• Quality and pricing decisions in production/inventory systems

      Jalali, Hamed; Raïsa, Carmen; Van Nieuwenhuyse, Inneke; Boute, Robert (European Journal of Operational Research, 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.
    • Quantify-me: consumer acceptance of wearable self-tracking devices

      Pfeiffer, Jurij; von Entreß-Fürsteneck, Matthias; Urbach, Nils; Buchwald, Arne (2016)
      The usage of wearable self-tracking technology has recently emerged as a new big trend in lifestyle and personal optimization in terms of health, fitness and well-being. Currently, only little is known about why people plan or start using such devices. Thus, in our research project, we aim at answering the question of what drives the usage intention of wearable self-tracking technology. Therefore, based on established technology acceptance theories, we deductively develop an acceptance model for wearable self-tracking technologies which sheds light on the pre-adoption criteria of such devices. We validate our proposed model by means of structural equation modeling using empirical data collected in a survey among 206 potential users. Our study identifies perceived usefulness, perceived enjoyment, social influ-ence, trust, personal innovativeness, and perceived support of well-being as the strongest drivers for the intention to use wearable self-tracking technologies. By accounting for the influence of the demographic factors age and gender, we provide a further refined picture.
    • Quantile-based inference for tempered stable distributions

      Veredas, David; Fallahgoul, Hassan; Fabozzi, Frank (2015)
      A simple, fast, and accurate method for the estimation of numerous distributions that belong to the tempered stable class is introduced. The method is based on the Method of Simulated Quantiles and it 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 under MLE. A Value-at-Risk and Expected Shortfall study for 13 years of daily data and for an array of market indexes world-wide shows that the tempered stable estimation with MSQ estimates provides reasonable risk assessments
    • Quantile-based inference for tempered stable distributions

      Fabozzi, Frank; Fallahgoul, Hassan; Veredas, David (Computational Economics, 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 (Informatie, 2010)
    • Quo vadis, customer experience quality

      Dzenkovska, Julija; Schoefer, Klaus; Lemke, Fred; Heirati, Nima (2017)
    • R&D collaborations and innovation speed of research projects

      Du, Jingshu; Leten, Bart; Vanhaverbeke, Wim (2013)
    • R&D cooperation and spillovers: some empirical evidence from Belgium

      Cassiman, Bruno; Veugelers, Reinhilde (American Economic Review, 2002)
    • (R)E-tail satisfaction: retail customer satisfaction in online and offline contexts

      Weijters, Bert; Schillewaert, Niels (2006)
      Building on the e-Satisfaction model proposed by Szymanski and Hise (2000) and further validated by Evanschitzky, Iyer, Hesse, and Ahlert (2004), we develop an instrument to measure shopper satisfaction in online and offline retail contexts: the (R)E-Tail Satisfaction scale. Using data from an online (N=202) and an offline (N=441) grocery shopper sample, the instrument is shown to be fit for cross-channel evaluation of levels of satisfaction and its antecedents. We find full metric invariance (identical factor loadings), sufficient partial scalar invariance (identical item intercepts for at least two items per construct), as well as some interesting structural differences. Most notably, online shoppers evaluate the facets of retail satisfaction generally lower than do offline shoppers.
    • Rabobank Nederland

      Gouka, P.T.; Sprokholt, E.; Thibeault, André (1996)
    • Radicale technologische innovatie: opportuniteit of bedreiging?

      Buelens, Marc (Vlerick Management Focus, 2004)
    • Radiographie d'un bilan

      Ooghe, Hubert; Van Wymeersch, Charles P. (1996)
    • Raising public awareness and trust in transmission infrastructure projects with incentive regulation: Tools and biases

      Bhagwat, Pradyumna; Keyaerts, Nico; Meeus, Leonardo (2018)
      Raising public awareness and trust in transmission infrastructure development is one of the key current challenges facing Transmission System Operators (TSOs) and other project developers. The result can be costly delays. Fine-tuning the regulatory toolbox that National Regulatory Authorities (NRAs) apply to incentivise TSOs can be part of the solution. The toolbox consists of cost-plus or rate of return regulation, price or revenue cap regulation, and output regulation. Each of these tools has strengths and limitations in terms of biases. In this brief, we identify the biases that are specific to stakeholder engagement activities that TSOs undertake to increase the public awareness and trust. Under the cost-plus approach, NRAs are biased towards the least controversial activity. Thus, the TSOs will try to anticipate the costs that will be more easily approved by the regulator. However, these least controversial activities may not be the most effective. Under the price/revenue cap, TSOs can be biased towards prioritising activities that result in the highest direct improvement of cost efficiency. They can also be biased in selecting the least controversial activities rather than the most cost-effective ones, simply because it can adversely affect their reputation and their engagement with the regulator. Under output regulation, independent experts can help the regulator to assess and challenge the stakeholder engagement activities undertaken by a TSO. This approach, however, requires a higher level of sophistication and complexity so that it can only be managed properly by a regulatory agency with sufficient resources and skills.
    • Raising the bar for smart city ecosystems

      Van den Bergh, Joachim; Danneels, Lieselot; Viaene, Stijn (2017)