• Quality and pricing decisions in production/inventory systems

      Jalali, Hamed; Raïsa, Carmen; Van Nieuwenhuyse, Inneke; Boute, Robert (Elsevier, 2019)
      In this article, we consider the impact of finite production capacity on the optimal quality and pricing decisions of a make-to-stock manufacturer. Products are differentiated along a quality index; depending on the price and quality levels of the products offered, customers decide to either buy a given product, or not to buy at all. We show that, assuming fixed exogenous lead times and normally distributed product demands, the optimal solution has a simple structure (this is referred to as the load-independent system). Using numerical experiments, we show that with limited production capacity (which implies load-dependent lead times) the manufacturer may have an incentive to limit the quality offered to customers, and to decrease market coverage, especially in settings where higher product quality leads to higher congestion in production. Our findings reveal that the simple solution assuming load-independent lead times is suboptimal, resulting in a profit loss; yet, this profit loss can be mitigated by constraining the system utilization when deciding on quality and price levels. Our results highlight the importance of the relationship between marketing decisions and load-dependent production lead times.
    • Quantile-based inference for tempered stable distributions

      Fabozzi, Frank; Fallahgoul, Hassan; Veredas, David (Springer, 2019)
      If the closed-form formula for the probability density function is not available, implementing the maximum likelihood estimation is challenging. We introduce a simple, fast, and accurate way for the estimation of numerous distributions that belong to the class of tempered stable probability distributions. Estimation is based on the Method of Simulated Quantiles (Dominicy and Veredas (2013)). MSQ consists of matching empirical and theoretical functions of quantiles that are informative about the parameters of interest. In the Monte Carlo study we show that MSQ is significantly faster than Maximum Likelihood and the estimates are almost as precise as MLE. A Value at Risk study using 13 years of daily returns from 21 world-wide market indexes shows that MSQ estimates provide as good risk assessments as with MLE.
    • Quo vadis BI?

      De Hertogh, Steven; Van den Bunder, Annabel; Viaene, Stijn (2010)
    • Rank based testing in linear models with stable errors

      Hallin, Marc; Swan, Yvik; Verdebout, Thomas; Veredas, David (2011)
    • Rapport in mediation

      Aaldering, H.; Codrington, T.; Jordaan, Barney (2016)
    • Rating SMEs

      Rikkers, Frieda; Thibeault, André (2009)
    • Re-framing CSR

      Louche, Céline; Dodd, T. (2009)
    • Re-positioning business process management

      Van den Bergh, Joachim; Isik, Öykü; Viaene, Stijn; Helsen, Eddy (2016)
      In this work we explore the future of BPM as management discipline and identify the key capabilities for process support units to remain meaningful in a world of business transformation. As BPM gets increasingly commoditized, we raise a call for researchers and practitioners in our discipline, to shape a future-proof BPM that is relevant for a business environment that is characterized by exploration, fast-paced change, and digitization. Therefor we propose 5 key capabilities which will help to redefine our current understanding of BPM.
    • Real-world evidence gathering in oncology: The need for a biomedical big data insight-providing federated network

      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.
    • Rebranding as fuel for growth

      Haspeslagh, Philippe (2012)
      Many companies have introduced the supply chain function in their organisation. Little attention, however, is devoted to the way the supply chain function is organised, e.g. the range of responsibilities it has, the position it occupies in the hierarchy and the skills it requires. The literature on this is scarce. This paper provides initial benchmarking data on company decisions regarding the roles and responsibilities of their supply chain managers and how the various supply chain tasks are coordinated and integrated. Our empirical study in the food, pharmaceutical, and chemical industries shows that differences in supply chain organisational structures are not random. We find that the way the supply chain function is organised seems to depend on the industry and its complexity and, we might speculate, on the strategy of the organisation. By highlighting and trying to explain these differences, we hope to raise top management awareness regarding the structuring options for their supply chain function and the importance of this issue for the organisation.
    • Reducing creative labour precarity: beyond network connections

      Farr-Wharton, Benjamin Stuart Rodney; Brown, Kerry; Keast, Robyn; Shymko, Yuliya (2015)
      Purpose: The purpose of this paper is to investigate the impact of organisational business acumen and social network structure on the earnings and labour precarity experienced by creative industry workers. Design/methodology/approach: Results from a survey that collected data from a random sample of 289 creative workers are analysed using structural equation modelling. Mediating effects of social network structure are explored. Findings Results support the qualitative findings of Crombie and Hagoort (2010) who claim that organisational business acumen is a significant enabler for creative workers. Further, social network structure has a partial mediating effect in mitigating labour precarity. Research limitations/implications: This exploratory study is novel in its use of a quantitative approach to understand the relationship between labour and social network dynamics of the creative industries. For this reason, developed scales, while robust in exploratory and confirmatory factor analysis, warrant further application and maturity. Practical implications: The organisational business acumen of creative workers is found to mitigate labour precarity and increase perceived earnings. Social implications: The results from this study call for policy and management shifts, to focus attention on developing business proficiency of creative workers, in an effort to curb labour precarity in the creative industries, and enhance positive spillovers into other sectors. Originality/value: The paper fills a gap in knowledge regarding the impact of organisational business acumen and social network structure on the pay and working conditions of people working in a sector that is dominated by self-employed and freelance arrangements.