• Unlocking the value of personalised healthcare in Europe — breast cancer stratification

      Van Dyck, Walter; Gassull, Daniel; Vértes, Gergely; Jain, Prateek; Palaniappan, Muhilan; Schulthess, Duane; Tambuyzer, Erik; Hudson, Richard; Moran, Nuala (Health Policy and Technology, 2012)
      Through stratification, this simulation shows that there is great potential to improve the efficiency of treating breast cancer. By segmenting the female population at the age of 50 based on family history and genetic testing, our model shows a reduction in costs of breast cancer treatments by 37% with no loss of efficacy accomplished primarily through a 60% drop in incidence of metastatic stages of the disease. These programmes are not inexpensive, and require substantial upfront investments of roughly 2 billion GBP and continued annual investments of several hundred million GBP. However, our simulations show a positive NPV and ROI in approximately year 7 of the programme.
    • Unveiling smart city implementation challenges: The case of Ghent Authors

      Van den Bergh, Joachim; Viaene, Stijn (Information Polity: The International Journal of Government & Democracy in the Information Age, 2016)
      The `smart city' label is internationally used by cities, researchers and technology providers with different meanings. As a popular concept it is widely used by city administrators and politicians to promote their efforts to prepare their cities for the future. There are decent definitions for what a smart city is, but it is much harder to find a trustworthy description of what it takes to become a smart city and how a city administration is impacted by that effort. This paper sets out to investigate how a city, aspiring to become a `smart city', can manage its internal organization to realize that ambition. Specifically, it describes the case of the City of Ghent, Belgium, and the key challenges it has been facing in its ongoing efforts to be a smart city. Based on in depth interviews with city representatives six key challenges for smart city realization were identified and tested with a panel of representatives from five European cities that are in the process of becoming a smart city. The study contributes to a more professional pursuit of the smart city concept and elaborates the academic body of knowledge on smart city development, as an instance of IT-enabled transformation in public services.
    • USDI on the up: AmCham study tracks investment and R&D trends

      Bowen, Harry; Onkelinx, Jonas (AmCham Business Journal, 2007)
    • Use of proximal policy optimization for the joint replenishment problem

      Vanvuchelen, Nathalie; Gijsbrechts, Joren; Boute, Robert (Computers in Industry, 2020)
      Deep reinforcement learning has been coined as a promising research avenue to solve sequential decision making problems, especially if few is known about the optimal policy structure. We apply the proximal policy optimization algorithm to the intractable joint replenishment problem. We demonstrate how the algorithm approaches the optimal policy structure and outperforms two other heuristics. Its deployment in supply chain control towers can orchestrate and facilitate collaborative shipping in the Physical Internet.
    • Using activity sensitivity and network topology information to monitor project time performance

      Vanhoucke, Mario (Omega - International Journal of Management Science, 2010)
    • Using ad hoc measures for response styles. A cautionary note

      De Beuckelaer, A.; Weijters, Bert; Rutten, A. (Quality and Quantity, 2010)
    • Using earned value management and schedule risk analysis with resource constraints for project control

      Song, Jie; Martens, Annelies; Vanhoucke, Mario (European Journal of Operational Research, 2021)
      The main goal of project control is to measure the actual project progress such that the deviations from the plan can be identified and corrective actions can be taken to bring the project back on track. However, in resource-constrained projects, disrupted activities affect their successors due to precedence relations and the other activities due to resource constraints, both of which will result in deviations during project progress. Since the project control approaches solely focus on the deviations based on the network analysis, they do not accurately reflect the progress of resource-constrained projects. This paper extends project control approaches for resource-constrained projects to measure and evaluate whether the project progress is acceptable. Moreover, we design three scenarios considering possible resource conflicts to take corrective actions when needed. In the computational experiment, this project control process is applied to a large set of projects with different characteristics and further validated on real-life project data. The results show that the proposed scenarios and different project control approaches are efficient and reliable, but their use depends on project network structure and resource scarceness.
    • Using real project schedule data to compare earned schedule and earned duration management project time forecasting capabilities

      André de Andrade, Paulo; Martens, Annelies; Vanhoucke, Mario (Automation in Construction, 2019)
      Since project control involves taking decisions that affect the future, the ability to accurately forecast the final duration and cost of projects is of major importance. In this paper, we focus on improving the accuracy of project duration forecasting by introducing a forecasting approach for Earned Value Management (EVM) and Earned Duration Management (EDM) that combines the schedule performance and schedule adherence of the project in progress. As the schedule adherence has not yet been defined formally for EDM, we extend the EVM-based measure of schedule adherence, the p-factor, to EDM and refer to this measure as the c-factor. Moreover, we aim to improve the ability to indicate the expected forecasting accuracy for a project by extending the EVM concept of project regularity to EDM. The introduced forecasting approach and the EDM project regularity indicator are applied to a large number of real-life projects, mainly situated in the construction sector. The conducted empirical experiment shows that the project duration forecasting accuracy can be increased by focusing on both the schedule performance and schedule adherence. Further, this study shows that the EDM project regularity indicator is indeed a more reliable indicator of forecasting accuracy.
    • Using schedule risk analysis with resource constraints for project control

