Recent Submissions

  • The prospective value creation potential of blockchain in business models: A Delphi study

    Schlecht, Laura; Schneider, Sabrina; Buchwald, Arne (Technological Forecasting & Social Change, 2021)
    Blockchain technology is gaining awareness and drawing attention in corporate practice and academia. Both fields expect a fundamental impact of blockchain on business and society. However, since blockchain research within the business model context is still in a nascent stage, more in-depth insights is required of blockchain’s impact on firms’ value creation and value capture. This study builds on a Delphi approach and aims to identify the future value creation potential of blockchain for organizations by 2030. Based on expert interviews, workshop insights, and prior literature, we developed a meaningful set of 36 projections of blockchain implications for business models. Our findings, based on the elements of the PEST framework, predict massive efficiency gains through technological progress and promise complementary offerings through various novel combination possibilities, novel forms of collaboration and business model opportunities, and a dissipation of the significance of blockchain types. The combined use of blockchain solutions with other technologies is likely to serve as the basis for ecosystem developments. Our projected finding is that the internet of value will replace the internet of information by 2030. Thereby, our research contributes to technological forecasting and strategic planning by providing managers clear indications of blockchain developments and action recommendations.
  • Venture capital winners: A configurational approach to high venture capital-backed firm growth

    Manigart, Sophie; Standaert, Thomas; Knockaert, Mirjam (British Journal of Management, 2021)
    The positive effect of venture capital (VC) on firm growth has been widely documented. However, there exists a large variation in growth, with only a small number of VC-backed firms reaching a substantial size. Prior studies have linked the variation in growth of VC-backed firms to differences in resource endowments of the entrepreneurial top management team, the firm or the venture capitalist, without considering their potentially complex interaction. In addition, the literature has taken strong growth aspirations in VC-backed firms as a given, without examining their potential variation, and its potential implications. Therefore, this study aims at examining which configurations of resource portfolios and growth aspirations lead to high VC-backed firm growth. In order to do so, it takes an inductive, theory-building approach, and builds upon fuzzy-set qualitative comparative analysis (fsQCA). Our results show that strong growth aspirations in the entrepreneurial top management team are a necessary condition for high VC-backed firm growth. Furthermore, we identify four configurations which, in combination with these aspirations, lead to high VC-backed firm growth.
  • When supplier development initiatives fail: Identifying the causes of opportunism and unexpected outcomes

    Tran, P.; Gorton, M.; Lemke, Fred (Journal of Business Research, 2020)
    This study investigates a ‘dark-side’ of supplier-buyer relationships, specifically the links between supplier development initiatives, relational norms and supplier opportunism, utilizing thematic analysis and qualitative comparative analysis. While buyers often employ supplier development initiatives to improve procurement, they can be ineffective and stimulate opportunistic behaviour by suppliers. Drawing on the case of agri-food supply chains in Vietnam, the paper analyses the relationships between specific supplier development initiatives and forms of opportunism, considering the role of relational norms. While often regarded as reducing the likelihood of opportunism, this study identifies that relational norms may include norms of opportunism in supply chain relationships, which sanction a degree of opportunistic behaviour. The study contributes to supply chain management theory and practice by investigating how buyers can address opportunism, so that supplier development initiatives curb supplier opportunism rather than trigger it.
  • Home location prediction with telecom data: Benchmarking heuristics with a predictive modelling approach

    Oosterlinck, Dieter; Baecke, Philippe; Benoît, Dries (Expert Systems with Applications, 2020)
    Correctly identifying the home location is crucial for human mobility analysis with telecom data, more specifically call detail record (CDR) data. To that end, multiple heuristics have been developed in literature. Nevertheless, due to the lack of ground truth home location data, no study has thoroughly validated these widely used methods so far. We present a detailed performance analysis of existing home detection heuristics, using a unique dataset that enables this important validation on the lowest level, being the level of the cell tower. Our research indicates that simple heuristics surprisingly outperform their more complex counterparts. The benchmark study revealed that the best heuristic is able to identify the home location with an average error of approximately 4.5 kilometres and selects the correct home tower in 60.69% of the cases. Based on the insights provided by our study, we propose a new heuristic that increases the accuracy to 61% and lowers the average distance error to 4.365 kilometres. Secondly, if the home location is known for possibly only a fraction of the instances, we propose a labelled predictive modelling approach. Adding social network based variables in this predictive model further enhances the predictive performance. Our best model reduces the average distance error to 2.848 kilometres and selects the correct home location in 72.08% of the cases. Furthermore, this result provides an indication of the upper bound for home detection with CDR data. Finally, models that only make use of social network based data are developed as well. Results show that even without using data of the focal individual, these models are able to select the correct home tower in 37.65% of the cases and achieve an average distance error of 8.1 kilometres.
  • Dual sourcing and smoothing under non-stationary demand time series: Re-shoring with speedfactories

