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Building information modelling (BIM), as an effective digital method of information representation in the field of construction engineering, helps to deal with a series of works including design optimization, construction planning, and facility management. BIM enhances sustainability through energy simulations, material selection, waste reduction, and energy monitoring. However, challenges like talent shortage, interoperability issues, data management, and lack of standardization hinder its widespread use. Current research lacks systematic exploration of BIM's application in green buildings' life cycle, limiting further development. To fill this research gap, this study aims to provide a systematic review of the application of BIM in the design, construction and operation stages of the whole life cycle of green buildings. As a guideline to conduct this research, the preferred reporting items for systematic reviews and meta-analyses (PRISMA) model are used to identify the main procedures for literature screening and review. Through the systematic review, the main applications of BIM technology in green buildings are summarized, while the challenges in the current applications and the corresponding solutions are discussed. Finally, the study proposes key points for the future development of BIM to help the construction industry truly realize the development of man and nature and harmony and greenery. [ABSTRACT FROM AUTHOR]

Introduction: This paper aims at examining the advancement of human resource management and finance through artificial intelligence. AI has become a new phenomenon in managing people and financial resources. This particular study focuses on the AI evolution and the issues that arise with the implementation of AI in the fields of HRM and finance. Artificial intelligence alters the dynamics of HRM and finance in that firms are able to leverage data to enhance their performance. Methodology: This research adopts the case-study approach with the UAE as the area of interest. The research involves conducting an online survey of the HR and finance departments of the selected organizations. They explore topics like cultural resistance, skills deficits, and data privacy. The case study highlights the practical deployment of AI in UAE organizations to manage and forecast human capital and financial data for decisionmaking. Conclusion: Artificial intelligence has a general impact on both the field of HRM and the field of finance through opening up possibilities and risks for improvements and changes. The UAE experience proves that the opposite is true: with the proactive approach and strategies, as well as investments in talent and data protection. It is possible to achieve success. The paper is informative for other countries and industries interested in the implementation of AI in HRM and finance. [ABSTRACT FROM AUTHOR]

This study investigates the influence of ecological innovations and sustainable financing in promoting the Chinese economy's green total factor productivity (GTFP) from Q1-2004 to Q4-2018. Initially, this study measures GTFP using Data Envelopment Analysis and applies Bootstrap Auto-regressive Distributed Lagged (BARDL) model for dynamic effects. The preliminary results confirm the existence of unit root and a long-term cointegrating relationship among the model variables. The long-run results demonstrate that ecological innovations and sustainable financing have promoted GTFP in China. Moreover, government intervention is imperative to support green productivity growth at the macro level. However, there is a need to control the adverse effect of unemployment in impeding GTFP. Notably, the long-run results reflect the more substantial impact of the stated variables compared to the short run with the convergence towards long-run equilibrium. The policymakers are suggested to prioritise the development of the financial market and technological innovations. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to study the reaction of construction project managers in coping with workforce productivity challenges that arise from the COVID-19 pandemic. Design/methodology/approach: Quantitative research via questionnaires targeting the project managers from G7 contractor companies in Malaysia was carried out in the data collection process. In total, 182 responses have been analysed descriptively and inferentially using SPSS software. Findings: The research discovers that most of the construction projects and their workforce productivity were adversely impacted by the COVID-19 pandemic. Besides, the strategies adopted by project managers in Malaysia and the ranking of strategies based on their effectiveness were indicated. Originality/value: The findings of this research have contributed to a new understanding of the construction workforce productivity during the COVID-19 era from the perspective of project managers in Malaysia. A guideline established from the ranking of strategies would be useful to ensure the survival of the industry in Malaysia aftermath of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Recently, the financial performance of the steel industry has faced several challenges due to a lack of focus on corporate social responsibilities (CSR), green finance, and information communication technology (ICT). Hence, this study investigates the impact of CSR, green finance, and ICT on the financial performance of the steel industry in China. The present research also investigates the moderating role of organizational support among CSR and firm performance and ICT and firm performance. We applied structural equation modeling to analyze the primary data of 290 employees collected from the employees of the steel industry in China. The findings indicated that CSR, green finance, and ICT have a positive and significant impact on the financial performance of this industry. The results also showed that organizational support significantly and positively moderates the interaction between CSR, ICT, and financial performance. These findings suggest that Chinese steel industries should adopt CSR practices and implement an ICT adoption strategy for better financial performance. [ABSTRACT FROM AUTHOR]

