Business and Economics

Phd defences Faculty of Business and Economics

Forthcoming PhD defences and past PhD defences in the archive

Forthcoming PhD defences

28 November 2022 - Hans Van Oorbeeck (Department Accountancy and Finance / AMS)

Hans Vanoorbeeck

  • Monday 28 November 2022 - 1 p.m.
  • Supervisor: Eddy Laveren
  • The defence takes place in the Graduation Hall - Cloister of the Grauwzusters, University of Antwerp, City Campus, Building S, Lange Sint-Annastraat 7, 2000 Antwerpen.

Past PhD defences 2022

14 September 2022 - Laura Caluwe (Department of Management Information Systems)

Laura Caluwe

  • Wednesday 14 September 2022 - 4 p.m.
  • Supervisors: Steven De Haes & Tim Huygh
  • The defence takes place in the Graduation Hall - Cloister of the Grauwzusters, University of Antwerp, City Campus, Building S, Lange Sint-Annastraat 7, 2000 Antwerpen.
    Please contact Mrs. Laura Caluwe ( ) to inform her whether you wish to attend the PhD defence before Monday 12 September 2022.

The role of the board of directors in governing digital transformation

Digitalization has a profound impact on organizational strategy and risk exposures. As both strategy and risk are key concerns of the board of directors, researchers are increasingly calling for boards to be more involved in IT governance. Indeed, studies show that board-level IT governance is positively related to organizational performance and IT risk management. However, figures from practice indicate a lack of board attention to IT-related topics as well as a lack of board IT competence to adequately carry out IT governance duties. This research focusses on this knowing-doing gap by investigating how boards of directors can take up accountability and responsibility for governing digital transformation.

We examine the current state of board-level IT governance literature and practice, gain a better understanding of board roles when IT governance is exercised as part of corporate governance, and focus on the board's IT strategic roles. Our findings suggest that, in order for boards to truly assume responsibility for governing digital technologies, IT governance should be regarded as an essential component of corporate governance. Furthermore, the board's IT expertise is a critical mechanism for carrying out IT governance responsibilities. Finally, the CIO plays an important role in increasing board involvement in IT governance.

Showing that IT governance should be an integral part of corporate governance is critical to move the board-level IT governance literature forward. Second, we lay the groundwork for future research by presenting a conceptual model for board-level IT governance, as well as a research agenda. Furthermore, we demonstrate the utility of various theoretical perspectives in addressing governance issues. Third, we open up the black box of board-level IT governance in practice through case study research. Finally, we add to the corporate governance literature by providing insights on digitalization, which creates both strategic and risk-related challenges for governing organizations.

For practice, our findings demonstrate the value of the board’s contribution in governing IT. Furthermore, we detail six roles that boards can take up to perform their IT governance duties and outline various governance mechanisms to implement them. We take a deep dive into one of these mechanisms, i.e., board-level IT governance committees, and a subset of these roles, i.e., the board’s IT strategic roles. In doing so, we hope to inspire boards of directors on how to shape their involvement in digitalization.

Rule-based explanation methods to gain insight into classification models using behavioral data - Yanou Ramon (8/09/2022)

Yanou Ramon

  • Thursday 8 September 2022
  • Supervisor: David Martens

Rule-based explanation methods to gain insight into classification models using behavioral data

Every step we take in the digital world leaves a record of our behavior; a digital footprint. Think about the pages we visit on the Internet, the songs we listen to on Spotify, or the online purchases we make on Amazon. The recent field of predictive analytics on these data demonstrated that fine-grained digital records of our behavior harbor much potential to improve decision-making in business and society. However, we still face challenges related to these technologies, among others, the black-box nature of prediction models that restricts users to answer why-questions about predictions, that is our central research focus.

In this PhD thesis, we study solutions to explain predictions driven by behavioral data, and contribute to the field of Explainable Artificial Intelligence (XAI), in which, up until now, the majority of research focused on methods suitable for data other than digital footprints. The first empirical part comprises two studies with theoretical advances in explanation methods to interpret predictions in our specific data context. First, we develop two novel algorithms to compute counterfactual explanations that explain individual predictions. Second, we propose a methodology to gain global insight into models by extracting rule sets that mimic the behavior of the model. The explanation rules aim to provide an accurate proxy for complex models, while at the same time being comprehensible to end users. The novelty lies in the use of higher level clusters of data (metafeatures) to extract explanation rules instead of the behavioral features on which the model was originally trained. The second part of the thesis includes two applied studies on model interpretability. In the first study, we demonstrate the use and importance of explanation methods in the context of psychological profiling, for which we use a real-world case study of predicting personality from financial transactions data. Lastly, in a final study, we show the potential of well-established experimental methods from the Marketing field to study people's preferences for explanations for algorithmic decisions.

