Recent Submissions

  • Patient-level effectiveness prediction modeling for glioblastoma using classification trees (Accepted)

    Geldof, Tine; Van Damme, Nancy; Huys, Isabelle; Van Dyck, Walter (Frontiers in Pharmacology, 2020)
    Little research has been done in pharmacoepidemiology on the use of machine learning for exploring medicinal treatment effectiveness in oncology. Therefore, the aim of this study was to explore the added value of machine learning methods to investigate individual treatment responses for glioblastoma patients treated with temozolomide.
  • Nearest neighbour propensity score matching and bootstrapping for estimating binary patient response in oncology: A Monte Carlo simulation (Accepted)

    Geldof, Tine; Dusan, Popovic; Van Damme, Nancy; Huys, Isabelle; Van Dyck, Walter (Scientific Reports: A Nature Research Journal, 2020)
  • A 2020 perspective on the building of online trust in e-business relationships (Accepted)

    Stouthuysen, Kristof (Electronic Commerce Research and Applications, 2020)
    Perhaps the most important trend we observe in an increasing digitalized landscape, is that the internet technology allows organizations and individuals to interact across the globe. More and more organizations, both start-ups and more mature ones, ranging from retail to healthcare to energy, from public to private institutions are aware about the possibilities of extending their services outside their walled offices and physical points of contacts. E-consumers also seem more satisfied with the possibility to interact and transact with organizations without the constraints of time and space.
  • From one-class to two-class classification by incorporating expert knowledge: Novelty detection in human behaviour (Published Online)

    Oosterlinck, Dries; Benoit, Dries F.; Baecke, Philippe (European Journal of Operational Research, 2019)
    One-class classification is the standard procedure for novelty detection. Novelty detection aims to identify observations that deviate from a determined normal behaviour. Only instances of one class are known, whereas so called novelties are unlabelled. Traditional novelty detection applies methods from the field of outlier detection. These standard one-class classification approaches have limited performance in many real business cases. The traditional techniques are mainly developed for industrial problems such as machine condition monitoring. When applying these to human behaviour, the performance drops significantly. This paper proposes a method that improves existing approaches by creating semi-synthetic novelties in order to have labelled data for the two classes. Expert knowledge is incorporated in the initial phase of this data generation process. The method was deployed on a real-life test case where the goal was to detect fraudulent subscriptions to a telecom family plan. This research demonstrates that the two-class expert model outperforms a one-class model on the semi-synthetic dataset. In a next step the model was validated on a real dataset. A fraud detection team of the company manually checked the top predicted novelties. The results show that incorporating expert knowledge to transform a one-class problem into a two-class problem is a valuable method.
  • De zorgkostenstructuur kan veel scherper

    Roodhooft, Filip (Management Scope, 2019)
    Zorginstellingen kunnen bijdragen aan het tegengaan van stijgende zorgkosten. Feit is dat bijdragen vanuit overheid en verzekeraars niet veel zullen en kunnen stijgen: de grens is wat dat betreft bereikt. Filip Roodhooft van Vlerick Business School pleit voor slimme oplossingen in de zorg.
  • The risk implications of diversification: Integrating the effects of product and geographic diversification (Published Online)

    Mammen, Jan; Alessandri, Todd; Weiss, Martin (Long Range Planning, 2019)
    The risk implications of product diversification have received considerable attention from scholars. However, our understanding of the effects of geographic diversification on risk is more limited. Relying on resource-based theory to frame our arguments, we argue that despite some similarities, the two types of diversification have differing effects on firm risk. We first establish the risk reducing effects for product diversification. We then integrate the unique aspects of geographic diversification that serve as a boundary condition to the RBV perspective, arguing for the risk increasing effects of geographic diversification. Finally, since many firms pursue both forms of diversification simultaneously, we explore the joint effects of both product and geographic diversification. We test our hypotheses in a longitudinal model on a sample of S&P 500 firms. Our findings suggest that total product diversification, as well as related diversification reduce risk, while total geographic diversification increases risk. Furthermore, our data provide evidence of a complex combination of joint effects of these two forms of diversification. These findings offer a more complete understanding of the risk effects of corporate diversification.
  • Imitation of management practices In supply networks: Relational and environmental effects (Published Online)

