Hee Sun Kim and Jia Wang
The purpose of this article is to examine the antecedents and consequences of organizational silence and employee silence to determine whether these two concepts should be…
Abstract
Purpose
The purpose of this article is to examine the antecedents and consequences of organizational silence and employee silence to determine whether these two concepts should be distinguished rather than used interchangeably in research.
Design/methodology/approach
This study conducted a systematic literature review of 79 studies on organizational silence and 113 on employee silence, leading to three major findings.
Findings
First, this study shows that organizational silence is a collective phenomenon and employee silence occurs at the individual level; therefore, indicating they should be treated as two distinct concepts. Second, both types of silence are influenced by contextual factors (internal and external) and leadership. Third, organizational silence impacts both individual and organizational outcomes, whereas employee silence mainly affects an individual’s psychological health and performance.
Originality/value
This research clarifies the distinction between organizational silence and employee silence, offering guidance for researchers on how to approach these concepts. It also highlights the critical need to address workplace silence and the potential harm it may cause to both organizational and individual well-being if left unaddressed. Furthermore, this research supports organizational leaders and human resource developers in fostering a healthier work culture, improving performance and driving continuous improvement.
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This chapter presents comparative analyses of the term structure of interbank interest rates in Japan under different regimes of non-traditional monetary policy. The yield curve…
Abstract
This chapter presents comparative analyses of the term structure of interbank interest rates in Japan under different regimes of non-traditional monetary policy. The yield curve under a ‘quantitative and qualitative easing policy’ is driven by three common trends and driven by two common trends under a ‘negative interest rate policy’. Market practitioners assumed that there was little room for interbank interest rates to be lowered because of the zero lower bound restriction under ‘a quantitative and qualitative easing policy’. But after the BOJ introduced ‘a negative interest rate policy’, the zero lower bound restriction was lifted. This is why the market function of interbank interest rate began to recover.
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Sahil Sholla and Iraq Ahmad Reshi
This paper does not concern with the “why” of ethics. Such questions are typically of interest to philosophers and are outside the scope of this work. In the next section, the…
Abstract
Purpose
This paper does not concern with the “why” of ethics. Such questions are typically of interest to philosophers and are outside the scope of this work. In the next section, the authors offer a look into “what” of ethics, i.e. various types and subtypes of ethics. Subsequently, the authors explore “how” of ethics, by summarising various computational approaches to ethical reasoning offered by researchers in the field.
Design/methodology/approach
The approaches are classified based on the application domain, ethical theory, agent type and design paradigm adopted. Moreover, promising research directions towards ethical reasoning are also presented.
Findings
Since the field is essentially interdisciplinary in nature, collaborative research from such areas as neuroscience, psychology, artificial intelligence, law and social sciences is necessary. It is hoped that this paper offers much needed insight into computational approaches for ethical reasoning paving way for researchers to further engage with the question.
Originality/value
In this paper, the authors discussed vaious computational approaches proposed by researchers to implement ethics. Although none of the approaches adequately answer the question, it is necessary to engage with the research effort to make a substantial contribution to the emerging research area. Though some effort has been made in the design of logic-based systems, they are largely in stages of infancy and merit considerable research.
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Sehrish Shahid, Kuldeep Kaur, Syed Mofazzal Mohyuddin, Verma Prikshat and Parth Patel
The purpose of the paper is to conduct a review of the literature on human-robot collaboration across different functions and activities of human resource management (HRM) and…
Abstract
Purpose
The purpose of the paper is to conduct a review of the literature on human-robot collaboration across different functions and activities of human resource management (HRM) and discuss its importance for change readiness in organizations.
Design/methodology/approach
A bibliometric analysis was conducted to identify emerging research themes in the fields of human resources (HR) and robotics, including change readiness. Based on the initial results of the bibliometric analysis, a systematic literature review was subsequently performed to gain a more specific understanding of research across various HRM functions and change readiness.
