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Article

Göran Svensson

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

Abstract

Purpose

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

Design/methodology/approach

A contingency approach to leadership performance in TQM is undertaken.

Findings

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.

Research limitations/implications

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.

Practical implications

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).

Originality/value

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.

Details

The TQM Magazine, vol. 17 no. 6
Type: Research Article
ISSN: 0954-478X

Keywords

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Article

Youjin Jang, Inbae Jeong and Yong K. Cho

The study seeks to identify the impact of variables in a deep learning-based bankruptcy prediction model, which has achieved superior performance to other prediction…

Abstract

Purpose

The study seeks to identify the impact of variables in a deep learning-based bankruptcy prediction model, which has achieved superior performance to other prediction models but cannot easily interpret hidden processes.

Design/methodology/approach

This study developed three LSTM-RNN–based models that predicted the probability of bankruptcy before 1, 2 and 3 years using financial, the construction market and macroeconomic variables as input variables. Then, the impacts of the input variables that affected prediction accuracy in each model were identified by using Shapley value and compared among the three models. This study also investigated the prediction accuracy using variants of input variables grouped sequentially by high-impact ranking.

Findings

The results showed that the prediction accuracies were largely impacted by “housing starts” in all models. As the prediction period increased, the effects of macroeconomic variables on prediction accuracy increased, whereas the impact of “return on assets” on prediction accuracy decreased. It also found that the “current ratio” and “debt ratio” significantly influenced the prediction accuracies in all models. Also, the results revealed that similar prediction accuracies could be achieved using only 8, 10, and 10 variables out of a total of 18 variables for the 1-, 2-, and 3-year prediction models, respectively.

Originality/value

This study provides a Shapley value-based approach to identify how each input variable in a deep-learning bankruptcy prediction model. The findings of this study can not only assist in obtaining better insights into the underlying concept of bankruptcy but also use to select variables by removing those identified as less significant.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

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Book part

B. G. Deepa and S. Senthil

Breast cancer (BC) is one of the leading cancer in the world, BC risk has been there for women of the middle age also, it is the malignant tumor. However, identifying BC…

Abstract

Breast cancer (BC) is one of the leading cancer in the world, BC risk has been there for women of the middle age also, it is the malignant tumor. However, identifying BC in the early stage will save most of the women’s life. As there is an advancement in the technology research used Machine Learning (ML) algorithm Random Forest for ranking the feature, Support Vector Machine (SVM), and Naïve Bayes (NB) supervised classifiers for selection of best optimized features and prediction of BC accuracy. The estimation of prediction accuracy has been done by using the dataset Wisconsin Breast Cancer Data from University of California Irvine (UCI) ML repository. To perform all these operation, Anaconda one of the open source distribution of Python has been used. The proposed work resulted in extemporize improvement in the NB and SVM classifier accuracy. The performance evaluation of the proposed model is estimated by using classification accuracy, confusion matrix, mean, standard deviation, variance, and root mean-squared error.

The experimental results shows that 70-30 data split will result in best accuracy. SVM acts as a feature optimizer of 12 best features with the result of 97.66% accuracy and improvement of 1.17% after feature reduction. NB results with feature optimizer 17 of best features with the result of 96.49% accuracy and improvement of 1.17% after feature reduction.

The study shows that proposal model works very effectively as compare to the existing models with respect to accuracy measures.

Details

Big Data Analytics and Intelligence: A Perspective for Health Care
Type: Book
ISBN: 978-1-83909-099-8

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Article

Swapnil Vyavahare, Shailendra Kumar and Deepak Panghal

This paper aims to focus on an experimental study of surface roughness, dimensional accuracy and time of fabrication of parts produced by fused deposition modelling (FDM…

Abstract

Purpose

This paper aims to focus on an experimental study of surface roughness, dimensional accuracy and time of fabrication of parts produced by fused deposition modelling (FDM) technique of additive manufacturing. The fabricated parts of acrylonitrile butadiene styrene (ABS) material have pyramidal and conical features. Influence of five process parameters of FDM, namely, layer thickness, wall print speed, build orientation, wall thickness and extrusion temperature is studied on response characteristics. Furthermore, regression models for responses are developed and significant process parameters are optimized.