Our research proposes novel rule-based explanation methods, and shows their potential to produce more trustworthy and explainable predictive technologies that use behavioral data. We hope the importance of XAI will be acknowledged by researchers and practitioners in fields beyond data science, who are discovering the possibilities of mining behavioral big data, and that more interaction will follow between XAI experts, marketeers, social scientists, and psychologists to tackle open questions about XAI, as to exploit the full potential of these data.

Efficient Prediction Markets - Jonas Vandenbruaene (30/06/2022)

Jonas Vandenbruaene

  • Thursday 30 June 2022
  • Supervisors: Marc De Ceuster & Jan Annaert


A core question in financial economics is whether markets are informationally efficient i.e., whether asset prices accurately reflect all available information. Although the empirical literature on market efficiency is vast, the subject is still heavily debated among academics and practitioners. A fundamental issue with informational efficiency is that it is virtually untestable in traditional financial markets. For example, in an ideal world, researchers would compare stock prices on stock markets with their true values to check whether they are aligned or not. However, as true values of stocks are never available, this is not possible. This untestability of market efficiency is referred to as the joint hypothesis problem. 

In this dissertation, we try to make an original, unconventional contribution to the market efficiency debate by studying prediction markets. Prediction markets are platforms where people can bet on the outcome of future events, like a presidential election or a football game. Prediction markets have many characteristics that make them interesting research labs. Their main advantage is that the outcomes of the events are exogenously revealed, the market prices collide with reality. This allows researchers to systematically compare market prices with terminal values to detect mispricing, which is not possible on stock markets and circumvents the joint hypothesis problem. 

This dissertation contains three empirical chapters. In the first, we review 40 years of literature on mechanical trading strategies in sports prediction markets. Many individual studies claim to have found profitable trading strategies which implies inefficient market pricing. However, when we consider the entire literature, the evidence is consistent with an efficient market where profit opportunities are chance results. Furthermore, we argue for more meta-scientific reflexes and put forward a hurdle rate of |z|>3 to benchmark the statistical significance of empirical results. 

The second empirical chapter studies the evolution of the UK fixed odds betting market between 2000 and 2018. This period is of particular interest as it coincides with the rise of online gambling. We find that over this period, transaction costs decreased very significantly, both statistically and economically. Furthermore, we document a decrease in the favorite-longshot bias, a persistent anomaly in prediction market research. 

The third empirical chapter tests whether time series momentum, a well-known irregularity in traditional financial markets, is also present in prediction market data. We find that a time series momentum effect is indeed present and by leveraging the prediction market characteristics, we show it is consistent with behavioral underreaction and not a rational premium for variance or skewness.

A techno-environmental economic assessment of a lignin-first biorefinery: a dynamic and prospective framework for emerging technologies - Maxim Tschulkow (29/06/2022)

Maxim Tschulkow

  • Wednesday 29 June 2022
  • Supervisors: Steven Van Passel & Tine Compernolle


Biorefining has gained interest and has the potential to tackle several sustainability challenges in our society. A lignin-first biorefinery process – reductive catalytic fractionation (RCF) – is currently being developed to process wood into high-value end-products. However, the RCF process has not matured yet, holding a certain degree of technological, economic, and environmental uncertainties. Hence, an appropriate assessment method is needed to assess emerging uncertain technologies (e.g lignin-first RCF process).

