Exposure Assessment for Pesticide Intake from Multiple Food Products: A Bayesian Latent‐Variable Approach

Pesticide risk assessment for food products involves combining information from consumption and concentration data sets to estimate a distribution for the pesticide intake in a human population. Using this distribution one can obtain probabilities of individuals exceeding specified levels of pesticide intake. In this article, we present a probabilistic, Bayesian approach to modeling the daily consumptions of the pesticide Iprodione though multiple food products. Modeling data on food consumption and pesticide concentration poses a variety of problems, such as the large proportions of consumptions and concentrations that are recorded as zero, and correlation between the consumptions of different foods. We consider daily food consumption data from the Netherlands National Food Consumption Survey and concentration data collected by the Netherlands Ministry of Agriculture. We develop a multivariate latent‐Gaussian model for the consumption data that allows for correlated intakes between products. For the concentration data, we propose a univariate latent‐t model. We then combine predicted consumptions and concentrations from these models to obtain a distribution for individual daily Iprodione exposure. The latent‐variable models allow for both skewness and large numbers of zeros in the consumption and concentration data. The use of a probabilistic approach is intended to yield more robust estimates of high percentiles of the exposure distribution than an empirical approach. Bayesian inference is used to facilitate the treatment of data with a complex structure.     

INCLUDING ENGINEERING IN OPERATIONS STRATEGY

Today's markets are characterized by time and product quality-based competition. Companies must compete through their ability to manage the whole cycle of product realization and delivery, from the initial concept through to delivery and support at the customer. They must do this through managing an integrated company, not a set of separate functions. This paper addresses the issue of how companies should develop operations strategies for engineering and manufacturing combined. It uses field research into 15 engineering companies to develop the concept of the manufacturing system mission, and proposes strategic choices for manufacturing, engineering and linked functions.     

Interface Style and Training Task Difficulty as Determinants of Effective Computer-Assisted Knowledge Transfer*

The transfer of expert knowledge to novices is one means of improving decision quality. Research needs to identify (1) the knowledge to be transferred to novices, and (2) the best method for transferring that knowledge. Studies that compare the judgment behavior of experienced and novice auditors address the first issue. The present study addresses the second issue in the context of using a computer-assisted training (CAT) program. CAT was selected for study because of evidence that it can both improve the effectiveness and reduce the costs of training. An experiment was conducted in which two factors were manipulated: (1) the design of the human-computer interface of the CAT program, and (2) the content of training tasks. The judgment of interest involved causal reasoning about the relationships between various internal control procedures and possible errors. The results indicate that alternative styles of interaction with a CAT program differ in terms of learning effectiveness. In addition, there was also evidence that training task content affected learning.