Design/methodology/approach

Comprehensive experimental study is performed using response surface methodology. Analysis of variance is used to investigate the influence of process parameters on surface roughness, dimensional accuracy and time of fabrication in both outer pyramidal and inner conical regions of part. Furthermore, a multi-response optimization using desirability function is performed to minimize surface roughness, improve dimensional accuracy and minimize time of fabrication of parts.

Findings

It is found that layer thickness and build orientation are significant process parameters for surface roughness of parts. Surface roughness increases with increase in layer thickness, while it decreases initially and then increases with increase in build orientation. Layer thickness, wall print speed and build orientation are significant process parameters for dimensional accuracy of FDM parts. For the time of fabrication, layer thickness and build orientation are found as significant process parameters. Based on the analysis, statistical non-linear quadratic models are developed to predict surface roughness, dimensional accuracy and time of fabrication. Optimization of process parameters is also performed using desirability function.

Research limitations/implications

The present study is restricted to the parts of ABS material with pyramidal and conical features only fabricated on FDM machine with delta configuration.

Originality/value

From the critical review of literature it is found that some researchers have made to study the influence of few process parameters on surface roughness, dimensional accuracy and time of fabrication of simple geometrical parts. Also, regression models and optimization of process parameters has been performed for simple parts. The present work is focussed on studying all these aspects in complicated geometrical parts with pyramidal and conical features.

Details

Rapid Prototyping Journal, vol. 26 no. 9
Type: Research Article
ISSN: 1355-2546

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Article

Zhanni Luo, Billy O'Steen and Cheryl Brown

To build adaptive learning systems for a better learning experience, designers need to identify users’ behaviour patterns and provide adaptive learning materials…

Abstract

Purpose

To build adaptive learning systems for a better learning experience, designers need to identify users’ behaviour patterns and provide adaptive learning materials accordingly. This study involved a quasi-experiment and also this paper aims to investigate the accuracy of eye-tracking technology in identifying visualisers and verbalisers and the contributing factors to diverse levels of accuracy, which lays the foundation for the establishment of adaptive learning systems.

Design/methodology/approach

The authors prepared eight documents with different image-text combinations with the intention of triggering participants’ natural reading habits. By analysing the eye-movement data, this author categorised the 22 participants as visualisers or verbalisers. The results were compared for accuracy measure with participants’ self-reports in response to the index of learning style questionnaire.

Findings

The results showed that visualisers and verbalisers presented significantly different eye-movement patterns, which was confirmed by the fixation data from the Tobii eye-tracker with the detection accuracy ranged from 38% to 77%. Various factors contributed to a range of levels of accuracy, including highlighted elements, learning context, complex background, low relevance of images and texts, learner differences, awareness of experimental settings, self-conception and prior knowledge.

Originality/value

To the authors’ knowledge, this is the first paper investigating the feasibility of eye-tracking technology to identify visualisers and verbalisers for the development of adaptive learning systems.

Details

Interactive Technology and Smart Education, vol. 17 no. 2
Type: Research Article
ISSN: 1741-5659

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Article

Faten Ben Ahmed, Bassem Salhi and Anis Jarboui

The purpose of this study is to present an extension to the research area dealing with the Tunisia initial public offering (IPO) associated earnings management forecasts…

Abstract

Purpose

The purpose of this study is to present an extension to the research area dealing with the Tunisia initial public offering (IPO) associated earnings management forecasts, by an examination of the corporate governance mechanisms and earnings forecast accuracy relating impacts.

Design/methodology/approach

The authors use a multiple regression technique (FGLS) to estimate the effect of corporate governance structures and audit quality on earnings forecast accuracy. A sample of 33 IPO companies (165 firm-year observations) collected over the period ranging between 2011 and 2015 was applied.

