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This study aims to investigate the association between corporate social responsibility (CSR) performance and the cost of debt financing (CODF) in Malaysia. It further explores whether the potential impact of CSR performance on debt pricing is moderated by the females’ representation on board and female directors’ foreign experience.

The authors use a sample of 845 firm-year observations from 2017 to 2021 and apply various regression techniques, including the pooled ordinary least squares (POLS), the Heckman two-stage self-selection model, propensity score matching (PSM) and quantile regression, to test the study’s hypotheses.

The results show that socially responsible firms incur lower costs of debt. Similarly, female directors and female directors with foreign exposure are negatively associated with CODF. However, their impact becomes positive when these two variables are interacted with CSR performance. The study findings are robust across alternative measures of board gender diversity, different model specifications and approaches addressing the endogeneity problem. In additional analyses, we find that the positive implication of CSR on CODF is more pronounced for firms with higher CSR performance and less financial constraint. Nevertheless, the results reveal that only firms with lower CSR performance but a high proportion of female directors and female directors with foreign experience exhibit lower CODF. This underscores the likelihood that female directors and their foreign exposure may substitute CSR practices in mitigating the cost of debt.

Existing literature generally emphasises the importance of CSR performance to corporate financing decisions, often neglecting the role of female directors and their attributes in financial institutions’ creditworthiness evaluation. This study is among the first to address this gap by examining the moderating effect of female directors and their characteristics on CSR–CODF relationship within an emerging economy context. The findings contribute to the literature on CSR and board gender diversity, indicating that CSR performance and board gender diversity function more as substitutes than complements. Despite the unexpected consequences of interacting with female directors and their foreign experience with CSR, the study affirms the significance of CSR practices and board gender diversity in shaping borrowers’ financial decisions.

The transition to green growth goals requires the concerted efforts of the whole society. Enterprises, as important players in the market, play a key role in promoting green and sustainable development. The rise of the concept of sustainable development has enabled more enterprises to disclose environmental, social and governance (ESG) information, and ESG behaviour is regarded as a positive strategic behaviour to implement the new development concept. This paper aims to explore the influence of ESG performance on enterprise green innovation.

This study applies a fixed effect model and the regulation effect of empirical analysis to explore the influence of ESG performance on enterprise green innovation. The object of investigation is 2014–2021 Shanghai and Shenzhen A-share listed companies.

The results of an empirical analysis outline the following conclusions: (1) ESG performance has a significant effect on enterprise green innovation, mainly by easing the pressure of the financing enterprise, fitting stakeholders’ environmental protection concept and obtaining employee organizational identity that influences enterprise green innovation. (2) Government regulation positively regulates the role of ESG performance in promoting the green innovation of enterprises. (3) Heterogeneity analysis found that the strengthening role of ESG performance on the green innovation of enterprises is stronger in green invention patents, state-owned enterprises and nonheavily polluting industries.

Despite the valuable findings, this study has a few limitations. Thus, it is necessary to extend the object of investigation by adding other Asian countries, which allows for comparison analysis and allocating best practices for promoting green innovation. Besides, innovation and ESG performance depend on the quality of institutions. In this case, the future study should incorporate the indicators that reveal the quality of institutions (corruption, transparency, digitalisation, voice, accountability, etc.).

According to the above conclusions, this paper proposes suggestions at the level of enterprises, government and investors. At the enterprise level, ESG responsibility should be strengthened, ESG information should be consciously disclosed and the quality of ESG disclosure should be improved. Government departments should play the role of supervisors, improve the construction of ESG information disclosure systems and promote the formation of ESG systems. At the social level, investors should improve the ESG information status and pay more attention to the ESG performance of enterprises.

This study fills the scientific gaps in the analysis impact of ESG performance on the green innovation of enterprises. This paper contributes to the theoretical landscape of ESG efficiency by developing approaches based on two empirical models: testing the impact of enterprise ESG performance on green innovation and testing whether government regulation plays a regulatory role in the relationship between ESG performance and green innovation. Besides, this study analysed the ESG performance and green innovation within the following categories: heavy and nonheavy polluter industries; state and nonstate-owned enterprise groups.