    Reusen, Evelien; Stouthuysen, Kristof; Van den Abbeele, Alexandra; Slabbinck, Hendrik (Journal of Supply Chain Management, 2019)
    This study investigates the imitative use of management practices across a multitier supply network. Although imitation may take the form of any management practice, operationally, we focus on whether the buyer's control practices used with first‐tier suppliers results in similar control practices being used by these first‐tier suppliers with the second‐tier suppliers. Drawing on institutional theory, we identify relational context (i.e., affective commitment) and environmental context (i.e., environmental uncertainty) as two important factors influencing the extent to which such imitation takes place. Using unique survey data of vertically linked supply chain triads, we generally find support for the occurrence of imitation and more so in cases of high affective commitment. The results regarding environmental uncertainty further reveal selectivity in imitative behavior, calling attention to the level of deliberateness in imitation decisions in supply networks. Besides contributing to theory on imitative behaviors in the supply chain, this study also generates practical implications on the spread of management practices across multiple tiers.
  • Partner selection decisions in interfirm relationships: The mimetic trust effect (Accepted)

    Reusen, Evelien; Stouthuysen, Kristof (Accounting, Organizations and Society, 2019)
  • Outcomes of team creativity: A person-environment fit perspective

    Bam, Louzanne; De Stobbeleir, Katleen; Vlok, PJ (Management Research Review, 2019)
    Limited research where team creativity (TC) is positioned as an independent variable constitutes a weak point in the body of knowledge. This paper aims to offer three contributions to address this research gap: empirical research that has been conducted on the outcomes of TC is summarized; a person–environment fit perspective is applied to develop a conceptual model for TC; and directions for future empirical research are proposed. A literature review is conducted to identify empirical research on the outcomes of TC. This is summarized into an extension of an existing framework that organizes empirical research on the antecedents of TC. Furthermore, the fit model for TC is developed, based on a person–environment fit perspective. Research on the outcomes of TC has focused on three themes: performance; affective state; and processes. Gaps in this body of knowledge include limited knowledge on performance outcomes and a lack of research on potential negative outcomes. Recommendations for future research include: potential moderators of the relationship between TC and two outcome, innovation and team performance, are proposed; strain and unethical decision-making are proposed as potential negative outcomes of TC; and it is proposed that incorporating a temporal dimension would improve the understanding of the cyclical manner in which certain variables and TC may interact over time. he organizing framework extension summarizes existing knowledge on the outcomes of TC, and together with the fit model for TC, this offers a basis for identifying research gaps and directions for future research. Specific directions for future empirical research are proposed.
  • When holding in prevents from reaching out: Emotion suppression and social support-seeking in multicultural groups (Published Online)

    Boros, Smaranda; Van Gorp, Lore; Boiger, Michael (Frontiers in Psychology: Organizational Psychology, 2019)
    Members of multicultural groups benefit from developing diverse social support networks. Engaging openly with people who have a different worldview (i.e., given by a different cultural background) broadens one’s cognitive horizons, facilitates one’s adaptation to new contexts, decreases stereotyping and discrimination and generally improves individual and group performance. However, if this social connection is hindered (either by limiting the number of people one reaches out to or in terms of preferring to connect to similar others), then the diversity advantage is lost – both for the individuals and for the groups. Through two case studies of professional groups with varying cultural diversity (moderate and superdiverse), we investigate the evolution of their members’ social support networks (i.e., to what extent and to whom they reach out for support) depending on (1) individuals’ habitual emotion suppression and (2) cultural orientation on the individualism-collectivism dimension. Results show that individualistic cultures suffer a double-whammy: when suppressing, their members seek less support (i.e., don’t reach out so much to ask for support) and tend to seek culturally similar others for it when they do. Suppressing collectivists are less affected in absolute levels of connectedness, but still prefer culturally similar others as sources of support. Our study offers an emotion-based view of why people stick together with similar others in diverse groups and how learning to better cope with emotions can make us more open-minded towards diversity in professional settings.
  • Negatieve feedback leidt zelden tot verbetering

    Van Steerthem, Angie (HR Magazine, 2019)
    Kritische beoordelingen van collega's zetten medewerkers ertoe aan hun rol aan te passen, zodat ze meer kunnen samenwerken met wie hen positievere beoordelingen geeft. Hoe negatiever de feedback, hoe verder de werknemers gaan om nieuwe netwerken te smeden. Dat blijkt uit onderzoek van Paul Green, doctoraatsstudent aan de Harvard Business School en twee van zijn collega’s. Het onderzoek werd onder meer gevoerd in een bedrijf dat een transparant peerreviewproces hanteert en de medewerkers toelaat hun job voor een stuk zelf vorm te geven.
  • De economie van morgen. Wat met de wendbaarheid van onze werkgevers en werknemers?