Findings

The finding of this study reveals that the companies displaying a respectable audit committee size have a significant level of earnings forecast accuracy. Similarly, the accuracy level associated with IPO earnings forecasts is positively influenced by the use of the brand-name auditor.

Research limitations/implications

This study is based on a small sample from a single jurisdiction and limited time period. In fact, the findings examine how financial statements are measured and reported and assess additional regulation to protect investors and understand as well as manage earnings forecast accuracy in IPO prospectuses.

Practical implications

The findings of the study provide some implications for regulators, financial analysts, investors and users of financial statements, particularly who are investigating in potentially IPO firms. This study has an implication for market regulators who suggest that a requirement to publish very detailed forecast information would improve market efficiency by reducing the forecast error.

Originality/value

Previous studies on this subject carried out in other countries with a regulatory framework differ from that of Tunisia, which obligatorily obliges the publication of the forecasts in the prospectus of IPO and capital increase. This is one of the most important studies that simultaneously tests the impacts of corporate governance and audit quality on earnings forecast accuracy in an emerging market, and the results of this study may give strength to Tunisian as well as other developing countries.

Details

Journal of Financial Reporting and Accounting, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1985-2517

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Article

Farid Esmaeili, Hamid Ebadi, Mohammad Saadatseresht and Farzin Kalantary

Displacement measurement in large-scale structures (such as excavation walls) is one of the most important applications of close-range photogrammetry, in which achieving…

Abstract

Purpose

Displacement measurement in large-scale structures (such as excavation walls) is one of the most important applications of close-range photogrammetry, in which achieving high precision requires extracting and accurately matching local features from convergent images. The purpose of this study is to introduce a new multi-image pointing (MIP) algorithm is introduced based on the characteristics of the geometric model generated from the initial matching. This self-adaptive algorithm is used to correct and improve the accuracy of the extracted positions from local features in the convergent images.

Design/methodology/approach

In this paper, the new MIP algorithm based on the geometric characteristics of the model generated from the initial matching was introduced, which in a self-adaptive way corrected the extracted image coordinates. The unique characteristics of this proposed algorithm were that the position correction was accomplished with the help of continuous interaction between the 3D model coordinates and the image coordinates and that it had the least dependency on the geometric and radiometric nature of the images. After the initial feature extraction and implementation of the MIP algorithm, the image coordinates were ready for use in the displacement measurement process. The combined photogrammetry displacement adjustment (CPDA) algorithm was used for displacement measurement between two epochs. Micro-geodesy, target-based photogrammetry and the proposed MIP methods were used in a displacement measurement project for an excavation wall in the Velenjak area in Tehran, Iran, to evaluate the proposed algorithm performance. According to the results, the measurement accuracy of the point geo-coordinates of 8 mm and the displacement accuracy of 13 mm could be achieved using the MIP algorithm. In addition to the micro-geodesy method, the accuracy of the results was matched by the cracks created behind the project’s wall. Given the maximum allowable displacement limit of 4 cm in this project, the use of the MIP algorithm produced the required accuracy to determine the critical displacement in the project.

Findings

Evaluation of the results demonstrated that the accuracy of 8 mm in determining the position of the points on the feature and the accuracy of 13 mm in the displacement measurement of the excavation walls could be achieved using precise positioning of local features on images using the MIP algorithm.The proposed algorithm can be used in all applications that need to achieve high accuracy in determining the 3D coordinates of local features in close-range photogrammetry.

Originality/value

Some advantages of the proposed MIP photogrammetry algorithm, including the ease of obtaining observations and using local features on the structure in the images rather than installing the artificial targets, make it possible to effectively replace micro-geodesy and instrumentation methods. In addition, the proposed MIP method is superior to the target-based photogrammetric method because it does not need artificial target installation and protection. Moreover, in each photogrammetric application that needs to determine the exact point coordinates on the feature, the proposed algorithm can be very effective in providing the possibility to achieve the required accuracy according to the desired objectives.