This study aims to provide a new perspective on the impact of mortality threats on consumer behavior through the lens of brand anthropomorphism. It examines the mediating effects of control and connectedness motives and the moderating effects of brand roles on the relationship between mediators and brand attitudes.

A preliminary study explored the relationship between pandemic-induced mortality threats and attitudes toward anthropomorphized brands. Study 1 investigated the underlying mechanism, and Study 2 examined the moderating effects of servant or partner roles. Study 3 confirmed the mortality threat effect on anthropomorphic brand attitudes in the absence of the pandemic.

The study revealed that mortality threats enhanced the desire for control and connectedness, which strengthened attitudes toward anthropomorphized brands. The results also indicated matching effects between the motivations for anthropomorphism and brand roles.

This research offers novel insights into the effects of pandemic-induced mortality threats and mortality threats in non-pandemic contexts on anthropomorphic motives. It highlights the influence of these psychological needs on consumer responses to brand roles and provides insights for brand management during a crisis.

This paper attempts to combine the application of artificial intelligence in predicting and evaluating the classification of surrounding rock grades and provides guidance for subsequent support design and reinforcement support operations.

This paper discusses the use of BPNN as the primary tool, combined with three swarm bionic optimization algorithms (GA, PSO, GWO), to solve stability evaluation and grade prediction of surrounding rock in ultra-deep roadway excavation.

Taking the Great Wall ore group as the core and the Shanghaimiao mining area as the extension, the optimal model is applied to the classification of surrounding rock grade in ultra-deep roadway engineering. Prediction results show that the performance of BPNN models is excellent.

Due to the limitations of geological conditions and construction environment in deep coal mines, the period of roadway excavation is too long, resulting in less data collection.

The prediction results can provide guidance for the excavation method, support scheme correction and reinforcement support scheme design of deep coal mine roadway engineering.

It provides guidance for deep mining of coal mine (the premise of surrounding rock support stability), so as to ensure the economic and safety benefits of coal enterprises.

The neural network is applied to rock mechanics in a deep site for the first time, which is used to solve the prediction direction of surrounding rock grade evaluation. The index of the input layer is determined by combining the “three high and one disturbance” with the on-site construction situation, which is closer to the actual project. The swarm intelligent bionic algorithms are selected to optimize the hyperparameters of back propagation neural network, so as to improve the accuracy of the models. The classification and evaluation system of surrounding rock for the Great Wall ore group is constructed, which is the core of Shanghaimiao mining area in the northwest of China, guiding the dynamic adjustment of on-site excavation and support operations.

This paper aims to examine the role of corporate governance (CG) in the earnings management (EM) of affiliated companies in family business groups (FBGs) listed on the Pakistan Stock Exchange (PSX), using principal–principal agency theory.

The sample of 327 nonfinancial firms of the PSX, consisting of 187 group-affiliated firms and 140 nonaffiliated firms has been used in this study for the period of 2010 to 2019. The study uses different regression models for analysis, with robustness tests of various alternative measures of EM and FBG affiliation. In addition, endogeneity is controlled with the propensity score matching method.

The findings show that EM is less prevalent in affiliated firms compared to nonaffiliated companies. The results show a negative and significant relationship between FBGs affiliated firms and EM. Moreover, the results also show a positive relationship between EM and the interaction term of the CG index and group affiliation. It refers to the fact that effective governance cannot reduce EM in affiliated companies of FBGs as well as in the nonfinancial companies of the PSX. In addition, the quality of CG is higher in affiliated companies compared to its counterpart in nonaffiliated firms. The findings support the principal–principal agency theory that CG cannot mitigate the expropriating behavior of controlling shareholders against minority shareholders by reducing EM in emerging markets due to the ownership concentration phenomenon.

This research study has implications for small investors, government agencies and regulators. The findings of the study show that CG code should make it mandatory for companies to reveal information about their complex ownership structure and ownership information about affiliated companies and directors. Furthermore, it is suggested to revisit the code of CG in the Pakistani context of principal–principal conflict instead of the agent–principal explanation of agency theory based on Anglo–Saxon countries.

