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The purpose of this paper is to develop an exponentially weighted moving average (EWMA) control chart based on the Wilcoxon rank-sum (WRS) statistic using repetitive sampling to improve the sensitivity of the EWMA control chart to process mean shifts regardless of the prior knowledge of the underlying process distribution.

The proposed chart is developed without any distributional assumption of the underlying quality process for monitoring the location parameter. The authors developed formulae as well as algorithms to facilitate the design and implementation of the proposed chart. The performance of the proposed chart is investigated in terms of the average run-length, standard deviation of the run-length (RL), average sample size and percentiles of the RL distribution. Numerical examples are given as illustration of the design and implementation of the proposed chart.

The proposed control chart presents very attractive RL properties and outperforms the existing nonparametric EWMA control chart based on the WRS in the detection of the mean process shifts in many situations. However, the performance of the proposed chart relatively deteriorates for small phase I sample sizes.

This study develops a new control chart for monitoring the process mean using a two-sample test regardless of the nature of the underlying process distribution. The proposed control chart does not require any assumption on the type (or nature) of the process distribution. It requires a small number of subgroups in order to reach stability in the phase II performance.

This paper aims to investigate the thermal performance involving larger heating rate, targeted heating, heating with least non-uniformity of the spatial distribution of temperature and larger penetration of heating within samples vs shapes of samples (circle, square and triangular).

Galerkin finite element method (GFEM) with adaptive meshing in a composite domain (free space and sample) is used in an in-house computer code. The finite element meshing is done in a composite domain involving triangle embedded within a semicircular hypothetical domain. The comparison of heating pattern is done for various shapes of samples involving identical cross-sectional area. Test cases reveal that triangular samples can induce larger penetration of heat and multiple heating fronts. A representative material (beef) with high dielectric loss corresponding to larger microwave power or heat absorption in contrast to low lossy samples is considered for the current study. The average power absorption within lossy samples has been computed using the spatial distribution and finite element basis sets. Four regimes have been selected based on various local maxima of the average power for detailed investigation. These regimes are selected based on thin, thick and intermediate limits of the sample size corresponding to the constant area of cross section, Ac involving circle or square or triangle.

The thin sample limit (Regime 1) corresponds to samples with spatially invariant power absorption, whereas power absorption attenuates from exposed to unexposed faces for thick samples (Regime 4). In Regimes 2 and 3, the average power absorption non-monotonically varies with sample size or area of cross section (A_c) and a few maxima of average power occur for fixed values of A_c involving various shapes. The spatial characteristics of power and temperature have been critically analyzed for all cross sections at each regime for lossy samples. Triangular samples are found to exhibit occurrence of multiple heating fronts for large samples (Regimes 3 and 4).

Length scales of samples of various shapes (circle, square and triangle) can be represented via Regimes 1-4. Regime 1 exhibits the identical heating rate for lateral and radial irradiations for any shapes of lossy samples. Regime 2 depicts that a larger heating rate with larger temperature non-uniformity can occur for square and triangular-Type 1 lossy sample during lateral irradiation. Regime 3 depicts that the penetration of heat at the core is larger for triangular samples compared to circle or square samples for lateral or radial irradiation. Regime 4 depicts that the penetration of heat is still larger for triangular samples compared to circular or square samples. Regimes 3 and 4 depict the occurrence of multiple heating fronts in triangular samples. In general, current analysis recommends the triangular samples which is also associated with larger values of temperature variation within samples.

GFEM with generalized mesh generation for all geometries has been implemented. The dielectric samples of any shape are surrounded by the circular shaped air medium. The unified mesh generation within the sample connected with circular air medium has been demonstrated. The algorithm also demonstrates the implementation of various complex boundary conditions in residuals. The numerical results compare the heating patterns for all geometries involving identical areas. The thermal characteristics are shown with a few generalized trends on enhanced heating or targeted heating. The circle or square or triangle (Type 1 or Type 2) can be selected based on specific heating objectives for length scales within various regimes.

The purpose of this study is to review the literature on strategic management in Africa with special emphasis on how strategy constructs have been measured and present a roadmap to help improve strategy research in Africa.

A content analysis of empirical research on strategic management published in journals using data from Africa from 2000 to 2013 is conducted to examine construct measurement practices.

The findings indicate that the average sample sizes in strategy research in Africa is not large as strategy research in general, and have low statistical power. While the studies rely heavily on single-indicator measures, there were also several studies using scale or multiple measures that report reliabilities.

Limitations of the research include small number of studies used, inability to examine journal effects’ of the findings due to few numbers of papers from many of the journals, and lack of examination of the influence of the context and topical areas of the articles on the use of the construct measurement techniques.

The study provides information about the use of construct measurement techniques and power analysis in strategy research in Africa. It further encourages the use of larger sample sizes, the examination of power, and more focus on variables which allow the assessment of reliabilities and validity.

Little is known about construct measurement practices of the empirical research in and about Africa in the discipline of strategic management. This chapter builds on extant research on construct measurement issues in strategic management research, but with the unique value-added contribution of focusing on the African environment where the discipline is beginning to take hold.

For central banks who study the use of cash, acceptance of card payments is an important factor. Surveys to measure levels of card acceptance and the costs of payments can be complicated and expensive. In this paper, we exploit a novel data set from Hungary to see the effect of stratified random sampling on estimates of payment card acceptance and usage. Using the Online Cashier Registry, a database linking the universe of merchant cash registers in Hungary, we create merchant and transaction level data sets. We compare county (geographic), industry and store size stratifications to simulate the usual stratification criteria for merchant surveys and see the effect on estimates of card acceptance for different sample sizes. Further, we estimate logistic regression models of card acceptance/usage to see how stratification biases estimates of key determinants of card acceptance/usage.