Findings
The results from bibliometric analysis and systematic review highlight that technological progression in HRM, such as AI-driven staffing and training techniques, improves effectiveness and personalization but raises concerns about privacy and job scrutiny. AI and robotics in performance evaluation enhance objectivity and reduce subjectivity, which can lead to disengagement. Generational differences, cultural factors and emotional quotient complicate readiness to adopt new technologies. The research emphasizes balancing technological effectiveness with employee involvement and meaningfulness to ensure successful implementation and engagement.
Originality/value
This paper synthesizes existing research, including literature, theoretical concepts and models, to identify best practices and successful strategies for implementing human-robot collaboration in HRM functions. It highlights gaps in the current literature and suggests areas for future research to advance the field of human-robot collaboration in HRM. By doing so, this paper enhances theoretical understanding while offering practical insights essential for effective change management.
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Zuhairan Yunmi Yunan and W. Alejandro Pacheco-Jaramillo
This paper aims to examine various indicators related to corruption and determine their impact on financial globalization in emerging countries. It will consider other factors…
Abstract
Purpose
This paper aims to examine various indicators related to corruption and determine their impact on financial globalization in emerging countries. It will consider other factors that may impact financial globalization and focus on how corruption within political, executive and public sector institutions can affect this process.
Design/methodology/approach
This paper uses a generalized method of moments (GMM) for a data sample of emerging countries covering 2000–2020. Corruption measurements are derived from the varieties of democracy data sets and Transparency International. It also includes data on foreign direct investment, portfolio flows, foreign exchange and international debt as separate indicators of financial globalization. These measures provide more detailed information on the types of financial transactions occurring across countries.
Findings
The results reveal that foreign investors may be less likely to enter certain sectors of the economy due to concerns about unethical practices and difficulties navigating the regulatory landscape in countries with high levels of corruption. This can lead to underdevelopment in sectors that are attractive to foreign investment and a reliance on a narrow range of sectors.
Originality/value
This paper offers valuable insights by integrating corruption and financial globalization indicators, using the GMM for robust analysis. It highlights how corruption influences foreign investment decisions, potentially leading to sectoral underdevelopment and overreliance in emerging countries.
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Dara Mojtahedi, Rosie Allen, Ellie Jess, Maria Ioannou and John Synnott
Employability skills training programmes are an effective means for reducing unemployment rates. Such programmes also have the potential to improve the general well-being (e.g…
Abstract
Purpose
Employability skills training programmes are an effective means for reducing unemployment rates. Such programmes also have the potential to improve the general well-being (e.g. self-efficacy) of disadvantaged individuals, however, reliable longitudinal evaluations of the psychological benefits of such programmes are limited. The present study evaluated the impact of an employability programme offered to disadvantaged adults in North-West England on self-efficacy. Additionally, the study aimed to identify risk factors for programme disengagement to identify at-risk groups that require further support.
Design/methodology/approach
Secondary longitudinal data pertaining to the background characteristics, programme engagement and self-efficacy scores (repeatedly measured on a monthly basis) of 308 programme users were analysed.
Findings
Results demonstrated that employability programme engagement significantly increased self-efficacy scores. Additionally, the findings suggested that individuals with mental health and learning difficulties were more likely to disengage from the programme. The findings demonstrate that employability programmes can have a positive impact on the well-being of individuals from disadvantaged backgrounds, however, prolonged engagement is needed for which some individuals require further support with.
Originality/value
The present study analysed longitudinal data from a diverse sample of disadvantaged individuals to reliably evaluate psychological outcomes from employability training programmes.
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Shokoofa Mostofi, Sohrab Kordrostami, Amir Hossein Refahi Sheikhani, Marzieh Faridi Masouleh and Soheil Shokri
This study aims to improve the detection and quantification of cardiac issues, which are a leading cause of mortality globally. By leveraging past data and using knowledge mining…
Abstract
Purpose
This study aims to improve the detection and quantification of cardiac issues, which are a leading cause of mortality globally. By leveraging past data and using knowledge mining strategies, this study seeks to develop a technique that could assess and predict the onset of cardiac sickness in real time. The use of a triple algorithm, combining particle swarm optimization (PSO), artificial bee colony (ABC) and support vector machine (SVM), is proposed to enhance the accuracy of predictions. The purpose is to contribute to the existing body of knowledge on cardiac disease prognosis and improve overall performance in health care.
