This paper investigates the effect of changes in ambiguity on the value of statistical life (VSL) under the smooth ambiguity model developed by Klibano, Marinacci and Mukerji (2005). Changes in ambiguity over the mortality risk are expressed through the specific concept of stochastic dominance of order n defined by Ekern (1980). We provide sufficient conditions on the individual attitudes towards ambiguity such that both an ambiguity-averse and an ambiguity-seeking individual modify their VSL in the face of changes in ambiguity. These results have important implications for cost-benefit applications on the risk of human life.
Product-harm crisis are the nightmare of any firm as they have a disastrous effect on their sales and image. This paper proposes a new model to compute the optimal investment in quality and advertising in order to reduce the probability of occurrence of a possible product-harm crisis and mitigate its effects. This method uses stochastic control theory and can be used for both tangible products and services.
This paper investigates how welfare losses for facing risks change as a function of the number of risk exposures. To that aim, we define the risk apportionment of order n (RA-n) utility premium as a measure of pain associated with facing the passage from one risk to a riskier one. Changes in risks are expressed through the specific concept of stochastic dominance of order n defined by Ekern (1980). Three configurations of risk exposures are considered. The paper first shows how the RA-n utility premium is modified when individuals wealth becomes riskier. This makes it possible to generalise earlier results on the topic. Second, the paper provides necessary and sufficient conditions on individual preferences for superadditivity and subadditivity of the RA-n utility premium. Third, the paper investigates welfare changes of merging increases in risks.
Logistics section is one of the most important industrial sections to contribute to European economy. To improving efficiency and energy efficient of logistics, European Commission call new research theme ‘smart, green and integrated transport’ in its H2020 program. The paper presents a version on providing a cloud based platform for supporting big data empowered logistics services to respond this call. The research is supported by inter-disciplinary approaches, which brings experts from telecommunication, cloud computing, sensor networking, service-oriented computing, data analysis, transportation, and logistics areas to work together to provide real-world solutions for future logistics. The research questions and challenges of the platform are highlighted. Overall architecture and data collection are presented.
Supply Chains have to be designed and managed holding simultaneously into account many different performance measures. Moreover, modern Supply Chains have to ensure satisfying performances despite an increasing degree of complexity and market uncertainty as well as be capable to limit the negative impacts of disruptive events. A multi-criteria robustness evaluation framework is proposed to deal with these challenges. The proposed approach allows to separately assessing the impact of various performance measures specifying tailor loss functions, being able to deal with non-linearity and asymmetric impacts. Moreover, an original Robustness Index is defined, in order to provide reliable estimations even in the presence of outliers and integrating information about kurtosis and skewness in the robustness estimation. The proposed framework is applied to a fictive industrial case to demonstrate its utilization and show the kind of analysis that can be done on the basis of the obtained results. The approach, simply requiring the definition of some parameters and the description of the characteristics of the Supply Chain configurations to be evaluated, is meant to be easily used by practitioners.
This study investigates the quay crane allocation problem with respect to vessel assigned to a particular discrete berth at a bulk material handling port. In the proposed model,vessels at the anchorage are berthed on a First in, first out (FIFO) basis at the port, and then the quay cranes are assigned to the berth dynamically before berthing and during unloading of the vessel. To solve the model, we used the Block Based Genetic Algorithm (BBGA) and Genetic Algorithm (GA). Computational study is conducted using the real data provided by a port located on theEastern Coast of India.
Building on a previous paper - which described one of the important applied teaching pilot initiatives of the University of Applied Sciences Western Switzerland in the field of Business creation and particularly its repercussions on marketing knowledge – the authors conducted a survey on 6 annual cohorts of participants, with the aim of assessing their individual experience throughout the program as well as their perceived learnings. Results show interesting characteristics and motivators for participants and lead to specific recommendations in order to adapt the curriculum to better fit participants’ expectations and better train them to be successful entrepreneurs.
Classical energy planning models assume that consumers are rational and this is obviously not always the case. This paper proposes an original method to take into account the consumer’s real behavior in an energy model. It couples a classical energy model with a Share of Choice model.