    Boute, Robert; Disney, Stephen M.; Gijsbrechts, Joren; Van Mieghem, Jan A. (Management Science, 2020)
    We investigate near-shoring a small part of the global production to local SpeedFactories that serve only the variable demand. The short lead time of the responsive SpeedFactory reduces the risk of making large volumes in advance, yet it does not involve a complete re-shoring of demand. Using a break-even analysis we investigate the lead time, demand, and cost characteristics that make dual sourcing with a SpeedFactory desirable compared to complete offshoring. Our analysis employs a linear generalization of the celebrated order-up-to inventory policy to settings where capacity costs exist. The policy allows for order smoothing to reduce capacity costs and performs well relative to the (unknown) optimal policy. We highlight the signficant impact of auto-correlated and non-stationary demand series, which are prevalent in practice yet challenging to analyze, on the economic bene t of re-shoring. Methodologically, we adopt a linear policy and normally distributed demand and use transforms to present exact analyses.
  • Absorptive capacity, socially enabling mechanisms, and the role of learning from trial and error experiments: A tribute to Dan Levinthal’s contribution to international business research

    Lewin, Arie Y.; Massini, Silvia; Peeters, Carine (Journal of International Business Studies, 2020)
    The concept of absorptive capacity (AC) of firms (Cohen and Levinthal 1989 and 1990) is a foundational feature of organizational learning and adaptation that has had enormous influence in international business (IB), and innovation studies and management research in general. In this tribute to Dan Levinthal, we discuss the close connection between AC and learning – two areas central to Dan Levinthal’s research – in relation to different contexts where AC comes into play in extant IB research. We discuss four specific aspects of the nexus of AC and learning in the context of IB: (1) bridging between intra- and inter-firm learning; (2) a routine-based framing of AC that emphasizes processes and capabilities underlying seeking, assimilating, and innovation in a global setting; (3) the role of socially enabling mechanisms, and (4) the logic of learning through trial and error experiments within firms and countries.
  • Hoogopgeleide nieuwkomers op de arbeidsmarkt: Bevindingen uit het newcomer induction management acceleration programme

    Quataert, Sarah; Buyens, Dirk (Over.Werk, 2020)
    Vlaanderen wordt steeds meer etnisch en cultureel divers, maar toch zien we die diversiteit niet altijd weerspiegeld in onze bedrijvenmarkt. Nog steeds heerst een tewerkstellingskloof tussen nieuwkomers en autochtonen, en die is groter voor hoog- dan voor laagopgeleiden. Met het Newcomer Induction Management Acceleration Programme (NiMAP project), probeerden we deze tegenstrijdigheid op een integratieve manier onder de loep te nemen. Het project werd gesteund door het Europees Sociaal Fonds (ESF) en de Vlaamse Overheid.
  • The sandwich game: Founder-CEOs and forecasting as impression management

    Collewaert, Veroniek; Vanacker, Tom; Anseel, Frederik; Bourgois, Dries (Journal of Business Venturing, 2021)
    Drawing on impression management and social exchange theory, we examine the use of positively biased forecasts by (non-)founder-CEOs as an impression management tactic vis-à-vis their existing investors. Contrary to their non-founder counterparts, founder-CEOs identify more with the venture they founded and, therefore, experience greater instrumental and affective concerns about the long-term relationship with their investors. Consequently, we hypothesize that founder-CEOs will strategically provide less positively biased forecasts to their investors than non-founder-CEOs. Using two independent samples with revenue forecasts reported to different venture capital investors and a causal chain scenario study consisting of two experiments, we find consistent support for our hypothesis. Overall, this study provides new insights into the use of forecasts as a post-investment impression management tactic by distinct types of CEOs in entrepreneurial ventures.
  • The impacts of internal quality management relations on the triple bottom line: A dynamic capability perspective

    Alsawafi, Ahmed; Lemke, Fred; Yang, Ying (International Journal of Production Economics, 2020)
    This paper takes the dynamic capability (DC) theory as a theoretical perspective to investigate empirically the role of the internal dimensional view of quality management (QM) relations (management and employee) in driving sustainability performance, specifically social, environmental and economic dimensions. Data was collected from 226 UK manufacturing firms, and the relationships were empirically tested using structural equation modelling (SEM). The results show that internal management relation contributes to supporting employee relations and quality training. However, it is indirectly related to sustainability performance. In addition, management relations are indirectly connected with sustainability performance through employee relations. This study is relevant to academics and practitioners as it focuses on significant QM relations that are beneficial for the triple bottom line (TBL) of firms. As firms adopt QM relations to sustain their competitive advantage and achieve operational performance, it is crucial to identify which internal quality management relations associated with social, environmental and economic sustainability performance dimensions exert an influence.
  • A systematic review of the value assessment frameworks used within health technology assessment of Omics technologies and their actual adoption from HTA agencies

