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This paper aims to provide a comprehensive insight into the role of mindfulness in organizational settings. A daily experience sampling method was used to explore the mechanism through which state mindfulness influences employees' work attentiveness. By collecting data from 153 full-time Chinese employees over 5 consecutive days, we used 765 matched cases to conduct a multilevel structural equation model with random slopes to test the conceptual model. The results showed that: 1) daily state mindfulness is positively related to employee work attentiveness; 2) employee moral self-efficacy mediates the indirect relationship between daily state mindfulness and work attentiveness; and 3) moral disengagement moderates the indirect relationship between state mindfulness and work attentiveness through moral self-efficacy, such that the indirect relationship will be weaker in the condition of low moral disengagement than in the condition of high moral disengagement. This research contributes to the work attentiveness literature by incorporating state mindfulness as a critical antecedent. [ABSTRACT FROM AUTHOR]

This paper deals with Monte Carlo simulation in case of dependent input random variables. We propose an algorithm to generate refined descriptive samples from dependent random variables for estimation of expectations of functions of output variables using the Iman and Conover algorithm to transform the dependent variables to independent ones. Therefore, such estimates obtained through a chosen mathematical model are compared with those obtained using the simple random sampling method, which proved that the former are the most efficient. Besides, using already published work on independent input variables, we can deduce in case of dependent input random variables, that asymptotically the variance of the RDS estimator is less than that of SRS estimator for any simulation function having finite second moment. [ABSTRACT FROM AUTHOR]

Purpose: In this paper, we present an exploratory, qualitative strand of a multiphase program evaluation of the Canadian-based SNAP® Youth Justice (SNAP YJ) model for males involved with the youth criminal justice system. SNAP YJ's therapeutic approach is founded on the evidence-based SNAP (Stop Now And Plan) model which focuses on strategies to enhance emotion regulation, self-control, and problem-solving for latency-aged children and their families. Integrating best practices from the literature, the SNAP YJ intervention uses technology (digital modules) to convey the manualized strategies and program sessions, engaging youth in an interactive manner. This systemic, cognitive behavioral intervention is designed to reduce further contact with the law and/or gang affiliation. The objectives of this study are to understand youth experiences of programing, enrich and contextualize preliminary outcome findings, and further develop programing through the inclusion of the youth perspective and feedback. Methods: A thematic analysis of 15 interviews with program participants from diverse backgrounds was conducted. Results: The results revealed a continuum of learning related to self-understanding and awareness of feelings; thinking and consequences; and prosocial skills and behavior. Discussion: Refinements to the program to target increased program effectiveness as a result of youth experiences are discussed. [ABSTRACT FROM AUTHOR]

The adaptive multivariate CUSUM (AMCUSUM) chart has received considerable attention because of its superior sensitivity against a range of mean shift sizes than that of the conventional non-adaptive multivariate CUSUM (MCUSUM) chart. Recently, weighted AMCUSUM (WAMCUSUM) charts with a fixed sampling interval (FSI) have been proposed, called the WAMCUSUM-FSI charts, which provide more sensitivity than the AMCUSUM-FSI charts. In this paper, we extend this work and propose WAMCUSUM charts with variable sampling interval (VSI), named the WAMCUSUM-VSI charts, for efficiently monitoring the mean of a multivariate normally distributed process. The Monte Carlo simulation method is used to compute the average time to signal (ATS) and the adjusted ATS (AATS) profiles of the existing and proposed charts. It is found that the WAMCUSUM-VSI charts perform substantially and nearly uniformly better than the WAMCUSUM-FSI charts in terms of the ATS and AATS performance criterion. An example is given to explain the implementation of the WAMCUSUM charts with fixed and VSIs. [ABSTRACT FROM AUTHOR]

In Balanced Sampling Plans Excluding Adjacent Units (BSA plans) first order inclusion probabilities are equal and second order inclusion probabilities are zero for pairs of units at a distance less than or equal to m and are constant for pairs of units which are at a distance greater than m. These plans are useful when the adjacent units in the population provide similar information. In this paper, an algorithm based on linear programming approach has been developed for construction of two-dimensional BSA plans under sharing a border and island adjacency schemes for m ≤ 2. Some results on existence of such BSA plans have also been obtained for each adjacency scheme separately. [ABSTRACT FROM AUTHOR]