This dissertation aims to develop a dynamic and prospective techno-environmental economic assessment framework to assess emerging technologies from economic and environmental points of view. First, a techno-economic assessment (TEA) was performed to assess the economic feasibility of the lignin-first RCF biorefinery and to identify the most influential economic and technological parameters affecting the profitability. Afterwards, an analytical real options analysis (ROA) was performed taking market uncertainties and the value of flexibility into account in order to identify the optimal investment decision. Next, a consequential life cycle assessment (LCA) was performed to assess the carbon emissions and the environmental consequences of the lignin-first RCF process and its products. Finally, the above-mentioned methods – TEA, ROA, and consequential LCA – were uniquely integrated within the newly developed integrated assessment framework. The framework has the aim to complement the shortcomings and combine the advantages of all three methods. It provides dynamic and prospective insights into the time-specific economic and environmental performances of the lignin-first RCF process implementation.

The newly developed integrated assessment framework offers decision support to several stakeholders of emerging technologies. Practitioners such as the technology developers, researchers, and policymakers can use the framework to evaluate emerging technologies that deal with high levels of technological, economic, and environmental uncertainties. The framework assesses emerging technologies on a detailed level to give decision-makers in-depth insights into the intertwined nature of the technological, economic, and environmental dimensions. It offers insights into the expected time-specific economic and environmental performances, potential, and challenges of the emerging technology to further improve the technology and direct R&Ds along the right path.

Unravelling complexity in digital servitization development: A multi-lens approach - Bieke Struyf (8/06/2022)

Bieke Struyf

  • Wednesday 8 June 2022
  • Supervisor: Paul Matthyssens


Since the launch of the Industry 4.0 concept in 2011, manufacturing firms have grown increasingly aware of the potential benefits digital technologies hold for improved efficiency, novel revenue streams, and enhanced competitive advantage. Despite promises made, however, firms continue to struggle with the realization of returns on digital investments made. For manufacturers to benefit from Industry 4.0 implementation, digitalization needs to be combined with servitization. Servitization refers to the creation of additional customer value through the offering of services in addition to the traditional product. Digital technologies can facilitate the creation and scale up of novel services. The transition toward digital servitization, however, entails a complex multi-actor, technological, managerial, and organizational challenge.

With this work, I aim to unravel digital servitization complexity and identify managerial approaches to it to support practitioners in smoothening their transitions and reaping the financial and competitive benefits of Industry 4.0 implementation. Comparative case studies are used to study the transitions of seven exemplary industrial firms. In applying multiple lenses to digital servitization journeys,  the dissertation provides insight into 1) novel digital servitization pathways, 2) internal and external tensions manufacturers, customers and value creating partners experience throughout the transition, and 3) key capabilities and effective managerial approaches that support digital servitization “champions” in dealing with the ensuing complexity.

The dissertation contributes to literature by taking a holistic approach to digital servitization in which the focal firm and the ecosystem perspective, intent and emergence, and ratio and emotion co-exist and merge together to determine the outcome of digital servitization journeys. Implicit assumptions underlying digital servitization literature are made explicit and are challenged illustrating the need for novel, more complex managerial approaches befitting the strategy’s non-linear, unpredictable nature. Finally, the work clearly illustrates the role emotions play in strategic change initiatives and extends a warm invitation to increasingly include the often-forgotten people perspective in future research efforts.

Efficiency and productivity in container terminal operation: A case study for the Hamburg – Le Havre range - Sisangile Nduna (18/03/2022)

Sisangile Nduna

  • Friday 18 March 2022 - 4 p.m.
  • Supervisor: Thierry Vanelslander

Efficiency and productivity in container terminal operation: A case study for the Hamburg – Le Havre range

The container sector's significance dates back to the 1950s. Times of economic turmoil, such as the 2008 financial crisis, the COVID-19 Pandemic, the 2021 Suez Canal blockade, are recent phenomena where the importance of the maritime and port sector became visible to the general public.

As an exchange interface, terminals handle hundreds of millions of containers every year  to facilitate trade and globalisation. Efficiency and productivity at container terminals are highly driven by frequent port calls, resilient infrastructure and adequate accessibility through the hinterlands. Investments in the infrastructure and the superstructure by  terminals can save customers a large amount of costs.

This thesis addresses the role of infrastructure and superstructure in evaluating efficiency in container terminals. The role of port competition is addressed to indicate implications of closeby terminals and ports to performance. The implications due to performancce can also be observed through costs, an element also investigated in this thesis.The methodological approach used for performance includes non-parametric and parametric methods to conclude. The analysis for productivity and efficiency is through the use of the Malmquist productivity Index (MPI) and the data envelopment analysis (DEA) (Charnes, Cooper and Rhodes (CCR) and Banker, Charnes and Cooper (BCC)). To evaluate the association of the external factors with the relative technical efficiency of the terminals, the Tobit regression and the Kruskal – Wallis models are used. The methods are applied in the Hamburg Le-Havre (HLH) context considering two periods, 2013 and 2018. For the costs analysis, only the terminals at the port of Antwerp are evaluated.

