Managing electronic documents and work flows: Enterprise content management at work in nonprofit organizations

Web management and knowledge management systems have made significant technological advances, culminating in large information management systems such as enterprise content management (ECM). ECM is a Web‐based publishing system that manages large numbers of electronic documents and other Web assets intended for publication to Web portals and other complex Web sites. Work in nonprofit organizations can benefit from adopting new communication technologies that promote collaboration and enterprisewide knowledge management. The unique characteristics of ECM are enumerated and analyzed from a knowledge management perspective. We identify three stages of document life cycles in ECM implementations—content, reification, and commodification/process—as the content management model. We present the model as a mechanism for decision makers and scholars to use in evaluating the organizational impacts of systems such as ECM. We also argue that decision makers in nonprofit organizations should take care to avoid overly commodifying business processes in the final stage, where participation may be more beneficial than efficiency.     

Use of Quality-Adjusted Life Year Weights with Dose-Response Models for Public Health Decisions: A Case Study of the Risks and Benefits of Fish Consumption

Risks associated with toxicants in food are often controlled by exposure reduction. When exposure recommendations are developed for foods with both harmful and beneficial qualities, however, they must balance the associated risks and benefits to maximize public health. Although quantitative methods are commonly used to evaluate health risks, such methods have not been generally applied to evaluating the health benefits associated with environmental exposures. A quantitative method for risk-benefit analysis is presented that allows for consideration of diverse health endpoints that differ in their impact (i.e., duration and severity) using dose-response modeling weighted by quality-adjusted life years saved. To demonstrate the usefulness of this method, the risks and benefits of fish consumption are evaluated using a single health risk and health benefit endpoint. Benefits are defined as the decrease in myocardial infarction mortality resulting from fish consumption, and risks are defined as the increase in neurodevelopmental delay (i.e., talking) resulting from prenatal methylmercury exposure. Fish consumption rates are based on information from Washington State. Using the proposed framework, the net health impact of eating fish is estimated in either a whole population or a population consisting of women of childbearing age and their children. It is demonstrated that across a range of fish methylmercury concentrations (0-1 ppm) and intake levels (0-25 g/day), individuals would have to weight the neurodevelopmental effects 6 times more (in the whole population) or 250 times less (among women of child-bearing age and their children) than the myocardial infarction benefits in order to be ambivalent about whether or not to consume fish. These methods can be generalized to evaluate the merits of other public health and risk management programs that involve trade-offs between risks and benefits.     

Nuclear Waste Management under Approaching Disaster: A Comparison of Decommissioning Strategies for the German Repository Asse II

This article compares different strategies for handling low‐ and medium‐level nuclear waste buried in a retired potassium mine in Germany (Asse II) that faces significant risk of uncontrollable brine intrusion and, hence, long‐term groundwater contamination. We survey the policy process that has resulted in the identification of three possible so‐called decommissioning options: complete backfilling, relocation of the waste to deeper levels in the mine, and retrieval. The selection of a decommissioning strategy must compare expected investment costs with expected social damage costs (economic, environmental, and health damage costs) caused by flooding and subsequent groundwater contamination. We apply a cost minimization approach that accounts for the uncertainty regarding the stability of the rock formation and the risk of an uncontrollable brine intrusion. Since economic and health impacts stretch out into the far future, we examine the impact of different discounting methods and rates. Due to parameter uncertainty, we conduct a sensitivity analysis concerning key assumptions. We find that retrieval, the currently preferred option by policymakers, has the lowest expected social damage costs for low discount rates. However, this advantage is overcompensated by higher expected investment costs. Considering all costs, backfilling is the best option for all discounting scenarios considered.     

Machine Learning Methods as a Tool for Predicting Risk of Illness Applying Next‐Generation Sequencing Data

Next‐generation sequencing (NGS) data present an untapped potential to improve microbial risk assessment (MRA) through increased specificity and redefinition of the hazard. Most of the MRA models do not account for differences in survivability and virulence among strains. The potential of machine learning algorithms for predicting the risk/health burden at the population level while inputting large and complex NGS data was explored with Listeria monocytogenes as a case study. Listeria data consisted of a percentage similarity matrix from genome assemblies of 38 and 207 strains of clinical and food origin, respectively. Basic Local Alignment (BLAST) was used to align the assemblies against a database of 136 virulence and stress resistance genes. The outcome variable was frequency of illness, which is the percentage of reported cases associated with each strain. These frequency data were discretized into seven ordinal outcome categories and used for supervised machine learning and model selection from five ensemble algorithms. There was no significant difference in accuracy between the models, and support vector machine with linear kernel was chosen for further inference (accuracy of 89% [95% CI: 68%, 97%]). The virulence genes FAM002725, FAM002728, FAM002729, InlF, InlJ, Inlk, IisY, IisD, IisX, IisH, IisB, lmo2026, and FAM003296 were important predictors of higher frequency of illness. InlF was uniquely truncated in the sequence type 121 strains. Most important risk predictor genes occurred at highest prevalence among strains from ready‐to‐eat, dairy, and composite foods. We foresee that the findings and approaches described offer the potential for rethinking the current approaches in MRA.     

How Within-Study Comparisons can Inform Research and Evaluation Design for the Third Sector

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Within-study comparisons (WSCs) compare quasi-experimental results to an experimental benchmark and assess the extent to...     

Brand Awareness and Attitudes Towards Political Advertisements in Sport Video Games

Due to the growth of the video game industry, the practice of in-game advertising, and the desirable game player demographics, then U.S. Presidential candidate Barack Obama placed early voting advertisements in a series of online sport video games during his 2008 presidential campaign. The purpose of this study was to examine the awareness of these political ads and the attitudes towards the ads when compared to advertisements featuring corporate brands. The results suggest there were higher levels of awareness for the political themed advertisements while attitude enhancement was more likely to occur for advertisements which featured corporate brands.