    Hoxhaj, Ilda; Govaerts, Laurenz; Simoens, Steven; Van Dyck, Walter; Huys, Isabelle; Gutiérrez-Ibarluzea, Iñaki; Boccia, Stefania (International Journal of Environmental Research and Public Health, 2020)
    Background: Omics technologies, enabling the measurements of genes (genomics), mRNA (transcriptomics), proteins (proteomics) and metabolites (metabolomics), are valuable tools for personalized decision-making. We aimed to identify the existing value assessment frameworks used by health technology assessment (HTA) doers for the evaluation of omics technologies through a systematic review. Methods: PubMed, Scopus, Embase and Web of Science databases were searched to retrieve potential eligible articles published until 31 May 2020 in English. Additionally, through a desk research in HTA agencies' repositories, we retrieved the published reports on the practical use of these frameworks. Results: Twenty-three articles were included in the systematic review. Twenty-two frameworks, which addressed genetic and/or genomic technologies, were described. Most of them derived from the ACCE framework and evaluated the domains of analytical validity, clinical validity and clinical utility. We retrieved forty-five reports, which mainly addressed the commercial transcriptomic prognostics and next generation sequencing, and evaluated clinical effectiveness, economic aspects, and description and technical characteristics. Conclusions: A value assessment framework for the HTA evaluation of omics technologies is not standardized and accepted, yet. Our work reports that the most evaluated domains are analytical validity, clinical validity and clinical utility and economic aspects.
  • Barriers and opportunities for implementation of outcome-based spread payments for high-cost, one-shot curative therapies

    Michelsen, Sissel; Nachi, Salma; Van Dyck, Walter; Simoens, Steven; Huys, Isabelle (Frontiers in Pharmacology, 2020)
    Background: The challenging market access of high-cost, one-time curative therapies has inspired the development of alternative reimbursement structures, such as outcome-based spread payments, to mitigate their unaffordability and answer remaining uncertainties. This study aimed to provide a broad overview of barriers and possible opportunities for the practical implementation of outcome-based spread payments for the reimbursement of one-shot therapies in European healthcare systems. Methods: A systematic literature review was performed investigating published literature and publicly available documents to identify barriers and implementation opportunities for both spreading payments and for implementing outcome-based agreements. Data was analyzed via qualitative content analysis by extracting data with a reporting template. Results: A total of 1503 publications were screened and 174 were included. Main identified barriers for the implementation of spread payments are reaching an agreement on financial terms while considering 12-month budget cycles and the possible violation of corresponding (inter)national accounting rules. Furthermore, outcome correction of payments is currently hindered by the need for additional data collection, the lack of clear governance structures and the resulting administrative burden and cost. The use of spread payments adjusted by population- or individual-level data collected within automated registries and overseen by a governance committee and external advisory board may alleviate several barriers and may support the reimbursement of highly innovative therapies. Conclusion: High-cost advanced therapy medicinal products pose a substantial affordability challenge on healthcare systems worldwide. Outcome-based spread payments may mitigate the initial budget impact and alleviate existing uncertainties; however, their effective implementation still faces several barriers and will be facilitated by realizing the required organizational changes.
  • Synchromodal transportation planning using travel time information

    Yee, Hannah; Gijsbrechts, Joren; Boute, Robert (Computers in Industry, 2020)
    Synchromodal transportation planning is de ned by the possibility to re-route shipments to alternative transportation modes at intermediate terminals based on real-time information about the shipment in transit. We present a synchromodal decision support model to determine the optimal modal choice for a single shipment in a multimodal network that is characterized by stochastic travel times. The model is formulated as a Markov decision process and allows adaptations to the modal choice based on real-time information on the travel time. Our formulation trades of transportation and late delivery penalty costs, and captures the value of synchromodal planning. We demonstrate the use of our model in a numerical case study, where we evaluate synchromodal against static intermodal transportation planning. The latter does not allow real-time adjustments to the modal choice. Compared to intermodality, synchromodal planning has most value when the penalty for late delivery is high and transportation services are more frequent.
  • Fitting activity distributions using human partitioning and statistical calibration