The emphasis in efficient handling of resources is identified as key in the functioning of the business. The external factors are recognised as additional major contributing factors to the container handling business. Through efficient handling of containers, terminal operators can save costs, not only for themselves, but also for the rest of the stakeholders. The outcomes indicate that relative efficiency is vital to evaluate especially in a business environment where competition is high. The HLH is found to maintain a positive trend of productivity and efficiency over the time measured. Scale inefficiencies contribute negatively to the overall efficiency in the region. The high efficiency and productivity in the region indicate proper management of resources by the terminal managers, which suggests that the capacity expansion investments are paying off. Although it is proven that environmental factors are not highly significant in terminals in close proximity, it is also emphasised that the external factors are generally substantial in shaping cargo flows, which is vital in determining efficiency.

In addressing the measurement and importance of terminal efficiency, this research provides insight to container terminal managers on effective ways to manage resources at their terminals. The research contributes by providing a holistic view of terminal handling to policymakers for large investment decision-making purposes. Research focusing on the terminal level, especially in a region with business operation characteristics such as the HLH, is limited thus this work helps to reduce that gap.

Digital technology acceptance during covid-19. An empirical study of data imperatives on digital acceleration - Mounir Boukadidi (25/02/2022)

Mounir Boukadidi

  • Friday 25 February 2022
  • Supervisior: Steven Poelmans


Covid-19 caused a global disruption demonstrated by unprecedented safety measures. The sudden change drove firms to accelerate digitalization as it was key to their business survival. In this thesis, I investigate on why and how covid-19 accelerated transformation of firms? and what lessons, if any, could firms learn for the future? This is relevant because decision makers and policy makers need to understand how firms can be more resilient.
Based on pragmatic interpretivist philosophy, using a mixed methods research, and following the dissertation analytical table approach, three research projects have been designed. I started with a systematic literature review that investigate on what empirical literature informs us on the construct of data and technology I contexts of decision making and crisis?
The second research is an inductive qualitative research conducted during covid-19, using semi structured interviews for data collection. The research yielded a consistent theoretical model that explains what explains digital acceleration. The Analytic Hierarchy Process (AHP) method is used for consistency check.
The third research is a deductive quantitative research that addressed the impact of trust and fear on digital acceleration with mediation of acceptance and use, and moderation of covid-19. Structural Equation Modeling (SEM) technique is used for reliability, validity and significance analysis.
The SLR suggests that technology is linked to technology acceptance to supports firms' cognition through design and communication of information, while acceptance miss a cognitive, social, and a business perspective. The domain of technology and judgement still requires inclusion of dimensions of temporality & urgency in contexts of covid-19. The qualitative research yielded 4 categories that explain acceleration, forming factors for the next study. Each factor is composed of sub-categories representing indicators of the next study.
The quantitative research suggest that digital acceleration is explained by trialability, result demonstrability, attitude towards technology, and behavioral intention. Trust doesn’t affect digital acceleration; however, it affects positively technology adoption. Fear failed test of consistency, and acceptance is explained by advantage, outcome, usefulness, and intrinsic motivation. Covid-19 influence acceptance and moderates the relation between trust and acceptance.
This thesis provides empirical evidence on aspects of digitalization of firms while testing validity of many theories in the context of covid-19. The research addresses a technology problem from a perspective of social science. The research provides empirical evidence on how firms can survive covid-19 through digital acceleration and provides lessons for decision makers and policy makers.

Essays on Innovation Performance - Farid Mammadaliyev (11/02/2022)

Farid Mammadaliyev

  • Friday 11 February 2022 - 5 p.m.
  • Supervisors: Victor Gilsing & Koen Vandenbempt

Essays on Innovation Performance

Technological innovation is crucial for firms’ future success and highly depends on those firms’ ability to continuously discover, develop and commercialize new technologies. Developing new technologies does not only play a vital role in firms’ adaptation to changing competitive environments, but also revolutionizes incessantly the economic structure through destroying the old one. Research by economists and management scholars has long argued and empirically shown that technological innovation is positively associated with superior financial performance. Unsurprisingly, foremost innovative firms are also the most valuable firms by market capitalization.

