Independent Directors Research Articles

Corporate culture, corporate governance, and independent directors: evidence from textual analysis

PurposeTaking advantage of a unique measure of corporate culture obtained from advanced machine learning algorithms, this study aims to explore how corporate culture strength is influenced by board independence, which is one of the most crucial aspects of the board of directors. Because of their independence from the corporation, outside independent directors are more likely to be unbiased. As a result, board independence is commonly used as a proxy for board quality.Design/methodology/approachIn addition to the standard regression analysis, the authors execute a variety of additional tests, i.e. propensity score matching, an instrumental variable analysis, Lewbel’s (2012) heteroscedastic identification and Oster’s (2019) testing for coefficient stability.FindingsThe results show that stronger board independence, measured by a higher proportion of independent directors, is significantly associated with corporate culture. In particular, a rise in board independence by one standard deviation results in an improvement in corporate culture by 32.8%.Originality/valueConducting empirical research on corporate culture is incredibly difficult due to the inherent difficulties in recognizing and assessing corporate culture, resulting in a lack of empirical research on corporate culture in the literature. The authors fill this important void in the literature. Exploiting a novel measure of corporate culture based on textual analysis, to the best of the authors’ knowledge, this study is the first to link corporate culture to corporate governance with a specific focus on board independence.

Are women greener? Board gender diversity and corporate green technology innovation in China

This article investigates how board gender diversity impacts corporate green technology innovation, and whether regional gender contexts as well as corporate financial constraints moderate this relationship. Using a panel of 20,834 firm-year observations of China, the results indicate a statistically significant positive association between board gender diversity and corporate green technology innovation. Specifically, the study finds that boards with three or more female directors have a stronger positive effect on green technology innovation than boards with two or fewer female directors, in line with the critical mass theory. Besides, the result shows that the effect of female executive directors outweighs that of female independent directors. Further, the positive association between female directors and green technology innovation is found to be more pronounced in firms located in regions with higher levels of gender equality and higher proportions of women in politics, while financial constraints act to alleviate the extent of the positive relationship. Additionally, female directors play a potent role in reducing corporate carbon emissions, particularly for high-polluting firms and those located in regions with stricter environmental regulation. The key results remain unchanged after correcting for endogeneity concern. Overall, this study has substantial practical implications and provides valuable insights for managers and policymakers regarding the contribution of female leadership in enhancing corporate environmental performance.

Investigating the Impact of Corporate Governance on Financial Performance and Firm Value Prior To And During the Covid-19 Pandemic

Objective: This study aims to compare the impact of Corporate Governance on Financial Performance and Firm Value before and during Covid-19 Pandemic. Theoretical framework: This research is based on stakeholders and shareholders who also have rights to what they have provided to the company. Method: The study focuses on companies listed on the Indonesia Stock Exchange, analyzing the period from 2018 to 2021, which limits its scope to these entities during and before the pandemic. Utilizing ordinary least squares regression analysis through STATA, this study includes data from 146 companies. Results and conclusion: The results indicate that company size favorably influenced Financial Performances and negatively affected Firm Value during the pandemic. However, aspects of Corporate Governance, including the board of directors, the size of the board, independent directors and the audit committee, had no significant impact on the Financial Performance of the company's value during this period. Before the pandemic, the audit committee negatively affected Firm Value, company size was favorably correlated with Financial Performance and company age favorably influenced Firm Value. However, other elements of Corporate Governance, such as the board of directors, board size and independent directors, did not significantly affect the Financial Performance of the company's value. Implications of the research: This research offers important insights for companies in seeing how firm-related factors can lead to firm value in the capital market. Originality/value: This study contributes to the understanding of the relationship between Corporate Governance, Financial Performance, and Firm Value in the context of the COVID-19 pandemic.

Research on high-rise building risk identification and safety risk factor analysis

High-rise building is the trend of the future construction industry and the symbol of the continuous development of urbanization in China. However, safety accidents often occur during the construction of high-rise buildings, which bring people property losses, and sometimes even endanger the safety of life. Therefore, in order to effectively reduce the construction safety accident rate and improve the level of risk management, the construction of high-rise building safety risk focus on and research. This paper first analyzes the construction characteristics of high-rise buildings and accident types. According to the accident cause theory and hazard identification method, the major hazard sources in high-rise building construction are identified. Finally, this paper analyzes the construction of high-rise building risk factors. This paper can provide a theoretical basis for the construction of high-rise building safety risk assessment system, and provide a scientific and reliable risk management platform for the relevant units, so as to improve the safety awareness and risk management level of construction personnel.

