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This study aims to investigate the relationship among liquidity, information asymmetry and political risk for non-US stocks listed on the NYSE. Additionally, the study aims to explore the impact of political tension on market quality.

This research adopts a quantitative methodology to examine the interplay between liquidity, information asymmetry and political risk in non-US stocks on the NYSE. A comprehensive analysis encompasses stocks from countries with varying political risk levels, demonstrating a correlation between lower political risk and improved market quality. In assessing the impact of US–China trade conflicts on Chinese stocks, political shocks are scrutinized. Results indicate that heightened political tension exacerbates information asymmetry and diminishes market liquidity, underscoring the susceptibility of stocks in politically strained environments to adverse shocks.

Non-US stocks from countries with lower political risk show higher liquidity and market efficiency, with narrower bid-ask spreads and smaller price impacts of trades. These stocks also demonstrate a higher market quality index, indicating improved overall market performance. In addition, during periods of escalated US –China political tension over trade policy, the liquidity of non-US stocks from China worsens, leading to wider bid-ask spreads and increased information asymmetry.

This study provides novel insights into the impact of political risk on stock market dynamics for non-US stocks listed on the NYSE, with a particular emphasis on the US –China trade conflict's effect on Chinese stocks.

Political risk has been identified as a major impediment to the success of foreign invested projects, in developing countries. Infrastructure projects are especially sensitive to host-country political climates. Governance in emerging economies can be unstable, which adversely impacts infrastructure projects, given their high capital-intensity, long operational periods and high asset specificity. While the detrimental impact of political risk is well documented, the mitigation of such impacts on infrastructure projects remains largely unexamined. This study, therefore, addresses this by exploring the available identified political risk management (PRM) strategies based on resilience theory and evaluating their effectiveness.

A mixed-method approach was employed to identify PRM strategies. Firstly, a comprehensive literature review identified 40 potential PRM strategies. However, the applicability of those 40 strategies was uncertain due to the scarcity of PRM studies. Thus, expert interviews, drawing on the insights of Chinese infrastructure industry professionals with experience in FII, were applied to review the identified strategies. This process reduced the pool of applicable strategies to 34. Subsequently, 356 questionnaires were sent out to investors from China, Australia and Singapore, with 218 valid responses returned. Based on the data collected from the surveys, statistical analysis was used to evaluate and classify applicable PRM strategies.

Results reveal the most effective top five strategies for offsetting the detrimental effects of political risk on foreign infrastructure investment to be: (1) selection of suitable markets and projects; (2) maintaining good relationship with government; (3) purchasing political insurance; (4) utilizing capable contractors from both host country and home country; and (5) adopting an appropriate entry mode. The 34 strategies were further consolidated into four meta-strategies through factor analysis, resulting in the formulation of a strategy selection matrix.

The findings of this study offer a rational means by which infrastructure investment practitioners considering projects in developing countries, may arrive at an optimal political risk mitigation strategy. The findings also offer government of host countries directives to improving the political environment in order to attract foreign investment flows into local infrastructure projects.

This study aims to investigate the relationship between political instability and the performance of Islamic banks in emerging countries.

For a data sample of 93 Islamic banks in 20 emerging countries during the period from 2011 to 2016, the authors identify indicators that matter most for the activities of Islamic banks.

The study finds that a stable government and law and order are positively correlated with the health of Islamic financial institutions. On the other hand, corruption and military involvement in politics can create an unstable environment for businesses, leading to uncertainty and risk. The study also reveals that Islamic banks operating in regions or communities with lower risk of socio-economic conditions tend to exhibit higher levels of profitability.

Overall, the study provides valuable insights into the impact of political instability on Islamic banks in emerging countries.

The shadow economy (SE) has been a serious issue with varied dimensions in all countries that significantly affect economic growth. Therefore, all countries have made an effort to tackle the SE by pursuing several measures. This study aims to investigate the impact of financial markets (stock and bond) in reducing the SE while considering the role of country risk (political, economic and financial) in N-11 countries.

The study employed first-generation methodological techniques, including a unit root test to identify stationarity in the series, a panel cointegration test and panel autoregressive distributive lag (ARDL) to estimate long-run and short-run relationships. Finally, the Granger causality is applied to determine the direction of the causal relationship.

The study explored that country risk factors are crucial in reducing the size of the SE. Moreover, the significant moderating role of country risk factors in the financial market development and SE nexus suggests that by controlling the country's risk, financial market development can negatively affect the SE.

