• A closer look at the productivity advantage of foreign affiliates

      De Backer, Koen; Sleuwaegen, Leo (International Journal of the Economics of Business, 2005)
    • A closer view at the patient surgery planning and scheduling problem: A literature review

      Samudra, Michael; Demeulemeester, Erik; Cardoen, Brecht (Review of Business and Economic Literature, 2013)
    • A comparative study of Artificial Intelligence methods for project duration forecasting

      Wauters, Mathieu; Vanhoucke, Mario (Expert Systems with Applications, 2016)
      This paper presents five Artificial Intelligence (AI) methods to predict the final duration of a project. A methodology that involves Monte Carlo simulation, Principal Component Analysis and cross-validation is proposed and can be applied by academics and practitioners. The performance of the AI methods is assessed by means of a large and topologically diverse dataset and is benchmarked against the best performing Earned Value Management/Earned Schedule (EVM/ES) methods. The results show that the AI methods outperform the EVM/ES methods if the training and test sets are at least similar to one another. Additionally, the AI methods report excellent early and mid-stage forecasting results. A robustness experiment gradually increases the discrepancy between the training and test sets and demonstrates the limitations of the newly proposed AI methods.
    • A comparison and hybridization of crossover operators for the nurse scheduling problem

      Maenhout, Broos; Vanhoucke, Mario (Annals of Operations Research, 2007)
    • A comparison of different project duration forecasting methods using earned value metrics

      Vandevoorde, Stephan; Vanhoucke, Mario (2005)
      Earned value project management is a well-known management system that integrates cost, schedule and technical performance. It allows the calculation of cost and schedule variances and performance indices and forecasts of project cost and schedule duration. The earned value method provides early indications of project performance to highlight the need for eventual corrective action. Earned value management was originally developed for cost management and has not widely been used for forecasting project duration. However, recent research trends show an increase of interest to use performance indicators for predicting total project duration. In this paper, we give an overview of the state-of-the-art knowledge for this new research trend to bring clarity in the often confusing terminology. The purpose of this paper is three-fold. First, we compare the classic earned value performance indicators SV & SPI with the newly developed earned schedule performance indicators SV(t) & SPI(t). Next, we present a generic schedule forecasting formula applicable in different project situations and compare the three methods from literature to forecast total project duration. Finally, we illustrate the use of each method on a simple one activity example project and on real-life project data. Keywords: Earned value, earned duration, earned schedule, project duration forecasting
    • A comparison of different project duration forecasting methods using earned value metrics

      Vandevoorde, Stephan; Vanhoucke, Mario (International Journal of Project Management, 2006)
    • A comparison of financial duration models via density forecast

      Bauwens, Luc; Giot, Pierre; Grammig, Joachim; Veredas, David (International Journal of Forecasting, 2004)
    • A comparison of priority rules for the job shop scheduling problem under different flow time- and tardiness-related objective functions

      Sels, Veronique; Gheysen, Nele; Vanhoucke, Mario (International Journal of Production Research, 2012)
    • A comparison of state-of-the-art classification techniques for expert automobile insurance claim fraud detection

      Viaene, Stijn; Derrig, Richard A.; Baesens, Bart; Dedene, Guido (+) (Journal of Risk and Insurance, 2002)
    • A comparison of the performance of various project control methods using earned value management systems

      Colin, Jeroen; Vanhoucke, Mario (Expert Systems with Applications, 2015)
      Recent literature on project management has emphasised the effort which is spent by the management team during the project control process. Based on this effort, a functional distinction can be made between a top down and a bottom up project control approach. A top down control approach refers to the use of a project control system that generates project based performance metrics to give a general overview of the project performance. Actions are triggered based on these general performance metrics, which need further investigation to detect problems at the activity level. A bottom up project control system refers to a system in which detailed activity information needs to be available constantly during the project control process, which requires more effort. In this research, we propose two new project control approaches, which combines elements of both top down and bottom up control. To this end, we integrate the earned value management/earned schedule (EVM/ES) method with multiple control points inspired by critical chain/buffer management (CC/BM). We show how the EVM/ES control approach is complementary with the concept of buffers and how they can improve the project control process when cleverly combined. These combined top down approaches overcome some of the drawbacks of traditional EVM/ES mentioned in the literature, while minimally increasing the effort spent by the project manager. A large computational experiment is set up to test the approach against other control procedures within a broad range of simulated dynamic project progress situations.
    • A composite index of the creative economy

      Bowen, Harry; Moesen, Wim; Sleuwaegen, Leo (Review of Business and Economics, 2008)
    • A composite index of the creative economy with application to regional best practices

      Bowen, Harry; Moesen, Wim; Sleuwaegen, Leo (2006)
      This paper develops a “Composite Index of the Creative Economy” (CICE) for the purpose of benchmarking an entity's (e.g., country or region) creative capacity as reflected by it's achievement in three dimensions: Innovation, Entrepreneurship and Openness. To determine the weight each sub-dimension should contribute to the total value of the CICE, we introduce a novel method - endogenous weighting - that allows each entity to have its own unique set of “best” weights. This method addresses the issue of whether an entity's CICE score value reflects underlying capabilities (or lack thereof) or an “inappropriate” weighting of the underlying dimensions. Our endogenous weight method isolates achievement on the underlying dimensions as the source of a higher or lower CICE score value. In this paper we construct a value of the CICE for each of nine regions: Baden-Württemberg, Catalonia, Flanders, Lombardy, Maryland, Nord-Pas-De-Calais, Quebec, Rhône-Alpes, Scotland. A region's CICE value indicates its distance from “best practice” and can therefore be used to benchmark a region's creative capacity relative to other regions. In this respect, a focus of our analysis is the relative creative capacity of Flanders. We also examine the absolute and relative achievement of each region on each of the three underlying dimensions to identify specific areas of strength or weakness. The results indicate that Baden-Württemberg ranks highest in terms of creative capacity while Nord-Pas-De-Calais ranks lowest among the nine regions. Flanders ranks 3rd behind 2nd ranked Maryland. However, Flanders' rank masks that its CICE score value is 25% below that of Baden-Württemberg and 11% below that of Maryland, indicating a non-trivial gap in creative capacity between Flanders and “best practice.” On the three dimensions underlying creative capacity, Flanders ranks 2nd behind Baden-Württemberg on Innovation and Openness, but ranks 7th on Entrepreneurship (only ahead of Rhône-Alpes and Nord-Pas-De-Calais). Flanders' relatively poor ranking on Entrepreneurship reflects it's below average level of achievement on each of the three sub-dimensions of Entrepreneurship (ratio of newly established to existing firms, absence of a fear of failure, and venture capital as a share of GDP). This indicates that fostering and improving conditions for Entrepreneurship remains a challenge for Flanders compared to the other top ranked regions.