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1 – 10 of 104This study aims to explore the relationship between risk governance characteristics (chief risk officer [CRO], chief financial officer [CFO] and senior directors [SENIOR]) and…
Abstract
Purpose
This study aims to explore the relationship between risk governance characteristics (chief risk officer [CRO], chief financial officer [CFO] and senior directors [SENIOR]) and regulatory adjustments (RAs) in Organization for Economic Cooperation and Development public commercial banks.
Design/methodology/approach
Using principal component analysis (PCA) and regression models, the research analyzes a representative data set of these banks.
Findings
A significant negative correlation between risk governance characteristics and RAs is found. Sensitivity analysis on the regulatory Tier 1 capital ratio and the total capital ratio indicates mixed outcomes, suggesting a complex relationship that warrants further exploration.
Research limitations/implications
The study’s limited sample size calls for further research to confirm findings and explore risk governance’s impact on banks’ capital structures.
Practical implications
Enhanced risk governance could reduce RAs, influencing banking policy.
Social implications
The study advocates for improved banking regulatory practices, potentially increasing sector stability and public trust.
Originality/value
This study contributes to understanding risk governance’s role in regulatory compliance, offering insights for policymaking in banking.
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Anna Chwiłkowska-Kubala, Małgorzata Spychała and Tomasz Stachurski
We aimed to identify factors that influence student engagement in distance learning.
Abstract
Purpose
We aimed to identify factors that influence student engagement in distance learning.
Design/methodology/approach
The research involved a group of 671 students from economic and technical higher education institutions in Poland. We collected the data with the CAWI technique and an original survey. Next, we processed the data using principal component analysis and then used the extracted components as predictors in the induced smoothing LASSO regression model.
Findings
The components of the students’ attitude toward remote classes learning conditions are: satisfaction with teachers’ approach, attitude to distance learning, the system of students’ values and motivation, IT infrastructure of the university, building a network of contacts and communication skills. The final model consisted of seven statistically significant variables, encompassing the student’s sex, level of studies and the first five extracted PCs. Student’s system of values and motivation as well as attitude toward distance learning, were those variables that had the biggest influence on student engagement.
Practical implications
The research result suggests that in addition to students’ system of values and motivation and their attitude toward distance learning, the satisfaction level of teachers’ attitude is one of the three most important factors that influence student engagement during the distance learning process.
Originality/value
The main value of this article is the statistical model of student engagement during distance learning. The article fills the research gap in identifying and evaluating the impact of various factors determining student engagement in the distance learning process.
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Douglas Aghimien, Clinton Ohis Aigbavboa, Wellington Didibhuku Thwala, Nicholas Chileshe and Bhekinkosi Jabulani Dlamini
This paper presents the findings of assessing the strategies required for improved work-life balance (WLB) of construction workers in Eswatini. This was done to improve the…
Abstract
Purpose
This paper presents the findings of assessing the strategies required for improved work-life balance (WLB) of construction workers in Eswatini. This was done to improve the work-life relationship of construction workers and, in turn, improve the service delivery of the construction industry in the country.
Design/methodology/approach
The study adopted a quantitative research approach using a questionnaire administered to construction professionals in the country. The data gathered were analysed using frequency, percentage, Mann–Whitney U test, exploratory and confirmatory factor analysis (CFA).
Findings
The findings revealed that the level of implementation of WLB initiatives in the Eswatini construction industry is still low. Following the attaining of several model fitness, the study found that the key strategies needed for effective WLB can be classified into four significant components, namely: (1) leave, (2) health and wellness, (3) work flexibility, and; (4) days off/shared work.
Practical implications
The findings offer valuable benefits to construction participants as the adoption of the identified critical strategies can lead to the fulfilment of WLB of the construction workforce and by extension, the construction industry can benefit from better job performance.
Originality/value
This study is the first to assess the strategies needed for improved WLB of construction workers in Eswatini. Furthermore, the study offers a theoretical platform for future discourse on WLB in Eswatini, a country that has not gained significant attention in past WLB literature.