The effect of MD&A disclosures on corporate performance: a panel quantile regression analysis

PurposeThe study aims to examine how the information disclosed by the managers in the management discussion and analysis (MD&A) reports varies at the different levels of corporate performance.Design/methodology/approachTo understand this quantile effect, first OLS technique was adopted and then, the quantile regression method was applied to explore the impact of MD&A disclosures on the firm performance across the lower and upper quantiles. The sample size for the study is 490 firms’ year observations for the period 2016–2022.FindingsThe results of the study demonstrate the negative but significant relationship between MD&A disclosures and corporate performance, supporting the two management strategies of “competitive disadvantage” in case of good performance and “management impression strategy” in case of poor performance. Furthermore, with other corporate governance variables, both the size of the board and the number of independent directors on the board are positively significant only in the case of the upper quantile indicating the heterogeneity in the relationship between the performance and the MD&A disclosures. Therefore, the overall findings of the study support that these results contradict the agency theory and the stakeholders’ theory as managers are not acting well as agents on behalf of the investors and work well only when they are controlled by the large board having more independent directors.Originality/valueTo the best of the authors’ knowledge, no study so far has incorporated quantile regression to assess the effect of MD&A disclosures on company performance at various levels of the firm performance, which gives more robust insights about the viewpoint of the managers on the different level of the firm performance. In other words, this study highlights the important information as to how the information provided in the MD&A reports varies as per the good or poor performance of the companies.

Supporting Consensus Reaching on Prioritizing Failure Modes in Reliability Management: The Role of Social-Trust-Driven Rating Modifications Willingness

Supporting Consensus Reaching on Prioritizing Failure Modes in Reliability Management: The Role of Social-Trust-Driven Rating Modifications Willingness

A Lithium-Ion Battery Degradation Prediction Model With Uncertainty Quantification for Its Predictive Maintenance

Battery degradation modeling in the presence of uncertainty is a key but challenging issue in the applications of battery predictive maintenance. This paper develops a capacity prediction model with uncertainty quantification for lithium-ion batteries and proposes a dynamic maintenance strategy which can help to make an optimized decision at each battery cycle stage. To be specific, after using the one-dimensional convolution neural network (1dCNN), deep representative features hidden in original measured signals are extracted. Then, the bi-directional long short-term memory (Bi-LSTM) is applied to estimate the battery capacities, while the quantile regression (QR) layer is embedded into the construction of the Bi-LSTM network to obtain the capacities for different quantiles. Next, the kernel density estimation (KDE) is utilized to derive the probability density of the predicted points at each battery cycle stage. Thus, the combination of 1dCNN, Bi-LSTM, QR and KDE, named 1dCNN-BiLSTMQR-KDE, forms an efficacious capacity prediction model with reliable uncertainty management. Finally, the costs of different decisions at each battery cycle stage are evaluated, and the decision with the lower cost will be chosen. The whole proposition is verified on battery degradation datasets from NASA, and the comparison with other methods show that the proposed method is competitive.

Performance of Hybrid Nanofluids of Mineral Oil and Vegetable oil based Ester

The prosperity and economic development of a nation depend on its capability to maintain reliable and high-quality electric power management. It is achieved through the availability of extremely reliable ancillary electrical equipment. A power transformer is one such piece of crucial equipment that transfers electricity from one circuit to another without altering the frequency. Mineral oil has been conventionally used as a liquid dielectric in transformers since the last century. However, in recent days, vegetable oil-based esters have emerged as a favourable alternative to mineral oils due to their biodegradability and sustainability. The introduction of nanotechnology led to massive studies to enhance the quality of liquid dielectrics. Further, the addition of more than one nanoparticle to the base fluid has broadened the scope of nanofluids’ property enhancement. This study focused on the assessment of the dielectric properties of hybrid nanofluids consisting of ZnO and reduced graphene. Mineral oil and vegetable-based transformer oil were chosen as base fluids to prepare the nanofluids. The mass of the added nanoparticles was 0.01%. The ratio between the nanoparticles was selected as 1:1. The hybrid nanofluids were characterized for breakdown voltage viscosity at temperatures ranging from 40 °C to 100 °C, interfacial tension, tan delta, and resistivity. The overall properties of hybrid nanofluids were found to be improved due to the inclusion of ZnO and reduced graphene.

