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This study aims to examine how auditors perceive the influence of crucial fraud prevention factors in deterring financial statement fraud within the corporate sector. Additionally, this research explores the mediating effect of fraud awareness in elucidating the impact of ethical leadership and internal control systems on preventing financial statement fraud.

The study used an online survey, targeting a sample of 141 professionally qualified auditors with at least one year of practical experience in the field. The researchers used “Structural Equation Modeling (SEM)” to examine relationships between latent variables using partial least squares structural equation modeling. The study investigated the impact of whistleblowing systems, fraud awareness, ethical leadership, internal control systems and corporate governance on fraud prevention.

This research finding provides evidence to the corporate sector by establishing the significance of fraud awareness as the most influencing factor in preventing financial statement fraud. Furthermore, the combined explanatory variables account for 77.4% of the overall variance in financial statement fraud prevention. The study reveals a partial mediation effect of fraud awareness on the relationship between the internal control system and financial statement fraud prevention.

This research finding may assist in developing an effective fraud prevention programme to mitigate fraud instances and improve financial reporting quality. In the corporate sector, each organisation should clearly specify the policies on whistleblowing systems, fraud awareness training, internal control systems and corporate governance. To foster a comprehensive fraud prevention programme, the leaders should enforce these policies with employee support.

This research integrated crucial elements to develop a new theoretical framework for investigating financial statement fraud prevention within the corporate context. Accordingly, this research framework provides a more in-depth explanation of preventing financial statement fraud from an auditor’s perspective. Additionally, this research is the first to explore the mediating role of fraud awareness in influencing the effectiveness of the internal control system in preventing financial statement fraud.

At the beginning of the Corona Virus Disease 2019 (COVID-19) pandemic, a digitalized construction environments surfaced in the heating, ventilation and air conditioning (HVAC) systems in the form of a modern delivery system called demand controlled ventilation (DCV). Demand controlled ventilation has the potential to solve the building ventilation's biggest problem of managing indoor air quality (IAQ) for controlling COVID-19 transmission in indoor environments. However, the improper evaluation and information management of infection prevention on dense crowd activities such as measurement errors and volatile organic compound (VOC) generation failure rates, is fragmented so the aim of this research is to integrate this and explore potentials with machine learning algorithms (MLAs).

The method used is a thorough systematic literature review (SLR) approach. The results of this research consist of a detailed description of the DCV system and digitalized construction process of its IAQ elements.

The discussion revealed that DCV has a potential for being further integrated by perceiving it as a MLAs and hereby enabling the management of IAQ level from the perspective of health risk function mechanism (i.e. VOC and CO₂) for maintaining a comfortable thermal environment and save energy of public and private buildings (PPBs). The appropriate MLA can also be selected in different occupancy patterns for seasonal variations, ventilation behavior, building type and locations, as well as current indoor air pollution control strategies. Furthermore, the conceptual framework showed that MLA application such as algorithm design/Model Predictive Control (MPC) integration can alleviate the high spread limitation of COVID-19 in the indoor environment.

Finally, the research concludes that a large unexploited potential within integration and innovation is recognized in the DCV system and MLAs which can be improved to optimize level of IAQ from the perspective of health throughout the building sector DCV process systems. The requirements of CO₂ based DCV along with VOC concentrations monitoring practice should be taken into consideration through further research and experience with adaption and implementation from the ventilation control initial stage of the DCV process.

Effective safety supervision plays a crucial role in ensuring safe production within coal mines. Conventional coal mine safety supervision (CMSS) in China has suffered from the problems of power-seeking, excessive resource consumption and poor timeliness. This paper aims to explore the Internet+ CMSS mode being emerged in China.

The evolution of CMSS systems underwent comprehensive scrutiny through a blend of qualitative and quantitative approaches. First, evolutionary game theory was used to analyze the necessity of incorporating Internet+ technology. Second, a system dynamics model of Internet+ CMSS was crafted, encompassing a system flow diagram and equations for various variables. The model was subsequently simulated by taking the W coal mine in Shanxi Province as a representative case study.

It was revealed that the expected safety profit from the Internet+ mode is 296.03% more than that from the conventional mode. The precise dissemination of law enforcement information was identified as a pivotal approach through which the Internet+ platform served as a conduit to foster synergistic collaboration among diverse elements within the system.

The outcomes of this study not only raise awareness about the potential of Internet+ technology in safety supervision but also establish a vital theoretical foundation for enhancing the efficacy of the Internet+ CMSS mode. The significance of these findings extends to fostering the wholesome and sustainable progress of the coal mining industry.

This research stands out as one of the limited studies that delve into the influence of Internet+ technology on CMSS. Building upon the pivotal approach identified, to the best of authors’ knowledge, a novel “multi-blind” working mechanism for Internet+ CMSS is introduced for the first time.

This study aims to investigate the fit of a promotion (prevention) focus with malicious (benign) envy and how this fit influences positive and negative behaviours, depending on the context.

