Learning about radon's risk

This article reports the results of an evaluation of the effectiveness of different types of information materials in communicating the risk from exposure to radon, a naturally occurring indoor air pollutant. The study involved a panel of 2300 homeowners who actually experienced risks from radon, and the information program used to explain these risks. The analysis considered information transfer and performance on specific tasks requiring information on the risk from radon to measure learning. The results suggest a systematic learning process, but indicate that the process can be influenced by how risk information is presented.     

A slacks-based inefficiency measure for a two-stage system with bad outputs

We model the performance of DMUs (decision-making units) using a two-stage network model. In the first stage of production DMUs use inputs to produce an intermediate output that becomes an input to a second stage where final outputs are produced. Previous black box DEA models allowed for non-radial scaling of outputs and inputs and accounted for slacks in the constraints that define the technology. We extend these models and build a performance measure that accounts for a network structure of production. We use our method to estimate the performance of Japanese banks, which use labor, physical capital, and financial equity capital in a first stage to produce an intermediate output of deposits. In the second stage, those deposits become an input in the production of loans and securities investments. The network estimates reveal greater bank inefficiency than do the estimates that treat the bank production process as a black box with all production taking place in a single stage.     

Robustness of Risk Maps and Survey Networks to Knowledge Gaps About a New Invasive Pest

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk‐ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.     

Now What Do People Know About Global Climate Change? Survey Studies of Educated Laypeople

In 1992, a mental‐models‐based survey in Pittsburgh, Pennsylvania, revealed that educated laypeople often conflated global climate change and stratospheric ozone depletion, and appeared relatively unaware of the role of anthropogenic carbon dioxide emissions in global warming. This study compares those survey results with 2009 data from a sample of similarly well‐educated laypeople responding to the same survey instrument. Not surprisingly, following a decade of explosive attention to climate change in politics and in the mainstream media, survey respondents in 2009 showed higher awareness and comprehension of some climate change causes. Most notably, unlike those in 1992, 2009 respondents rarely mentioned ozone depletion as a cause of global warming. They were also far more likely to correctly volunteer energy use as a major cause of climate change; many in 2009 also cited natural processes and historical climatic cycles as key causes. When asked how to address the problem of climate change, while respondents in 1992 were unable to differentiate between general “good environmental practices” and actions specific to addressing climate change, respondents in 2009 have begun to appreciate the differences. Despite this, many individuals in 2009 still had incorrect beliefs about climate change, and still did not appear to fully appreciate key facts such as that global warming is primarily due to increased concentrations of carbon dioxide in the atmosphere, and the single most important source of this carbon dioxide is the combustion of fossil fuels.     

Hierarchical linear modeling as an example for measuring change over time in a leadership development evaluation context

One of the difficulties in evaluating leadership development is measuring whether and how people change over the time period of the leadership development initiative. Even when change over time is an inherent part of the design and evaluation of leadership development, events may occur outside of the control of evaluators that limit the effectiveness of adequately and accurately assessing change over time. With data from a leadership development initiative designed to account for change over time, this article suggests hierarchical linear modeling (HLM) as a multilevel methodological technique to assess change over time in a leadership development context. This article will use real change over time data from a leadership development initiative and discuss the logic and rationale of HLM. We use HLM as an example of a multilevel methodological tool to investigate typical change over time questions in leadership development evaluation.     

Using Malmquist Indexes to measure changes in the productivity and efficiency of US accounting firms before and after the Sarbanes–Oxley Act

There have been many criticisms of the Sarbanes–Oxley (SOX) Act passed in July of 2002 to correct business accountability and performance practices. The act has a major emphasis on accounting and its practices. This paper attempts a response to these criticisms by investigating changes in productive efficiency for 62 of the largest US public accounting firms between the periods (2000–2001) and (2003–2004)—the periods before and after enactment of SOX in July of 2002. DEA is used to calculate Malmquist indexes of productivity and efficiency changes. This index is used because it can distinguish between changes in technical efficiency, which limit the possibilities, and changes in the performance efficiencies for each firm. Contrary to many of the criticisms, results indicate that accounting firms have exhibited significant post SOX growth in productive efficiency which is better than pre-SOX performances.     

Examining Facilitative Configurations of Entrepreneurially Oriented Growth: An Information Processing Perspective

This study examines how the relationship between entrepreneurial orientation and firm growth is shaped by learning orientation in technologically sophisticated environments. We draw upon an information processing perspective that emphasizes alignment between information processing demands and support mechanisms. Using data from 116 small to medium‐sized enterprises in the Netherlands, we observe that the ability of entrepreneurial orientation to drive firm growth greatly depends on the joint consideration of technological sophistication and learning orientation. Our findings contribute to a better understanding of how configurations of strategic orientations and environmental considerations work in concert to influence the efficacy of organizational entrepreneurial efforts dramatically.