This research study has contributed to the CG and FBG literature in relation to EM in idiosyncratic settings of Pakistan. One of the prime contributions of the paper is the development of a comprehensive CG index. This research study used detailed, manually collected novel data on affiliated firms of FBGs in Pakistan.

The impact of enterprise social media (ESM) on employees is not always beneficial. The constant connectivity of ESM can trigger emotional issues, threatening employees' psychological states. This study aims to explore the potential risks of ESM usage on thriving at work by examining how ESM usage affects thriving and for whom this relationship is amplified.

Drawing on Affect Event Theory, this study proposes a research model for investigating the underlying mechanisms and boundary conditions of the negative impacts of different ESM usage patterns on employees' thriving at work. This study employed Smart-PLS 4.0 with structural equation modeling to analyze multi-wave survey data from 255 employees, testing the proposed model.

The results indicate the following: (1) ESM usage triggers employees' workplace fear of missing out (WFoMO), increasing their online vigilance and consequently hindering their thriving at work. (2) The impact of ESM usage on employees' WFoMO and thriving at work varies with their ambition levels, with high-ambition employees being more susceptible to negative effects and (3) Different types of ESM usage exert distinct effects on employees.

This study substantiates the potential negative impact of ESM usage on employees' thriving at work, contributing to the literature on the “dark side” of ESM usage and thriving at work. This study confirms the critical mediating role of emotion, offering a novel theoretical perspective on understanding the mechanisms linking ESM usage and its outcomes. Additionally, this study identifies the moderating role of employee ambition, complementing the boundary conditions of ESM usage.

A combined approach of additive Holt–Winters, support vector regression, simple moving average and generalized simulated annealing with error correction and optimal parameter selection techniques emphasizing optimal smoothing period in residual adjustment is developed and proposed to predict datasets of container throughput at major ports.

The additive Holt–Winters model describes level, trend and seasonal patterns to provide smoothing values and residuals. In addition, the fitted additive Holt–Winters predicts a future smoothing value. Afterwards, the residual series is improved by using a simple moving average with the optimal period to provide a more obvious and steady series of the residuals. Subsequently, support vector regression formulates a nonlinear complex function with more obvious and steady residuals based on optimal parameters to describe the remaining pattern and predict a future residual value. The generalized simulated annealing searches for the optimal parameters of the proposed model. Finally, the future smoothing value and the future residual value are aggregated to be the future value.

The proposed model is applied to forecast two datasets of major ports in Thailand. The empirical results revealed that the proposed model outperforms all other models based on three accuracy measures for the test datasets. In addition, the proposed model is still superior to all other models with three metrics for the overall datasets of test datasets and additional unseen datasets as well. Consequently, the proposed model can be a useful tool for supporting decision-making on port management at major ports in Thailand.

The proposed model emphasizes smoothing residuals adjustment with optimal moving period based on error correction and optimal parameter selection techniques that is developed and proposed to predict datasets of container throughput at major ports in Thailand.

To enhance the fit, comfort and overall satisfaction of lower body attire for online shoppers, this study introduces a reclassification method of the lower body profiles of young females in complex environments, which is used in the framework of remote clothing mass customization.

Frontal and lateral photographs were collected from 170 females prior, marked as size M. Employing a salient object detection algorithm suitable for complex backgrounds, precise segmentation of body profiles was achieved while refining the performance through transfer learning techniques. Subsequently, a skeletal detection algorithm was employed to delineate distinct human regions, from which 21 pivotal dimensional metrics were derived. These metrics underwent clustering procedures, thus establishing a systematic framework for categorizing the lower body shapes of young females. Building upon this foundation, a methodology for the body type combination across different body parts was proposed. This approach incorporated a frequency-based filtering mechanism to regulate the enumeration of body type combinations. The automated identification of body types was executed through a support vector machine (SVM) model, achieving an average accuracy exceeding 95% for each defined type.