However, despite the fact that innovation is widely recognized as being crucial for firms’ overall organizational performance, firms still tremendously differ in terms of their innovation performance. Although previous research has endeavored to explain differences in innovation performance with firms’ unique internal organizational attributes (e.g., organizational structure and processes, governance and incentive systems) and environments’ unique characteristics (e.g., market structure, market and technological uncertainty), there is still a need to understand the behavioral perspectives of the variation in innovation performance across different firms. Therefore, in this dissertation we focus on the role of individuals in explaining how firms successfully transform innovation inputs into innovation outputs, which has only marginally been subject to inquiry in the literature until now. By focusing on the behavioral aspects of firms’ innovation performance, we propose and show that strategic choices at top management team level and knowledge recombination at individual invention level have strong implications for ultimate innovation performance.

This dissertation contains three empirical studies. The first study (Chapter 2) focuses on firms’ innovation performance aspirations formed by boundedly rational top managers and their influence on ultimate strategic choices in sourcing technological knowledge, which is important to resolve internal R&D difficulties. The second study (Chapter 3) examines how top managers’ education and experience affect their firms’ alliance portfolio diversity and how this diversity provides implications for these firms’ innovation performance. Finally, the third study (Chapter 4) considers the possibility that differences in innovation performance do not depend only on top managers’ strategic choices, but also on knowledge recombination of individual inventions at lower echelons. Therefore, it focuses on knowledge recombination patterns and endeavors to explain why certain inventions reach bigger audiences compared to others.

Sustainability of maritime supply chain; economic analysis to comply with environmental regulations and social issues - Majid (Seyed Abolfazl) Mohseni (25/01/2022)

Majid (Seyed Abolfazl) Mohseni

  • Tuesday 25 January 2022
  • Supervisors: Thierry Vanelslander & Edwin van Hassel


Maritime transport is considered the most significant transport mode in world trade and maritime trade have risen in recent years, which leads to economic growth. However, at the same time, it causes severe environmental effects that jeopardize the ecosystem and human health. The adverse impacts of the maritime supply chain (MarSC) are not limited to greenhouse gas (GHG) emissions and air pollution, but they include other significant issues such as the spread of invasive species via ballast water, oil spill, chemical and waste management, cargo handling, safety and security at the ports, and noise pollution.

The sustainability of this sector is a challenging issue for the stakeholders involved in this industry. Several aspects are indispensable to enhancing the sustainability of MarSC, grouped as economic, social, and environmental elements. In this thesis, some of the main significant issues in containerized maritime shipping are addressed economically, in which the main objective is to improve the sustainability of MarSC under environmental and social regulations. This Ph.D. covers different segments and stages of the MarSC, including hinterland transport, seawaters, maritime shipping, and port and terminal operations to improve the sustainability of the MarSC at regional, national, and global levels.

The main objective of this Ph.D. is to provide the economic assessment of the most selected and promising technologies and methodologies to overcome the negative impacts of the marine shipping and port industry and bridge some of the available shortcomings. Besides, it will enhance the sustainability of maritime shipping in terms of economic, environmental, and social perspectives concerning the current international conventions and legislations. The overarching research question is: What is the economic impact of sustainability issues on maritime shipping in various trade routes from different stakeholders’ standpoints?

This Ph.D. thesis is based on an application approach, and each one is researched in an independent chapter in which several methodologies are applied to fulfill the objectives and to respond to the key research question. Four main application studies are as follows: economic impact of the instalment of Same Risk Area (SRA) under the Ballast Water Management Convention (BWMC), economic evaluation of alternative technologies to mitigate sulfur emissions, enhancing the supervision of containerized cargo from an economic perspective and supply chain analysis in terms of dry and reefer cargo.

This Ph.D. supports the governments and policy-decision makers by providing the costs and benefits of selected cases of addressing the sustainability of MarSC. Moreover, the outcomes are beneficial for a large groups of maritime stakeholders including port authorities, terminal operators, customs brokers, shipping companies, shippers and academia.