Four empirical studies (two laboratory and two online experiments) were used to test key hypotheses. Study 1 manipulated regulatory focus and envy in a job application setting with university students. Study 2 engaged similar manipulations in a social media setting. Studies 3 and 4 extended the regulatory focus and envy manipulations to the general population in pay-what-you-want (PWYW) and pay-it-forward (PIF) restaurant contexts.

The findings showed that a promotion (prevention) focus fits with the emotion of malicious (benign) envy. In the social media context, promotion and prevention foci demonstrated negative behaviour, including unfollowing the envied person, when combined with malicious and benign envy. In the PWYW and PIF contexts, combining envy with a specific type of regulatory focus encouraged both positive and negative behaviours through influencing payments.

Future research could validate and extend this study’s findings with different product/service categories, cross-cultural samples and research methods such as field experiments.

The four studies’ findings will assist managers in formulating marketing strategies to enhance their positioning of target products/services, possibly leading to higher prices for PWYW and PIF businesses.

The conceptual model is novel as, to the best of the authors’ knowledge, no prior research has proposed and tested the fit between envy type and regulatory foci.

Fire is the fundamental element of most people’s lives, and when not controlled, the same fire can lead to several catastrophes in homes, offices, schools, lives and other public places with severe repercussions. Hence, this study aims to examine the adequacy and extent of the application of fire suppression systems in residential and commercial property in Ghana.

This study adopts a sequential mixed-mode design comprising quantitative and qualitative research strategies to analyse factors to produce findings. The target population for this study includes shop occupiers, end users of office buildings, and residents in the Accra Central of Ghana. Systematic random sampling was used for the quantitative research, and a sample size of 385 was obtained using a multi-stage and cluster sampling method. A structured survey and semi-structured interviews were used to collect the primary data. The quantitative data were analysed using descriptive and inferential statistics, whereas the qualitative data were analysed using content analysis.

From an empirical literature review and the analysis, the three main factors contributing to fire breakouts are equipment malfunction, improper use of heat sources and human mistakes. According to the respondents, fire suppression systems were also inadequate, as most of the suppression systems prescribed in the building code were unavailable. Regarding the ability to manually operate fire suppression systems, most property occupiers stated that they are generally unaware of these suppression systems.

This study will aid policymakers in developing interventions for fire safety enforcement by ensuring that fire safety regulations are consistently followed by design team members and property developers, resulting in a positive effect on public building structures performing their required functions. It is also critical to provide end users with education and training on how to operate the fire suppression system as well as effective handling of firefighting installations in the event of a fire.

The findings of this investigation contribute to knowledge and comprehension of the effect of fire suppression systems on building users and may serve as a precursor to the development of a “As Built” certification system for ascertaining the adequacy of fire suppression systems for new and existing residential and commercial property.

The construction industry remains one of the most hazardous industries worldwide, with a higher number of fatalities and injuries each year. The safety and well-being of workers at a job site are paramount as they face both immediate and long-term risks such as falls and musculoskeletal disorders. To mitigate these dangers, sensor-based technologies have emerged as a crucial tool to promote the safety and well-being of workers on site. The implementation of real-time sensor data-driven monitoring tools can greatly benefit the construction industry by enabling the early identification and prevention of potential construction accidents. This study aims to explore the innovative method of prototype development regarding a safety monitoring system in the form of smart personal protective equipment (PPE) by taking advantage of the recent advances in wearable technology and cloud computing.

The proposed smart construction safety system has been meticulously crafted to seamlessly integrate with conventional safety gear, such as gloves and vests, to continuously monitor construction sites for potential hazards. This state-of-the-art system is primarily geared towards mitigating musculoskeletal disorders and preventing workers from inadvertently entering high-risk zones where falls or exposure to extreme temperatures could occur. The wearables were introduced through the proposed system in a non-intrusive manner where the safety vest and gloves were chosen as the base for the PPE as almost every construction worker would be required to wear them on site. Sensors were integrated into the PPE, and a smartphone application which is called SOTER was developed to view and interact with collected data. This study discusses the method and process of smart PPE system design and development process in software and hardware aspects.

This research study posits a smart system for PPE that utilises real-time sensor data collection to improve worksite safety and promote worker well-being. The study outlines the development process of a prototype that records crucial real-time data such as worker location, altitude, temperature and hand pressure while handling various construction objects. The collected data are automatically uploaded to a cloud service, allowing supervisors to monitor it through a user-friendly smartphone application. The worker tracking ability with the smart PPE can help to alleviate the identified issues by functioning as an active warning system to the construction safety management team. It is steadily evident that the proposed smart PPE system can be utilised by the respective industry practitioners to ensure the workers' safety and well-being at construction sites through monitoring of the workers with real-time sensor data.

The proposed smart PPE system assists in reducing the safety risks posed by hazardous environments as well as preventing a certain degree of musculoskeletal problems for workers. Ultimately, the current study unveils that the construction industry can utilise cloud computing services in conjunction with smart PPE to take advantage of the recent advances in novel technological avenues and bring construction safety management to a new level. The study significantly contributes to the prevailing knowledge of construction safety management in terms of applying sensor-based technologies in upskilling construction workers' safety in terms of real-time safety monitoring and safety knowledge sharing.