Young females prior to being marked as the same lower garment size can be further subdivided based on their lower body types. Participants' torso types were classified into barrel-shaped, hip-convex and fat-accumulation types. Leg profile shapes were categorized into slender-elongated and short-stocky types. The frontal straightness of participants’ legs was classified as X-shaped, I-shaped and O-shaped types, while the leg side straightness was categorized based on the knee hyperextended degree. The number of combinations can be controlled based on the frequency of occurrence of combinations of different body types.

This methodological advancement serves as a robust cornerstone for optimizing clothing sizing and enabling remote clothing mass customization in E-commerce, providing assistance for body type database and clothing size database management as well as strategies for establishing a comprehensive remote customization supply chain and on-demand production model.

This paper aims to highlight the factors affecting health and safety (H&S) and the SMART Technologies (ST) used to mitigate them in the construction industry through a range of selected papers to encourage readers and potential audiences to consider the need for intelligent technologies to minimize the risks of injuries, illnesses and severe harm in the construction industry.

This paper adopts a double systematic literature review (SLR) to analyse studies investigating the factors affecting H&S and the ST in the construction industry using databases such as Google Scholar, Scopus, Science Direct and Emerald Insight publication.

The SLR identified “fatal or focus five factors” that include objects Fall from heights (FFH) and trapped between objects; Falls, Trips and slips (FTS); Machinery/Equipment Malfunction and Moving Equipment; Pollutants: Chemicals, Airborne Dust, Asbestos; and Electrocution. The ST includes Safety Boots/SMART Glasses/SMART Helmet/SMART Vests/SMART PPE/SMART Watch, Mobile Apps, Building Information Modelling (BIM), Virtual Reality/Augmented Reality (VR/AR), Drones/Unmanned Aerial Vehicles and Wearable Technology/Mobile Sensors help mitigate the risk posed by “Fatal five”. However, other factors within the scope of ST, such as Weather Conditions, Vibrations, Violence, Disease and illness, Fire and Explosion and Over Exertion, are yet to be adopted in the field.

SLR methodology limitations of not obtaining the most updated field knowledge are critical and are offset by choosing 72% of H&S and 92% of SM review literature post-2017. Limitations to capturing articles because of the restriction of database access: only English language search and journals that are not a part of the databases selected are acknowledged. However, key database search that recognizes rigorous peer-reviewed articles offset these limitations. The researcher’s Bias is acknowledged.

This paper unravels the construction H&S factors and their interlinks with ST, which would aid industry understanding and focus on mitigating associated risks. The paper highlights the Fatal five and trivial 15, which would help better understand the causes of the H&S risks. Further, the paper discusses ST’s connectivity, which would aid the organization’s overall H&S management. The practical and theoretical implications include a better understanding of all factors that affect H&S and ST available to help mitigate concerns. The operating managers could use the ST to reduce H&S risks at every construction process stage. This paper on H&S and ST and relationships can theorize that the construction industry is more likely to identify clear root causes of H&S and ST usage than previously. The theoretical implications include enhanced understanding for academics on H&S factors, ST and gaps in ST concerning H&S, which can be expanded to provide new insights into existing knowledge.

This paper highlights all factors affecting H&S and ST that help mitigate associated risks and identifies the “Fatal five” factors. The paper is the first to highlight the factors affecting H&S combined with ST in use and their interactions. The paper also identified factors within the ST scope that are yet to be explored.

Through the review of several journal articles on the adoption of information and communication technologies (ICTs) and how it impacts students’ motivation to continue with their studies or to drop out of their academic program, this study aims to review the literature on the impact of ICTs on student motivation at a university.

This paper is based on a systematic literature review steered by the PRISMA guidelines. This paper uses both Durban University of Technology subscription-based and publicly available papers. The research articles examined were published between 2018 and 2023 in Scopus, Web of Science and ScienceDirect.

Reviewed literature bespeaks that ICTs can increase student motivation by enhancing interactive, engaging and individualized learning. Digital technologies that engage students and offer a more engaging learning environment include instructional apps, online simulations and multimedia content. Using ICTs may be useful in lowering university dropout rates.

The systematic review yielded valuable insights for both academic research and real-world applications in education regarding the Durban University of Technology. The study offers a comprehensive analysis of the nexus between ICTs and student motivation.