    Vanhoucke, Mario; Batselier, Jordy (Computers and Industrial Engineering, 2019)
    Many project management and scheduling studies have modelled activity durations as a range of values to express the stochastic nature of projects in progress. A wide variety of simulation models have been proposed that all rely on pre-defined statistical probability distributions for the durations of project activities. Ideally, these distributions reflect the real stochastic nature of the activities to assure that the simulations imitate the expected reality in the best possible way. However, the distributions are often selected ad hoc, relying on a class of distributions that are often used in the statistical literature, but without having much links with the features of real projects. Recently, a calibration method has been proposed in literature and validated on a set of 24 projects that makes use of real project data to derive realistic statistical distributions. This paper builds further on the validation of this calibration method in three different ways. First, the procedure is now successfully used on a set of 125 projects (for which 83 could be used for the final analysis) from different sectors. Secondly, the procedure has been extended with a partitioning step performed by humans with experience in the particular project. Finally, some procedural extensions have been proposed to test the necessity of each step of the procedure.
  • 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.
  • Performance comparison of activity sensitivity metrics in schedule risk analysis

    Ballesteros-Pérez, Pablo; Cerezo-Narváez, Alberto; Otero-Mateo, Manuel; Pastor-Fernández, Andrés; Vanhoucke, Mario (Automation in Construction, 2019)
    In Schedule Risk Analysis (SRA), activity sensitivity metrics measure the importance of activities in a project schedule. Highly sensitive activities are those more likely to increase project duration variability and/or cause project duration extensions. Several activity sensitivity metrics have been proposed over the years, but a comparison of all of them has never been made. This has made it difficult to know which metrics perform better and under what circumstances. In this paper, an extensive comparison of all relevant SRA activity sensitivity metrics is performed using a set of 4100 artificial projects. Unlike previous studies, the comparison framework is decoupled from corrective actions (e.g. activity crashing) which allows the merits of each metric to be assessed individually. Additionally, a new metric that performs better for overall sensitivity ranking is proposed. Results show that most sensitivity metrics do not perform well unless they are applied iteratively (the sensitivity of the remaining scheduled activities has to be recalculated whenever the duration variability of at least one activity has been restricted). However, if applied iteratively, most metrics can enhance project monitoring and control, while significantly shortening project duration.
  • The impact of applying effort to reduce activity variability on the project time and cost performance

    Martens, Annelies; Vanhoucke, Mario (European Journal of Operational Research, 2019)
    During project execution, deviations from the baseline schedule are inevitable due to the presence of uncertainty and variability. To assure successful project completion, the project’s progress should be monitored and corrective actions should be taken to get the project back on track. This paper presents an integrated project control procedure for measuring the project’s progress and taking corrective actions when necessary. We apply corrective actions that reduce the activity variability to improve the project outcome. Therefore, we quantify the relation between the applied managerial effort and the reduction in activity variability. Moreover, we define three distinct control strategies to take corrective actions on activities, i.e. an interventive strategy, a preventive strategy and a hybrid strategy. A computational experiment is conducted to evaluate the performance of these strategies. The results of this experiment show that different strategies are preferred depending on the topological network structure of projects. More specifically, the interventive strategy and hybrid strategy are preferred for parallel projects, while the preventive strategy is preferred for serial projects.
  • Digital operations: Autonomous automation and smart execution of work

    Boute, Robert; Van Mieghem, Jan (Management and Business Review, 2021)
    The integration of digital technologies is changing the way organizations operate and deliver value. Digitizing operations may replace manual work through increased automation, but it may also enable smarter execution of workflows thereby augmenting human work. Evaluating the level and reach of these three pillars--digitization, automation, and smart--across the organization’s value chain provides a diagnostic tool that can inspire future desired directions of digitization.
  • Safeguarding serendipitous creativity during the COVID-19 Pandemic

    Ben-Menahem, Shiko; Erden, Zeynep (California Management Review, 2020)
    How does a firm ensure creative interactions among people within and outside of the organization in pandemic conditions?
  • Optimizing production capacity and safety stocks in general acyclic supply chains

    Ghadimi, Foad; Aouam, Tarik; Vanhoucke, Mario (Computers and Operations Research, 2020)
    This paper addresses the joint optimization of production capacity and safety stocks in supply chains under the guaranteed service approach (GSA). The integrated problem is formulated as a mixed integer nonlinear program (MINLP) and solution procedures are proposed in the cases of general acyclic and spanning tree networks. For general acyclic supply chains, the integrated problem is solved using a Lagrangian decomposition method which iteratively solves capacity planning and safety stock placement subproblems, and adds budget feasibility constraints to strengthen the Lagrangian decomposition lower bound. When the supply chain has a spanning tree structure, an efficient Lagrangian relaxation heuristic dualizes the budget constraint and solves the relaxed problem using a dynamic programming algorithm. Computational experiments on real-world instances show that the Lagrangian decomposition method is able to solve all instances within 0.1% optimality, while a state-of-the-art solver is unable to provide feasible solutions for large instances. In the case of spanning tree networks, the proposed Lagrangian relaxation heuristic finds optimal or near-optimal solutions and greatly improves running time in comparison to the Lagrangian decomposition method. In addition, numerical experiments show that savings can be achieved through joint optimization of capacity and safety stocks.

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