    Van Steerthem, Angie; Baeten, Xavier (Over.Werk, 2019)
    Tijdens de voorbije beleidscyclus zette het arbeidsmarktbeleid in op het voorzien van de langetermijnrandvoorwaarden die moeten toelaten dat werknemers en bedrijven opportuniteiten zien en initiatief nemen in onze huidige veranderende economische context. De overheid investeerde in een innovatiecultuur en in een waardengedreven beleid ter voorbereiding op de economie van morgen. Om dat te verwezenlijken linkte de Vlaamse Regering een aantal hefbomen aan een reeks kernwaarden (Vlaamse Regering, 2014) zoals wendbaarheid, duurzaamheid met een focus op de lange termijn en op transparantie, responsabilisering van individuen en organisaties, klantgerichtheid en zorg voor de werknemer en maatwerk. Vanuit eigen onderzoek binnen het Vlerick Centre for Excellence in Strategic Rewards gaan we dieper in op elk van de vermelde kernwaarden en wat deze betekenen voor een beloningsbeleid gericht op het stimuleren van wendbaarheid en innovatie binnen bedrijven én bij medewerkers.
  • Zo worden overheidsinvesteringen een succes

    Manigart, Sophie; Standaert, Thomas (Management Scope, 2019)
    Overheden kunnen met investeringen het verschil maken voor bedrijven met groeipotentie, betogen Sophie Manigart en Thomas Standaert van Vlerick Business School. Zij ontleden vier modellen voor overheidsinvesteringen en pleiten voor een proactieve overheid met een hands-off-mentaliteit.
  • Book highlight - Setting a clear strategic direction

    Verweire, Kurt; Letens, Geert; De Prins, Peter (Global Business and Organizational Excellence Journal, 2019)
    It is important to have an inspiring change vision, an ambition to create a future that is better than what exists now. It is equally important to translate that aspiration into a well-defined direction and strategy. An aspiration without a strategy is little more than a dream. In too many organizations, the“how”of change is often as unclear as the“why”of change.
  • A decomposed branch-and-price procedure for integrating demand planning in personnel staffing problems

    Van Den Eeckhout, Mick; Vanhoucke, Mario; Maenhout, Broos (European Journal of Operational Research, 2020)
    Project staffing with discrete time/resource trade-offs and calendar constraints. • A cut-branch-and-price procedure is proposed. Decomposition into subproblems with a specific staffing composition. Dedicated cuts include personnel information in the workload pricing problem. The personnel staffing problem calculates the required workforce size and is determined by constructing a baseline personnel roster that assigns personnel members to duties in order to cover certain staffing requirements. In this research, we incorporate the planning of the duty demand in the staff scheduling problem in order to lower the staffing costs. More specifically, the demand originates from a project scheduling problem with discrete time/resource trade-offs, which embodies additional flexibility as activities can be executed in different modes. In order to tackle this integrated problem, we propose a decomposed branch-and-price procedure. A tight lower and upper bound are calculated using a problem formulation that models the project scheduling constraints and the time-related resource scheduling constraints implicitly in the decision variables. Based upon these bounds, the strategic problem is decomposed into multiple tactical subproblems with a fixed workforce size and an optimal solution is searched for each subproblem via branch-and-price. Fixing the workforce size in a subproblem facilitates the definition of resource capacity cuts, which limit the set of eligible project schedules, decreasing the size of the branching tree. In addition, in order to find the optimal integer solution, we propose a specific search strategy based upon the lower bound and dedicated rules to branch upon the workload generated by a project schedule. The computational results show that applying the proposed search space decomposition and the inclusion of resource capacity cuts lead to a well-performing procedure outperforming different other heuristic and exact methodologies.
  • A statistical method for estimating activity uncertainty parameters to improve project forecasting

    Vanhoucke, Mario; Batselier, Jordy (Entropy, 2019)
    Just like any physical system, projects have entropy that must be managed by spending energy. The entropy is the project’s tendency to move to a state of disorder (schedule delays, cost overruns), and the energy process is an inherent part of any project management methodology. In order to manage the inherent uncertainty of these projects, accurate estimates (for durations, costs, resources, …) are crucial to make informed decisions. Without these estimates, managers have to fall back to their own intuition and experience, which are undoubtedly crucial for making decisions, but are are often subject to biases and hard to quantify. This paper builds further on two published calibration methods that aim to extract data from real projects and calibrate them to better estimate the parameters for the probability distributions of activity durations. Both methods rely on the lognormal distribution model to estimate uncertainty in activity durations and perform a sequence of statistical hypothesis tests that take the possible presence of two human biases into account. Based on these two existing methods, a new so-called statistical partitioning heuristic is presented that integrates the best elements of the two methods to further improve the accuracy of estimating the distribution of activity duration uncertainty. A computational experiment has been carried out on an empirical database of 83 empirical projects. The experiment shows that the new statistical partitioning method performs at least as good as, and often better than, the two existing calibration methods. The improvement will allow a better quantification of the activity duration uncertainty, which will eventually lead to a better prediction of the project schedule and more realistic expectations about the project outcomes. Consequently, the project manager will be able to better cope with the inherent uncertainty (entropy) of projects with a minimum managerial effort (energy).
  • Flexible multivariate hill estimators (Accepted)