Does Institutional Ownership Moderate the Relationship Between Audit Committee Composition and Audit Report Lag: Evidence From Saudi

This research explores the moderating effect of institutional ownership on the relationship between audit committee attributes and audit report lag. The paper sampled data from 102 Saudi non-financial listed firms from 2012 to 2021. The data was analyzed using a fixed effect regression, while the generalized method of moments approach (GMM) was employed for robustness check. The research finding strongly suggests that the audit committee size may increase audit report lag. In contrast, it was found that audit committee independence and financial expertise may reduce audit report lag. In addition, the interaction effect reveals that the impact of audit committee financial expertise and the committee meetings on reducing audit report lag may be higher as institutional shareholding rises. Thus, the outcome validates the agency theory perspective that the active monitoring of institutional investors may shape firms’ internal governance systems. More importantly, the finding implies that firms should prefer a smaller audit size with a higher ratio of independent directors and financial experts to improve financial reporting quality. They should also embrace institutional shareholding to reduce audit report lag. Thus, lowering audit report lag may mitigate information disparity between firms and prospective investors, reducing agency conflicts and boosting firm value.

Reviewing the application of big data analytics in satellite network management to optimize performance and enhance reliability, with implications for future technology developments

The application of big data analytics in satellite network management has emerged as a transformative approach to optimize performance and enhance reliability in the satellite telecommunications industry. This paper reviews the current state of big data analytics in satellite network management, highlighting its key applications and benefits. By analyzing large volumes of data generated by satellite networks, big data analytics enables satellite telecommunications companies to gain valuable insights into network performance, identify potential issues, and take proactive measures to ensure optimal performance. One of the key applications of big data analytics in satellite network management is predictive maintenance. By analyzing historical data and equipment performance metrics, companies can predict when equipment is likely to fail and take preventive measures to avoid downtime. This not only improves network reliability but also reduces maintenance costs and improves overall operational efficiency. Another important application is network optimization. Big data analytics can analyze network traffic, weather conditions, and other factors to optimize satellite beam coverage, frequency allocation, and routing. This helps companies maximize bandwidth utilization, reduce interference, and improve service quality. The implications of big data analytics for future technology developments in satellite network management are significant. As the volume of data generated by satellite networks continues to grow, there is a need for advanced analytics tools and techniques to process and analyze this data efficiently. Future technology developments in areas such as AI, machine learning, and data visualization are expected to play a key role in enhancing the capabilities of big data analytics in satellite network management. In conclusion, the application of big data analytics in satellite network management offers significant benefits in terms of optimizing performance and enhancing reliability. By leveraging the insights provided by big data analytics, satellite telecommunications companies can improve operational efficiency, reduce costs, and deliver better services to their customers. Future technology developments will further enhance the capabilities of big data analytics, paving the way for more efficient and reliable satellite network management.

Design and On-Orbit Performance of the Payload Rack Thermal Management System for China Space Station Experimental Lab Module

An efficient and reliable spacecraft payload thermal management method is one of the key problems to build China Space Station (CSS). Aiming at the outstanding characteristics and difficulties of the payloads rack in the experimental lab module of CSS, in the aspects of thermal control interface, boundary constraint, scale quantity, space layout, diversity of temperature control, operation mode and working life, etc., a two-stage thermal management scheme based on single-phase fluid loop is proposed and constructed. A fluid drive unit is designed to drive the fluid circulation and health management of the module thermal control bus (TCB). In view of the different characteristics of the payload racks, three different types of second-stage thermal control systems are proposed, and different thermal control terminals are designed, in order to solve the problem of thermal control resource allocation and health management in payload racks. A method based on “pump bypass” and “valve resistance ratio” is used to control the flow rate of the thermal management system. Based on the overall scheme of the thermal management system and the developed flight products, on-orbit verification and data analysis are carried out. Flight verification shows that the key parameters of the fluid loop in the thermal management system on orbit are basically consistent with the ground data; the maximum deviation is 1.84%. The pressure control accuracy of the bypass system reaches ±2%, and the active heat transfer efficiency of the integrated thermal management system is over 83%, which can effectively meet the thermal control requirements of the two-stage payloads in the module and rack. After on-orbit flight verification, the designed thermal control system works well on orbit and exhibits good stability.