Due to the availability of data, the study used data, ranging from 1995 to 2015, because the tax burden data is available from 1995 while the maximum data for the SE is available till 2015, using Medina and Schneider's (2019) data estimates for the SE.

The previous studies have focused explicitly on the role of financial institutions' development in the SE. To the best of the author's knowledge, no previous study is attempted to investigate the role of financial markets (bonds and stock) in the size of the SE. Furthermore, previous studies have ignored the important role of country risk factors in the size of the SE. This study investigates the impact of country risk on the SE and the moderating role of country risk in the development of financial markets and the SE nexus.

The paper investigates whether political geography, as measured by the degree of alignment of state politicians with the party of the USA President, has an impact on corporate fraud convictions.

Prior research shows that the degree of alignment between state politicians and the president's political party is positively correlated with measures of earnings management for firms headquartered in the state. Political alignment is conducive to earnings management because it affects a firm's information and enforcement environment by increasing policy risk and promoting lenient regulatory oversight. The paper posits that this environment is also conducive to corporate fraud and tests this hypothesis using pooled ordinary least squares (OLS) and panel regressions with annual state-level data for 2003–2018.

The paper documents a positive and statistically significant relationship between political alignment and corporate fraud conviction rates by state.

The conclusions are tempered by data limitations. First, the conviction data are available at the state level only. Second, the true level of fraud is inherently unobservable and the conviction data may not reflect the actual number of frauds that are committed.

Fraud examiners might benefit from considering the role of political connectedness in determining fraud risk. Although additional research is needed before making concrete recommendations, the initial indications clearly point to political connections as a potential concern.

The findings build on evidence that political connections influence earnings management. Rather than focusing on direct measures of connectedness, such as lobbying expenditures, the paper examines a plausibly exogenous measure: political geography.

Critical infrastructures are susceptible to unexpected disruptive events that affect their functional performance. Public–private partnership (PPP) offers opportunities for stakeholders to build resilience by proactively coordinating and positioning the capabilities of the stakeholders. Partnerships are mostly riddled with risks that affect the performance and goal attainment of the partnerships. The purpose of this study was to develop a risk assessment model for PPP in critical infrastructure resilience (CIR) using fuzzy synthetic evaluation.

This study used a quantitative approach to analyse survey responses from respondents. Mean score ranking, Kendall’s coefficient of concordance and fuzzy synthetic evaluation were used to analyse the responses from respondents.

This study identified seven risk categories; Political, Financial, Ethical, Bureaucracies and red tapes, Legal, Coordination and Institutional as the critical risk categories that may frustrate the partners in a PPP arrangement from performing their responsibilities. A risk assessment model was also developed in the form of a risk index equation to ascertain the risk level of using a PPP to build critical infrastructure resilience in Ghana. It was found that the risk level in using PPP to build critical infrastructure resilience is high.

The outcome of this study can be used as an informative and guiding tool to streamline any future PPP arrangement or even amend current PPP arrangements in critical infrastructure resilience.

The study has drawn attention to the risks in using PPP to build critical infrastructure resilience within the Ghanaian context. It has also established a risk index to assess the risk level of using PPP to build critical infrastructure resilience. This risk index can be used to ascertain the risk level in different countries. In addition, no research has been conducted to empirically test the risks in using PPP to build critical infrastructure resilience thus making this study a novel contribution to the critical infrastructure resilience research domain.

The success of public–private partnership (PPP) projects is highly correlated to the successful management of risks encountered during the operation phase. PPP projects are especially exposed to risk due to the long operation period over which revenues need to be generated to recoup substantial initial investment and operational running costs. Despite the critical impact of risk exposure, limited research has been specifically undertaken on the matter of operational risk management. This study seeks to address this oversight by identifying and evaluating operational risk management strategies for PPPs.

Vulnerability theory is the theoretical lens used, with context drawn from Chinese PPP projects. Based on the data collected from expert interviews and questionnaires, 28 operational risk management strategies are identified. A fuzzy synthetic method is employed to analyze the effectiveness of the 28 strategies.

The findings reveal that providing an exit mechanism clause into the contract, establishing a comprehensive performance evaluation mechanism and developing a clear compensation mechanism are the top three effective strategies. This study also reveals that risk mitigation approaches that reduce vulnerability prove more effective than attempts to reduce external threats. Specifically, strategies aimed at managing contract, political, technical and financial risk are the most effective.

The findings of this study extend current knowledge regarding the risk management of PPP projects. They also offer a reference by which practitioners may select effective operational risk management pathways and thereby, galvanize the sustainable development of PPPs.

