Relevance of Risk Predictions Derived from a Chronic Species Sensitivity Distribution with Cadmium to Aquatic Populations and Ecosystems

Criteria to protect aquatic life are intended to protect diverse ecosystems, but in practice are usually developed from compilations of single‐species toxicity tests using standard test organisms that were tested in laboratory environments. Species sensitivity distributions (SSDs) developed from these compilations are extrapolated to set aquatic ecosystem criteria. The protectiveness of the approach was critically reviewed with a chronic SSD for cadmium comprising 27 species within 21 genera. Within the data set, one genus had lower cadmium effects concentrations than the SSD fifth percentile‐based criterion, so in theory this genus, the amphipod Hyalella, could be lost or at least allowed some level of harm by this criteria approach. However, population matrix modeling projected only slightly increased extinction risks for a temperate Hyalella population under scenarios similar to the SSD fifth percentile criterion. The criterion value was further compared to cadmium effects concentrations in ecosystem experiments and field studies. Generally, few adverse effects were inferred from ecosystem experiments at concentrations less than the SSD fifth percentile criterion. Exceptions were behavioral impairments in simplified food web studies. No adverse effects were apparent in field studies under conditions that seldom exceeded the criterion. At concentrations greater than the SSD fifth percentile, the magnitudes of adverse effects in the field studies were roughly proportional to the laboratory‐based fraction of species with adverse effects in the SSD. Overall, the modeling and field validation comparisons of the chronic criterion values generally supported the relevance and protectiveness of the SSD fifth percentile approach with cadmium.     

The Determinants of Management Development: The Views of MBA Graduates

This article is derived from survey data obtained from a structured sample of 450 MBA graduates and is part of a wider programme of research investigating the current state of management development in Britain. The intention is to analyse the determinants of the amount, the methods and the impact of management development systems in UK organizations and to assess these findings in relation to a comparable analysis of HRD managers. Both the amount and the variety of management development methods are greater than has been previously reported and, for the HRD sample, the impact of this activity is broadly positive. While agreeing on the amount, MBA managers are less enthusiastic about the availability and effectiveness of management development they have experienced. Overall, the management development policy choices made by organizations are consistently the most influential in determining outcomes, and the implications for this are discussed.     

Joint Ordering and Pricing Strategies for Managing Substitutable Products

Starr and Rubinson (1978) develop a model to establish the relationship between product demand and relative prices. The notion of relative prices motivates us to consider a situation in which a retailer would either charge the same retail price for all products if he adopts a ‘fixed’ pricing strategy or charge different prices for different products if he adopts a ‘variable’ pricing strategy. In this paper, we develop a base model with deterministic demand that is intended to examine how a retailer should jointly determine the order quantity and the retail price of two substitutable products under the fixed and variable pricing strategies. Our analysis indicates that the optimal retail price under the variable pricing strategy is equal to the optimal retail price under the fixed pricing strategy plus or minus an adjustment term. This adjustment term depends on product substitutability and price sensitivity. We also present two different extensions of our base model. In the first extension, our analysis indicates that the underlying structure of the optimal retail price and order quantity is preserved when there is a limit on the total order quantity. The second extension deals with the issue of retail competition. Relative to the base case, we show that the underlying structure of the optimal retail price and order quantity is preserved in a duopolistic environment. Moreover, our analysis suggests that both retailers would adopt the variable pricing strategy at the equilibrium.     

The competitive advantage: strategic thinking for physician leaders

Physician executives should manage their career strategies like a well-run company. Learn how to start thinking aout your career strategy.     

Institutional theory-based research on corporate social responsibility: Bringing values back in

Research applying institutional theory to corporate social responsibility (CSR) has experienced remarkable momentum. Institutional theory-based CSR research illustrates the role of values in guiding both agentic choices for CSR and the influence of institutional structures on CSR agency. Although values have been explored in this literature, systematic studies of values that seek to gain insights into the mutual relationship between agentic choices and structures are lacking. Such insights are crucial for exploring whether and how CSR is enabled or constrained. We thus ask two interrelated questions: (1) What is the role of values in institutional theory-based CSR research? (2) How and along which avenues should future institutional theory-based CSR research that focuses on values be mobilised? Based on our analysis of this line of literature from 1989 until 2021, first, we take stock of established institutional theory perspectives on CSR and disentangle what role values have played in this literature. Second, we outline how to mobilise values in future institutional CSR research based on four promising but under-investigated areas. From our literature analysis, two central functions emerge (which we label ‘bridging’ and ‘referencing’) that values can perform in the institutional analysis of CSR. Based on these two functions, our values-focused framework will help scholars examine the moral foundations that inform business–society interactions as well as understand how companies can responsibly manage those interactions with societal stakeholders.     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

Reduction of bias and skewness with applications to second order accuracy

Suppose [^(q)]{\widehat{\theta}} is an estimator of θ in \mathbbR{\mathbb{R}} that satisfies the central limit theorem. In general, inferences on θ are based on the central limit approximation. These have error O(n ^−1/2), where n is the sample size. Many unsuccessful attempts have been made at finding transformations which reduce this error to O(n ⁻¹). The variance stabilizing transformation fails to achieve this. We give alternative transformations that have bias O(n ⁻²), and skewness O(n ⁻³). Examples include the binomial, Poisson, chi-square and hypergeometric distributions.     

Relation of Goal Setting and Goal Sharing to Performance and Conflict for Interdependent Tasks

Despite the prevalence of goal setting in organizations, researchers have not thoroughly examined the implications of goal setting to work outcomes in interdependent work settings. A field survey (n= 442) assessed the relation of goal setting and goal sharing, the extent to which others are aware of an individual's work goal, to performance and conflict across varying levels of task interdependence. The results of moderated regression analyses demonstrate that in highly interdependent tasks, the use of goal setting resulted in lower performance levels. Moreover, goal setting and goal sharing in highly interdependent tasks resulted in individuals' reporting more somatic symptoms. The results are discussed in terms of clarifying the role of goal setting for interdependent tasks.