• A simulation analysis of interactions between errors in costing system design

      Labro, Eva; Vanhoucke, Mario (Vlerick Business School, 2005)
      The academic accounting literature has established that the conditions under which costing systems in general and Activity Based Costing (ABC) in particular provide accurate costs are very stringent. Less is known, however, about the nature, level and bias of costing errors and their interactions, when these conditions are not met. The main problem to overcome to enable us to learn about these is the notion of the unobservable true cost benchmark to which to compare the costing system approximation. This paper presents a simulation method to deal with this problem, allowing a variety of research questions in this research area to be addressed with more generalizable answers. Using our methodology, we test a variety of hypotheses on the interaction between various errors in costing system design that were developed in the previous analytical, empirical, and practitioner literature. We also provide some interesting new insights on interactions between errors that were previously not discussed in the literature. This paper presents new results on (1) conditions under which partial refinement in costing systems does or does not work to improve overall accuracy, (2) the contexts in which it is most effective to correct a particular type of error in terms of improving overall accuracy and (3) indicators of robustness or sensitivity of costing system designs to errors. In doing so, we also provide insights relevant to practitioners, costing system designers and users of costing information alike. Keywords: costing system design, costing accuracy, simulation, costing errors
    • A simulation and evaluation of earned value metrics to forecast the project duration

      Vanhoucke, Mario; Vandevoorde, Stephan (Vlerick Business School, 2005)
      It is well-known that well managed and controlled projects are more likely to be delivered on time and within budget. The construction of a (resource-feasible) baseline schedule and the follow-up during execution are primary contributors to the success or failure of a project. Earned value management systems have been set up to deal with the complex task of controlling and adjusting the baseline project schedule during execution. Although earned value systems have been proven to provide reliable estimates for the follow-up of cost performance, it often fails to predict the total duration of the project. In this paper, we extensively review the existing methods to forecast the total project duration. Moreover, we investigate the potential of a newly developed method, the earned schedule method, which makes the connection between earned value metrics and the project schedule. We present an extensive simulation study where we carefully control the level of uncertainty in the project, the influence of the project network structure on the accuracy of the forecasts, and the time horizon where the newly developed measures provide accurate and reliable results. Keywords: Earned value, earned duration, earned schedule, CPM
    • A Typology of Plants in Global Manufacturing Networks

      Vereecke, Ann; Van Dierdonck, Roland; De Meyer, Caroline (INSEAD Global Leadership Center, 2002)
    • ABS, MBS and CDO compared: an empirical analysis

      Vink, Dennis; Thibeault, André (2008)
    • Access decision-making in the Belgian Commission for reimbursement of medicines 2010-2017: Investigating the readiness for value-based pricing

      Van Dyck, Walter; Schoonaert, Lies; Geldof, Tine; Govaerts, Laurenz (2018)
      To balance the societal need for affordability of medicines with the industrial need for sustained innovation, the present pharmaceutical technology supply-driven system needs to become a societal demand-driven system. Value-based pricing is considered to be a key component of such a system, next to the conditional dialogue between payer and industry we proposed in previous work (Van Dyck, De Grève et al. 2016) in which it should be embedded. To find out how far Belgian pharmaceutical healthcare-related decision-making has evolved within this paradigm, we empirically investigated the access and reimbursement decision-making of the Belgian Commission for Reimbursement of Medicines (CRM) for the period 2010 – 2017. We combined this investigation with previous work in a meta-analysis in order to have the most complete picture possible of the present factors influencing decision-making in the Belgian system.
    • Acquisitions as a Real Options bidding game

      De Maeseneire, Wouter; van den Berg, Ward; Smit, Han (UGent, Fac. Economie & Bedrijfskunde, 2005)
    • Acquisitions as a Real Options bidding game

      De Maeseneire, Wouter; van den Berg, Ward; Smit, Han (Tinbergen institute, 2004)
    • Adaptive leadership: Shape your path through turbulence

      De Stobbeleir, Katleen; Peeters, Carine; Pfisterer, Matthias; Muylle, Steve (2019)
      The findings of the study are described in the white paper ‘Adaptive Leadership: shape your path through turbulence’. With the aim of providing practical relevance, the white paper also offers concrete examples from the corporate world to help other organisations and their leaders reflect on how to boost adaptiveness. One of the elements is a checklist that gives leaders recommendations on how to strengthen their adaptive leadership behaviour.
    • Agency and similarity effects and the VC's attitude towards academic spin-out investing

      Knockaert, Mirjam; Clarysse, Bart; Wright, Mike; Lockett, Andy (2008)
    • Agency, strategic entrepreneurship and the performance of private equity backed buyouts

      Meuleman, Miguel; Amess, K.; Wright, Mike; Scholes, L. (2008)
    • Alternative methodologies in studies on business failure: do they produce better results than the classic statistical methods?