Environmental pollution has become the matter of concern all over the world with the increase in urbanization, transport, industrialization and several other factors. The researcher has therefore designed this study to investigate the impact of urbanization, research and development R&D expenditure, infrastructure development and real income on the emission of carbon dioxide in Asian countries. The data collection process involved six Asian countries from 1997 and ending 2019. The panel data estimation and analysis tools and techniques were applied on the collected data and the results were obtained. The results of regression estimation suggest that as per MG estimator, all the variables have significant and positive impact on CO2 emission but infrastructure development has insignificant impact. In case of FMOLS, again all the variables have significant and positive impact on CO2 emission but infrastructure development has insignificant impact. However, in case of DOLS, all the variables have shown significant impact on CO2 emission. In the last, DK estimator indicates that urbanization, real income and population density have significant and positive impact on CO2 emission but R&D expenditure and infrastructure development has insignificant impact. In this way, the impacts of all independent and control variables on CO2 emission were estimated. [ABSTRACT FROM AUTHOR]

Building information modelling (BIM) has been considered an effective and efficient tool among stakeholders of the construction sector as it delivers prominent results. Hence, this work aimed to determine the intangible benefits of BIM in construction projects. Various statistical analyses were performed to identify the most critical intangible benefits of BIM required for justification. To rank the intangible benefits of BIM, the relative importance index was adopted. Then, the rotated component matrix was conducted to correlate each intangible benefit to its estimated components. In the last phase of the research, interviews were conducted to validate and confirm the critical intangible benefits. Five critical intangible benefits were identified: better understanding of design, better information received and given, improved communication through visualization, reduce design error and improved accuracy of drawings. By knowing these five critical benefits, clients should prioritise these benefits in their justification of BIM implementation. [ABSTRACT FROM AUTHOR]

A project meeting is an event in which stakeholders communicate amongst themselves to meet expectations in the projects by follow up, update, and get feedback. It is a platform for the team to communicate in any projects to serve the purpose of the meeting. As there is a limited study from the literature on the time performance of the project meeting, it is important to determine whether the impact of the project meeting contributes significantly to project time performance or leads to time waste and affects the project time performance. This qualitative study investigates the most significant factors that impact the project meeting to project time performance. Data analysis was obtained from interviews with twenty-seven project managers in the construction industry among local property developers based in Klang Valley, West Malaysia. The study using nvivo technique of analysis revealed most of the project managers agreed scheduling project meetings will improve time performance. The study also proposed guidelines for project meetings incorporating insightful general elements of meetings and time monitoring by incorporating project time spend and analysis of time spent that will assist the project manager to manage meetings efficiently. The findings revealed most of the project managers agreed that the presence of guidelines for meetings helps to guide meetings efficiently and enhance time project performance. [ABSTRACT FROM AUTHOR]

The ongoing climate changes have created various challenges for each industry to achieve sustainable environmental goals. Like other extensively growing industries, China's film and drama industry and inbound tourism are also responsible for contributing effectively toward a sustainable environment. Despite its significant importance, there is a dearth of empirical evidence that analyses these industry's environmental performance. Thus, this study fills the gap by applying the novel bootstrap ARDL approach and found that Inbound Tourism and Film and Drama industry increased environmental performance (reducing ecological footprint) in China. These results imply that entertainment industries and inbound tourism increased social awareness and encouraged environmental protection in societies and industries. Manifestly, the coefficient's magnitude of the Film and Drama industry is relatively lower due to a smaller share of the overall economy. However, it shows significant potential for sustainability by creating awareness about sustainable practices and corporate social responsibility, leading to higher environmental performance. Moreover, a feedback effect (two-way causality) exists between Film and Drama industry, Inbound Tourism, and environmental performance. These results offer valuable policy recommendations. [ABSTRACT FROM AUTHOR]

Socio-economic and environment-friendly initiatives are imperative to ensure sustainable development. And corporate social responsibility (CSR) emerged as a solution to create a balance in society through sustainable business performance. However, organizations need plentiful resources to comply with the philosophies of sustainability and CSR. Therefore, the current study explores the role of green financing that covers the social, environmental, and economic aspects of green financing for achieving, excelling and enhancing CSR in the banking sector. Through the employment of survey methodology and the application of Partial Least Square-Structural Equation Modelling (PLS-SEM), the data confirms the contributing role of green finance and its respective dimensions (Environmental, Economics, and Social) in enhancing the multiple facets of CSR. Based on these findings, it is recommended that the banking sector should allocate additional financial resources to promote CSR attributes. [ABSTRACT FROM AUTHOR]