Technology acceptance has been studied extensively within the IS discipline. Few, if any, have studied end users’ acceptance of newly implemented technologies within organisational contexts before end users start using the technology. Thus, by integrating variables from multiple relevant literature, this research attempts to answer this research question: will the introduction of a richer model for technology acceptance in a mandatory adoption environment, specifically in the pre-implementation phase, allow us to capture and account for the complexities of organisational technology implementations? The research model was tested in an organisational setting where a new content management system was being implemented. A total of 148 employees participated in this survey and partial least squares method was used to analyse the data to test the model. Implementation climate, valence, attitude, and perceived ease of use positively influence goal commitment to technology acceptance in a mandatory environment, and the model has displayed relatively large explanatory and predictive power. Theoretical and practical implications are discussed in the paper. [ABSTRACT FROM PUBLISHER]

By releasing the unbiasedness condition, we often obtain more accurate estimators due to the bias–variance trade-off. In this paper, we propose a class of shrinkage proportion estimators which show improved performance over the sample proportion. We provide the “optimal” amount of shrinkage. The advantage of the proposed estimators is given theoretically as well as explored empirically by simulation studies and real data analyses. [ABSTRACT FROM AUTHOR]

Users of social network sites (SNSs) use three main strategies that help to manage the privacy of their profile information: (1)limiting the level of data revealed, (2)using privacy settingsto exert control over data and (3)audience/friendship managementby being restrictive about whom to accept as a ‘friend’. Extant research does not show whether these strategies operate as independent mechanisms or whether they are interdependent and work as asystem. Given what offline privacy theorist Irwin Altman (1977) designates as themulti-mechanic natureof privacy protection, we test a model in which we expect to find that the three discerned strategies are related to one another. Structural equation modelling analysis performed on the subsample (n = 1564) of our study’s data – collected among 1743 adolescents by means of a paper-and-pencil survey – demonstrates that, in line with Altman’s vision of privacy protection, the three discerned strategies effectively operate as an interdependent system. In congruence with the hypotheses derived from extant research, we found that adolescents’ level of disclosure influences adolescents’ involvement in the two other discerned strategies: Adolescents with high levels of personal information disclosure share an increased tendency to have many friends on SNSs and a lower level of using privacy settings. [ABSTRACT FROM AUTHOR]

In an effort to improve the performance of the linear sampling method in situations involving sparse data-sets, this method in inverse scattering has recently been extended from the frequency domain to the time domain. In this paper, we consider the relative merits of the time and multifrequency linear sampling methods for sparse, limited aperture, and data-sets. Among our conclusions are that, for limited aperture measurements single-frequency data can fail to reconstruct the scatterer, whereas both time and multifrequency domain data perform satisfactorily. On the other hand, if the aperture is too small all the sampling methods fail and increasing the number of measurements in a fixed size aperture is of no help. [ABSTRACT FROM AUTHOR]

In this paper, we conduct a Monte Carlo simulation study to evaluate three propensity score (PS) scenarios for estimating an average treatment effect (ATE) in observational studies when treatment switching exists: (a) ignoring treatment switching in subjects (UPS), (b) removing subjects with treatment switching (RPS), and (c) adjusting for treatment switching effect (APS) with two inverse probability weighting estimators, IPW1 and IPW2. We evaluate these six estimators in terms of bias, mean squared error (MSE), empirical standard error (ESE), and coverage probability (CP) under various simulation scenarios. Simulation results show that the IPW2 estimator with RPS has relatively good performance. [ABSTRACT FROM AUTHOR]

Although the historical impact of racial segregation and ongoing health and economic inequities between older Black and White adults is well documented, little is known about the relationships among race, individual- and neighborhood-resources, and formal volunteering in later life. This study explores this intersection. Individual-level data from 268 respondents aged 55+ were collected in the St. Louis metropolitan area through paper-based mail surveys. Objective neighborhood data were obtained at the zip code level from secondary sources and matched with respondents. Using exploratory factor analysis, we constructed a 14-item environmental scale with 3 neighborhood dimensions (economic, social, and built environment). Older Black adults had lower levels of education; had fewer financial assets; lived in neighborhoods with less economic resources and lower built environment scores; and fewer formally volunteered when compared to older White adults. Individual resources (financial assets, health) and neighborhood resources (social and built environment) were positively associated with formal volunteering among older Black adults. Only individual resources (age, marital status, financial assets, health) were associated with formal volunteering among older White adults. A coherent set of policies that bolsters individual and environmental capacities may increase the rate of volunteerism among older black adults. [ABSTRACT FROM AUTHOR]

