Recent Submissions

  • Business intelligence (BI) success and the role of BI capabilities

    Isik, Öykü; Jones, Mary; Sidorova, Anna (Wiley, 2011)
    Business intelligence (BI) has become the top priority for many organizations who have implemented BI solutions to improve their decision‐making process. Yet, not all BI initiatives have fulfilled the expectations. We suggest that one of the reasons for failure is the lack of an understanding of the critical factors that define the success of BI applications, and that BI capabilities are among those critical factors. We present findings from a survey of 116 BI professionals that provides a snapshot of user satisfaction with various BI capabilities and the relationship between these capabilities and user satisfaction with BI. Our findings suggest that users are generally satisfied with BI overall and with BI capabilities. However, the BI capabilities with which they are most satisfied are not necessarily the ones that are the most strongly related to BI success. Of the five capabilities that were the most highly correlated with overall satisfaction with BI, only one was specifically related to data. Another interesting finding implies that, although users are not highly satisfied with the level of interaction of BI with other systems, this capability is highly correlated with BI success. Implications of these findings for the successful use and management of BI are discussed.
  • Business intelligence success: The roles of BI capabilities and decision environments

    Isik, Öykü; Jones, Mary; Sidororva, Anna (Elsevier, 2013)
    This study examines the role of the decision environment in how well business intelligence (BI) capabilities are leveraged to achieve BI success. We examine the decision environment in terms of the types of decisions made and the information processing needs of the organization. Our findings suggest that technological capabilities such as data quality, user access and the integration of BI with other systems are necessary for BI success, regardless of the decision environment. However, the decision environment does influence the relationship between BI success and capabilities, such as the extent to which BI supports flexibility and risk in decision making.
  • Are modular and customizable smartphones the future, or doomed to fail? A case study on the introduction of sustainable consumer electronics

    Hankammer, Stephan; Jiang, Ruth; Kleer, Robin; Schymanietz, Martin (Elsevier, 2018)
    Mass Customization (MC) has become a major trend in the consumer goods market in recent years. While the economic chances and threats are already described very well, the social and environmental impact of MC products remain unclear. Phonebloks, a design study of a modular smartphone launched in 2013, created a vision about fostering sustainability through MC. Teaming up with Google’s Project Ara, a modular and customizable smartphone approach seemed very likely to reach market maturity. In 2016, Google canceled Project Ara shortly before the awaited market introduction. Analyzing the rise and fall of the first large scale MC based business model that was initially designed to foster sustainability in the consumer electronics market, gives us the opportunity to revise the economic, social and ecologic potential of modular and customizable smartphones in general. Furthermore, with constantly growing consumer requirements for new product iterations in shorter time frames, traditional measures for success, such as time-to-market, could change inherently as we are moving closer towards iterative product development processes and much shorter product life-cycles. This, in turn, leads to major changes for ramp-up processes. Using a qualitative case study approach based on expert interviews at two different stages of the Project Ara development process (2015 and 2017), we shed light on the future of modular and customizable smartphones and their economic, social and ecologic sustainability potential. We show that while Project Ara failed in the end, it had the economic potential to outperform its competitors in the field of modular smartphones. We find that an MC approach could lead to longer smartphone or, at least, component life cycles. Finally, we affirm a positive potential for influencing sociocultural behavior in the long tail of the smartphone market.
  • Collaborative value creation from a degrowth perspective

    Hankammer, Stephan; Kleer, Robin (Elsevier, 2018)
    The concept of degrowth aims fundamentally at reducing material and energy throughput equitably, while questioning the desirability of further economic growth. In order to achieve this reduction of society’s throughput, radical changes in the ways goods and services are produced, distributed and used are required. In this think piece, concepts of consumer integration into the value creation process and (new) enabling technologies are discussed as possible constituting elements of alternative organizational models in a degrowth society. To date, collaborative value creation concepts, such as crowdsourcing and mass customization, have been discussed almost exclusively as business model patterns for companies in economies that are set to grow. The same applies to the assessment of (new) technologies, such as additive manufacturing, web-based user interfaces for co-creation, and other flexible production technologies that allow for collaborative and individualized production. Potential positive and negative effects of these concepts and technologies with regard to the objectives of degrowth are discussed in order to initiate a debate about the inclusion of CVC for the design of alternative organizational models that are in line with degrowth thinking. This think piece illustrates that several elements of collaborative value creation and its enabling technologies coincide with degrowth objectives but do not lead per se to their attainment. Thereby, a starting point for future (empirical) work in this area is generated.
  • Real-world evidence gathering in oncology: The need for a biomedical big data insight-providing federated network (Published Online)