This research aims to systematically review studies on significant risks for Critical Infrastructure Projects (CIPs) from selected top-tier academic journals from 2011 to 2023.

In this research, a three-step systematic literature review methodology was employed to analyse 55 selected articles on Critical Infrastructure Risks (CIRs) from well-regarded and relevant academic journals published from 2011 to 2023.

The findings highlight a growing research focus on CIRs from 2011 to 2023. A total of 128 risks were identified and grouped into ten distinct categories: construction, cultural, environmental, financial, legal, management, market, political, safety and technical risks. In addition, literature reviews combined with questionnaire surveys were more frequently used to identify CIRs than any other method. Moreover, oil and gas projects were the subjects most often explored in the reviewed papers. Furthermore, it was observed that publications from Iran, the USA and China dominated CIRs research, making significant contributions, accounting for 49.65% of the analysed articles.

This research specifically focuses on five types of CIPs (i.e. roadways, bridges, water supply systems, dams and oil and gas projects). Other CIPs like cyber-physical systems or electric power systems, were not considered in this research.

Governments and contracting firms can benefit from the findings of this study by understanding the significant risks associated with the execution of CIPs, irrespective of the nation, industry or type of project. The results of this investigation can offer construction professionals valuable insights to formulate and implement risk response plans in the early stages of a project.

As a novel literature review related to CIRs, it lays the groundwork for future research and deepens the understanding of the multi-faceted effects of these risks, as well as sets practical response strategies.

The purpose of this paper is to develop a comprehensive understanding of the public safety risks of international construction projects (ICPs) from the perspective of threat and vulnerability. A novel and comprehensive risk assessment approach is developed from a systemic perspective and applied to the Belt and Road Initiative (BRI) to improve the public safety risk management strategy for ICPs in BRI.

First, a public safety risk indicator system was constructed from the two dimensions, namely threat and vulnerability. Next, an integrated measurement model was constructed by combining the Genetic Algorithm-Backpropagation (GA-BP) neural network, fuzzy comprehensive evaluation method and matter-element extension (MME) method. Data from 49 countries involved in the BRI, as well as five typical projects, were used to validate the model. Finally, targeted risk prevention measures were identified for use at the national, enterprise and project levels.

The findings indicate that while the vulnerability risks of typical projects in each region of the BRI were generally low, threat risks were high in West Asia and North Africa, Commonwealth of Independent States (CIS) countries and South Asia.

First, the structure of the public safety risk system of ICPs was analyzed using vulnerability and system theories. The connotation of public safety risk was defined based on two dimensions, namely threat and vulnerability. The idea of measuring threat risk with public data and measuring vulnerability risk with project data was clarified, and the risk measurement was integrated into the measurement results to help researchers and managers understand and systematically consider the public safety risks of ICPs. Second, a public safety risk indicator system was constructed, including 18 threat risk indicators and 14 vulnerability risk indicators to address the gaps in the existing research. The MEE model was employed to overcome the problem of incompatible indicator systems and provide stable and credible integrated measurement results. Finally, the whole-process public safety risk management scheme designed in this study can help to both provide a reference point for the Chinese enterprises and oversea contractors in market selection as well as improve ICP public safety risk management.

Construction projects, and particularly highway infrastructures, are known to be major contributors to the socio-economic growth of developing countries. However, these types of projects are infamous for being highly risky due to the interplay of numerous risk factors. This study aims to explore the key risk factors impacting on the performance of highway infrastructure projects in Nigeria from the contextual viewpoint of key industry stakeholders.

Qualitative data was collected using semi-structured interviews. Specifically, 17 in-depth expert interviews were conducted with experienced stakeholders in the highway sector of the Nigerian construction industry. The collected data was transcribed and analysed using an established coding framework (grounded on case study approach, principles of thematic analysis and saliency analysis).

Overall, 17 key risks were identified from the data analysis process, and 6 risks were recognised as the most significant, based on the combination of prevalence of occurrence and significance of the coded information. The six top risks were: change in government, corruption, cost of construction materials, inflation, project funding issues and construction project delay. However, the first two of these risks (change in government and corruption) are politically related, which is specific and unique to the setting of Nigeria and thus might be seen as discouraging indicators that could have an impact on attracting foreign investors/contractors to Nigeria.

The study addressed the gap related with identifying context-specific risk factors impeding the performance of highway projects in Nigeria from the viewpoints of industry experts. It is expected that the findings will provide a better insight into the various risk factors and thus aid relevant policymakers to provide context-specific mitigating strategies.