Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.     

Correlational biases in mean response latency differences

Multifarious psychological constructs are indexed by the mean latency difference (MLD), the within-subject difference between mean response latency on two tasks. Two associations consistently emerge in mean latency data. Firstly, across subjects, mean latencies on distinct tasks are positively correlated. This correlation arises from individual differences in general rates of information processing that are a shared influence on response latency in diverse tasks. Secondly, across tasks, the mean and variance of mean latency are positively correlated. Compared to a simple task, a complex task has both a larger average mean latency and a larger variance of mean latency, across subjects. Taken together, these associations make the interpretation of the MLD problematic by biasing correlations between the MLD and (a) task mean latencies, (b) the average of the mean latencies, (c) external criteria, and (d) other MLDs. A variety of mean latency transformations were evaluated and, while they differed in their effectiveness, they did not satisfactorily rectify MLD biases. An alternative approach, focusing on scale invariant contrasts of within-subject response latency distributions, is introduced in the conclusion.     

Electronic Data Interchange: Research Review and Future Directions*

For nearly two decades, electronic data interchange (EDI) has been widely viewed as a technology pivotal to supply chain management that has also provided benefits to firms on multiple levels. Despite a substantial body of literature, there are a number of conflicting and inconclusive research results in this field. In this study, we synthesize the diverse body of research in EDI by organizing the literature into an initial theoretical framework. Based on a meta‐analysis of results from the empirical literature, we seek to clarify conflicting results from the literature in order to develop a more unified theoretical framework of contextual variables associated with EDI adoption factors and outcomes. From a managerial standpoint, our literature‐based framework offers a set of guidelines for making successful EDI adoption and implementation decisions.     

Uncertainty Analysis Based on Probability Bounds (P-Box) Approach in Probabilistic Safety Assessment

A wide range of uncertainties will be introduced inevitably during the process of performing a safety assessment of engineering systems. The impact of all these uncertainties must be addressed if the analysis is to serve as a tool in the decision-making process. Uncertainties present in the components (input parameters of model or basic events) of model output are propagated to quantify its impact in the final results. There are several methods available in the literature, namely, method of moments, discrete probability analysis, Monte Carlo simulation, fuzzy arithmetic, and Dempster-Shafer theory. All the methods are different in terms of characterizing at the component level and also in propagating to the system level. All these methods have different desirable and undesirable features, making them more or less useful in different situations. In the probabilistic framework, which is most widely used, probability distribution is used to characterize uncertainty. However, in situations in which one cannot specify (1) parameter values for input distributions, (2) precise probability distributions (shape), and (3) dependencies between input parameters, these methods have limitations and are found to be not effective. In order to address some of these limitations, the article presents uncertainty analysis in the context of level-1 probabilistic safety assessment (PSA) based on a probability bounds (PB) approach. PB analysis combines probability theory and interval arithmetic to produce probability boxes (p-boxes), structures that allow the comprehensive propagation through calculation in a rigorous way. A practical case study is also carried out with the developed code based on the PB approach and compared with the two-phase Monte Carlo simulation results.     

Work, employment, and mental illness: expanding the domain of Canadian social work

Despite established evidence that work and employment are an important component of recovery for people who experience mental illness, social work education in Canada seldom offers graduate training or courses on the significance of work in peoples' lives or on the practices involved in helping to gain and retain employment for these individuals. In this article the authors argue that the high levels of unemployment among people who experience mental illness, and the rising incidence of mental health and addictions issues in workplaces, offer the opportunity, as well as the mandate, for social work educators to provide professional education in the area of employment support and assistance.     

Association of Family Challenges with Self-esteem and Perceived Social Support among Indian Adolescents

The family micro-system is important in the development of any individual. Defects or deviations in its normative functioning affect the development of a child. These defects may include child maltreatment or abuse, be it physical, sexual, emotional, or neglect. Within this domain, in our view, there does not appear to be adequate development related to the understanding of, and intervention for, emotional abuse. Emotional abuse extends from explicit acts to invisible causative factors of neglect or humiliation. In this work, through quantitative and qualitative empirical evidence, we have attempted to associate family challenges with self-esteem (SE) and perceived social support. The study was carried out on a sample of early-adolescent high school students in the state of Kerala, India. We found a significant difference in SE between adolescents who reported challenges at home and those who did not. We also observed the limited role of age as a determinant in this differentiation. The current work serves to significantly supplement the understanding of causal relationships in the discourse on emotional abuse in the context of child development.     

Operational Productivity,Corporate Social Performance,Financial Performance,and Risk in Manufacturing Firms

We examine the relationship between Operational Productivity (OP), Corporate Social Performance (CSP), Financial Performance (FP), and risk. Our sample frame comprises 476 firms in nine US manufacturing industries during the period 1999–2009. We employ DEA‐based measures for OP and CSP, two operationalizations for FP to reflect current profitability and market value, and two operationalizations for risk to reflect bankruptcy risk and stock price volatility. We confirm that OP is essential for good financial performance and reduced risk (as expected), but the main effects of CSP are mixed. Importantly, we find that OP moderates the CSP–FP and CSP–risk relationships. Specifically, if OP is poor, CSP is of limited benefit to FP or risk. However, at or above a threshold level of OP, firms can use CSP to build upon it to yield further improvements in FP and reductions in risk. We discuss the implications of our findings for theory and practice.     

An economic reliability test plan: Log-logistic distribution

Sampling plans in which items that are put to test, to collect the life of the items in order to decide upon accepting or rejecting a submitted lot, are called reliability test plans. The basic probability model of the life of the product is specified as the well-known log-logistic distribution with a known shape parameter. For a given producer's risk, sample size, termination number, and waiting time to terminate the test plan are computed. The preferability of the test plan over similar plans existing in the literature is established with respect to cost and time of the experiment.     

Social Policy Practice

This paper identifies and discusses issues for a school of social work in the context of collective bargaining. Attention is given to the implications of collective bargaining on a professional social work program. The paper is based on a theoretical framework and an experience of approximately three years in the advent and development of collective bargaining in a large midwestern public university. Major substantive areas discussed have to do with intragroup and intergroup relations among students, community professionals, faculty and administration; the definition of “work” and “work load”; and the reward system for promotion, tenure, and recognition of merit. Major implications relate to the concerns of professionalism, the balancing of. democratic participation and responsible management, and the codification in contract of social work's historical role in participatory decision making.     

Offshoring Business Process Services and Governance Control Mechanisms: An Examination of Service Providers from India

As emerging markets increasingly rely on service businesses through offshore outsourcing, we examine the role of governance control mechanisms in improving performance among business process outsourcing (BPO) service providers in India. Using data collected from 205 emerging market‐based BPO service providers in India, we examine the antecedents and consequences of establishing governance control mechanisms in BPO service providers. Specifically, we examine how structural (use of contracts with the client), administrative (effective allocation and demarcation of responsibilities within the firm), and relational (collaboration and information sharing with the client) mechanisms drive the performance of a BPO service provider operating in an emerging market. We also examine how key task‐related (task connectivity and task security) and client‐related (end customer orientation and global control) antecedents influence the use of different governance control approaches in this environment. Our analysis finds that both task connectivity and task security significantly impact use of structural and administrative mechanisms, whereas end customer orientation is significantly associated with the strength of the relational mechanisms governing the emerging market‐based BPO service provider and its client. Further global control significantly influences the strength of the structural mechanisms between the client and the BPO service provider. Finally, the three mechanisms have a complementary influence in driving the BPO service provider's performance.