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The objective is to describe and conceptualize leadership performance in total quality management (TQM).

A contingency approach to leadership performance in TQM is undertaken.

Contingency models of leadership performance in TQM are introduced. Principal parameters in these models are timely contextual accuracies – as well as they contain foresight versus improvidence accuracies – of TQM. A contingency process of leadership performance accuracy in TQM is also introduced. The accuracy parameters are linked by a process accuracy zone. It serves as a descriptive tool of leadership performance. Finally, a typology of leadership performances in TQM is conceptualised.

Generally, this paper is restricted to the core values of TQM, in which a set of core values unites the descriptions of TQM. In particular, this paper is limited to the core value of leadership/management commitment. An important area of further research is to examine the actual accuracy of leadership performance across contexts and over time, as well as foresight versus improvidence accuracy in TQM.

The models, process and typology introduced may be applicable to examine and describe corporate leadership performance in TQM. They may also be used for teaching and training purposes, and in particular as an eye‐opener to the leadership itself, as well as to the employees, the shareholders and other stakeholders (e.g. analysts) in the marketplace. Furthermore, they may be used to position an organisation's specific leadership performance and to compare it with the leadership performance of others (e.g. competitors, suppliers and customers).

The contributions of this paper are: two linked contingency models of leadership performance in TQM, a contingency process, and a typology, both of which are of interest to both practitioners and scholars.

Concerns about the effectiveness of performance management systems (PMS) have long-driven researchers and practitioners to explore ways of measuring it. It is imperative for organizations to understand, how employees perceive the effectiveness of their PMS, for positive employee outcomes. Hence, the purpose of this paper is to explore the operationalization of the construct “employee perception of PMS effectiveness” (PMSE). An evidence of construct validity for the “two-factor PMS effectiveness” measure with perceived “PMS accuracy” and “PMS fairness” as its two factors is provided. In addition, a scale to measure “employee perception of PMS accuracy” is developed.

Mixed-methods research methodology.

Findings confirmed the possible existence of the two-factor PMSE construct, with PMS accuracy and fairness as its factors. Construct validity is established through its correlations with important outcome variables. The development of a valid and reliable 12-item scale for perceived PMS accuracy (Cronbach α value=0.83) is an additional key contribution.

The research presents opportunities for future empirical studies to examine the influence of PMS accuracy and effectiveness on employee outcomes (engagement, retention, etc.). Researchers may also cross-validate the PMSE measure in different socio-cultural contexts.

The perceived PMS accuracy and effectiveness measures can serve as powerful investigative tools to measure employee perceptions regarding PMS. It can help organizations identify and correct the shortcomings in their existing PMS.

This is the first paper to offer a cogent conceptualization and operationalization of employee perceptions of PMS accuracy and effectiveness. Hence, it has key implications for academics and practitioners.

Assessing front end engineering design (FEED) accuracy is significant for project owners because it can support informed decision-making, including confidence in cost and schedule predictions. A framework to measure FEED accuracy does not exist in the literature or in practice, not does systematic data directly linking FEED accuracy to project performance. This paper aims to focus first on gauging and quantifying FEED accuracy, and second on measuring its impact on project performance in terms of cost change, schedule change, change performance, financial performance and customer satisfaction.

A novel measurement scheme was developed for FEED accuracy as a comprehensive assessment of factors related to the project leadership and execution teams, management processes and resources; to assess the environment surrounding FEED. The development of this framework built on a literature review and focus groups, and used the research charrettes methodology, guided by a research team of 20 industry professionals and input from 48 practitioners representing 31 organizations. Data were collected from 33 large industrial projects representing over $8.8 billion of installed cost, allowing for a statistical analysis of the framework's impact on performance.

This paper describes: (1) twenty-seven critical FEED accuracy factors; (2) an objective and scalable method to measure FEED accuracy; and (3) data showing that projects with high FEED accuracy outperformed projects with low FEED accuracy by 20 percent in terms of cost growth in relation to their approved budgets.

