Flexible work planning of service agents with load balancing

This work emerged from the need to better plan the daily work of 29 travelling service agents, who provide 1090 services to 412 customers in 283 sites, on daily average. A handy and flexible tool was developed and is presented herein. A major contribution of this study is an explicit consideration of the multi-dimensional nature of the problem by the inclusion of workload balancing, which may stand in conflict to cost minimisation. Further, the geographical distribution of the demand is highly irregular. Therefore, two load measures are required and balanced. This required to fitting a proper planning scheme. The planning tool has been applied successfully by the commercial service provider. Improvements in the order of 20% and more were obtained in key performance measures. Moreover, cost reductions, service improvement and load balance were obtained simultaneously: the standard deviations of the service times and working day’s duration were reduced by 18 and 58%, respectively. This enables to reduce the number of agents with no significant harm in performance. Additional practical advantages of the proposed tool are also discussed and demonstrated, for example, the ability to cope with geographical distributions and the flexibility to respond to daily variations in demand.     

Spatially varying dynamic coefficient models

In this work we present a flexible class of linear models to treat observations made in discrete time and continuous space, where the regression coefficients vary smoothly in time and space. This kind of model is particularly appealing in situations where the effect of one or more explanatory processes on the response present substantial heterogeneity in both dimensions. We describe how to perform inference for this class of models and also how to perform forecasting in time and interpolation in space, using simulation techniques. The performance of the algorithm to estimate the parameters of the model and to perform prediction in time is investigated with simulated data sets. The proposed methodology is used to model pollution levels in the Northeast of the United States.     

Das 360-Grad-Feedback zur Unterstützung der Kompetenzerweiterung von Führungskräften

Zusammenfassung:  Der Beitrag beschreibt die Einbettung des 360-Grad-Feedbacks in ein Programm der Führungskr?fteentwicklung. 360-Grad-Feedback ist eine Voraussetzung für die systematische Kompetenzentwicklung der Führungskr?fte eines Unternehmens. Darüber hinaus k?nnen die Entwicklungs- und Lernm?glichkeiten, die ein individuelles Coaching bietet, durch ein vorheriges 360-Grad-Feedback optimiert werden. Die bei ThyssenKrupp Services mit dem F?rderprogramm „best-for-best“ gesammelten Erfahrungen zeigen deutlich, dass die Kombination von einem 360-Grad-Feedback mit gezielten Coaching-Angeboten ein echtes Erfolgsmodell darstellt.

A semiparametric Bayesian approach to extreme value estimation

This paper is concerned with extreme value density estimation. The generalized Pareto distribution (GPD) beyond a given threshold is combined with a nonparametric estimation approach below the threshold. This semiparametric setup is shown to generalize a few existing approaches and enables density estimation over the complete sample space. Estimation is performed via the Bayesian paradigm, which helps identify model components. Estimation of all model parameters, including the threshold and higher quantiles, and prediction for future observations is provided. Simulation studies suggest a few useful guidelines to evaluate the relevance of the proposed procedures. They also provide empirical evidence about the improvement of the proposed methodology over existing approaches. Models are then applied to environmental data sets. The paper is concluded with a few directions for future work.     

Semiparametric bivariate modelling with flexible extremal dependence

Statistics and Computing - Inference over multivariate tails often requires a number of assumptions which may affect the assessment of the extreme dependence structure. Models are usually...     

Bayesian dynamic models for survival data with a cure fraction

In this paper, we propose a new class of semi-parametric cure rate models. Specifically, we construct dynamic models for piecewise hazard functions over a finite partition of the time axis. Allowing the size of partition and the levels of baseline hazard to be random, our proposed models provide a great flexibility in controlling the degree of parametricity in the right tail of the survival distribution and the amount of correlations among the log-baseline hazard levels. Several properties of the proposed models are derived, and propriety of the implied posteriors with improper noninformative priors for regression coefficients based on the proposed models is established for the fixed partition of the time axis. In addition, an efficient reversible jump computational algorithm is developed for carrying out posterior computation. A real data set from a melanoma clinical trial is analyzed in detail to further demonstrate the proposed methodology.     

Reference model for implementing an MRP system in a highly diverse component and seasonal lean production environment

Companies are currently choosing to integrate logics and systems to achieve better solutions. These combinations also include companies striving to join the logic of material requirement planning (MRP) system with the systems of lean production. The purpose of this article was to design an MRP as part of the implementation of an enterprise resource planning (ERP) in a company that produces agricultural implements, which has used the lean production system since 1998. This proposal is based on the innovation theory, theory networks, lean production systems, ERP systems and the hybrid production systems, which use both components and MRP systems, as concepts of lean production systems. The analytical approach of innovation networks enables verification of the links and relationships among the companies and departments of the same corporation. The analysis begins with the MRP implementation project carried out in a Brazilian metallurgical company and follows through the operationalisation of the MRP project, until its production stabilisation. The main point is that the MRP system should help the company's operations with regard to its effective agility to respond in time to demand fluctuations, facilitating the creation process and controlling the branch offices in other countries that use components produced in the matrix, hence ensuring more accurate estimates of stockpiles. Consequently, it presents the enterprise knowledge development organisational modelling methodology in order to represent further models (goals, actors and resources, business rules, business process and concepts) that should be included in this MRP implementation process for the new configuration of the production system.     

Migrant and asylum-seeker children returned to Kosovo and Albania: predictive factors for social–emotional wellbeing after return

The return of rejected asylum seekers has a high priority on the national agendas of European States. In order to make well-informed asylum decisions involving children, knowledge of how asylum-seeker children fare after their return to their countries of origin is needed. This study aims to gain knowledge about the child-rearing environment and the social–emotional wellbeing of migrant children who have returned to Kosovo and Albania after a stay in a European host country. Based on a sample of 106 returned families, the study investigated the predictive factors for children’s social–emotional wellbeing using regression analyses. The findings show that procedural characteristics and ethnicity predict wellbeing, mediated through the quality of the child-rearing environment. The most vulnerable children did not have a stable resident status in the host country, belonged to a minority ethnic group and were older adolescents. The findings indicate that the wellbeing of returned children is not only dependent on conditions after repatriation, but also on the conditions which the families left in the host country. To enable sustainable return in a child’s best interests, the needs of vulnerable families and children should be thoroughly assessed prior to return, and reintegration support should be tailored to their situation.