Nowadays, sustainable performance (SP) has become an obligation of every organization globally, which captures the attention of recent researchers and policymakers. Following the green theory, this study aims to examine the impact of corporate social responsibilities (CSR), transactional and transformational leadership on the SP. Besides, examining the moderating role of sustainable entrepreneurship and mediating role of organizational commitment among the nexus of CSR, transactional and transformational leadership, and SP is another target of this research. This study adopted the questionnaires to collect the data from the respondents of the internet services industry in China, and structural equation modeling (SEM)was employed to analyze the data. This research revealed that CSR, transactional, and transformational leadership have a positive effect on SP. Secondly, this study also indicated that sustainable entrepreneurship significantly moderates among nexus of transactional and transformational leadership to SP. Besides, our results show that organizational commitment positively mediates the links between CSR, transactional leadership, transformational leadership, and the SP. The conclusion of this research signifies that organizational leadership strongly influences the adoption of green and sustainable operations, which further influences the SP. These results help the regulation-making authorities make new policies related to CSR, leadership, entrepreneurship, and SP. [ABSTRACT FROM AUTHOR]

The Internet of Railways (IoR) network is made up of a variety of sensors, actuators, network layers, and communication systems that work together to build a railway system. The IoR's success depends on effective communication. A network of railways uses a variety of protocols to share and transmit information amongst each other. Because of the widespread usage of wireless technology on trains, the entire system is susceptible to hacks. These hacks could lead to harmful behavior on the Internet of Railways if they spread sensitive data to an infected network or a fake user. For the previous few years, spotting IoR attacks has been incredibly challenging. To detect malicious intrusions, models based on machine learning and deep learning must still contend with the problem of selecting features. k-means clustering has been used for feature scoring and ranking because of this. To categorize attacks in two datasets, the Internet of Railways and the University of New South Wales, we employed a new neural network model, the extended neural network (ENN). Accuracy and precision were among the model's strengths. According to our proposed ENN model, the feature-scoring technique performed well. The most accurate models in dataset 1 (UNSW-NB15) were based on deep neural networks (DNNs) (92.2%), long short-term memory LSTM (90.9%), and ENN (99.7%). To categorize attacks, the second dataset (IOR dataset) yielded the highest accuracy (99.3%) for ENN, followed by CNN (87%), LSTM (89%), and DNN (82.3%). [ABSTRACT FROM AUTHOR]

Cloud enterprise resource planning (ERP) is one of the most sought-after information technology (IT) solutions for improving business performance due to its affordability, scalability, and pay-per-use subscription model. The impact of cloud ERP implementation on business performance, on the other hand, remains inconclusive. Additionally, an important factor that transverses all organizational processes, including IT implementation, is top management support (TMS). However, the TMS's role in the latter stage (business value realization) of cloud ERP implementation is unclear. The purpose of this paper is to examine the mediating and moderating impacts of top management support (TMS) on the relationship between cloud ERP implementation and financial performance. A total of 204 small and medium enterprises (SMEs) in Malaysia were surveyed, and data analysis was conducted using partial least square structural equation modelling (PLS-SEM). The results demonstrate that TMS plays a partial mediating role in the relationship between cloud ERP implementation and financial performance and that this relationship is significantly stronger in SMEs with low TMS levels. As a result, it is concluded that top management should provide the required support following successful cloud ERP implementation in order to achieve positive financial results. However, such support must be adjusted in order to avoid the deterioration of the firm's financial performance. [ABSTRACT FROM AUTHOR]

Information and communication technology (ICT) is an important sector that contributes to the development of a country. However, the success of this sector depends on the success of the ICT projects. Hence, ICT projects must be managed efficiently and effectively to ensure that they are successfully implemented. The literature review reveals that most of the ICT projects around the globe are in a challenged state, especially in terms of cost. This quantitative research aims to explore the cost influencing factors of the ICT projects in Malaysia and to build a cost influencing factors framework as a knowledge base for project managers. A 5-point Likert scale survey was conducted using the purposive sampling and the snowball sampling method to solicit responses from a large population of ICT project managers. The responses of 194 ICT project managers in Malaysia were analyzed, and the top 15 cost influencing factors were identified at different phases of a project. This result was used to build a cost influencing factors framework as a knowledge base for ICT project management. [ABSTRACT FROM AUTHOR]

The construction business plays a significant part in economic growth nowadays, conflicts occurred in the project phases will slow down the construction progress, or drive to the worst scenario in abandoning the project. Negotiators need to overcome the conflict and smoothen the progress of the construction project with minimum harm to project stakeholders. This study conducted a systematic literature review of 60 publications published globally on conflict and negotiation areas to analyse and identify the negotiation factors. Based on the review and descriptive statistical analysis, the findings show there are linkages among the construction, business, and psychology sectors in handling conflicts through negotiation. However, culture-based negotiation or conflict management in construction industry studies are very few. There is an opportunity for future researches to bridge the study on culture-based negotiation and conflict management in the construction industry with multicultural context. [ABSTRACT FROM AUTHOR]

