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With the increasing use of small unmanned aircrafts (SUAs), many countries have enacted laws and regulations to ensure the safe use of SUAs. However, there is a lack of industry-specific regulations accounting for the unique features of construction-related SUA operations. Operating SUAs in the construction industry is attributed to specific risks and challenges, which should be regulated to maximize the utility of SUAs in construction. This study, therefore, aims to develop a multi-dimensional regulatory framework for using SUAs in the construction industry.

A combination of quantitative and qualitative methods was used to compare seven selected national/regional SUA regulations to identify the applicability of implementing the existing regulations in construction. The interview surveys were then conducted to diagnose the challenges of construction-related SUA operations and gather interviewees' suggestions on the regulatory framework for SUA uses in construction.

The research found that some challenges of construction-related SUAs operations were not addressed in the current regulations. These challenges included the complex and time-consuming SUA operation permit, lack of regulation for special SUA operations in construction, insufficient regulatory compliance monitoring and a lack of construction-related remote pilots' training. A regulatory framework was then developed based on the findings of comparative analysis and interview surveys.

This study mainly compared seven representative countries/regions' regulations, leading to a small sample size. Further research should be carried out to study the SUA regulations in other places, such as South Africa, South America or Middle East countries. Besides, this study's respondents to the interviews were primarily concentrated in Hong Kong, which may cause the interview results to differ from the construction industry in other countries/regions. A large-scale interview survey should be conducted in other places in the future to validate the current findings.

The proposed regulatory framework provides a reference for the policy-makers to formulate appropriate industry-specific SUA regulations and improve the applicability of SUA regulations in the construction industry. It sheds light upon the future of SUA regulations and the development of regulatory practice in this area.

This study is the first to propose a multi-dimensional regulatory framework for operating SUAs in construction by comprehensive policy comparisons and interviews. The regulatory framework offers a fresh insight into the unexplored research area and points out the direction for subsequent studies on SUA regulations in the construction industry.

The need for infrastructure is growing as urbanization picks up speed, and the infrastructure REITs financing model has been crucial in reviving the vast infrastructure stock, alleviating the pressure on government funds and diversifying investment entities. This study aims to propose a framework to better assess the risks of infrastructure REITs, which can serve for the researchers and the policy makers to propose risk mitigation strategies and policy recommendations more purposively to facilitate successful implementation and long-term development of infrastructure REITs.

The infrastructure REITs risk evaluation index system is established through literature review and factor analysis, and the optimal comprehensive weight of the index is calculated using the combination weight. Then, a risk evaluation cloud model of infrastructure REITs is constructed, and experts quantify the qualitative language of infrastructure REITs risks. This paper verifies the feasibility and effectiveness of the model by taking a basic REITs project in China as an example. This paper takes infrastructure REITs project in China as an example, to verify the feasibility and effectiveness of the cloud evaluation method.

The research outcome shows that infrastructure REITs risks manifest in the risk of policy and legal, underlying asset, market, operational and credit. The main influencing factors in terms of their weights are tax policy risk, operation and management risk, liquidity risk, termination risk and default risk. The financing project is at a higher risk, and the probability of risk is 64.2%.

This research contributes to the existing body of knowledge by supplementing a set of scientific and practical risk evaluation methods to assess the potential risks of infrastructure REITs project, which contributes the infrastructure financing risk management system. Identify key risk factors for infrastructure REITs with underlying assets, which contributes to infrastructure REITs project management. This research can help relevant stakeholders to control risks throughout the infrastructure investment and financing life cycle, provide them with reference for investment and financing decision-making and promote more sustainable and healthy development of infrastructure REITs in developing countries.

This study aims to investigate the effect of the diversity of the board of directors (BOD) and the shariah supervisory board (SSB) on credit risk, insolvency, operations, reputation, rate of deposit return risk (RDRR) and equity-based financing risk (EBFR) of Islamic banks (IB).

The study uses 68 IBs from 19 countries covering 2009 to 2019. BOD and SSB diversity attributes data were hand-collected from the annual reports. Financial data were collected from the bankscope database. The robustness test and two-step system generalized method of moment estimation technique were used to address potential endogeneity issues.

This study provides evidence that diversity in the experience and cross-membership of board members decreases the risk. Gender diversity increases the risk, but the BOD’s education level diversity has no relationship with risk. More interestingly, influences in the experience and cross-membership of the SSB’s members positively influence risk. However, members’ education levels and gender diversity have not been proven to affect risk.