    Geldof, Tine; Huys, Isabelle; Van Dyck, Walter (Frontiers Editorial Office, 2019)
    Moving towards new adaptive pathways for the development and access to innovative medicines implies that real-world data (RWD) collected throughout the medicinal product life cycle is becoming increasingly important. Big data analytics on RWD can obtain new and powerful insights into medicines’ effectiveness. However, the healthcare ecosystem still faces many sector-specific challenges that hamper the use of big data analytics delivering real world evidence (RWE). We distinguish between exploratory (ExTE) and hypotheses-evaluating (HETE) studies testing treatment effectiveness in the real world. From our experience and in the context of the four V’s of data management, we show that to get meaningful results data Variety and Veracity are needed regardless of the type of study conducted. More so, for ExTE studies high data Volume is needed while for HETE studies high Velocity becomes essential. Next, we highlight what are needed within the biomedical big data ecosystem, being: (a) international data reusability; (b) real-time RWD processing information systems; and (c) longitudinal RWD. Finally, in an effort to manage the four V’s whilst respecting patient privacy laws we argue for the development of an underlying federated RWD infrastructure on a common data model, capable of bringing the centrally-conducted big data analysis to the de-centrally kept biomedical data.
  • Nieuwe kennis uit ongestructureerde tekst

    Elzinga, Paul; Poelmans, Jonas; Viaene, Stijn; Dededene, Guido (AG Connect Intelligence, 2012)
    De Katholieke Universiteit Leuven en de Regiopolitie Amsterdam-Amstelland hebben nieuwe analysemethoden ontwikkeld voor ongestructureerde tekst. Het voornaamste doel is de ontwikkeling van een efficiënte en operationeel inzetbare methode om bruikbare kennis te onttrekken aan de grote hoeveelheid ongestructureerde informatie in de politiedatabases en die toe te passen om potentiële daders en slachtoffers beter en sneller te herkennen.
  • Payments: Refurbish or rebuild

    Slagmulder, Regine; Cumps, Bjorn; Dillen, Yannick (Henry Stewart Publications, 2018)
    The payments industry is facing its most radical change in decades. This is due to at least four change drivers — increased regulation, changing customer behaviour, technological innovation and new entrants. The sector faces increased competition from large established tech companies and small FinTech start-ups that are moving into the payments space. Based on the authors’ work with companies in the financial services industry and expert interviews, this paper identifies two distinct types of trends: those enhancing the existing payments system and those trying to build a completely new system. It is clear that a lot of the innovations focus on disintermediating the incumbent organisations. But how can these organisations best address these changes? Building on previous research the authors discuss four crucial capabilities for incumbents to master in an increasingly turbulent environment like the payments sector — designing superior customer experiences, setting up data-driven infrastructures, building multiparty collaborations and providing platform-based solutions. It is impossible for organisations to predict what will happen, but they will be better prepared for the road ahead by investing in these four capabilities.
  • Inferring comprehensible business/ICT alignment rules

    Cumps, Bjorn; Martens, David; De Backer, Manu; Haesen, Raf; Viaene, Stijn; Dedene, Guido; Baesens, Bart; Snoeck, Monique (Elsevier, 2009)
    We inferred business rules for business/ICT alignment by applying a novel rule induction algorithm on a data set containing rich alignment information polled from 641 organisations in 7 European countries. The alignment rule set was created using AntMiner+, a rule induction technique with a reputation of inducing accurate, comprehensible, and intuitive predictive models from data. Our data set consisted of 18 alignment practices distilled from an analysis of relevant publications and validated by a Delphi panel of experts. The goal of our study was to describe practical guidelines for managers in obtaining better alignment of ICT investments with business requirements. Our obtained rule set showed the multi-disciplinary nature of B/ICT alignment. We discuss implication of the alignment rules for practitioners.
  • New directions in entrepreneurial finance (Accepted)

    Cumming, Douglas; Deloof, Marc; Manigart, Sophie; Wright, Mike (Elsevier, 2019)
  • Comparative and combined effectiveness of innovative therapies in cancer: A literature review (Published Online)

    Geldof, Tine; Rawal, Smita; Van Dyck, Walter; Huys, Isabelle (Future Medicine Ltd, 2019)
    To achieve therapeutic innovation in oncology, already expensive novel medicines are often concomitantly combined to potentially enhance effectiveness. While this aggravates the pricing problem, comparing effectiveness of novel yet expensive (concomitant) treatments is much needed for healthcare decision-making to deliver effective but affordable treatments. This study reviewed published clinical trials and real-world studies of targeted and immune therapies. In total, 48 studies compared and/or combined multiple novel products on breast, colorectal, lung and melanoma cancers. To a great extent, products evaluated in each study were owned by one manufacturer. However, cross-manufacturer assessments are also needed. Next to costs and intensive market competition, the absence of a regulatory framework enforcing real-world multiproduct studies prevents these from being conducted. Trusted third parties could facilitate such real-world studies, for which appropriate and efficient data access is needed.
  • Why some are more equal: Family firm heterogeneity and the effect on management’s attention to CSR (Published Online)

