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This study provides a safety prewarning mechanism, which includes a comprehensive risk assessment model and a safety prewarning system. The comprehensive risk assessment model is capable of assessing nine safety indicators, which can be categorised into workers’ behaviour, environment and machine-related safety indicators, and the model is embedded in the safety prewarning system. The safety prewarning system can automatically extract safety information from surveillance cameras based on computer vision, assess risks based on the embedded comprehensive risk assessment model, categorise risks into five levels and provide timely suggestions.

Firstly, the comprehensive risk assessment model is constructed by adopting grey multihierarchical analysis method. The method combines the Analytic Hierarchy Process (AHP) and the grey clustering evaluation in the grey theory. Expert knowledge, obtained through the questionnaire approach, contributes to set weights of risk indicators and evaluate risks. Secondly, a safety prewarning system is developed, including data acquisition layer, data processing layer and prewarning layer. Computer vision is applied in the system to automatically extract real-time safety information from the surveillance cameras. The safety information is then processed through the comprehensive risk assessment model and categorized into five risk levels. A case study is presented to verify the proposed mechanism.

Through a case study, the result shows that the proposed mechanism is capable of analyzing integrated human-machine-environment risk, timely categorising risks into five risk levels and providing potential suggestions.

The comprehensive risk assessment model is capable of assessing nine risk indicators, identifying three types of entities, workers, environment and machine on the construction site, presenting the integrated risk based on nine indicators. The proposed mechanism, which adopts expert knowledge through Building Information Modeling (BIM) safety simulation and extracts safety information based on computer vision, can perform a dynamic real-time risk analysis, categorize risks into five risk levels and provide potential suggestions to corresponding risk owners. The proposed mechanism can allow the project manager to take timely actions.

With the advent of the information age, this paper aims to apply risk analysis theories to study the risk prevention mechanism of information disclosure, thus supporting the green electricity supply.

This paper conducts a comprehensive evaluation and analysis of the impact of power market transactions, power market operations and effective government supervision, so as to figure out the core risk content of power market information disclosure. Moreover, AHP-entropy method is adopted to weigh different indicators of information disclosure risks for the participants in the electricity market.

The potential reasons for information disclosure risk in the electricity market include insufficient information disclosure, high cost of obtaining information, inaccurate information disclosure, untimely information disclosure and unfairness of information disclosure.

Some suggestions and implications on risk prevention mechanism of information disclosure in the electricity market are provided, so as to ensure the green electricity supply and promote the electricity market reform in China.

This study proposes a new model for assessing supply chain sustainability risk integrating subjectivity and objectivity of decision-maker. Research has shown the vacancy of study in dealing with the above issue. To fill this research gap, a new decision support model considering the subjectivity and objectivity of decision-makers in assigning the weight of the supply chain risk reprioritization criteria is presented and demonstrated using a case example.

This study adopts a new decision support model for assessing supply chain sustainability risk based on additional failure mode and effect analysis (FMEA) parameters and its integration with preference selection index (PSI) methodology and the Shannon entropy. A case example of the supply chain small and medium enterprise (SME) producing handy crafts has been used in this study.

The result of the study reveals critical sustainability risk dimensions and their risk elements demanding management attention to support realization to a more sustainable business operation.

The use of a single case study is often associated as a limitation in the research studies, and this study is based on findings from SMEs in the handy craft sector in a developing country. Nonetheless, future studies may focus on replicating this study using more samples. This preliminary study provides academics and practitioners with an exemplar of supply chain sustainability risk assessment from the SME in a developing country.

The result of this study is beneficial for practitioners, particularly owner-managers of SMEs who can use this study as guidance on how to identify and select the critical sustainability risks and plan mitigating strategies accordingly.

Scientific effort on appraising criticality of supply chain sustainability risks considering subjectivity and objectivity of decision-maker simultaneously is missing in earlier studies. To the best of the author’s knowledge, this is the first paper applying the PSI and Shannon entropy method and using it for evaluating the impact of supply chain risk based on five sustainability pillars. The findings and suggestions for future research initiatives will provide new insights for scholars and practitioners in managing SME supply chain sustainability risks.

Labeling women as risk‐averse limits the positive benefits both women and organizations can gain from their risk taking. The purpose of this paper is to explore women's risk taking and reasons for stereotype persistence in order to inform human resource practice and women's career development.

The paper draws on literature about gender and organizations to identify reasons for the persisting stereotype of women's risk aversion. Utilizing literature and concepts about risk appetite and decision making, the paper evaluates results of the Simmons Gender and Risk Survey database of 661 female managers.

The paper finds evidence of gender neutrality in risk propensity and decision making in specific managerial contexts other than portfolio allocation.

More in‐depth research is needed to explore the gender‐neutral motivators of risk decision making and to explore risk taking in a more diverse sample population.

The paper explores why women's risk taking remains invisible even as they take risks and offers suggestions on how women and organizations may benefit from their risk‐taking activities.

The paper synthesizes evidence on risk taking and gender, and the evidence of female risk taking is an important antidote to persisting stereotypes. The paper outlines reasons for this stereotype persistence and implications for human resource development.

The focused case is a “disguised case” developed based on a real-life apparel company in Sri Lanka. The authors have disguised the company name and have not revealed the identity of the key respondents and any data, which makes the firm obvious. However, the processes and practices reported represent the actual scenario of the company (gathered through interviews done mainly with the case protagonist, General Manager (GM) – Risk and Controls) and the authors have not fabricated any data.