The paper recommends that Islamic banking authorities play a stronger role and make a greater effort in driving corporate governance reform. Also, determining individual characteristics of the board is a requirement to become a member of a BOD or an SSB.

This paper expands the commitment literature through the diversity of the BOD’s and the SSB’s members in terms of their education levels, experience, cross-membership and gender. This study expands the list of potential risks for IBs, by including the RDRR and EBFR.

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.

Many waste-to-energy (WTE) plants are constructed and operated using the public-private partnership (PPP) mode in China. However, risk events of PPP WTE incineration projects sometimes occur. This study aims to clarify the relationship of risks in China's PPP WTE incineration projects and identify the key risks accordingly and risk transmission paths.

A risk list of PPP WTE incineration projects was obtained based on literature analysis. Moreover, a hybrid approach combining fuzzy sets, decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) was developed to analyze the causality of risks, explore critical risks and reveal the risk transmission paths. The quantitative analysis process was implemented in MATLAB.

The results show that government decision-making risk, government credit risk, government supervision behavior risk, legal and policy risk, revenue and cost risk and management capacity risk are the critical risks of PPP WTE incineration projects in China. These critical risks are at different levels in the risk hierarchy and often trigger other risks.

Currently, there is a lack of exploration on the interaction between the risks of PPP WTE incineration projects. This study fills this gap by examining the key risks and risk transfer pathways of PPP WTE incineration projects from the perspective of risk interactions. The findings can help the public and private sectors to systematically understand the risks in PPP WTE incineration projects, thus enabling them to identify the risks that need to be focused on when making decisions and to optimize risk prevention strategies. The proposed hybrid approach can offer methodological ideas for risk analysis of other types of PPP projects.

Early termination of public–private partnerships (PPPs) in China is caused by various risk factors, resulting in significant losses. This study aimed to clarify the key factors and identify the causal relationships among these factors.

Social network analysis (SNA) was used to analyze 37 risk factors that were summarized from 97 early terminated PPP cases and to identify the relationships among these key risk factors. Interpretive structural modeling (ISM) was conducted to explore the causal relationships. Data were collected from case documents, questionnaires and interviews.

A total of 17 key risk factors were identified and distributed in a hierarchical structure with six tiers. Among these key risk factors, the root causes affecting the early termination of PPP projects were government oversight in decision-making, local government transition, policy and law changes and force majeure. The direct cause was insufficient returns. Furthermore, local government and private sector defaults were essential mediating factors. Local government transition and the low willingness of the private sector were highlighted as potential key risks.

The cases and experts were all from China, and outcomes in other countries or cultures may differ from those of this study. Therefore, further studies are required.

This research provides knowledge regarding the key risk factors leading to the early termination of PPP projects and guidance on avoiding these factors and blocking the factors' transmission in the project lifecycle.

This study contributes to the knowledge of risk management by emphasizing the importance of local government transition, the low willingness of the private sector and project cooperation and operation, whose significance is ignored in the existing literature. The proposed ISM clarifies the role of risk factors in causing early termination and explains their transmission patterns.

This study aims to examine the effect of Industry 4.0 technology on resilience in established cross-border supply chain(s) (SC).

A literature review provides insight into the resilience capabilities of cross-border SC. The research uses a case study of operational international SC: the producers, importers, logistics companies and UK Government (UKG) departments. Semi-structured interviews determine the resilience capabilities and approaches of participants within cross-border SC and how implementing an Industry 4.0 Internet of Things (IoT) and capitals Distributed Ledger (blockchain) based technology platform changes SC resilience capabilities and approaches.

A blockchain-based platform introduces common assured data, reducing data duplication. When combined with IoT technology, the platform improves end-to-end SC visibility and information sharing. Industry 4.0 technology builds collaboration, trust, improved agility, adaptability and integration. It enables common resilience capabilities and approaches that reduce the de-coupling between government agencies and participants of cross-border SC.

The case study presents challenges specific to UKG’s customs border operations; research needs to be repeated in different contexts to confirm findings are generalisable.

Operational SC and UKG customs and excise departments must align their resilience strategies to gain full advantage of Industry 4.0 technologies.

Case study research shows how Industry 4.0 technology reduces the de-coupling between the SC and UKG, enhancing common resilience capabilities within established cross-border operations. Improved information sharing and SC visibility provided by IoT and blockchain technologies support the development of resilience in established cross-border SC and enhance interactions with UKG at the customs border.