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Temidayo Oluwasola Osunsanmi, Timothy O. Olawumi, Andrew Smith, Suha Jaradat, Clinton Aigbavboa, John Aliu, Ayodeji Oke, Oluwaseyi Ajayi and Opeyemi Oyeyipo
The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present…
Abstract
Purpose
The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.
Design/methodology/approach
This study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.
Findings
The model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.
Originality/value
Numerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.
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Dieudonné Sawadogo, Seydou Sané and Somnoma Edouard Kaboré
The objectives of this study are twofold: first, to identify the effect of sustainability management on the success of international development projects, and second, to…
Abstract
Purpose
The objectives of this study are twofold: first, to identify the effect of sustainability management on the success of international development projects, and second, to investigate the moderating role of political and social skills on this relationship.
Design/methodology/approach
This study adopted a quantitative research methodology based on questionnaire data collected from 43 international development project managers from various fields in Burkina Faso (West Africa). Descriptive statistics and exploratory and confirmatory analyses using principal component analysis were used to assess the quality of the measurement model. A multiple regression analysis based on the partial least squares approach was used to test the hypotheses.
Findings
The results show that sustainability management positively contributes to the success of international development projects. However, given the specificities of these projects and their perception of success, the project coordinator's political and social skills do not predict a greater impact of sustainability management on the success of international development projects. The study also found that project coordinators prioritize their technical skills over behavioral ones.
Originality/value
This study fills a gap in the literature, given that little is known about the moderating role of political and social skills in the effect of sustainability management on the success of specific projects such as international development projects.
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Douglas Aghimien, Clinton Aigbavboa, Ayodeji Emmanuel Oke and John Aliu
Digitalisation, which involves the use of digital technologies in transforming an organisation’s activities, transcends just the acquiring of emerging digital tools. Having the…
Abstract
Purpose
Digitalisation, which involves the use of digital technologies in transforming an organisation’s activities, transcends just the acquiring of emerging digital tools. Having the right people to drive the implementation of these technologies and attaining strategic organisational goals is essential. While most studies have focused on the use of emerging technologies in the construction industry, less attention has been given to the ‘people’ dimension. Therefore, this study aims to assess the people-related features needed for construction digitalisation.
Design/methodology/approach
The study adopted pragmatic thinking using a mixed-method approach. A Delphi was used to achieve the qualitative aspect of the research, while a questionnaire survey conducted among 222 construction professionals was used to achieve the quantitative aspect. The data gathered were analysed using frequency, percentage, mean item score, Kruskal–Wallis H test, exploratory factor analysis and confirmatory factor analysis.
Findings
Based on acceptable reliability, validity and model fit indices, the study found that the people-related factors needed for construction digitalisation can be grouped into technical capability of personnel, attracting and retaining digital talent and organisation’s digital culture.
Practical implications
The findings offer valuable benefits to construction organisations as understanding these identified people features can help lead to better deployment of digital tools and the attainment of the digital transformation.
Originality/value
This study attempts to fill the gap in the shortage of literature exploring the people dimension of construction digitalisation. The study offers an excellent theoretical backdrop for future works on digital talent for construction digitalisation, which has gained less attention in the current construction digitalisation discourse.
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Łukasz Kurowski and Paweł Smaga
Financial stability has become a focal point for central banks since the global financial crisis. However, the optimal mix between monetary and financial stability policies…
Abstract
Purpose
Financial stability has become a focal point for central banks since the global financial crisis. However, the optimal mix between monetary and financial stability policies remains unclear. In this study, the “soft” approach to such policy mix was tested – how often monetary policy (in inflation reports) analyses financial stability issues. This paper aims to discuss the aforementioned objective.
Design/methodology/approach
A total of 648 inflation reports published by 11 central banks from post-communist countries in 1998-2019 were reviewed using a text-mining method.