FEED accuracy is defined as the degree of confidence in the measured level of maturity of the FEED deliverables to serve as a basis of decision at the end of detailed scope, prior to detailed design. Assessing FEED accuracy is significant for project owners because it can support informed decision-making, including confidence in cost and schedule predictions.

FEED accuracy has not been assessed before, and it turned out to have considerable project performance implications. The new framework presented in this paper is the first of its kind, it has been tested rigorously, and it contributes to both the literature body of knowledge as well as to practice. As one industry leader recently stated, “it not only helped to assess the quality and adequacy of the technical documentation required, but also provided an opportunity to check the organization's readiness before making a capital investment decision.”

This chapter investigates the nature of tax preparers’ confidence, as well as how the introduction of a tax decision support system (TDSS) affects tax preparers’ confidence levels. Psychological theories of confidence (e.g., Einhorn & Hogarth, 1978) are drawn upon to develop predictions regarding the role of process (ex ante) and outcome (ex post) confidence in tax return preparation. An experimental methodology is used with 114 inexperienced and experienced participants who prepare an individual income tax return manually or with tax preparation software (a TDSS). Less-experienced tax preparers have lower levels of ex-ante confidence and are more likely to be overconfident in the accuracy of their performance. Furthermore, when examining only the participants who made errors in their tax return preparation task, those that prepare the return with the TDSS are significantly more likely to be overconfident in their performance. These results support the predictions of Noga and Arnold (2002) and suggest that inexperienced users’ over-reliance on a TDSS (Masselli, Ricketts, Arnold, & Sutton, 2002) may be due to individuals’ overconfidence in the accuracy of their performance with the software.

The current chapter focuses on environmental and organizational factors that affect the performance appraisal context, performance evaluations, and rating accuracy. Drawing on the extant literature and focusing on current organizational practices, we propose a dynamic multi-level model of performance rating that takes these distal factors into consideration. In doing so, we also provide propositions explicating causal linkages between these distal factors, more proximal performance appraisal factors, and ultimately the accuracy of performance ratings. Furthermore, we identify current and emerging directions in performance appraisal research and practice. The implications of the current and emerging trends are then discussed in the context of our proposed model.

This study aims to investigate the influence of interpersonal justice, a sub-concept of interactional justice, on information accuracy and logistics performance in the pharmaceutical supply chain.

For this purpose, 600 pharmacies in Korea were surveyed through questionnaires distributed via mail and direct visits and 293 valid responses were used for statistical analysis.

According to the results, the perception of interpersonal justice between buyers and sellers showed a positive effect on information accuracy, which, in turn, had a positive effect on logistics performance within the supply chain. In contrast, interpersonal justice showed an insignificant effect on logistics performance.

This signifies that if buyers treat sellers with respect and politeness, the accuracy of the information provided by the seller will improve, which may ultimately have a positive effect on performance. In addition, ethical behavior by both parties ensures information accuracy in the supply chain, even though it does not directly affect performance.

In contrast to previous research, which has focused on distributive and procedural justice, the study investigates interpersonal justice and its effects on information accuracy and logistics performance in the pharmaceutical supply chain.

Hundreds of thousands of deaths each year in the world are caused by breast cancer (BC). An early-stage diagnosis of this disease can positively reduce the morbidity and mortality rate by helping to select the most appropriate treatment options, especially by using histological BC images for the diagnosis.

The present study proposes and evaluates a novel approach which consists of 24 deep hybrid heterogenous ensembles that combine the strength of seven deep learning techniques (DenseNet 201, Inception V3, VGG16, VGG19, Inception-ResNet-V3, MobileNet V2 and ResNet 50) for feature extraction and four well-known classifiers (multi-layer perceptron, support vector machines, K-nearest neighbors and decision tree) by means of hard and weighted voting combination methods for histological classification of BC medical image. Furthermore, the best deep hybrid heterogenous ensembles were compared to the deep stacked ensembles to determine the best strategy to design the deep ensemble methods. The empirical evaluations used four classification performance criteria (accuracy, sensitivity, precision and F1-score), fivefold cross-validation, Scott–Knott (SK) statistical test and Borda count voting method. All empirical evaluations were assessed using four performance measures, including accuracy, precision, recall and F1-score, and were over the histological BreakHis public dataset with four magnification factors (40×, 100×, 200× and 400×). SK statistical test and Borda count were also used to cluster the designed techniques and rank the techniques belonging to the best SK cluster, respectively.