    Dominicy, Yves; Heikkilä, Matias; Ilmonen, Pauliina; Veredas, David (Journal of Econometrics, 2019)
    Dominicy et al. (2017) introduce a family of Hill estimators for elliptically distributed and heavy tailed random vectors. They propose to use the univariate Hill to a norm of order of the data. The norms are homogeneous functions of order one. We show that the family of estimators can be generalized to homogeneous functions of any order and, more importantly, that ellipticity is not required. Only multivariate regular variation is needed, as it is preserved under well-behaved homogeneous functions. This enables us to have flexibility in terms of the estimator and the underlying distribution. Consistency and asymptotic normality are shown, and a Monte Carlo study is conducted to assess the finite sample properties under different asymmetric and heavy tailed multivariate distributions. We illustrate the estimators with an application to 10 years of daily data of paid claims from property insurance policies across 15 regions of Belgium.
  • Comparison and classification of flexible distributions for multivariate skew and heavy-tailed data

    Babic, Sladana; Ley, Christophe; Veredas, David (Symmetry, 2019)
    We present, compare and classify popular families of flexible multivariate distributions. Our classification is based on the type of symmetry (spherical, elliptical, central symmetry or asymmetry) and the tail behaviour (a single tail weight parameter or multiple tail weight parameters). We compare the families both theoretically (relevant properties and distinctive features) and with a Monte Carlo study (comparing the fitting abilities in finite samples).
  • Fostering multidisciplinary collaboration in drug discovery

    Erden, Zeynep; Ben-Menahem, Shiko; von Krogh, Georg; Schneider, Andreas; Koch, Guido; Widmer, Hans (Drug Discovery World, 2019)
    Drug discovery teams combine specialists with in-depth knowledge from a variety of scientific disciplines. Such diversity in thought worlds poses a challenging exercise in cross-disciplinary collaboration and project coordination. Based on a longitudinal field study of five projects in a leading pharmaceutical company we present a framework outlining the conditions for effective cross-disciplinary collaboration in drug discovery teams. We show that knowledge creation in multidisciplinary teams relies on a combination of formal team structures and informal co-ordination practices. Formal team structures set the boundary conditions for cross-disciplinary co-ordination. Within their boundaries self-managed sub-teams draw on informal co-ordination practices involving cross-disciplinary anticipation, synchronization and triangulation to overcome knowledge boundaries and high uncertainty. We identify five key insights and two questions which are important for managers to consider for fostering multidisciplinary collaboration in drug discovery.
  • Choice for entrepreneurial career: Do cognitive styles matter? (Published Online)

    Deprez, Jana; Cools, Eva; Robijn, Wouter; Euwema, Martin (Entrepreneurship Research Journal, 2019)
    Upon graduation, students make the decision to either become an entrepreneur or an employee. Numerous studies have thus investigated personal and environmental factors that impact this decision. As cognitive styles have become more and more important in determining individual and organisational behaviour, and as they are presumed to provide new valuable insights over and above other personal factors, they provide the ideal focus to further explore this career choice. In this article, we aim to explore how creating, planning, and knowing cognitive style relate to entrepreneurial attitudes, intentions, and career choices. Using the Theory of Planned Behaviour, in a first sample, we investigate the direct and indirect impact that cognitive styles have on entrepreneurial intention through attitudes. In our second sample, we look at how career preferences for entrepreneurship or a more traditional career as an employee are affected by cognitive styles. Using structural equation modelling analysis, this study finds evidence for the importance of creating cognitive style on entrepreneurial outcomes. Additionally, we find evidence for the relationship between planning cognitive style and wanting to be an employee. Knowing style does not lead to either preference. This paper extends the current knowledge on cognitive styles and entrepreneurship by analysing the impact of other cognitive styles than the predominantly used innovative styles and by also exploring its impact on important antecedents of entrepreneurial intentions, such as entrepreneurial attitude and career preferences.

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