Recent Submissions

  • A social-psychological perspective on angel investment decision-making

    Imhof, Zoë (2020)
    Academics and practitioners have all often claimed that acquiring resources is a challenging task that entrepreneurs need to overcome to develop their ventures (e.g., Stinchcombe, 1965). This challenge is particularly acute for young, high-growth potential ventures because they often involve unproven technologies or business models (e.g., Berger & Udell, 1998). Angel investors are a primary source of early-stage (i.e., seed and startup) risk capital available to such entrepreneurs, and tend to come in after entrepreneurs have depleted their personal savings and money from family and friends (e.g., Drover et al., 2017). Many highly successful companies such as Zoom, Airbnb, Google, Starbucks, The Body Shop, Innocent Smoothies, and Showpad have all been backed by angels. The pitch represents a critical first step towards raising interest among angel investors and securing much-needed funding (e.g., Chen et al., 2009; Kanze, Huang, Conley, & Higgins, 2018; Maxwell, Jeffrey, & Lévesque, 2011). The pitch is a decisive moment in entrepreneurs' quest for money as investors reject 70 to 90 percent of pitches (e.g., Chen et al., 2009; Huang & Pearce, 2015; Maxwell et al., 2011). This dissertation contributes to the growing stream of research that examines angels' investment decision-making. By drawing on theories from social psychology literature, this dissertation seeks to offer a more relational perspective to explore how angels judge entrepreneurs during their pitch and how angel and entrepreneur interact with each other during their first face-to-face meeting. The first paper of this dissertation focuses on the impact of angel's judgment about the entrepreneur on their decision to invest at the end of the pitching phase (i.e., after Q&A session), the second paper focuses on explaining why angels lose interest to invest within the pitching phase (from after the presentation to after the Q&A session) and the third paper focuses on the social interaction between entrepreneur and angel during the Q&A session. More specifically, building on social judgment research and resource allocation theory, the first study explores entrepreneur's warmth and competence as two critical dimensions along which angels perceive and judge entrepreneurs when making investment decisions and how angels' mental resources explain the interplay between perceived warmth, perceived competence and pitch sequence. The second study builds on the Elaboration Likelihood Model as dual-process theory to examine the impact of angel's experience and entrepreneur's verbal and nonverbal behavior on angel's likelihood to lose interest to invest from the presentation to after the Q&A session. In the third study examines the impact of angel's power words when asking questions on entrepreneur's answers.
  • Distressed M&A and the role of m&a in corporate restructuring

    Bruyland, Evy (2013)
    The global financial and economic crisis have led to a moderation in global M&A activity. The large M&A deals have disappeared and deal volume has fallen. Nonetheless, M&A remains a core part of business growth. Firms continue to look for acquisitions that allow them to capture a new customer base, technologies and products, access new markets and increase market share. While some years ago the M&A market was characterized by growing firms with a healthy track record, transactions involving distressed firms are increasing. Many investors, managers, advisors and academics are familiar with traditional mergers and acquisitions but little is known about distress-related M&A. However the surge in restructurings and failures has marked the M&A landscape and triggered a growing interest in these type of transactions. The practitioner-oriented and academic literature provide us with some insights but the risks and benefits of such transactions remain largely ambiguous. The goal of this dissertation is to increase our understanding of transactions involving troubled firms.
  • Advanced analytics in pharmaceutical innovation: The use of real-world evidence in oncology

    Geldof, Tine (2019)
    The smart use of real-world evidence (RWE) is known to enable more flexible forms of access to novel medicines. This flexibility may be especially promising for targeted cancer medicines, which often do not align with the traditional approach to medicinal development, and for which therapeutic innovation (i.e. favourable and clinically significant benefits at an affordable price) in routine clinical practice is becoming ever more difficult to achieve due to its highly complex nature. Amongst others, RWE should include information on the performance of those medicines for every individual patient. However, the current estimation of this patientlevel performance using conventional methods from pharmaceutical and medical sciences is challenging. This is because these methods are unable to derive causal conclusions on medicinal performance from the complex real-world environment, as opposed to controlled and randomised clinical trial settings. Simultaneously, the increasing emergence of novel medicines, and their promising combined effects are now creating a new combinatorial complexity level on the captured data. At the same time, new and advanced analytical methods within the field of data science are continuously being developed and have recently been applied to pharmaceutical and medical research, including the domain of pharmacoepidemiology. These powerful methods include techniques such as machine learning and Bayesian approaches, both being recognised as having a transformative potential in clinical research and practice. Specifically, they may be used to gain new insights into the patient-level performance of novel medicines in the messy real world, thereby providing a better understanding of RWE. In doing so, studies may generate new hypotheses through the exploration of data sets, or test existing hypotheses prespecified during prior clinical research. In this dissertation, I present the specific methods of advanced analytics to unravel the complexity of RWE , therefore, increasing our understanding of the individual performance of cancer treatments. These methods are investigated for their use in both hypothesis generation (part 1) and hypothesis testing (part 2) studies. A general ntroduction into the field is provided in Chapter 1, followed by the research objectives. In Chapter 2, I validate the use of an advanced modelling technique, i.e. machine learning, as a personal performance prediction model for glioblastoma. Optimisations of this model to be used on novel medicines in more complex situations are proposed in Chapter 3. In Chapter 4, the importance of multi-product RWE assessments is explored, for which hypotheses. Lastly, for these investigated analytics to become useful in healthcare, the need for an insight-providing federated network is introduced in Chapter 6. Chapter 7, the last chapter of this dissertation, presents a general conclusion with discussion of the research contributions.
  • Topics in financial economics

