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.     

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.     

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.     

A Systematic Uncertainty Analysis of an Evaluative Fate and Exposure Model

Multimedia fate and exposure models are widely used to regulate the release of toxic chemicals, to set cleanup standards for contaminated sites, and to evaluate emissions in life-cycle assessment. CalTOX, one of these models, is used to calculate the potential dose, an outcome that is combined with the toxicity of the chemical to determine the Human Toxicity Potential (HTP), used to aggregate and compare emissions. The comprehensive assessment of the uncertainty in the potential dose calculation in this article serves to provide the information necessary to evaluate the reliability of decisions based on the HTP A framework for uncertainty analysis in multimedia risk assessment is proposed and evaluated with four types of uncertainty. Parameter uncertainty is assessed through Monte Carlo analysis. The variability in landscape parameters is assessed through a comparison of potential dose calculations for different regions in the United States. Decision rule uncertainty is explored through a comparison of the HTP values under open and closed system boundaries. Model uncertainty is evaluated through two case studies, one using alternative formulations for calculating the plant concentration and the other testing the steady state assumption for wet deposition. This investigation shows that steady state conditions for the removal of chemicals from the atmosphere are not appropriate and result in an underestimate of the potential dose for 25% of the 336 chemicals evaluated.     

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.     

The Informal Sector: A Review and Agenda for Management Research

Despite its connotations of non‐compliance, illegality, social exploitation and marginality, the informal sector is a substantial contributor to economic life in developing countries and, increasingly, in more technologically advanced activities. Its prevalence in developed economies has also become more widely recognized. In light of its significance, this paper reviews research on the informal sector from a management and organization scholarship perspective, rather than from an entrepreneurship view, as has been the focus until now. It sets out the atypical management practices that are inherent in the sector, explores the under‐researched relationship between formal and informal firms, and highlights definitional, conceptual and other limitations in extant research. As a step in resolving these issues, the authors present a conceptual model of formality and informality in a three‐dimensional framework that highlights an organizational infrastructure dimension, a view of firms operating along a continuum, and a multi‐level analytical context. Building on this, the authors detail opportunities for enhanced appreciation of in situ management and organizational practices in the informal sector and outline tools for pursuing a management and organization scholarship agenda. Overall, the authors argue that management scholarship has great potential to improve understanding of the informal sector, and that the informal sector provides opportunities to advance management theory, research and practice.