Auditing is seasonal, with the majority of U.S. public companies having a December fiscal year-end. This results in an audit “busy season” and “off-season” with a non-trivial seasonal impact on the pricing of audit services. We apply an economic framework that explains how audit seasonality affects both the magnitude and the price elasticity of audit demand and audit supply. We find that the audit busy season is associated with an audit fee premium of approximately 10% based on a meta-analysis of 97 analyses from 18 audit fee studies of U.S public companies. A meta-regression of the contextual differences in research design between studies reveals that examining only Big N attenuates the busy season effect size but does not eliminate it, and that the busy season effect size may be larger post-SOX.

The purpose of the present chapter was to synthesize the research that directly compares children with and without reading disabilities on measures of working memory (WM). Working memory has considered at key element children success on reading performance and, therefore, the published literature was assessed. Twenty-eight (28) studies were included in the synthesis, which involved 207 effect sizes. The overall mean effect size estimate in favor of children without reading disabilities (RD) was –0.89 (SE=0.08). Effect sizes were submitted to a hierarchical linear modeling. Results indicated that children with RD were distinctively disadvantaged compared with average readers when memory manipulations required a transformation of information. Age, IQ, reading level, and domain specificity (verbal vs. visual/spatial measures) were not significant predictors of effect size estimates. The findings indicated that domain general WM differences persisted across age, and these differences operated independent of effect size differences in reading and IQ.

The purpose of this paper is to investigate a new sampling methodology previously proposed for systems with a known lifetime distribution: the Predetermined Sampling Intervals (PSI) method.

The methodology is defined on basis of system hazard cumulative rate, and is compared with other approaches, particularly those whose parameters may change in real time, taking into account current sample information.

For different lifetime distributions, the results obtained for adjusted average time to signal (AATS) using a control chart for the sample mean are presented and analysed. They demonstrate the high degree of statistical performance of this sampling procedure, particularly when used in systems with an increasing failure rate distribution.

This PSI method is important from a quality and reliability management point of view.

This methodology involves a process by which sampling instants are obtained at the beginning of the process to be controlled. Also this new approach allows for statistical comparison with other sampling schemes, which is a novel feature.

The purpose of this paper is to propose a double exponentially weighted moving average control chart using repetitive sampling (RS-DEWMA) for a normally distributed process variable to improve the efficiency of detecting small process mean shift.

The algorithm for the implementation of the proposed chart is developed and the formulae for the in-control and out-of-control average run lengths (ARLs) are derived. Tables of ARLs are presented for various process mean shift. The performance of the proposed chart is investigated in terms of the average run-length for small process mean shift and compared with the existing DEWMA control chart. Numerical examples are given as illustration of the design and implementation of the proposed chart.

The proposed control chart is more efficient than the existing DEWMA control chart in the detection of small process mean shifts as it consistently gives smaller ARL values and quickly detects the process shift. However, the performance of the proposed chart relatively deteriorates for large smoothing constants.

The application of repetitive sampling in the control chart literature is gaining wide acceptability. The design and implementation of the RS-DEWMA control chart offers a new approach in the detection of small process mean shift by process control personnel.

This paper fills a gap in the literature by examining the performance of the repetitive sampling DEWMA control chart. The use of repetitive sampling technique in the control chart is discussed in the literature, however, its use based on the DEWMA statistic has not been considered in this context.

Previous research has explored the link between sustainability disclosure and reputation but produced contradictory results. This study aims to clarify the sustainability disclosure–reputation relationship through a quantitative analysis of the correlations between these variables reported in empirical research papers. The second objective was to determine how various moderators affect the sustainability disclosure–reputation link.

The meta-analysis was based on a systematic review of the literature covering empirical research on the corporate sustainability disclosure and reputation relationship. A total of 92 articles were meta-analyzed to compile their findings on four extrinsic moderators: company size, ownership, stock listing status and activity sector.

The findings confirm that a significant positive correlation exists between corporate sustainability disclosure and reputation. The moderator analysis also revealed that companies’ different characteristics can explain researchers’ divergent results.

The results have considerable practical relevance for organizational management. First, they can motivate managers to improve and disclose their company’s social and environmental impacts to strengthen their reputation, which in turn will help accelerate the achievement of the Sustainable Development Goals. Second, the findings can ensure organizations develop disclosure and reputation management strategies adapted for each firm’s size, ownership, stock listing status and activity sector.

The results have considerable practical relevance for organizational management. First, they can motivate managers to improve and disclose their company’s social and environmental impacts to strengthen their reputation, which in turn will help accelerate the achievement of the Sustainable Development Goals. Second, the findings can ensure organizations develop disclosure and reputation management strategies adapted for each firm’s size, ownership, stock listing status and activity sector.

To the best of the authors’ knowledge, this meta-analysis is the first to clarify the link between disclosure and reputation, which makes a unique contribution to the field of social and environmental accounting. A larger sample of primary research was collected, and key extrinsic moderators were examined to explain prior studies’ contradictory findings.

In management accounting research, the capabilities of Partial Least Squares Structural Equation Modelling (PLS-SEM) have only partially been utilized. These yet unexploited capabilities of PLS-SEM are a useful tool in the often explorative state of research in management accounting. After reviewing eleven top-ranked management accounting journals through the end of 2013, 37 articles in which PLS-SEM is used are identified. These articles are analysed based on multiple relevant criteria to determine the progress in this research area, including the reasons for using PLS-SEM, the characteristics of the data and the models, and model evaluation and reporting. A special focus is placed on the degree of importance of these analysed criteria for the future development of management accounting research. To ensure continued theoretical development in management accounting, this article also offers recommendations to avoid common pitfalls and provides guidance for the advanced use of PLS-SEM in management accounting research.