Kang Rae Cho, Suresh Krishnan and Douglas Nigh
Since 1970 there has been a phenomenal growth in the establishment of foreign commercial banks in the United States thus altering the competitive dimension of US banking markets…
Abstract
Since 1970 there has been a phenomenal growth in the establishment of foreign commercial banks in the United States thus altering the competitive dimension of US banking markets. An analysis of the state of foreign banking presence in the United States is here provided using recent disaggregated bank‐level information. Foreign commercial banks' country of origin, timing of entry, forms of involvement, main areas of specialisation, and related offices in the United States are investigated.
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Suhang Yang, Tangrui Chen and Zhifeng Xu
Recycled aggregate self-compacting concrete (RASCC) has the potential for sustainable resource utilization and has been widely applied. Predicting the compressive strength (CS) of…
Abstract
Purpose
Recycled aggregate self-compacting concrete (RASCC) has the potential for sustainable resource utilization and has been widely applied. Predicting the compressive strength (CS) of RASCC is challenging due to its complex composite nature and nonlinear behavior.
Design/methodology/approach
This study comprehensively evaluated commonly used machine learning (ML) techniques, including artificial neural networks (ANN), random trees (RT), bagging and random forests (RF) for predicting the CS of RASCC. The results indicate that RF and ANN models typically have advantages with higher R2 values, lower root mean square error (RMSE), mean square error (MSE) and mean absolute error (MAE) values.
Findings
The combination of ML and Shapley additive explanation (SHAP) interpretable algorithms provides physical rationality, allowing engineers to adjust the proportion based on parameter analysis to predict and design RASCC. The sensitivity analysis of the ML model indicates that ANN’s interpretation ability is weaker than tree-based algorithms (RT, BG and RF). ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.
Originality/value
ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.
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The application of steel fiber reinforced concrete (SFRC) beams is limited in practice, partially due to the lack of accurate shear strength prediction models. This study aims to…
Abstract
Purpose
The application of steel fiber reinforced concrete (SFRC) beams is limited in practice, partially due to the lack of accurate shear strength prediction models. This study aims to develop a reliable shear strength prediction model for SFRC beams.
Design/methodology/approach
In this study, an artificial neural network was employed to predict the shear strength of SFRC beams, utilizing a comprehensive database of 562 experimental studies. Multiple neural networks were established with varying hyperparameters, and their performance was evaluated using statistical parameters.
Findings
The neural network with 11 neurons showed superior results than other networks. The performance evaluation, efficiency and accuracy of the selected neural network were examined using margin of deviation, k-fold cross-validation, Shapley analysis, sensitivity analysis and parametric analysis. The proposed artificial neural network model accurately predicts the shear strength and outperforms other existing equations.
Originality/value
This research contributes to overcoming the limitations of existing prediction models for shear strength of SFRC beams without stirrups by developing a highly accurate model based on ANN. Utilizing a comprehensive database and rigorous evaluation techniques enhances the reliability and applicability of the proposed model in practical engineering applications.
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Naman Kaur, Anjana Kumari, Aparna Agarwal, Manisha Sabharwal and Saumya Dipti
This study aims to discuss the nutritional value and potential nutraceutical properties of Diospyros kaki L. (DKL); to encapsulate recent studies conducted across the world to…
Abstract
Purpose
This study aims to discuss the nutritional value and potential nutraceutical properties of Diospyros kaki L. (DKL); to encapsulate recent studies conducted across the world to develop functional foods using different parts of Persimmon fruit to emphasise on the need for further research on Persimmon fruit.
Design/methodology/approach
The methodology of the study involved surveying primary and secondary information generated in the respective field of interest. The papers found most suited for the research problem and objective of the study were selected. The perspectives taken by different studies and researchers were synthesised to generate a solution to the research problems and to bridge the research gaps in the field.