Optimization Strategies for Electric Vehicle Charging and Routing: A Comprehensive Review

Based on information from recent research, by 2045, Electric Vehicles (EV) will dominate the roads with presence of more than 80% of its kind. Hence, these vehicles' grid level penetration will increase proportionally, which challenges the existing grid infrastructure in terms of its reliability and energy management capabilities. New techniques to store and consume massive quantities of energy from the power grid, as well as infusing the captive energy within the EV in response to grid demands, are emerging with the advent of electric vehicles. Everything could be handled smoothly only if we schedule the EV operation (charging/discharging) more optimally and efficiently using scheduling algorithms. Despite the existence of many routings and charging schedule computations, nature-inspired optimization approaches might play a critical role in responding to such routing challenges. Researchers have created several optimum scheduling approaches, such as Dynamic Programming, Differential Evolutionary Optimization Techniques, Collaborative Optimization Scheduling, Two-stage optimal scheduling strategy, and so on. The optimum schedule review examines the operation of an EV fleet while considering uncertainty sources and varied EV operating circumstances by integrating heuristic and meta-heuristic techniques. This paper exhibits a deep review on the various EV optimal scheduling techniques and adopted algorithms which are the emerging best practices like predictive analytics, dynamic routing, user centric planning, multi-objective optimization, etc. that reflect the industry's focus on leveraging advanced technologies, data-driven decision-making, and collaborative approaches to enhance the efficiency and sustainability of electric vehicle routing and charging scheduling.

Concept of structure and principles of management of project and product IT management

In the current article, the issues of two related specialties such as project management and product management are raised. The problem of overlapping responsibilities of these two directions and their interaction in terms of project activity is highlighted. In addition, the modern market of projects from various web platforms and the demand for specialists in these fields of activity were analyzed. The main duties and requirements for these specialties are highlighted. As well as areas in which the use of project and product managers is more oriented. IT management is the most important function in an organization because it ensures that the organization's technologies and IT systems are aligned with its shared business goals and that they are used effectively and efficiently. It includes a wide range of tasks and responsibilities, such as: development and implementation of IT strategy and policies, management of IT resources, ensuring security and reliability of IT systems, supervision of development and maintenance of IT systems and applications, management of IT projects, managing relationships with suppliers and other external partners and managing IT budgets and costs. It includes such professions as: business analyst, project manager, product manager and others. As the role of technology continues to play a critical role in the success of organizations, management in IT is becoming an increasingly important function and IT universities know that effective management can help organizations increase their competitiveness, reduce costs and increase the efficiency of their operations. The reason for the transition from general management to PM is often reliability - instead of a relatively abstract perspective to predictable results.The main problem is the overlapping of the duties of specialties and levels of responsibilities in accordance with the roles on the project.

Absorbent hygiene products disposal behaviour in informal settlements: identifying determinants and underlying mechanisms in Durban, South Africa

BackgroundWithin South Africa, many low-income communities lack reliable waste management services. Within these contexts, absorbent hygiene product (AHP) waste, including nappies (diapers), are not recycled, and are often dumped, ending up in watercourses and polluting the local environment. The structural barriers to collection which have been well explored, however the behavioural determinants of safe disposal for AHPs remains poorly understood. The purpose of this study is to determine the psycho-social factors driving AHP disposal behaviour for caregivers, while identifying potential underlying mechanisms (such as mental health), which may be influencing disposal behaviour, with the intention of informing a future, contextually appropriate and sustainable, collection system.MethodsThe cross-sectional study was conducted within three low-income communities located within eThekwini Municipality (Durban), South Africa. The study included a pre-study and a quantitative survey of 452 caregivers, utilising the RANAS approach of behaviour change. The quantitative questionnaire was based on the RANAS model to measure psycho-social factors underlying sanitary disposal of AHPs. Mental health was assessed using the Self-Reporting Questionnaire (SRQ-20). Statistical analysis involved regressing psycho-social factors onto disposal behaviour and exploring their interaction with mental health through a moderation model.ResultsOur findings suggest that one third of caregivers do not dispose of nappies sanitarily, despite intent (86.9%). Regression analysis revealed ten psycho-social factors which significantly predict the desired behavioural outcome, the sanitary disposal of AHPs. Caregivers with poor mental health were less likely to dispose of AHP sanitarily, which reflects previous research linking poor mental health and the impairment of health-related daily activities, particularly within vulnerable groups. Specifically, several psycho-social factors underlying were moderated by poor mental health, the prevalence of sanitary disposal of AHPs depended on mental condition of caregiver.ConclusionsOur findings confirmed the link between poor mental health and unsanitary AHPs disposal. This is especially relevant because poor mental health is common within South Africa. Addressing mental health problems within these communities is an essential step to providing sustainable waste management services. The findings informed an intervention strategy to implement a future collection system for these communities, and similar low-income or informal contexts within South Africa.