      Balcaen, Sofie; Ooghe, Hubert (Vlerick Business School, 2004)
      Over the last 35 years, the topic of company failure prediction has developed to a major research domain in corporate finance. Academic researchers from all over the world have been developing a gigantic number of corporate failure prediction models, based on various types of modelling techniques. Besides the classic cross-sectional statistical methods, which have produced numerous failure prediction models, researchers have also been using several alternative methods for analysing and predicting business failure. To date, a clear overview and discussion of the application of alternative methods in corporate failure prediction is still lacking. Moreover, frequently, different designations or names are used for one method. Therefore, this study aims to provide a clear overview of the alternative research methods, attributing each of them a fixed designation. More in particular, this paper extensively elaborates on the most popular methods of survival analysis, machine learning decision trees and neural networks. Furthermore, it discusses several other alternative methods, which can be considered to have a certain value added in the empirical literature on business failure: the fuzzy rules-based classification model, the multi-logit model, the CUSUM model, dynamic event history analysis, the catastrophe theory and chaos theory model, multidimensional scaling, linear goal programming, the multi-criteria decision aid approach, rough set analysis, expert systems and self-organizing maps. This paper discusses the main features of these methods and their specific assumptions, advantages and disadvantages and it gives an overview of a number of academically developed corporate failure prediction models. Several issues viewed in isolation by earlier studies are here considered together, which is of major importance for gaining a clear insight into the possible alternative methods of corporate failure modelling and their corresponding features. A second aim of this paper is to find an answer to the question whether the more sophisticated, alternative modelling methods produce better performing failure prediction models than the rather simple classic statistical methods. The analysis of the conclusions of a large number of empirical studies comparing the classification results and/or the prediction abilities of failure prediction models based on different techniques seems to indicate that we may question the benefits to be gained from using the more sophisticated alternative methods.
    • An assessment of government funding of business angel networks: a regional study

      Collewaert, Veroniek; Manigart, Sophie; Aernoudt, Rudy (2007)
    • An Assessment of Validity in Small Business and Entrepreneurship Research

      Buelens, Marc; Bouckenooghe, Dave; De Clercq, Dirk; Willem, Annick (UGent, Fac. Economie & Bedrijfskunde, 2005)
    • An efficient hybrid search algorithm for various optimization problems

      Vanhoucke, Mario (2006)
      This paper describes a detailed study of a recursive search algorithm for different optimization problems. Although the algorithm has been originally developed for a project scheduling problem with financial objectives, we show that it can be extended to many other application areas and therefore, can serve as a sub-procedure for various optimization problems. The contribution of the paper is threefold. First, we present a hybrid recursive search procedure for the project scheduling problem with net present value maximization and compare it with state-of-the-art procedures by means of computational tests. Second, we show how the procedure can be adapted to two other application areas: project scheduling with work continuity minimization and the open pit mining problem. Last, we highlight some future research areas where this hybrid procedure might bring a promising contribution.
    • An electromagnetism meta-heuristic for the nurse scheduling problem

      Maenhout, Broos; Vanhoucke, Mario (Vlerick Business School, 2005)
      In this paper, we present a novel meta-heuristic technique for the nurse scheduling problem (NSP). This well-known scheduling problem assigns nurses to shifts per day taking both hard and soft constraints into account. The objective is to maximize the preferences of the nurses and to minimize the total penalty cost from violations of the soft constraints. The problem is known to be NP-hard. Due to its complexity and relevance, many algorithms have been developed to solve practical, and often case-specific versions of the NSP. The enormous amount of different constraints has led to an overwhelming amount of exact and meta-heuristic procedures, and hence comparison and state-of-the-art reporting of standard results seem to be a utopian idea. The contribution of this paper is twofold. First, we present a meta-heuristic procedure for the NSP based on the framework proposed by Birbil and Fang (2003). The Electromagnetic (EM) approach is based on the theory of physics, and simulates attraction and repulsion of sample points in order to move towards a promising solution. Second, we present computational experiments on a standard benchmark dataset, and solve problem instances under different assumptions. We show that our procedure performs consistently well under many different circumstances, and hence, can be considered as robust against case-specific constraints. Keywords: meta-heuristics, electromagnetism, nurse scheduling
    • An electromagnetism Meta-Heuristic for the Resource-Constrained Project Scheduling Problem

      Debels, Dieter; Vanhoucke, Mario (UGent, Fac. Economie & Bedrijfskunde, 2004)