Findings
As a result of the global rise in the prevalence of metabolic disorders, researchers are aimed at identifying nutrient rich foods and techniques to develop functional foods for the population. Researchers have recognised the role of fresh fruits and vegetables, whole grains and probiotics, are now interested in leveraging these foods by incorporating them in conventional foods, such as breads, jams, pastas and yoghurts as functional ingredients. One such food that has gained the interests of various researchers is DKL. Owing to its rich macro-and micro-nutrient, as well as phytochemical content various studies have been conducted to explore the possibility of using it as a functional ingredient to develop a range of foods.
Research limitations/implications
A limited studies are available that have investigated the effect of the functional foods developed using different parts of Persimmon fruit on different ailments.
Originality/value
This study collected the data/information from recently published research in the field of health and medicinal benefits of Persimmon fruits and its utilisation to develop functional food.
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Examines the seventeenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects…
Abstract
Examines the seventeenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.
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Jun Sik Kim and Sol Kim
This paper investigates a retrospective on the Journal of Derivatives and Quantitative Studies (JDQS) on its 30th anniversary based on bibliometric. JDQSs yearly publications…
Abstract
This paper investigates a retrospective on the Journal of Derivatives and Quantitative Studies (JDQS) on its 30th anniversary based on bibliometric. JDQSs yearly publications, citations, impact factors, and centrality indices grew up in early 2010s, and diminished in 2020. Keyword network analysis reveals the JDQS's main keywords including behavioral finance, implied volatility, information asymmetry, price discovery, KOSPI200 futures, volatility, and KOSPI200 options. Citations of JDQS articles are mainly driven by article age, demeaned age squared, conference, nonacademic authors and language. In comparison between number of views and downloads for JDQS articles, we find that recent changes in publisher and editorial and publishing policies have increased visibility of JDQS.
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Meng Chenli, Ge Yuhui, Liu Xihuai and Eugene Abrokwah
The purpose of this paper is to test the mediating role of top management team (TMT) team trust in examining the relationship between team processes (internal and external) and…
Abstract
Purpose
The purpose of this paper is to test the mediating role of top management team (TMT) team trust in examining the relationship between team processes (internal and external) and human resource management (HRM) decision performance (quality and satisfaction) in the context of the People’s Republic of China.
Design/methodology/approach
The sample data of this study include 524 team members from 76 TMTs in east China’s Shanghai, Jiangsu, Zhejiang, Anhui provinces. IBM SPSS AMOS 22.0 software was employed for the data analysis.
Findings
The study finds that TMT internal and external processes have significant positive effects on HRM decision quality and satisfaction. The study further finds that TMT team trust partially mediates the relationship between TMT processes (internal and external processes) and HRM decision quality and satisfaction.
Practical implications
This research provides useful insights into the role of TMT team trust in enhancing managerial decision performance.
Originality/value
This study is among the limited studies that explore the influence of team trust in the relationship between TMT processes (internal and external processes) and HRM decision quality and satisfaction among TMTs in China. This study has extended TMT knowledge in mainstream management with guidelines on how to enhance organizational decision performance.
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Han-Cheng Chiu and Pin-Hua Chiang
The purpose of this paper is to examine the relationships between managers’ and supervisors’ trust in subordinates and team cooperation and to suggest that the downward flow of…
Abstract
Purpose
The purpose of this paper is to examine the relationships between managers’ and supervisors’ trust in subordinates and team cooperation and to suggest that the downward flow of trust affects team employees.
Design/methodology/approach
Data were collected from supervisor-employee dyads from a multisource field study.
Findings
Feeling trusted by managers has an indirect effect on team cooperation through feeling trusted by supervisors. In addition, there was a strong positive relation between feeling trusted by supervisors and team cooperation when team size was smaller, but a weak positive relation when team size was larger.
Practical implications
In order for subordinates to feel trusted, management leaders must implement actions that include: delegation and empowerment, participative decision-making and listening with respect and full attention. It is also suggested that the team size should not be too large.
Originality/value
We integrate theories of social exchange, social information processing, social learning and attraction-selection-attrition to test a trickle-down model of how trust in subordinates cascades down through management levels and ultimately affects team cooperation.