Women Directors: An Empirical Test of Critical Mass Hypothesis

This paper offers integrated theoretical-based empirical evidence regarding the role of female directors in promoting corporate common good using resource dependency model built on critical mass hypothesis. Using panel regression involving 220 firm-year observations from 2011 to 2021, the paper empirically assesses the moderating impacts of diversity and social inclusion policy, and gender-based power separation in determining the direction of causality between composition of female directors and foreign capital importation by the top 20 commercial banks in Nigeria. With approximately 30 per cent female director representation in the sampled banks (i.e., optimal gender threshold), the paper offers support to critical mass hypothesis and validates intrinsic benefits of women in corporate boardroom. The empirical result shows that female director representation in boards with strong diversity and social inclusion policy and greater independent non-executive directors, is positively linked to resource dependency role of foreign capital importation. Diversity of power separation is found to be detrimental to such board tasks due to overwhelming tokenism effect that surrounds gender-based power delineation. These key findings are statistically significant and robust to a series of iterated sensitivity tests. In addition to offering emerging market contributions to the growing literature on critical mass theory application, findings from this study demonstrate the inherent value of combining multiple governance theories (such as resource dependency and critical mass models) and the dynamic research framework opportunities it offers for robust empirical testing.

Intellectual capital and financial performance: does board size and independent directors matter? An empirical enquiry

Purpose Intellectual capital (IC) is a paramount resource for competitiveness in the knowledge-based financial sectors of the economy. As financial technology advances, specifically in the banking industry, it is vital to understand the effect of IC on financial performance. This study aims to investigate the effect of IC on return on equity (ROE), with a unique emphasis on the moderating role of board attributes. Previous studies have overlooked this moderating role. Design/methodology/approach The study sample consists of 17 banks and a panel data set spanning 2016–2021, extracted from annual reports. Antel Pulic’s value-added intellectual coefficient (VAIC) model is used to compute IC. To analyze the data, a generalized least squares analysis is conducted. The robustness of the analysis is ensured by using the two-stage least squares (2SLS) econometric technique. Findings The findings indicate that both the VAIC and human capital efficiency (HCE) have a significant impact on the ROE of banks. In terms of moderation, it is observed that board size (BS) exerts a negative effect on the association between VAIC, HCE, structural capital efficiency and ROE. Additionally, BS positively compounds the connection between capital employed efficiency and ROE. Similarly, the presence of independent directors (IND) significantly moderates the effects of VAIC and its components on the ROE of banks in Pakistan. Practical implications Banks should focus on the HCE for a higher ROE. Moreover, banks ought to prioritize appointing more independent directors in the boardroom for effective utilization of IC and greater ROE. Originality/value The findings of the study, which analyzed data from Pakistan’s banking sector, are original and provide additional insights into the literature on IC and board attributes.

Analyzing the Impact of Renewable Energy Integration on Power System Reliability

The integration of renewable energy sources is pivotal in addressing climate change and ensuring sustainable energy provision. Reliability management in power systems plays a crucial role in this endeavor, ensuring a consistent supply of clean energy while reducing carbon emissions. Extensive national and international research has demonstrated the effectiveness of modeling techniques, analytical methods, and management strategies in mitigating the volatility and uncertainty inherent in renewable energy. Reserve capacity planning, intelligent control systems, and energy storage technologies are instrumental in enhancing power system reliability. Case studies and empirical analyses offer valuable insights for other regions dealing with renewable energy challenges. With continuous technological advancements and policy support, the obstacles of renewable energy integration can be surmounted, moving us closer to a sustainable energy future. Ongoing research and international cooperation provide further opportunities and solutions to achieve clean energy objectives.

