacturers to engage in Nutri-Score-driven product reformulations.
Employing a range of methodologies - including a naturalistic field experiment, discrete choice modelling, a randomized controlled trial, and retrospective observational study – this work provides fresh insights into the Nutri-Score’s effectiveness. By extending our knowledge and insights on the multifaceted puzzle that surrounds the Nutri-Score, this thesis contributes to a robust evidence base that will eventually enable the European Commission to make well-informed and evidence-driven decisions on harmonized labelling efforts.

Hendrik Leder

• Monday 20 January 2025 at 9:30 am
• Supervisors: Sascha Albers & Markus Reihlen

Navigating Endgames: Conceptualization, Strategies and Successful Turnarounds 

The pace of technological change and digital transformation is accelerating, leading to the emergence of new industries as others decline. Responding to this phenomenon, this PhD thesis explores the challenges of industry decline, endgames and organizational turnarounds. I draw on a rich theoretical foundation and empirical evidence to identify the strategies firms can follow to navigate these challenges.

This PhD thesis is structured around three studies researching the social construction of endgames, how strategy is adapted within an endgame and how firms can achieve successful turnarounds. In the first study, I use a fictional institutionalist perspective to show how endgames are socially constructed, shedding light on the dynamic interplay of industry actors’ fictional expectations and the subsequent strategies they chose as an endgame diffuses through an industry. The second study investigates the patterns of strategic change in endgames and introduces a dialectical model that conceptualize the dynamics of organizational responses to industry decline. The last study focuses on organizational turnarounds as organizations initiate turnaround efforts to recover from prolonged decline in an endgame. This study uses a qualitative meta-analysis of turnaround cases to identify the underlying mechanisms and temporal sequences of successful recovery efforts. The four distinct process archetypes that this study identifies contributes both theoretical insights for researchers and practical insights for managers navigating turnaround scenarios. Together, these three studies provide a detailed understanding of endgames, from how endgames are conceptualized to which organizational strategies firms follow in endgames to the archetypes of organizational turnarounds that firms use to recover from prolonged decline during an endgame.

Overall, this thesis contributes theoretically and practically to the fields of strategic management and organizational studies. I provide a nuanced understanding of how organizations can navigate the tumultuous waters of decline, adapt to changing industry landscapes and orchestrate successful turnarounds in the face of adversity.