Managing from the Inside Out: Drawing on 'Receptivity' to Explain Variation in Strategy Implementation

With the rise of 'New Public Management' (NPM), government policy has encouraged public-sector organizations to downsize and outsource their services. There is, however, local variation in the use of outsourcing – this is 'managing from the inside out'. This paper draws on the notion of receptivity for organizational change to explain variation in strategy implementation. Four receptivity factors are identified which seem to explain the success of two contrasting English local government outsourcing strategies: ideological vision, leading change, institutional politics and implementation capacity. The organization level of change is interconnected with two other levels of change (the public service and environment levels) to illustrate the dynamic nature of change.     

The efficacy of using judgmental versus quantitative forecasting methods in practice

In an era where forecasts drive entire supply chains forecasting is seen as an increasingly critical organizational capability. However, business forecasting continues to rely on judgmental methods despite large advancements in information technology and quantitative method capability, prompting calls for research to help understand the reasons behind this practice. Our study is designed to contribute to this knowledge by profiling differences between firms identified as primary users of either judgmental or quantitative forecasting methods. Relying on survey data from 240 firms we statistically analyzed differences between these categories of users based on a range of organizational and forecasting issues. Our study finds large differences in forecast error rates between the two groups, with users of quantitative methods significantly outperforming users of judgmental methods. The former are found to be equally prevalent regardless of industry, firm size, and product positioning strategy, documenting the benefits of quantitative method use in a variety of settings. By contrast, the latter are found to have significantly lower access to quantifiable data and to use information and technology to a lesser degree.     

ATSDR Science Panel on the Bioavailability of Mercury in Soils: Lessons Learned

On the basis of discussion and analysis during and following an ATSDR science panel on the bioavailability of mercury in soils, it is apparent that the default assumption of 100% relative bioavailability for mercury-contaminated soils is excessively conservative. However, current knowledge does not allow the development of default assumptions or guidelines for determining relative bioavailability of mercury in soils. Until such default assumptions or guidelines can be developed, site-specific assays of bioavailability, preferably using either animal bioassays or validated in vitro techniques, may provide the best approach for estimating soil-mercury bioavailability.     

On the effectiveness of cognitive feedback from an interface agent

The objective of this study was to determine the impact of task information (TI) provided by an interface agent during the idea evaluation and integration step of the problem formulation stage of the problem solving process. The effectiveness assessment was based on solving diagnostic decision problems in the domain of complex industrial machinery. Ten domain experts participated in this study. Decision support was provided by a case-based reasoning system. Findings suggest that TI provided by the interface agent had no effect on the decision maker's performance, nor on the associated cognitive effort. However, a verbal protocol analysis revealed that the ten subjects used the interface agent to verify their decision processes. The results and their implications are discussed with respect to current findings in the area of decision support systems.     

Microaggressions,perceptions of campus climate,mental health,and alcohol use among first-year college students of color

Depressive and anxiety symptoms are increasingly common, and problematic alcohol use remains prevalent in college. To expand on prior research on mostly white samples, we surveyed first-year students of color from our predominately white university (Southeastern US) to identify risk factors for mental health symptoms and potentially co-occurring problematic alcohol use. Results showed significant associations between microaggressions and poor campus climate (hypothetical predictors) with depressive, anxiety, somatic symptoms (hypothetical outcomes) that were indirectly linked through perceived stress, poor sleep, and academic burnout (hypothetical mediators). Poor campus climate, academic burnout, and using alcohol to cope were the most relevant to alcohol use disorder symptoms. Results support efforts to address and reduce racial microaggressions and promote a positive campus climate for all.     

A MINIMUM-COST AUDIT SAMPLING METHODOLOGY UNDER CONDITIONS OF PREDETERMINED BETA RISK

This paper presents a minimum-cost methodology for determining a statistical sampling plan in substantive audit tests. In this model, the auditor specifies β, the risk of accepting an account balance as correct when it is not, according to audit evidence requirements. Using β as a constraint, the auditor then selects a sampling plan to optimize the trade-off between sampling costs and the costs of follow-up audit procedures. Tables to aid in this process and an illustration are provided.     

离村与不离村:发现与思考

社会人口流动和城市化在中国和全球范围内不断地加强,这些都为中国大多数的农村青年提供了机遇.同时,大量的人口仍然留守农村,无论流动人口输出地有多么偏僻,它们仍继续与日新月异的城市密不可分.正因为如此,农村居民对城市和国家的发展与未来发挥着同等重要的内在作用.     

Construction Safety Risk Modeling and Simulation

By building on a genetic‐inspired attribute‐based conceptual framework for safety risk analysis, we propose a novel approach to define, model, and simulate univariate and bivariate construction safety risk at the situational level. Our fully data‐driven techniques provide construction practitioners and academicians with an easy and automated way of getting valuable empirical insights from attribute‐based data extracted from unstructured textual injury reports. By applying our methodology on a data set of 814 injury reports, we first show the frequency‐magnitude distribution of construction safety risk to be very similar to that of many natural phenomena such as precipitation or earthquakes. Motivated by this observation, and drawing on state‐of‐the‐art techniques in hydroclimatology and insurance, we then introduce univariate and bivariate nonparametric stochastic safety risk generators based on kernel density estimators and copulas. These generators enable the user to produce large numbers of synthetic safety risk values faithful to the original data, allowing safety‐related decision making under uncertainty to be grounded on extensive empirical evidence. One of the implications of our study is that like natural phenomena, construction safety may benefit from being studied quantitatively by leveraging empirical data rather than strictly being approached through a managerial perspective using subjective data, which is the current industry standard. Finally, a side but interesting finding is that in our data set, attributes related to high energy levels (e.g., machinery, hazardous substance) and to human error (e.g., improper security of tools) emerge as strong risk shapers.