Design/methodology/approach
This research uses a knowledge-mining strategy to enhance the detection and quantification of cardiac issues. Decision trees are used to form predictions of cardiovascular disorders, and these predictions are evaluated using training data and test results. The study has also introduced a novel triple algorithm that combines three different combination processes: PSO, ABC and SVM to process and merge the data. A neural network is then used to classify the data based on these three approaches. Real data on various aspects of cardiac disease are incorporated into the simulation.
Findings
The results of this study suggest that the proposed triple algorithm, using the combination of PSO, ABC and SVM, significantly improves the accuracy of predictions for cardiac disease. By processing and merging data using the triple algorithm, the neural network was able to effectively classify the data. The incorporation of real data on various aspects of cardiac disease in the simulation further enhanced the findings. This research contributes to the existing knowledge on cardiac disease prognosis and highlights the potential of leveraging past data for strategic forecasting in the health-care sector.
Originality/value
The originality of this research lies in the development of the triple algorithm, which combines multiple data mining strategies to improve prognosis accuracy for cardiac diseases. This approach differs from existing methods by using a combination of PSO, ABC, SVM, information gain, genetic algorithms and bacterial foraging optimization with the Gray Wolf Optimizer. The proposed technique offers a novel and valuable contribution to the field, enhancing the competitive position and overall performance of businesses in the health-care sector.
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Hasan Tutar, Hakan Eryüzlü, Ahmet Tuncay Erdem and Teymur Sarkhanov
This study investigates the correlation between economic development and scientific knowledge production indicators in the BRICS countries from 2000 to 2020, highlighting the…
Abstract
Purpose
This study investigates the correlation between economic development and scientific knowledge production indicators in the BRICS countries from 2000 to 2020, highlighting the importance of human resources, natural resources, and innovation. Addressing a gap in the existing literature, this study aims to contribute significantly to understanding this relationship.
Design/methodology/approach
Employing a descriptive statistical approach, this study utilizes GDP and per capita income as economic indicators and scientific data from WoS and SCOPUS databases, focusing on scientific document production and citations per document.
Findings
The analysis reveals a strong correlation between economic development and scientific performance within the BRICS nations during the specified period. It emphasizes the interdependence of economic progress and scientific prowess, underscoring that they cannot be considered independently.
Research limitations/implications
However, limitations exist, notably the reliance on specific databases that might not cover the entire scientific output and the inability to capture all factors influencing economic and scientific development.
Originality/value
Understanding this interdependence has crucial originality. Policymakers and stakeholders in BRICS countries can leverage these insights to prioritize investments in human capital development and scientific research. This approach can foster sustainable economic growth by reducing reliance on natural resources.
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This article examines the contribution of artificial intelligence to augmenting Intelligent Transportation Systems (ITS) to enhance traffic flow, safety, and sustainability.
Abstract
Purpose
This article examines the contribution of artificial intelligence to augmenting Intelligent Transportation Systems (ITS) to enhance traffic flow, safety, and sustainability.
Design/methodology/approach
The research investigates using AI technologies in ITS, including machine learning, computer vision, and deep learning. It analyzes case studies on ITS projects in Poznan, Mysore, Austin, New York City, and Beijing to identify essential components, advantages, and obstacles.
Findings
Using AI in Intelligent Transportation Systems has considerable opportunities for enhancing traffic efficiency, minimizing accidents, and fostering sustainable urban growth. Nonetheless, issues like data quality, real-time processing, security, public acceptability, and privacy concerns need resolution.
Originality/value
This article thoroughly examines AI-driven ITS, emphasizing successful applications and pinpointing significant difficulties. It underscores the need for a sustainable economic strategy for extensive adoption and enduring success.
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Shailendra Singh, Mahesh Sarva and Nitin Gupta
The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and…
Abstract
Purpose
The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.
Design/methodology/approach
The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.
Findings
Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.
Research limitations/implications
The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.
Practical implications
Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.
Originality/value
This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.