LEC-MiCs: Low-Energy Checkpointing in Mixed-Criticality Multi-Core Systems

With the advent of multicore platforms in designing Mixed-Criticality Systems (MCSs), simultaneous management of reliability and energy while guaranteeing an acceptable service level for low-criticality tasks is a crucial challenge. To ensure the reliability of the MCSs against transient faults, fault-tolerant techniques are employed which will increase energy consumption. To mitigate the energy overhead, the Dynamic Voltage and Frequency Scaling (DVFS) technique will be exploited. However, this technique might lead to violating the timing constraints of high-criticality tasks. Therefore, this paper presents, for the first time, the low-energy checkpointing technique to guarantee the reliability of multiple preemptive periodic mixed-criticality tasks in a multicore platform. In contrast to the previous works in checkpointing technique which consider a specific number of faults that all the tasks in the system should tolerate, in this paper, the number of tolerable faults for each execution section of a task, and in each voltage and frequency level is determined through proposed formulas to meet the reliability target based on safety standards. Then, our proposed method determines the number of checkpoints and their non-uniform intervals for the normal and overrun sections of each task to reduce energy consumption, respectively. Moreover, the unified demand bound function (DBF) analysis is proposed for analyzing the schedulability of the task set, where each high-criticality task meets its timing and reliability constraints, and low-criticality tasks execute based on their derived guaranteed periods in each operational mode of the system. Experimental results show that our proposed scheme meets the timing and reliability constraints while at the same time, improving the QoS of low-criticality tasks, and managing energy consumption with an average of 29.49%, and 32.78%, respectively.

Board independence, women directors and firm performance in Malaysian small-cap firms

This study examined how board independence and female directors (i.e., women in leadership) affected the performance of Malaysian small-cap firms. Small-cap firms trading on the Bursa Malaysia ACE (Access, Certainty Efficiency) market were the subject of this study due to the less strict listing standards imposed on them than large-listed firms. The 2012-2014 annual reports of firms listed on the ACE market were downloaded through the Bursa Malaysia website and the required data was hand-collected. The hypotheses were tested using quantile regression (QR). The data reveal that board independence and firm performance are unrelated unless company performance is in the 0.10 quantile. Board independence has a negative impact on business performance at the 0.10 quantile. Similarly, the connection between women directors and business success was negative in the lower quintiles particularly in the 0.10 and 0.30 quantiles. Nevertheless, in other quantiles, board independence and the presence of female directors on firm performance were not associated. The significance of the study lies in the possibility that small firms might find it excessively expensive to comply with the Malaysian Code of Corporate Governance (MCCG). This study examines the hitherto ignored roles of board independence and women directors in small-cap enterprises on firm performance.

Corporate Governance and Ownership Structure Effect on Corporate Social Performance: Evidence from Non-Financial Industries of Pakistan

This paper will examine the diversified associations between corporate governance and ownership structure impact on corporate social performance in dissimilar industries across Pakistan non-financial. The OLS models regression are estimation to using data from 2011 to 2020, that the non-financial industries of Pakistan. Corporate governance including board independence (BINDP), board size (BSIZE), and audit size and committee (A&COM), and structure ownership including, ownership managerial (MOWN), ownership family (FOWN), and ownership concentration (COWN), inspires of organizations corporate social performance with environmental and social risk market capitalization. Generally, the outcomes significant of ownership structure and corporate governance is recognized in industries of non-financial different at a joint level while examines the organizations with a risk whole risk market capitalization disclosure. That suggest to identifying the ownership structure and corporate governance can risk mitigate the market capitalization disclosure non-financial industries in term of correlation the corporate social performance improving and the developed the benefits with the calculation of identical female director in women on board and family ownership organizations (independent or executive) to the panel. This study also demand consideration to the corporate governance and improve structure ownership to enhance the corporate social responsibility in industries non-financial with market risk capitalization analysis, whereas risk control performance of industries analysis after complement by critical mass and independent directors properties.