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This paper explores the effect of natural disasters on the profitability and solvency of US banks.

Employing a sample of 187 large-scale natural disasters that occurred in the United States between 2000 and 2014 and a sample of 2,891 banks, we examine whether and how disaster-related damages affect various measures of bank profitability and bank solvency. We differentiate between different types of banks (with local, regional and national operations) based on a breakdown of their state-level deposits and explore the reaction of these banks to damages weighted by the GDP of the states they operate in.

We find that natural disasters have a pronounced effect on the net-income-to-assets and the net-income-to-equity ratio of banks, as well as the banks' impaired loans and return on average assets. We also observe significant effects on the equity ratio and the tier-1 capital ratio (two solvency measures). Interestingly, the latter are positive for regional banks which appear to benefit from increased customer deposits related to safekeeping, government payments for post-disaster recovery, insurance payouts and decreased withdrawals, while they are significantly negative for banks that operate locally or nationally.

We contribute to the literature by offering various new insights regarding the effects natural disasters have on financial institutions. With climate change-driven natural disasters widely expected to increase both in terms of frequency and severity, their economic fallout is likely to impose an increasing burden on financial institutions. Large, nationally operating banks tend to be well diversified both geographically and in terms of their product offerings. Small, locally operating banks, however, are increasingly at risk – particularly if they operate in disaster-prone areas. Current banking regulations generally do not factor natural disaster risks into their capital requirements. To avoid the next big financial crisis, regulators may want to adjust their reserve requirements by taking this growing risk exposure into consideration.

The purpose of this paper is to facilitate understanding of how to mitigate the privacy concerns of users who have experienced privacy invasions.

Drawing on the communication privacy management theory, the authors developed a model suggesting that privacy concerns form through a cognitive process involving threat-coping appraisals, institutional privacy assurances and privacy experiences. The model was tested using data from an empirical survey with 913 randomly selected social media users.

Privacy concerns are jointly determined by perceived privacy risks and privacy self-efficacy. The perceived effectiveness of institutional privacy assurances in terms of established privacy policies and privacy protection technology influences the perceptions of privacy risks and privacy self-efficacy. More specifically, privacy invasion experiences are negatively associated with the perceived effectiveness of institutional privacy assurances.

Privacy concerns are conceptualized as general concerns that reflect an individual’s worry about the possible loss of private information. The specific types of private information were not differentiated.

This paper is among the first to clarify the specific mechanisms through which privacy invasion experiences influence privacy concerns. Privacy concerns have long been viewed as resulting from individual actions. The study contributes to literature by linking privacy concerns with institutional privacy practice.

Natural disasters profoundly influence agricultural trade sustainability. This study investigates the effects of natural disasters on agricultural production imports in China within 2002 and 2018. This exploration estimates the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations.

This investigation uses Probit, Logit, Cloglog and Ordinary Least Squares (OLS) models.

The results confirm the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations in China. According to the findings, natural disasters in trading partners heighten the risk to the agricultural imports. This risk raises, if disasters damage overall agricultural yield or transportation infrastructure. Moreover, governments’ effective response or diplomatic ties with China mitigate the risk. Finally, the effect of disasters varies by the developmental status of the country involved, with events in developed nations posing a greater risk to China’s imports than those in developing nations.

China should devise an early warning system to protect its agricultural imports by using advanced technologies such as data analytics, remote sensing and artificial intelligence. In addition, it can leverage this system by improving its collaboration with trading partners, involvement in international forums and agreement for mutual support in crisis.

Drawing on social capital theory, this study investigated the effects of structural, cognitive and relational family social capital on employees' career advancement through the mechanism of family-to-work enrichment (FWE), taking perceived organizational politics (POP) as a moderator.

Survey data were collected from 252 full-time employees working in public institutions and government departments in China, a collectivist cultural context. Hierarchical regression and path analysis were conducted to test the hypotheses.

FWE significantly mediated the positive relationships between the three subtypes of family social capital and career advancement. The effects of structural and cognitive family social capital, but not relational family social capital (RFSC), on FWE were stronger when POP was low (vs high).

FWE is arguably a promising mechanism for explaining the links between family social capital and career outcomes. However, due to the cross-sectional nature of the data, conclusions regarding causality remain limited.

Family social capital may enrich the careers of employees in collectivist cultures. Managers should mitigate their organization's political climate to promote employees' career advancement.

This study contributes to career research by linking family social capital to career outcomes through the lens of FWE for the first time and by identifying organizational politics as an important moderator that can influence the dynamics of resource enrichment in a collectivist culture.

This study aims to investigate the relationship between corporate environmental responsibility (CER) and risk-taking in Chinese A-share listed companies from 2011 to 2020. It seeks to understand the influence of CER on risk-taking behavior and explore potential moderating factors.