    Fehre, Kerstin; Weber, Florian (Wiley, 2019)
    Research at the family firm–Corporate Social Responsibility (CSR) nexus lacks agreement about whether family firms are more or less socially responsible than their non‐family counterparts, which leads discussion relating to the bright and dark side of socioemotional wealth (SEW). We add to this ongoing debate in two different ways. First, we build on family firm heterogeneity and argue for a gray side to SEW, located between the bright and dark sides that is dependent upon the kind of family firm ownership. Second, we assume that prior research on a diverse set of CSR behaviors may, to some extent, explain the contradicting results; thus, we propose going back a step and focusing on management’s attention to CSR as an important antecedent of CSR behavior. By analyzing the letters to the shareholders of German HDAX firms from 2003 to 2012, this study finds that family ownership positively affects management’s attention to CSR, mainly driven by founders and family foundations. The research adds to our understanding of the family firm–CSR nexus by scrutinizing the role SEW plays in management’s attention to CSR when it comes to family firm heterogeneity.
  • The performance of acquisitions by high default risk bidders (Accepted)

    Bruyland, Evy; Lasfer, Meziane; De Maeseneire, Wouter; Song, Wei (Elsevier, 2019)
    We investigate the takeover strategies of high default risk acquirers and their value impact. We find that these bidders select bigger, less profitable and unrelated targets, pursue transactions during recessions, and pay with shares by offering target shareholders high premiums. Their long-term buy-and-hold returns are extremely negative, and reflect fundamentally their substantial drop in profitability combined with high leverage. We show that the well-established long-run under performance of acquiring firms is largely driven by this sub-set of acquirers. The results are similar when we use alternative measures of default risk and performance, and a global sample of non-US bidders.
  • Analysis of lead time correlation under a base-stock policy

    Hellemans, Tim; Boute, Robert; Van Houdt, Benny (Elsevier, 2019)
    We analyze the impact of lead time correlation on the inventory distribution, assuming a periodic review base-stock policy. We present an efficient method to compute the shortfall distribution for any Markovian lead time process, and we provide structural results when lead times are characterized by a 2-state Markov-modulated process. The latter reveals how lead time correlation increases the inventory variance and enables a closed form for the asymptotic behavior of the shortfall's variance in case the two possible lead time values are sufficiently different. We also establish upper and lower bounds on the inventory variance, which hold for any general time-homogeneous lead time process. Our results are complemented by a numerical experiment that indicates how commonly used approximations of the shortfall distribution mis-specify base-stock levels in the presence of lead time correlation. Not only does the inventory distribution increase in variance as the lead time correlation increases, it also becomes multi-modal.
  • The impact of solution representations on heuristic net present value optimization in discrete time/cost trade-off project scheduling with multiple cash flow and payment models

    Leyman, Pieter; Van Driessche, Niels; Vanhoucke, Mario; De Causmaecker, Patrick (Elsevier, 2019)
    The goal of this paper is to investigate the impact of different solution representations, as part of a metaheuristic approach, on net present value optimization in project scheduling. We specifically consider the discrete time/cost trade-off problem with net present value optimization and apply three payment models from literature. Each of these models determines the timing and size of cash flows from the contractor’s viewpoint. The contribution of this paper to literature is twofold. First, we include cash flow distribution variants in the payment models, to also distinguish between different manners in which value is created and costs are incurred, as part of a general model for the contractor’s cash flow management. This general model is developed in order to explicitly include the progress of activities in the determination of the timing and size of payments to the contractor, which is currently lacking in literature. Second, we employ an iterated local search framework to compare different solution representations and their corresponding local search and repair heuristics. The goal is to unambiguously show that the choice of a solution representation deserves a fair amount of attention, alongside the selection of appropriate diversification and intensification operators, even though this is not always the case in literature. Each part of the proposed algorithm is validated on a large dataset of test instances, generated to allow for a broad comparison of the solution representations. Our results clearly quantify the statistically significant differences between three types of representations for the project scheduling problem under study.
  • Computing project makespan distributions: Markovian PERT networks revisited

    Burgelman, Jeroen; Vanhoucke, Mario (Elsevier, 2019)
    This paper analyses the project completion time distribution in a Markovian PERT network. Several techniques to obtain exact or numerical expressions for the project completion time distribution are evaluated, with the underlying assumption that the activity durations are exponentially distributed random variables. We show that some of the methods advocated in the project scheduling literature are unable to solve standard datasets from the literature. We propose a framework to analyse the applicability, accuracy and sensitivity of different methods to compute project makespan distributions. An alternative data generation process is proposed to benchmark the different methods and the influence of project dataset parameters on the obtained results is extensively assessed.
  • Tolerance limits for project control: An overview of different approaches (Published Online)

