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This chapter combines quantitative studies of the connections between stressors and performance in accounting settings and identifies the mediators and moderators of stressors–performance relationships. Using meta-analyses and path analyses, this research compiles 72 studies to investigate the relationships of stressors with accountant and auditor performance. As hypothesized, bivariate meta-analyses results indicate that work-related stressors negatively affect performance, and burnout and stress are negatively related to performance, whereas motivation is positively related to performance. Moreover, a meta-analytical structural equation modeling indicates that role stressors have significant direct and indirect effects (through burnout and stress) on job performance. Accumulation of multiple samples through meta-analysis bolsters statistical power compared to single-sample studies and thus reveals the sign of residual direct effects of role stressors on job performance in accounting settings.

Actual costs frequently deviate from the estimated costs in either favorable or adverse direction in construction projects. Conventional cost evaluation methods do not take the uncertainty and correlation effects into account. In this regard, a simulation-based cost risk analysis model, the Correlated Cost Risk Analysis Model, previously has been proposed to evaluate the uncertainty effect on construction costs in case of correlated costs and correlated risk-factors. The purpose of this paper is to introduce the detailed evaluation of the Cost Risk Analysis Model through scenario and sensitivity analyses.

The evaluation process consists of three scenarios with three sensitivity analyses in each and 28 simulations in total. During applications, the model’s important parameter called the mean proportion coefficient is modified and the user-dependent variables like the risk-factor influence degrees are changed to observe the response of the model to these modifications and to examine the indirect, two-sided and qualitative correlation capturing algorithm of the model. Monte Carlo Simulation is also applied on the same data to compare the results.

The findings have shown that the Correlated Cost Risk Analysis Model is capable of capturing the correlation between the costs and between the risk-factors, and operates in accordance with the theoretical expectancies.

Correlated Cost Risk Analysis Model can be preferred as a reliable and practical method by the professionals of the construction sector thanks to its detailed evaluation introduced in this paper.

This article aims to discuss the binary matrix of spatial association which is suggested by Moran, and proposes a new method of the definition of the w matrix to obtain a new space‐time correlation coefficient considering the correlation of both time and space.

From the perspective of the multi‐dimension of space and time, this article proposes a new computational method of a correlation coefficient considering both temporal and spatial factors, based on the analysis of the characteristics of Moran's Global Index and Moran's Local Index. The number of patents granted in mainland China's provinces and municipalities is taken as an example of multi‐dimensional analysis.

The results of quantitative analysis using this space‐time correlation coefficient show that the outcomes calculated by this new correlation coefficient are not only highly correlated with Moran's Index, but also have advantages in analyzing the trends of both spatial and temporal indicators simultaneously, which is verified by the illustration of the algorithm.

Due to a scarcity of data in China, the algorithm is based on data for the last 20 years, which may not be long enough for this research. Although this does not reduce the value of the conclusions of this article, a closer look should be taken at the effectiveness of the new space‐time correlation coefficient in the future.

The results of space‐time correlation coefficient are highly correlated with Moran's Index. In addition, it can not only analyze the “flow” indicators in a certain period but also analyze the “stock” indicators to reflect both space and time changes. These may reflect superiority of space‐time correlation coefficient to Moran's Index.

This new correlation coefficient that considers both temporal and spatial factors and will provide a more scientific and effective tool for spatial econometric analysis in time and space changes of management on society and the economy.

Addresses the standardization of the measurements and the labels for concepts commonly used in the study of work organizations. As a reference handbook and research tool, seeks to improve measurement in the study of work organizations and to facilitate the teaching of introductory courses in this subject. Focuses solely on work organizations, that is, social systems in which members work for money. Defines measurement and distinguishes four levels: nominal, ordinal, interval and ratio. Selects specific measures on the basis of quality, diversity, simplicity and availability and evaluates each measure for its validity and reliability. Employs a set of 38 concepts ‐ ranging from “absenteeism” to “turnover” as the handbook’s frame of reference. Concludes by reviewing organizational measurement over the past 30 years and recommending future measurement reseach.

This paper investigates, theoretically and empirically, differences between blacks and whites in the United States concerning the intergenerational transmission of occupational skills and the effects on sons’ earnings. The father–son skill correlation is measured by the correlation coefficient (or cosine of the angle) between the father’s skill vector and the son’s skill vector. The skill vector comprises an individual’s occupational characteristics from the Dictionary of Occupational Titles (DOT). According to data from the U.S. National Longitudinal Survey of Youth (NLSY79), white sons earn higher wages in occupations that require skills similar to those of their fathers, whereas black sons in such circumstances incur a wage loss. A large portion of the racial wage gap is explained by the father–son skill correlation. However, a significant unexplained racial wage gap remains at the lower tail of the wage distribution.