Having established itself as a pioneer in the apparel industry in Sri Lanka, Dots & Lines reached the pinnacle of its performance in 2019. Following the outbreak of COVID-19, the situation turned unfavorable: global customers canceled orders by the end of the first quarter of 2020. It experienced settlement delays, increased freight charges and supply chain barriers. The virus spread among the operational staff, leading to health and safety issues and absenteeism. On April 2020, the executive committee gathered and decided to form a position titled “General Manager (GM) – Risk and Controls” and a team to turn around the company. Dots & Lines witnessed the harvest of the risk management turnaround measures pioneered by GM – Risk and Controls, from the first quarter of 2021 with impressive revenue and profit figures. It developed a pool of key strategic customers, while key performance indicators dashboards and the risk matrix provided vital insights in moving forward.

The case, Dots & Lines is written for use in undergraduate and graduate-level classes in business administration and management degree programs. The focus aligns with discussions on industry competition, controls and risk management. Of further importance, the case is applicable to discussions on topics in strategic management accounting courses.

The aim of this study is to analyze the influence mechanism of real estate enterprises' status on debt default risk and explore the heterogeneity effect of the characteristics of enterprises.

Against the background of the “three red lines” regulation of the financing of real estate enterprises and the COVID-19 pandemic, the authors select 123 real estate enterprises listed on China's Shanghai and Shenzhen A-shares markets from the first quarter of 2021 to the second quarter of 2022 as a research sample. The social network analysis method and Z-score financial risk early warning model are used to measure real estate enterprises' status and debt default risk. The authors construct a panel regression model to analyze how the status of real estate enterprises influences their debt default risk.

The results show that the status of real estate enterprises negatively and significantly affects their debt default risk. Economic policy uncertainty and financing constraints play negative moderating and mediating roles, respectively. Further research has found that the effect of real estate enterprises' status on debt default risk is characterized by heterogeneity in equity characteristics, i.e. it is significant in the sample of nonstate-owned enterprises but not in the sample of state-owned enterprises.

It is helpful for real estate enterprises to attach importance to the value of social networks, and the authors provide policy suggestions for real estate enterprises to constantly improve their risk management systems.

Using economic policy uncertainty as the moderating variable and financing constraints as the mediating variable, the authors analyze how the status of real estate enterprises influences debt default risk, which contributes to a better understanding of the formation of the debt default risk of real estate enterprises.

Wales Applied Risk Research Network (WARRN) is a formulation-based technique for the assessment and management of serious risk (e.g. violence to others, suicide, etc.) for users of mental health services. It has been gradually adopted as the risk evaluation and safety-planning technique for all seven health boards in Wales. The purpose of this paper is to examine the opinions of WARRN as used within these health boards.

An online survey was disseminated to NHS clinicians in secondary mental health services to evaluate their perceptions of the use and effectiveness of WARRN. Data from 486 clinicians were analysed with both quantitative and qualitative methods.

Results indicated that the overall impact of WARRN on secondary mental health care was very positive, with clinicians reporting increased skills in the domains of clinical risk formulation, safety-planning and communication, as well as increased confidence in their skills and abilities in these areas. Clinicians also reported that the “common-language” created by having all NHS health boards in Wales using the same risk assessment process facilitated the communication of safety-planning. Crucially, NHS staff believed that the safety of service users and of the general public had increased due to the adoption of WARRN in their health board and many believed that lives had been saved as a result.

WARRN is perceived to have improved clinical skills in risk assessment and safety-planning across Wales and saved lives.

This paper examines the perceptions of senior auditors in large firms in Sydney, Kuala Lumpur and Auckland concerning the nature and assessment of the inherent risk in risk based auditing. The geographic dispersion of participants from internationally linked firms does not appear to result in any cultural and geographic effects. Assessment of inherent risk appears predominantly qualitative and is not necessarily linked to the comprehensive aggregation of risks typically presented in audit risk models. There is some blurring of control risk factors with inherent risk and one‐third of participants assess inherent and control risk jointly. Risk factors appear to be grouped in importance in a manner that suggests different attitudes to management, system‐oriented, environmental and oversight risks. The identification of four possible factors (internal risk, external risk, system risk and oversight threats) may provide a basis for further investigation of how auditors assess inherent risk. There is an apparent division between “internally” and “externally” sourced risk.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.

The “Social Determinants of Health” construct is well-entrenched in the way that both health care providers and researchers think about the effects of social conditions on health. Although there are a number of theories that fall under this rubric for the social production of health and illness, the core of this construct is the idea that social stratification leads to health disparity. In this chapter we show how such a mechanism might work for relating social stratification and job stress.

We used the pooled 2002, 2006, 2010 Quality of Work Life modules of the General Social Survey to test a model of the relationships between gender, age, education, and nativity with “bad jobs” and indicators of health status.

Findings show that social status is positively associated with job quality and with health in turn. Lower social status characteristics are related to bad jobs and poorer health.

Health disparities are thus “explained” by the consequences of social status for occupation and job quality, thereby depicting exactly how health disparities arise in normal social life. The theory and results underscore the importance of explicitly modeling social status factors in explanations of health disparities.

It is common to relate health disparities to social status but it is not common to show the mechanisms whereby social status actually produces health disparities. Addressing health disparities means addressing the consequences of social inequalities for normal activities of social life such as work. Improving job quality would be a health “treatment” that addresses health disparities.

This chapter demonstrates the value of explicitly tracing the consequences of status differences on differences in social context such as work conditions and then health. In the study of health disparities this is not often done. In this chapter we show how social inequality leads to occupational and job quality differences that, in turn, lead to health differences.