Despite the potential of virtual fitting rooms (VFRs) to enhance the consumer experience, their adoption is in the preliminary stages. Little is known about inherent reasons why consumers would adopt VFRs. As consumers' attributional processes can be influenced by their enduring chronic traits, this study aims to investigate the influence of chronic regulatory focus on consumers' VFR adoptions via consumers' perceptions of value provided by VFRs. Additionally, the mediating effects of perceived functional and experiential values were examined. Further, the moderating effect of prior VFR experience was tested to allow for variations in consumer experiences.

Data were collected via an online survey of 480 consumers who have at least heard of VFRs via convenience sampling. Established measures were utilized to develop the survey questionnaire. Data were analysed using structural equation modelling to test the main model with mediation effects as well as multi-group comparisons to test the moderating effect.

Empirical results revealed that respective chronic regulatory foci, as preconceived factors that drive consumers' differences in processing, exerted significant influences on consumers' perceptions of VFRs, which, in turn, positively influenced their adoption intention. Also, perceived values mediated the relationship between regulatory foci and consumers' adoption intention. Further, prior VFR experience moderated the relationship between regulatory focus and perceived value.

The paper empirically tested the importance of chronic regulatory foci in understanding consumers' cognitive and affective attributional processes, explaining inherent psychological reasons why consumers would (not) adopt VFRs.

This paper aims to bring these areas closer by exploring the relationship between the dimensions of strategic intelligence (SI) for leadership and the proactive work behaviours (PWBs) of Upper Egypt universities' employees. Therefore, the research question revolves around: is there a relationship between SI and PWB?

The study relied on a descriptive analytical approach and a stratified random sample. The paper opts for a descriptive study using the survey lists that depends on three scales: strategic leadership intelligence. The sampling unit is represented by the individuals working in Upper Egypt Universities, distributed on a sample of 364 Upper Egypt universities' employees.

The results indicate a significant relationship between dimensions of SI for leadership and the PWBs.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further. This paper is the first to examine, to the authors' knowledge the relationship between intelligence for leadership and the PWBs.

This study aims to objectively synthesize the volume of accounting literature on financial statement fraud (FSF) using a systematic literature review research method (SLRRM). This paper analyzes the vast FSF literature based on inclusion and exclusion criteria. These criteria filter articles that are present in the accounting fraud domain and are published in peer-reviewed quality journals based on Australian Business Deans Council (ABDC) journal ranking. Lastly, a reverse search, analyzing the articles' abstracts, further narrows the search to 88 peer-reviewed articles. After examining these 88 articles, the results imply that the current literature is shifting from traditional statistical approaches towards computational methods, specifically machine learning (ML), for predicting and detecting FSF. This evolution of the literature is influenced by the impact of micro and macro variables on FSF and the inadequacy of audit procedures to detect red flags of fraud. The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper chronicles the cluster of narratives surrounding the inadequacy of current accounting and auditing practices in preventing and detecting Financial Statement Fraud. The primary objective of this study is to objectively synthesize the volume of accounting literature on financial statement fraud. More specifically, this study will conduct a systematic literature review (SLR) to examine the evolution of financial statement fraud research and the emergence of new computational techniques to detect fraud in the accounting and finance literature.

The storyline of this study illustrates how the literature has evolved from conventional fraud detection mechanisms to computational techniques such as artificial intelligence (AI) and machine learning (ML). The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper contributes to the literature by providing insights to researchers about why the evolution of accounting fraud literature from traditional statistical methods to machine learning algorithms in fraud detection and prediction.

This article summarizes the international scientific research output of global forest product models, infers future research trends and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

In 1999, Joseph Buongiorno, a scholar at the University of Wisconsin in the United States of America, proposed the global forest products model (GFPM), which was first applied to research in the global forestry sector. GFPM is a recursive dynamic model based on five assumptions: macroeconomics, local equilibrium, dynamic equilibrium, forest product conversion flow and trade inertia. Using a certain year from 1992 to present as the base period, it simulates and predicts changes in prices, production and import and export trade indicators of 14 forest products in 180 countries (regions) through computer programs. Its advantages lie in covering a wide range of countries and a wide variety of forest products. The data mainly include forest resource data, forest product trade data, and other economic data required by the model, sourced from the Food and Agriculture Organization (FAO) of the United Nations and the World Bank, respectively.

Compared to international quantitative and modeling research in the field of forest product production and trade, China's related research is not comprehensive and in-depth, and there is not much quantitative and mathematical modeling research, resulting in a significant gap. This article summarizes the international scientific research output of global forest product models, infers future research trends, and provides reference for quantitative analysis and mathematical modeling of Chinese forest product problems, with the aim of contributing to promoting domestic production of Chinese forest products and strengthening international trade competitiveness of forest products.

On the basis of summarizing and analyzing the international scientific research output of GFPM, sorting out the current research status and progress at home and abroad, this article discusses potential research expansion directions in 10 aspects, including the types, yield and quality of domestic forest product production, international trade of forest products, and external impacts on the forestry system, in order to provide new ideas for global forest product model research in China.