    Matthys, Thomas (2018)
  • Der Realoptionsansatz als Controllinginstrument in jungen Wachstumsunternehmen

    Fehre, Kerstin (2007)
    Auf der Basis des Rationalitätssicherungsansatzes untersucht Kerstin H. Faaß die controllingrelevanten Merkmale von JWU sowie die Anforderungen an ein Controllinginstrument in JWU und nimmt anschließend eine umfassende Kosten- und Nutzenanalyse des Realoptionsansatzes vor. Sie leitet einen Handlungsleitfaden für die stufenweise Anwendung des Ansatzes ab und zeigt Möglichkeiten zur Nutzung des Wertbeitrages des Realoptionsansatzes als Controllinginstrument in JWU auf.
  • Three essays on competition policy and innovation incentives

    Kleer, Robin (2009)
    This thesis deals with the economics of innovation. In a general introduction we illustrate how several aspects of competition policy are linked to firms’ innovation incentives. In three individual essays we analyze more specific issues. The first essay deals with interdependencies of mergers and innovation incentives. This is particularly relevant as both topics are central elements of a firm’s competitive strategy. The essay focuses on the impact of mergers on innovative activity and competition in the product market. Possible inefficiencies due to organizational problems of mergers are accounted for. We show that optimal investment strategies depend on the resulting market structure and differ significantly from insider to outsider. In our linear model mergers turn out to increase social surplus. The second essay analyzes the different competitive advantages of large and small firms in innovation competition. While large firms typically have a better access to product markets, small firms often have a superior R&D efficiency. These distinct advantages immediately lead to the question of cooperations between firms. In our model we allow large firms to acquire small firms. In a pre-contest acquisition game large firms bid sequentially for small firms in order to combine respective advantages. Innovation competition is modeled as a patent contest. Sequential bidding allows the first large firms to bid strategically to induce a reaction of its competitor. For high efficiencies large firms prefer to acquire immediately, leading to a symmetric market structure. For low efficiencies strategic waiting of the first large firm leads to an asymmetric market structure even though the initial situation is symmetric. Furthermore, acquisitions increase the chances for successful innovation. The third essay deals with government subsidies to innovation. Government subsidies for R&D are intended to promote projects with high returns to society but too little private returns to be beneficial for private investors. Apart from the direct funding of these projects, government grants may serve as a signal of good investments for private investors. We use a simple signaling model to capture this phenomenon and allow for two types of risk classes. The agency has a preference for high risk projects as they promise high expected social returns, whereas banks prefer low risk projects with high private returns. In a setup where the subsidy can only be used to distinguish between high and low risk projects, government agency’s signal is not very helpful for banks’ investment decision. However, if the subsidy is accompanied by a quality signal, it may lead to increased or better selected private investments. The last chapter summarizes the main findings and presents some concluding remarks on the results of the essays
  • Transforming government: The way towards digital era governance

    Danneels, Lieselot (2017)
    The aim of this research chair is to conduct scientific research on the possibilities for the digitization of public services. This includes research into innovation of business processes, services and service models within digital ecosystems for public services.
  • Salespeople are from Mars, Purchasers are from Venus: matching sales to purchasing

    Paesbrugghe, Bert (2017)
    There is no business without sales and no sales without customers. The bridge that spans business‐to‐business (B2B) selling and their customers is termed a buyer‐seller relationship. The contemporary buyer‐seller environment presents salespeople with the challenge of finding ways to overcome the current ineffectiveness of many previously effective sales approaches. The effectiveness of many sales approaches has been questioned based on the ongoing paradigm shift in the purchasing domain. Purchasing based changes have had, and are expected to continue to have a tremendous influence on the buying process. Yet, the different roles in buyer‐seller relationships are, in the Marketing and Sales domain, either studied from the buyer’s perspective or from the seller’s point of view. Buying organizations, however, are gradually shifting power to the purchasing function. For sales practitioners and sales researchers, this ongoing shift demands a study in the evolution of the purchasing function in order to improve their sales approaches. This doctoral thesis analyzes the domain of Buyer‐Seller Relationships in B2B contexts, with an emphasis on Personal Selling and Sales Management. The objective of this dissertation is to obtain a better understanding of how changes in market conditions and advances in technology have empowered the B2B purchaser, thereby creating new challenges to the sales organization and sales function. The first essay of this dissertation is based on an extensive review of the Buyer‐Seller literature and is a call to sales practitioners to pay more attention to the purchasing function and to develop sales strategies.

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