    Vanhoucke, Mario (Elsevier, 2018)
    Monitoring the performance of projects in progress and controlling their expected outcome by taking corrective actions is a crucial task for any project manager. Project control systems are in use to quantify the project performance at a certain moment in time, and allow the project manager to predict the expected outcome if no action is taken. Consequently, these systems serve as mechanism that provide warning signals that tell the project manager when it is time to take corrective actions to bring the expected project outcome back on track. In order to trust these generated warning signals, the project manager has to set limits on the provide performance metrics that serve as thresholds for these actions. This paper gives an overview of different approaches discussed in the literature to control projects using such actions thresholds. First and foremost, the paper discusses three classes of actions thresholds,ranging from very easy-to-use rules-of-thumb to more advanced statistical project control methodologies. Each of these tools have been the subject to research studies, each of which aim at showing their power to predict project problems during its progress. In addition, the paper will emphasize the fundamental different between statistical project control using tolerance limits and statistical process control for projects. Finally, three different quality metrics to evaluate the performance of such control methods are presented and discussed.
  • The regulatory experience of Italy and the United States with dedicated incentives for strategic electricity transmission investment

    Keyaerts, Nico; Meeus, Leonardo (Elsevier, 2017)
    There is a trend in regulatory practice towards providing dedicated incentives for strategic investments. Italy and the United States have the longest experience with authorizing returns and risk-mitigating incentives that deviate from standard regulatory treatment for policy purposes. In these countries, the regulatory incentives are based on a case-by-case assessment of capital projects. We find that the Italian scheme is simpler, which reduces administrative costs. The U.S. scheme is more advanced in the case-by-case assessment. Even though dedicated incentives may be controversial, our analysis of both experiences shows that, notwithstanding significant learning costs, both schemes have facilitated substantial financial investment in strategically important infrastructure.
  • Judgmental forecast adjustments over different time horizons (Published Online)

    Van den Broeke, Maud; De Baets, Shari; Vereecke, Ann; Baecke, Philippe; Vanderheyden, Karlien (Elsevier, 2018)
    Accurate demand forecasting is the cornerstone of a firm’s operations. The statistical system forecasts are often judgmentally adjusted by forecasters who believe their knowledge can improve the final forecasts. While empirical research on judgmental forecast adjustments has been increasing, an important aspect is under-studied: the impact of these adjustments over different time horizons. Collecting data from 8 business cases, retrieving over 307,200 forecast adjustments, this work assesses how the characteristics (e.g., size and direction) and accuracy of consecutive adjustments change over different time horizons. We find that closer to the sales point, the number of adjustments increases and adjustments become larger and more positive; and that adjustments, both close and distant from the sales point, can deteriorate the final forecast accuracy. We discuss how these insights impact operational activities, such as production planning.
  • A tabu search procedure for the resource-constrained project scheduling problem with alternative subgraphs

    Servranckx, T.; Vanhoucke, Mario (Elsevier, 2019)
    This paper investigates the resource-constrained project scheduling problem with alternative subgraphs (RCPSP-AS). In this scheduling problem, there exist alternative ways to execute subsets of activities that belong to work packages. One alternative execution mode must be selected for each work package and, subsequently, the selected activities in the project structure should be scheduled. Therefore, the RCPSP-AS consists of two subproblems: a selection and a scheduling subproblem. A key feature of this research is the categorisation of different types of alternative subgraphs in a comprehensive classification matrix based on the dependencies that exist between the alternatives in the project structure. As the existing problem-specific datasets do not support this framework, we propose a new dataset of problem instances using a well-known project network generator. Furthermore, we develop a tabu search that uses information from the proposed classification matrix to guide the search process towards high-quality solutions. We verify the overall performance of the metaheuristic and different improvement strategies using the developed dataset. Moreover, we show the impact of different problem parameters on the solution quality and we analyse the impact of distinct resource characteristics of alternatives on the selection process.
  • Short selling in extreme events

    Geraci, Marco Valerio; Garbaravicius, Tomas; Veredas, David (Elsevier, 2018)
    We study the association between daily changes in short selling activity and financial stock prices during extreme events using TailCoR, a measure of tail correlation. For the largest European and US banks, as well as European insurers, we uncover a strong relation during exceptional (extreme) days and a weak relation during normal (average) days. Examining days with large increases in short positions and large downfalls in stock prices, we find evidence of both momentum and contrarian short selling taking place. For North American bank stocks, contrarian short selling appears more practiced than for European bank and insurance stocks. We find that the uncovered relationship decreases with firm size and increases during ban periods, which is in line with short selling becoming more informative when constrained.

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