The value of rescheduling functionality within standard MRP packages

One of the basic functions of an MRP system is to issue rescheduling messages that urge the planner tospeed up or slow down open orders. It seems in practice that these messages are not used at all by planners. This is mostly due to the inaccuracy of MRP, that more or less ignores safety time, safety stocks and lotsize flexibility in the calculation of reschedule-in messages. Reschedule-out messages are usually ignored because planners do not see the value of the message. Other reasons for not adhering to rescheduling messages are a lack of maintenance of MRP parameters or simply the wrong use of the MRP function. In the future, MRP rescheduling functionality will be used even less than today, due to the changing role of MRP within the planning framework. With the uprise of finite capacity scheduling packages, MRP is being pushed one level upward in the planning hierarchy. This means that rescheduling functionalities for the short term will become completely obsolete in MRP systems.     

The Risk Perception Paradox—Implications for Governance and Communication of Natural Hazards

This article reviews the main insights from selected literature on risk perception, particularly in connection with natural hazards. It includes numerous case studies on perception and social behavior dealing with floods, droughts, earthquakes, volcano eruptions, wild fires, and landslides. The review reveals that personal experience of a natural hazard and trust—or lack of trust—in authorities and experts have the most substantial impact on risk perception. Cultural and individual factors such as media coverage, age, gender, education, income, social status, and others do not play such an important role but act as mediators or amplifiers of the main causal connections between experience, trust, perception, and preparedness to take protective actions. When analyzing the factors of experience and trust on risk perception and on the likeliness of individuals to take preparedness action, the review found that a risk perception paradox exists in that it is assumed that high risk perception will lead to personal preparedness and, in the next step, to risk mitigation behavior. However, this is not necessarily true. In fact, the opposite can occur if individuals with high risk perception still choose not to personally prepare themselves in the face of a natural hazard. Therefore, based on the results of the review, this article offers three explanations suggesting why this paradox might occur. These findings have implications for future risk governance and communication as well as for the willingness of individuals to invest in risk preparedness or risk mitigation actions.     

Further specification of the leader political skill–leadership effectiveness relationships: Transformational and transactional leader behavior as mediators

The present investigation was a three-source test of the intermediate linkages in the leader political skill–leader effectiveness and follower satisfaction relationships, which examined transformational and transactional (i.e., contingent reward behavior) leader behavior as mediators. Data from 408 leaders (headmasters) and 1429 followers (teachers) of state schools in the western part of Germany participated in this research. The results of mediation analyses, based on bias-corrected bootstrapping confidence intervals, provided support for the hypotheses that political skill predicts both transformational and transactional leader behavior, beyond other established predictors, and that transformational and transactional leader behavior mediate the relationships between leader political skill and leadership effectiveness. The contributions to theory and research, strengths and limitations, directions for future research, and practical implications are discussed.     

Serial dependence and regression of Poisson INARMA models

Time series of counts occur in many fields of practice, with the Poisson distribution as a popular choice for the marginal process distribution. A great variety of serial dependence structures of stationary count processes can be modelled by the INARMA family. In this article, we propose a new approach to the INMA(q) family in general, including previously known results as special cases. In the particular case of Poisson marginals, we will derive new results concerning regression properties and the serial dependence structure of INAR(1) and INMA(q) models. Finally, we present explicit expressions for the distribution of jumps in such processes.     

On robust forecasting in dynamic vector time series models

In this article, robust estimation and prediction in multivariate autoregressive models with exogenous variables (VARX) are considered. The conditional least squares (CLS) estimators are known to be non-robust when outliers occur. To obtain robust estimators, the method introduced in Duchesne [2005. Robust and powerful serial correlation tests with new robust estimates in ARX models. J. Time Ser. Anal. 26, 49–81] and Bou Hamad and Duchesne [2005. On robust diagnostics at individual lags using RA-ARX estimators. In: Duchesne, P., Rémillard, B. (Eds.), Statistical Modeling and Analysis for Complex Data Problems. Springer, New York] is generalized for VARX models. The asymptotic distribution of the new estimators is studied and from this is obtained in particular the asymptotic covariance matrix of the robust estimators. Classical conditional prediction intervals normally rely on estimators such as the usual non-robust CLS estimators. In the presence of outliers, such as additive outliers, these classical predictions can be severely biased. More generally, the occurrence of outliers may invalidate the usual conditional prediction intervals. Consequently, the new robust methodology is used to develop robust conditional prediction intervals which take into account parameter estimation uncertainty. In a simulation study, we investigate the finite sample properties of the robust prediction intervals under several scenarios for the occurrence of the outliers, and the new intervals are compared to non-robust intervals based on classical CLS estimators.     

Judgment aggregation without full rationality

Several recent results on the aggregation of judgments over logically connected propositions show that, under certain conditions, dictatorships are the only propositionwise aggregation functions generating fully rational (i.e., complete and consistent) collective judgments. A frequently mentioned route to avoid dictatorships is to allow incomplete collective judgments. We show that this route does not lead very far: we obtain oligarchies rather than dictatorships if instead of full rationality we merely require that collective judgments be deductively closed, arguably a minimal condition of rationality, compatible even with empty judgment sets. We derive several characterizations of oligarchies and provide illustrative applications to Arrowian preference aggregation and Kasher and Rubinstein’s group identification problem. This paper was circulated in August 2006 and presented at the Yale workshop on Aggregation of Opinions, September 2006, at the Centre interuniversitaire de rechere en économie quantitative, Montreal, October 2006, and at the 1st International Workshop on Computational Social Choice, Amsterdam, December 2006. We are grateful to the participants at these occasions and the anonymous referees for comments. We also thank Ton Storcken for discussion. Elad Dokow and Ron Holzman have independently proved closely related results, which were also presented at the Yale workshop in September 2006, and circulated in the December 2006 paper (Dokow and Holzman 2006).