      Song, Jie; Martens, Annelies; Vanhoucke, Mario (European Journal of Operational Research, 2021)
      Schedule Risk Analysis (SRA) has shown to provide reliable activity sensitivity information for taking corrective actions during project control. More precisely, by selecting a small subset of activities with high sensitivity values for taking corrective actions, the project outcome can be improved. In resource constrained projects, disrupted activities can affect both their successors as well as other activities when resource conflicts are induced. Since SRA focuses solely on the project network to determine the sensitivity of activities, the traditional SRA metrics do not accurately reflect the activity sensitivity for resource constrained projects. In this paper, the traditional SRA metrics are extended for resource constrained projects, and a novel resource-based sensitivity metric is introduced (RC-SRA metrics). A computational experiment is conducted to investigate the ability of the RC-SRA metrics to identify activities with higher sensitivity values. In addition, two activity selection strategies, defined as the normal strategy and sequential strategy, are designed to select activities for taking corrective actions. Further, two types of corrective actions are proposed to reduce the activity duration or resource demand in case of delays, respectively. Finally, the impact of dynamically updating the RC-SRA metrics during project execution is examined. The computational results show that the normal activity selection strategy is recommended for serial projects, while the sequential strategy is preferred for parallel projects. The results also indicate that reducing the activity durations performs better than reducing the resource demand of activities. Finally, it is shown that updating the RC-SRA metrics dynamically during project execution improves the efficiency of the corrective action taking process.
    • Using styles for more effective learning in multicultural and e-learning environments

      Cools, Eva; Evans, Carol; Redmond, J.A. (Multicultural Education and Technology journal, 2009)
    • Using the right emotion to promote the right product to the right person

      Faseur, Tine; Geuens, Maggie (Communication Research, 2010)
    • Using the weapons you have: the role of resources and competitor orientation as enablers and inhibitors of competitive reaction to new products

      Debruyne, Marion; Frambach, Ruud; Moenaert, Rudy (Journal of Product Innovation Management, 2010)
      It is a well‐accepted notion that to respond to competitive attacks firms need the necessary resources to do so. However, the presence of resources may not be a sufficient condition to enhance competitive responsiveness. Following a managerial decision‐making approach, the present paper investigates how the availability of resources affects decision makers' assessment of a competitor's new product and their subsequent reaction to it. This study posits that competitive reaction follows from a decision maker's assessment of a competitive action. This assessment contains a motivation dimension and an ability dimension. The effect of three types of resources—financial, marketing, and technological—are examined. A quasi‐experiment with the Markstrat business game as an empirical setting provided 339 questionnaires containing information on 29 different new product introductions. The motivation and ability dimensions are confirmed as important antecedents explaining reaction behavior. The results show that resources possess a dual, and opposing, role in influencing competitive reaction to new products. On the one hand, resources enhance decision makers' belief that they are able to react effectively to competitive attacks, but the presence of resources also makes them less motivated to react. The paper introduces two explanations for this: the liability‐of‐wealth hypothesis and the strong‐competitor hypothesis. The addition of competitor orientation as a moderator allows us to discern between the two competing rationales for the existence of a negative effect of resources on the expected likelihood of success of a competitive new product introduction, supporting the liability‐of‐wealth hypothesis. The paper demonstrates the key role of competitor orientation and formulates implications from that.
    • Validity and reliability of scores on the reduced Emotional Intensity Scale

      Geuens, Maggie; De Pelsmacker, Patrick (Educational and Psychological Measurement, 2002)
    • Valuation of Angel-backed companies: The role of investor human capital

      Collewaert, Veroniek; Manigart, Sophie (Journal of Small Business Management, 2016)
      This paper examines how angel investors' human capital affects the valuation of their portfolio companies, based on the pre-money valuation of 123 investment rounds in 58 Belgian companies. We argue that angel investors with higher levels of human capital will perceive a higher value-creating potential in entrepreneurial opportunities through their ability to see more value-creating options, a higher value-adding potential post-investment and an enhanced legitimacy provided to the venture. Economic theories suggest they appropriate these rents through lower valuations, while stewardship theory suggests they share value creation with entrepreneurs. Consistent with stewardship theory, we show angel investors negotiate higher valuations when they have higher levels of human capital, more specifically if they studied longer, have a business degree, more entrepreneurial experience or previous professional law experience. As such, our results contrast with the behaviour of venture capital investors who negotiate lower valuations when they have more experience.
    • Value creation and the alliance experiences of Dutch companies

      Sleuwaegen, Leo; Schep, K.; den Hartog, Gijs; Commandeur, Harry (Long Range Planning, 2003)
    • Value Creation in Mergers and Acquisitions: A Study of European Transactions during the Fifth Wave

      Huyghebaert, Nancy; Luypaert, Mathieu (Bank- en Financiewezen, 2009)
    • The value of installed base information for spare part inventory control

      Van der Auweraer, Sarah; Zhu, Sha; Boute, Robert (International Journal of Production Economics, 2021)
      This paper analyzes the value of different sources of installed base information for spare part demand forecasting and inventory control. The installed base is defined as the set of products (or machines) in use where the part is installed. Information on the number of products still in use, the age of the products, the age of their parts, as well as the part reliability may indicate when a part will fail and trigger a demand for a new spare part. The current literature is unclear which of this installed base information adds most value – and should thus be collected – for inventory control purposes. For this reason, we evaluate the inventory performance of eight methods that include different sets of installed base information in their demand forecasts. Using a comparative simulation study we identify that knowing the size of the active installed base is most valuable, especially when the installed base changes over time. We also find that when a failure-based prediction model is used, it is important to work with the part age itself, rather than the machine age. When one is not able to collect information on the part age, a logistic regression on the machine age might be a valuable alternative to a failure-based prediction model. Our findings may support the prioritization of data collection for spare part demand forecasting and inventory control.