Results showed that the deep hybrid heterogenous ensembles outperformed both their singles and the deep stacked ensembles and reached the accuracy values of 96.3, 95.6, 96.3 and 94 per cent across the four magnification factors 40×, 100×, 200× and 400×, respectively.

The proposed deep hybrid heterogenous ensembles can be applied for the BC diagnosis to assist pathologists in reducing the missed diagnoses and proposing adequate treatments for the patients.

The purpose of this paper is to examine the effect of acquaintance on performance rating accuracy and halo.

After expert ratings were obtained, US Air Force Officers (n=104) with an average of six years experience rated the performance of four officers who delivered 6‐7 minute briefings on their research projects; 26 raters reported being acquainted with one or more of the briefers. Raters were randomly assigned to use a rating format designed to encourage between‐ratee comparisons on each dimension or a format in which each ratee was separately rated on all dimensions.

Ratings made by acquainted raters were more accurate than ratings by unacquainted raters. Accuracy was positively correlated with halo for both sets of ratings. Rating format had no discernible effect on accuracy or halo.

One limitation of this study is that the measure of acquaintance was not designed as a surrogate for familiarity. Development of a multi‐item, psychometrically‐valid measure of acquaintance should be the first step in pursuing this research. The use of a laboratory design where only a small percentage of the sample was acquainted with those being rated also limits the study's generalizability.

The results show that prior acquaintance with the ratee results in more accurate ratings. Ratings were also more positive when raters had prior contact with the person they rated.

The hypothesis is that the cognitive processes used to produce ratings are different for raters who have had no prior contact with a ratee and raters who are in some manner acquainted with a ratee. In the past, a positive halo effect from acquaintance between raters and ratees has been a concern. However, this limited study indicates that acquaintance may actually result in more accurate ratings.

This paper addresses the problem of using accuracy index values based on the squared difference between participant scores and true scores, the D² index, at the practical level. It clarifies ambiguity existing in the literature regarding the use of these index values to evaluate the scoring accuracy of human raters (evaluators). The paper critically investigates the effect of frame‐of‐reference (FOR) training on improving the accuracy of third‐party evaluators’ scores for organisations, such as those going through the Malcolm Baldrige National Quality Award (MBNQA) self‐assessment exercise. It discusses a case study where 90 individual participants took part. The scores of these participants were recorded before training was given to them (no training) and after receiving FOR training. The study showed that providing FOR training has an effect on improving the elevation accuracy index (p < 0.05) in five of the seven categories used in this exercise. An observed leniency effect was also reduced. However, no improvement in the DA was observed. Thus, the evaluators’ ability to assign an accurate overall score was improved, while the ability to discriminate between relative strengths and weaknesses did not show improvement. This implies evaluator training, particularly for heterogeneous pools of volunteers like those of corporate and state and local quality awards, should include more content on the performance dimensions.

The aim of this paper is to experimentally evaluate the effectiveness of the state-of-the-art printed Arabic text recognition systems to determine open areas for future improvements. In addition, this paper proposes a standard protocol with a set of metrics for measuring the effectiveness of Arabic optical character recognition (OCR) systems to assist researchers in comparing different Arabic OCR approaches.

This paper describes an experiment to automatically evaluate four well-known Arabic OCR systems using a set of performance metrics. The evaluation experiment is conducted on a publicly available printed Arabic dataset comprising 240 text images with a variety of resolution levels, font types, font styles and font sizes.

The experimental results show that the field of character recognition for printed Arabic still requires further research to reach an efficient text recognition method for Arabic script.

To the best of the authors’ knowledge, this is the first work that provides a comprehensive automated evaluation of Arabic OCR systems with respect to the characteristics of Arabic script and, in addition, proposes an evaluation methodology that can be used as a benchmark by researchers and therefore will contribute significantly to the enhancement of the field of Arabic script recognition.