The Smart Grid (SG) is a system with a lot of controls and communications. Both local and global controls are included in these controls. One of the advantages of SG over a traditional utility grid is that it uses a two-way communication mechanism at each stage. However, challenges such as complexity, data gathering and administration, and so on are brought into the SG system as a result of this two-way communication. As a result, an SG needs connectivity, automation and device tracking. The Internet of Things is used to do this (IoT). This study presents an IoT-enabled smart grid monitoring and control system in a computer network. Here the IoT module has been used in monitoring the network which is integrated with (MLDRNN). Renewable (DER) should be combined in grids to make electricity supply more reliable and reduce transmission losses. The control system of smart grid has been enhanced using (CPCS). The suggested system is scalable, modular, and allows for the interoperability of various types of inverters, as well as data transmission over a secure communication channel. All of these characteristics, combined with its low cost, make the created control system and monitoring platform ideal for monitoring smart microgrids online. The experimental results show scalability, QoS, power consumption, efficiency of the network. • The Smart Grid (SG) is a system with a lot of controls and communications. • This study presents an IoT-enabled smart grid monitoring and control system in a computer network. • Here the IoT module has been used in monitoring the network which is integrated with (MLDRNN). • Renewable (DER) should be combined in grids to make electricity supply more reliable and reduce transmission losses. [ABSTRACT FROM AUTHOR]

The selection of proper risk management tools and techniques is critical for better decision-making. Because very few studies scrutinize the use of a workshop as a risk management approach, this paper aims to explore how a risk management workshop can be effectively used in managing project risks, by studying a risk management workshop that was conducted in a public project. An in-depth case study approach was adopted to identify the benefits and challenges of this method of risk management. The subsequent performance of the public organization in managing risks was examined by evaluating its functional risk management implementation. In addition to furthering an organization's understanding of major project risks, a risk management workshop also provides opportunities for team building. However, a breakdown in the risk communication that eventually resulted in a poor risk management implementation was uncovered in the implementation of the project. Continued efforts to improve risk management implementation are needed to overcome the shortcomings associated with the current practices. [ABSTRACT FROM AUTHOR]

Due to growing awareness and increased pressure from stakeholders, global economies impose stringent environmental policies to control climate changes, which instigate the transition of renewable energy. Following the same aspects, the present study elucidates the impacts of environmental policy stringency and renewable energy transition on environmental quality for BRICS economies. This study employs a cross-section augmented autoregressive distributed lag (ARDL) framework on data from 1990 to 2019. The results reveal that stringent environmental policies are one of the most significant ways to impede carbon emissions (CE) in BRICS economies. Besides, renewable energy has an inverse relationship with CE. On the other hand, the industrial value-added and economic growth are positively significant to CE. Furthermore, renewable energy transition is integrated into the model using interaction terms of renewable energy and stringent environmental policies. The finding described that the combined effects of these two variables are more substantial than their individual impacts on CE reduction, confirming the transition of renewable energy through stringent regulations. The study provides valuable insights to policymakers to facilitate the overall environmental quality in BRICS economies by focusing on strict environmental policies. These results have also delineated the importance of renewable energies to mitigate CE. • Advance panel estimators are applied. • Environmental policy stringency mitigates carbon emissions. • Renewable energy reduces carbon emissions. • Transition of renewable energy is confirmed through stringent regulations. [ABSTRACT FROM AUTHOR]

• To propose novel techniques to predict greenhouse gas emissions and minimize energy consumption in renewable sources based on a sustainable environment. • The deep neural network has improved energy efficiency to predict greenhouse gas emissions using a statistic regression neural network. • This research proposed a novel technique in predicting greenhouse gas emission and minimization of energy consumption in renewable sources based on a sustainable environment. • Here, the greenhouse gas emission has been predicted using statistic regression neural network. The long-term viability of energy resources as a main input is essential to achieve long-term economic growth of a country and the energy efficiency significantly reduces energy consumption and greenhouse gas emissions, supporting environmental sustainability. As a result, a number of governments, led by those in the developed world, are making an effort to enact laws governing energy efficiency. This study suggests cutting-edge methods for forecasting greenhouse gas emissions and reducing energy demand from renewable sources based on a sustainable environment. Utilizing the statistical regression neural network (SRNN), greenhouse gas emissions have been predicted, and the deep neural network's (DNN) energy efficiency has increased. The SRNN_DNN intensity method out predicts evaluated MLR (multiple linear regression) and second- and third-order non-linear MPR (multiple polynomial regression) techniques according to MAPE (mean absolute percentage error) results. Furthermore, presented methods are considered suitable for computing GHG emissions due to the high accuracy of the SRNN DNN model. The anticipated greenhouse gas emissions related to energy were remarkably similar to the actual emissions of EU (European Union) nations. [ABSTRACT FROM AUTHOR]