We study the statistical properties of Pearson correlation coefficients of Gaussian ranks, and Gaussian rank regressions – ordinary least-squares (OLS) models applied to those ranks. We show that these procedures are fully efficient when the true copula is Gaussian and the margins are non-parametrically estimated, and remain consistent for their population analogs otherwise. We compare them to Spearman and Pearson correlations and their regression counterparts theoretically and in extensive Monte Carlo simulations. Empirical applications to migration and growth across US states, the augmented Solow growth model and momentum and reversal effects in individual stock returns confirm that Gaussian rank procedures are insensitive to outliers.

Normal transformation is often required in structural reliability analysis to convert the non-normal random variables into independent standard normal variables. The existing normal transformation techniques, for example, Rosenblatt transformation and Nataf transformation, usually require the joint probability density function (PDF) and/or marginal PDFs of non-normal random variables. In practical problems, however, the joint PDF and marginal PDFs are often unknown due to the lack of data while the statistical information is much easier to be expressed in terms of statistical moments and correlation coefficients. This study aims to address this issue, by presenting an alternative normal transformation method that does not require PDFs of the input random variables.

The new approach, namely, the Hermite polynomial normal transformation, expresses the normal transformation function in terms of Hermite polynomials and it works with both uncorrelated and correlated random variables. Its application in structural reliability analysis using different methods is thoroughly investigated via a number of carefully designed comparison studies.

Comprehensive comparisons are conducted to examine the performance of the proposed Hermite polynomial normal transformation scheme. The results show that the presented approach has comparable accuracy to previous methods and can be obtained in closed-form. Moreover, the new scheme only requires the first four statistical moments and/or the correlation coefficients between random variables, which greatly widen the applicability of normal transformations in practical problems.

This study interprets the classical polynomial normal transformation method in terms of Hermite polynomials, namely, Hermite polynomial normal transformation, to convert uncorrelated/correlated random variables into standard normal random variables. The new scheme only requires the first four statistical moments to operate, making it particularly suitable for problems that are constraint by limited data. Besides, the extension to correlated cases can easily be achieved with the introducing of the Hermite polynomials. Compared to existing methods, the new scheme is cheap to compute and delivers comparable accuracy.

The aim of this paper is to determine whether or how academic libraries affect student achievement.

The paper uses computation of Pearson's r coefficients and predictor values for correlations of academic library statistics with first‐year retention and six‐year graduation rates reported to the Integrated Postsecondary Education Data System by Southern Regional Education Board four‐year colleges and universities in 2010.

Book collection size in doctoral university libraries has the strongest correlation with retention and graduation rates, in the sample, and predicts for every 10 percent increase a 0.5 percent improvement in retention and a 0.7 percent higher graduation rate.

The paper documents the first impact study to correlate library statistics with both retention and graduation rates from a large sample of doctoral, Masters' and bachelors' degree‐conferring institutions. It calculates 21 predictor values of interest to academic administrators.

The purpose of this paper is to investigate the correlation between university libraries and academic research achievement and analyze if university library resources correlate with academic research achievement.

The paper seeks to verify the correlation between university libraries and academic research achievement and to examine which university library resources relate to research achievement. A variety of research questions were posed concerning the relationship between a university's library resources and academic research achievement. Structural equation models (SEMs) were developed to answer the research questions. Most research questions posed were affirmatively answered using the SEM process.

This study confirmed that labor and budget, investment in e‐resources and an investment in university libraries enhances academic research achievement.

An SEM for verifying the correlation between university libraries and academic research achievement was developed in the study.

This study is the first including an investment factor in e‐resources for verifying the correlation between university libraries and academic research achievement.

The usefulness of ex‐post data as a proxy for ex‐ante returns in the portfolio problem rests on the stability of the co‐movement between returns. Yet despite its importance, this issue has not received sufficient examination in the financial literature, particularly in the direct real estate market. This study aims to address this issue.

To examine the temporal stability of covariance and correlation matrices and individual correlation coefficients this paper uses the Box M tests and the methodology of Shaked using monthly real estate data in the UK over the period 1987 to 2002 and four investment horizons.

The Box M tests reveal that the covariance and correlation matrices both display temporal instability. This suggests that the returns between real estate returns are unstable over time and so provide poor estimates in the ex‐ante modelling process. The analysis also indicates that the covariance matrices are less stable than the corresponding correlation matrices. Nonetheless, when we tested the stability of individual correlation coefficients using the methodology of Shaked we find that stability increases consistently and substantially with the lengthening of the investment horizon and holding period.

Thus, for all practical purposes the pair‐wise correlation between real estate returns can be considered nearly stationary in the long run. This implies that investors can use ex‐post data as a proxy for ex‐ante data in portfolio models especially if longer investment horizons are used to estimate the parameters.

This study is the first to examine temporal co‐movements between UK real estate returns in a portfolio context over different investment horizons.