A quantitative approach is used, using data from Chinese A-share listed companies over the specified period. Regression analysis is used to examine the relationship between CER and risk-taking, while considering moderating variables such as performance aspiration, environmental enrichment and contextual factors.

The findings indicate that CER positively influences corporate risk-taking, with significant impacts on information asymmetry and corporate reputation. Moreover, positive performance aspiration strengthens the effect of CER on risk-taking, while negative performance aspiration and environmental enrichment weaken this effect. Cross-sectional analysis shows that the positive association between CER and risk-taking is more prominent for firms located in areas with strict environmental regulation, for nonstate-owned firms, and for firms with higher levels of internal control.

This research contributes to the literature by providing insights into the dynamics between CER and risk-taking in the Chinese market context. It expands existing knowledge by considering the influence of performance aspiration on this relationship, offering practical implications for firms seeking to enhance corporate performance through strategic management of environmental responsibilities.

This study aims to identify the counterproductive knowledge behavior (CKB) of volunteers in nonprofit organizations and its influencing factors, based on the theories of planned behavior and well-being.

An online survey was used to collect 496 valid responses. A structural equation model was constructed, and the relationships among the constructs were estimated via the maximum likelihood method. To analyze the direct and indirect effects, 2,000 bootstrapping runs were conducted. A Kruskal-Wallis test was also conducted to analyze the relationship between the variables.

A combination of organizational factors and individual attitudes and perceptions can be used to explain CKB. Insecurity about knowledge sharing had the greatest impact on CKB. A competitive organizational norm induced CKB while a knowledge-sharing organizational norm did not have a significant impact. Further, the more self-determined the volunteer activity was, the more the CKB was suppressed. However, well-being did not have a significant direct effect. Volunteers with high levels of well-being and self-determination had significantly lower levels of insecurity about knowledge sharing compared to those who did not.

Well-being arising from volunteering did not directly suppress CKB. To improve organizational efficiency by reducing CKB, nonprofit organization managers should provide intrinsically motivating tasks and interact with the volunteers.

There is a lack of empirical research on CKB in volunteer organizations; therefore, the authors propose a new approach to knowledge management in volunteer activities.

This study aims to understand elderly people and their family members’ perceptions and usage of a mobile personal safety service.

The study adopts both interviews and analysis of actual usage data to cross-validate the findings. Four family groups and 11 subjects participated in the study.

Elderly people are willing to learn to use the mobile safety service, and some elderly people explore more features than their younger family members. Family support facilitates their learning. Elderly people feel psychologically secure when using the mobile safety service. Privacy concerns are mitigated because they consider location sharing is necessary for the service.

The current sample is small, as it involves collection of both interview data and actual usage data. Considering the emergency of the mobile personal safety service, the study is exploratory.

The findings suggest that elderly people are willing to learn and use technology such as the mobile safety service, which is relevant to their daily lives. Designers may think about how to highlight the relevancy aspect of technologies in elderly peoples’ lives.

This study is one of the earliest studies about elderly people’s usage of mobile safety service. This study reveals that elderly people are willing to learn to use the mobile safety service and explore its features. Technical support from family members and relevancy of the service in their daily lives may encourage them to use the technology.

This paper aims to explore the impact of cycle superposition on bank liquidity risk under different levels of financial openness so that banks can better manage their liquidity risk. Meanwhile, it can also provide some ideas for banks in other emerging economies to better cope with the shocks of the global financial cycle.

Employing the monthly data of 16 commercial banks in China from 2005 to 2021 and based on the time-varying parameter vector autoregressive model with stochastic volatility (TVP-SV-VAR) model, the authors first examine whether the cycle superposition can magnify the impact of China's financial cycle on bank liquidity risk. Subsequently, the authors investigate the impact of different levels of financial openness on cycle superposition amplification. Finally, the shock of the financial cycle of the world's major economies on the liquidity risk of Chinese banks is also empirically analyzed.

Cycle superposition can magnify the impact of China's financial cycle on bank liquidity risk. However, there are significant differences under different levels of financial openness. Compared with low financial openness, in the period of high financial openness, the magnifying effect of cycle superposition is strengthened in the short term but obviously weakened in the long run. In addition, the authors' findings also demonstrate that although the United States is the main shock country, the influence of other developed economies, such as Japan and Eurozone countries, cannot be ignored.

Firstly, the cycle superposition index is constructed. Secondly, the authors supplement the literature by providing evidence that the association between cycle superposition and bank liquidity risk also depends on financial openness. Finally, the dominant countries of the global financial cycle have been rejudged.

The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.

In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.

The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.

In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.