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Article

Jinlei Zhuang, Ruifeng Li, Chuqing Cao, Yunfeng Gao, Ke Wang and Feiyang Wang

This paper aims to propose a measurement principle and a calibration method of measurement system integrated with serial robot and 3D camera to identify its parameters…

Abstract

Purpose

This paper aims to propose a measurement principle and a calibration method of measurement system integrated with serial robot and 3D camera to identify its parameters conveniently and achieve high measurement accuracy.

Design/methodology/approach

A stiffness and kinematic measurement principle of the integrated system is proposed, which considers the influence of robot weight and load weight on measurement accuracy. Then an error model is derived based on the principle that the coordinate of sphere center is invariant, which can simultaneously identify the parameters of joint stiffness, kinematic and hand-eye relationship. Further, considering the errors of the parameters to be calibrated and the measurement error of 3D camera, a method to generate calibration observation data is proposed to validate both calibration accuracy and parameter identification accuracy of calibration method.

Findings

Comparative simulations and experiments of conventional kinematic calibration method and the stiffness and kinematic calibration method proposed in this paper are conducted. The results of the simulations show that the proposed method is more accurate, and the identified values of angle parameters in modified Denavit and Hartenberg model are closer to their real values. Compared with the conventional calibration method in experiments, the proposed method decreases the maximum and mean errors by 19.9% and 13.4%, respectively.

Originality/value

A new measurement principle and a novel calibration method are proposed. The proposed method can simultaneously identify joint stiffness, kinematic and hand-eye parameters and obtain not only higher measurement accuracy but also higher parameter identification accuracy, which is suitable for on-site calibration.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

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Article

Changjoon Lee

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

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Practical implications

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.

Originality/value

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.

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-6123

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Article

Khawla Hlel, Ines Kahloul and Houssam Bouzgarrou

This paper aims to examine whether International Financial Reporting Standards (IFRS) adoption and corporate governance attributes increase the management earnings…

Abstract

Purpose

This paper aims to examine whether International Financial Reporting Standards (IFRS) adoption and corporate governance attributes increase the management earnings forecasts’ accuracy disclosed in prospectuses for French Initial Public Offerings (IPOs).

Design/methodology/approach

The analysis is based on cross-sectional regression explaining the absolute forecast errors by using 45 French firms that made IPOs between 2005 and 2016 in two French financial markets: Euronext and Alternext.

Findings

In agreement with the agency theory and the signaling theory, the authors find that the IFRS adoption and the effective corporate governance, proxied by the board characteristics, increase the accuracy of management forecasts. As a result, this latter gives a credible signal in constructing and sustaining shareholders’ trust on the transparency and the reliability of such financial information.

Research limitations/implications

It is plausible that the limited size of the sample represents a limitation of this study. Another limitation is that no other corporate governance attributes such as board meeting frequency, audit committee measures and ownership structure are used.

Practical implications

Shareholders can take benefit from management forecasts accuracy to structure their investment portfolios efficiently to allocate their funds more effectively and mitigate the costs of adverse selection that they have to face. Furthermore, the authors expect the findings to be interesting to IPO firms, as this study highlights the efficiency of larger and independent boards in decreasing managerial discretion, increasing disclosure quality and supervising management. The results could encourage GAAP-adopters countries to move toward IFRS, as this research reinforces the role of IFRS in enhancing the quality of financial disclosure by offering the required information for shareholders.

Originality/value

This study is important because the potential investors should assess management earnings forecasts accuracy before they consider it when evaluating IPO firms. Also, this paper has some implications for the financial market. It is recommended that future investors pay more attention, when assessing the accuracy of management earnings forecasts, to the accounting regulations of the financial reporting along with the corporate governance mechanisms. Moreover, this study could incite French regulators to revise the AFEP-MEDEF code. Under this code, it could insist that larger and independent boards are more effective in performing their governing roles than smaller boards.

Details

Journal of Financial Reporting and Accounting, vol. 18 no. 2
Type: Research Article
ISSN: 1985-2517

Keywords

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