In this paper, a new control chart is proposed by using an auxiliary variable and repetitive sampling in order to enhance the performance of detecting a shift in process mean. The product-difference type estimator of the mean is plotted on the proposed control chart, which utilizes the information of an auxiliary variable correlated with the main quality variable. The proposed control chart is based on the outer and inner control limits so that repetitive sampling is allowed when the plotted statistic falls between the two limits. The average run length (ARL) of the proposed control chart is evaluated using the Monte Carlo simulation. The proposed control chart is compared with the Riaz M control chart and the results show the outperformance of the proposed control chart in terms of the ARL. [ABSTRACT FROM PUBLISHER]

Needs assessments are a useful part of the program development cycle. However, while step-by-step models are available to guide assessments, they may not be detailed enough for the pragmatic questions that arise. The planning process should be viewed as dynamic and flexible, able to be tailored to the agency’s specific organisational and environmental characteristics. This paper presents a practical discussion for social workers charged with planning and implementing a needs assessment. Practitioners are empowered to consider several concerns or issues simultaneously, to build upon their organisational knowledge, and start the process where it intuitively makes sense. Major issues discussed are: planning the needs assessment, evaluating contextual factors, and design considerations. [ABSTRACT FROM PUBLISHER]

Acceptance sampling, a category of statistical quality control, deals with the confidence of the product's quality. In certain times, it is necessary to deal with the error in the demanding distribution counting on the sample size and the pertained population size, in determining the necessitated sample size for the acute exactitude. Further this sample size with minimized error is utilized in deriving the most beneficial OC curve. Neural networks have been used to train the data with the resulting error and their matching toleration level for the sample sizes of different population sizes. This trained network can be used to foster automated acceptance or rejection of the sample size to be used for a better OC curve based on the minimized error, ensuing time reduction of the burdened work. It is better explained in this paper with the geo-statistics data, using SAS program. [ABSTRACT FROM PUBLISHER]

The exponential–Poisson (EP) distribution with scale and shape parameters β>0 and λ∈ℝ, respectively, is a lifetime distribution obtained by mixing exponential and zero-truncated Poisson models. The EP distribution has been a good alternative to the gamma distribution for modelling lifetime, reliability and time intervals of successive natural disasters. Both EP and gamma distributions have some similarities and properties in common, for example, their densities may be strictly decreasing or unimodal, and their hazard rate functions may be decreasing, increasing or constant depending on their shape parameters. On the other hand, the EP distribution has several interesting applications based on stochastic representations involving maximum and minimum of iid exponential variables (with random sample size) which make it of distinguishable scientific importance from the gamma distribution. Given the similarities and different scientific relevance between these models, one question of interest is how to discriminate them. With this in mind, we propose a likelihood ratio test based on Cox's statistic to discriminate the EP and gamma distributions. The asymptotic distribution of the normalized logarithm of the ratio of the maximized likelihoods under two null hypotheses – data come from EP or gamma distributions – is provided. With this, we obtain the probabilities of correct selection. Hence, we propose to choose the model that maximizes the probability of correct selection (PCS). We also determinate the minimum sample size required to discriminate the EP and gamma distributions when the PCS and a given tolerance level based on some distance are before stated. A simulation study to evaluate the accuracy of the asymptotic probabilities of correct selection is also presented. The paper is motivated by two applications to real data sets. [ABSTRACT FROM AUTHOR]

In this paper, the problem of monitoring process data that can be modelled by exponential distribution is considered when observations are from type-II censoring. Such data are common in many practical inspection environment. An average run length unbiased (ARL-unbiased) control scheme is developed when the in-control scale parameter is known. The performance of the proposed control charts are investigated in terms of the ARL and standard deviation of the run length. The effects of parameter estimation on the proposed control charts are also evaluated. Then, we consider the design of the ARL-unbiased control charts when the in-control scale parameter is estimated. Finally, an example is used to illustrate the implementation of the proposed control charts. [ABSTRACT FROM AUTHOR]

In this paper, a two-stage dispatching rule for the on-time delivery of an order-driven FAB is presented. Dispatching rules have a significant impact on the performance of FABs. Consequently, many such rules have been created, such as first in first out, earliest due data, operation due date, and critical ratio. Because these conventional dispatching rules make decisions only by considering the due date of each lot, they might not be suitable for dynamic order-driven FABs, for which it is very essential to monitor not only the due date of each lot but also the production rate of each step. In the first stage of the proposed two-stage dispatching rule, the production rate of each step is taken into account, and the due date of each lot is considered in the second stage. In this paper, the production rates of steps are computed by combining forward simulation and backward pegging. A simulation model, based on a wafer FAB data-set, has been developed, and simulation is conducted using commercial software SEEPLAN®. The simulation results clearly show the advantages of the proposed dispatching rule over existing rules. [ABSTRACT FROM PUBLISHER]