This paper examine whether social performance moderates the linkage between financial risk and financial performance in microfinance institutions (MFIs). The study focuses on the financial self-sufficiency and long-term sustainability of MFIs.

The empirical study uses unbalanced panel data of 2,694 worldwide MFIs from 2009 to 2019. In the first step, the study inspects the impact of social performance and risk on financial performance, proxied as return on assets and operational self-sufficiency. In the second stage, moderated hierarchical regression is applied to test whether social performance moderates the relationship between risk and financial performance. Lastly, the study confirms the significant moderation effects with slope tests.

The study detects robust evidence that financial risk is negatively related to financial performance. Though social performance exhibits a weak positive link with financial performance in silos, the evidence of its moderating effects on risk is mixed and significant. Social performance indicators, such as the borrower retention rate and female representation, positively moderate the relationship between financial risk and financial performance. The study documents that social performance impacts financial performance and operational self-sufficiency through risk moderation. Thus, social performance fosters the sustainability of these institutions over the long haul.

The study is relevant to academics and theorists to consider the stakeholder approach in microfinancing. In the context of stakeholder theory, the study advances the specific social responsiveness process, namely stakeholder engagement.

The evidence that socially sensitive operations can curtail the adverse effects of credit risks on financial performance signify the required attention to social performance. For MFI managers and practitioners, the findings justify the business case for social performance. Stakeholder engagement, under the auspices of social responsiveness, acts as a risk-mitigation mechanism to eventually foster financial performance and self-sufficiency.

The study motivates MFIs to do more for their stakeholders and society by highlighting the benefits of social performance.

The study reaffirms that social performance remains at the epicenter of the MFIs' mission and is an essential risk mitigation mechanism. The study adds to the extant literature on stakeholder engagement and its effects on MFIs.

Insurance companies play a significant role in every economy; hence, it is essential to investigate and understand the factors that propel their profitability. Unlike previous studies that present a linear relationship, this study provides initial evidence by exploring the non-linear impacts of the determinants of profitability amongst life insurers in South Africa.

The study uses a panel dataset of 62 life insurers in South Africa, covering 2013–2019. The generalised method of moments and the dynamic panel threshold estimation technique were used to estimate the relationship.

The empirical results from the direct relationship reveal that investment income and solvency significantly predict life insurance companies' profitability. On the other hand, underwriting risk, reinsurance and size reduce profitability. Further, the dynamic panel threshold analysis confirms non-linearities in the relationships. The results show that insurance size, investment income and solvency promote profitability beyond a threshold level, implying a propelling effect on life insurers' profitability at higher levels. Below the threshold, these factors have an adverse effect. The study further points to underwriting risk, reinsurance and leverage having a reduced effect on life insurers' profitability when they fall above the threshold level.

The findings suggest that insurers interested in boosting their profit position must commit more resources to maintain their solvency and manage their assets and returns on investment. The study further recommends that effective control of underwriting risk is critical to the profitability of the life insurance industry.

The study contributes to the literature by providing first-time evidence on the determinants of life insurance companies' profitability by way of exploring threshold effects in South Africa.

This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of promoting the adoption of PPP housing scheme in Nigeria.

The research design adopts the census sampling approach by using well-structured questionnaires distributed to stakeholders involved in PPP-procured mass housing projects, i.e. consultants, in-house professionals, contractors and the organized private sector, registered with PPP departments in the Federal Capital Territory Development Authority, Abuja, Nigeria. Sixty-three risk factors, nine risk allocation criteria and nine project delivery indices were submitted for the respondents to rank on a Likert scale of 7. Two hypotheses were formulated to test whether the risk allocation criteria impacted PPP mass housing delivery or otherwise. The study adopts partial least square-structural equation modeling to model the effect of risk on risk allocation criteria on project delivery indices and risk severity.

The finding shows that project risk allocation criteria have less effect on project delivery indices than on risk severity. The study concludes that risk allocation principles do not directly affect the delivery of PPP-procured mass housing projects. This is evident by the path coefficient of 0.724 values, which is not statistically significant at a 5% alpha protection value. The study concludes that allocating critical risk factors influences the performance of PPP-procured mass housing projects, as the path coefficient of 0.360 is also not significantly far from 0 and at a 5% alpha protection value.

The study is one of the recent studies conducted in PPP-procured mass housing projects in Nigeria owing to the novelty of procurement option in the sector. It highlights the risk factors that can jeopardize the PPP-procured mass housing project objectives. The study is of immense value to PPP actors in the sector by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP mass housing projects.