Findings
Results show that financial stability topics (mainly cyclical aspects of systemic risk) on average account for only 2%of inflation reports’ content. Although this share has grown somewhat since the global financial crisis (in CZ, HU and PL), it still remains at a low level. Thus, not enough evidence was found on the use of a “soft” policy mix in post-communist countries.
Practical implications
Given the strong interactions between price and financial stability, this paper emphasizes the need to increase the attention of monetary policymakers to financial stability issues.
Originality/value
The study combines two research areas, i.e. monetary policy and modern text mining techniques on a sample of post-communist countries, something which to the best of the authors’ knowledge has not been sufficiently explored in the literature before.
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Stratos Moschidis, Angelos Markos and Dimosthenis Ioannidis
The purpose of this paper is to develop a software-library in the R programming language that implements the concepts of the interpretive coordinate, interpretive axis and…
Abstract
Purpose
The purpose of this paper is to develop a software-library in the R programming language that implements the concepts of the interpretive coordinate, interpretive axis and interpretive plane. This allows for the automatic and reliable interpretation of results from the multiple correspondence analysis (MCA) as previously proposed and published. Consequently, the users can seamlessly apply these concepts to their data, both via R commands and a corresponding graphical interface.
Design/methodology/approach
Within the context of this study, and through extensive literature review, the advantages of developing software using the Shiny library were examined. This library allows for the development of full-stack applications for R users without the need for knowledge of the corresponding technologies required for the development of complex applications. Additionally, the structural components of a Shiny application were presented, leading ultimately to the proposed software application.
Findings
Software utilizing the Shiny library enables nonexpert developers to rapidly develop specialized applications, either to present or to assist in the understanding of objects or concepts that are scientifically intriguing and complex. Specifically, with this proposed application, the users can promptly and effectively apply the scientific concepts addressed in this study to their data. Additionally, they can dynamically generate charts and reports that are readily available for download and sharing.
Research limitations/implications
The proposed package is an implementation of the fundamental concepts of the exploratory MCA method. In the next step, discoveries from the geometric data analysis will be added as features to provide more comprehensive information to the users.
Practical implications
The practical implications of this work include the dissemination of the method’s use to a broader audience. Additionally, the decision to implement it with open-source code will result in the integration of the package’s functions by other third-party user packages.
Originality/value
The proposed software introduces the initial implementation of concepts such as interpretive coordination, the interpretive axis and the interpretive plane. This package aims to broaden and simplify the application of these concepts to benefit stakeholders in scientific research. The software can be accessed for free in a code repository, the link to which is provided in the full text of the study.
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Martin Novák, Berenika Hausnerova, Vladimir Pata and Daniel Sanetrnik
This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass…
Abstract
Purpose
This study aims to enhance merging of additive manufacturing (AM) techniques with powder injection molding (PIM). In this way, the prototypes could be 3D-printed and mass production implemented using PIM. Thus, the surface properties and mechanical performance of parts produced using powder/polymer binder feedstocks [material extrusion (MEX) and PIM] were investigated and compared with powder manufacturing based on direct metal laser sintering (DMLS).
Design/methodology/approach
PIM parts were manufactured from 17-4PH stainless steel PIM-quality powder and powder intended for powder bed fusion compounded with a recently developed environmentally benign binder. Rheological data obtained at the relevant temperatures were used to set up the process parameters of injection molding. The tensile and yield strengths as well as the strain at break were determined for PIM sintered parts and compared to those produced using MEX and DMLS. Surface properties were evaluated through a 3D scanner and analyzed with advanced statistical tools.
Findings
Advanced statistical analyses of the surface properties showed the proximity between the surfaces created via PIM and MEX. The tensile and yield strengths, as well as the strain at break, suggested that DMLS provides sintered samples with the highest strength and ductility; however, PIM parts made from environmentally benign feedstock may successfully compete with this manufacturing route.
Originality/value
This study addresses the issues connected to the merging of two environmentally efficient processing routes. The literature survey included has shown that there is so far no study comparing AM and PIM techniques systematically on the fixed part shape and dimensions using advanced statistical tools to derive the proximity of the investigated processing routes.
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