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This study investigated whether the quality of governance, trustworthiness, and confidence impacts bank credit growth. In addition, we examined credit growth cyclicality in 10 members of the Association of Southeast Asian Nations. By employing data concerning 282 banks between 2012 and 2019, this study found that trustworthiness boosted bank credit growth. Overall, the increased quality of governance was found to increase credit growth, except for the specific indicators of voice and accountability and political stability, which were found not to influence bank credit growth. Moreover, similar to prior findings in related fields, the empirical results of this study confirmed the complementary effect of informal and formal institutions on bank credit growth. Lastly, results indicated that banks were pro-cyclical regarding credit growth. Overall, the results of this study highlighted the role of the supervisory powers of governments in boosting credit expansion, mainly during economic upturns.

Globally, the coronavirus disease (COVID-19) pandemic has sparked unexpected and violent outbursts against doctors, nurses, and other health personnel. In the Indian context, studies on violence against doctors and other medical staff largely focus on supply-demand imbalances in health care, overcrowding, drug shortages, negligence of critical care patients, lack of diagnostic and other essential devices (e.g., X-ray and ultrasound equipment and oxygen cylinders), deaths of patients, and bribery and corruption (collusion between doctors and pharmaceutical companies). While these factors explain such violence against medical personnel partly, we argue that it is largely rooted in a lack of trust in doctors and hospitals, which eroded rapidly during the COVID-19 pandemic. We analyze the covariates of trust in public and private health-care providers based on an all-India panel survey and delineate policies to rebuild trust, especially in public health care.

The role of social capital in economic development has been a subject of interest to both academics and practitioners of development for several decades. However, empirical evidence on social capital in the context of developing countries is still relatively scant. This study explores the effects of social capital on economic development in Indonesia, a large and multi-ethnic developing country. Using district-level data for 2006–2019, we find that the relationships between social capital and economic development are complex. There are both favorable and unfavorable effects of social capital on economic development, as well as nonlinear effects. Hence, we cannot draw unequivocal conclusions on the benefits or disadvantages of social capital for economic development. Nevertheless, this study finds that trust among people across different ethnic groups, participation in communal works and social activities, and trust in government are the most important forms of social capital needed to improve people’s welfare.

We study the stability of non-cognitive skills by comparing experimental data gathered before and during the COVID-19 pandemic. Using a sample of professional traders, we find a significant decrease in Agreeableness and Locus of Control and a moderate decrease in Grit. These patterns are primarily driven by those with more negative experiences of the pandemic. Other skills, such as Trust, Conscientiousness, and Self-Monitoring, are unchanged. We contrast these results with those from a sample of undergraduate students whose non-cognitive skills remain constant (except Conscientiousness). Our findings provide evidence against the stability of some non-cognitive skills, particularly among professional traders.

In this paper, we explore the relations among institutional quality, households’ level of trust, and stock market participation. We find that institutional quality has a significant impact on both trust and participation. The individual level of trust significantly affects participation, but trust plays a small role in the effect of institutional quality on participation. Further, we demonstrate that immigrants are affected by the institutional quality of both their country of residence and their home country, and that education emerges as an important learning factor in immigrants’ adaptation to new institutional environments.

Sharing of risk knowledge for extreme events is taking place against a backdrop of changing societal communication patterns, in which the flow of information is increasingly multi-directional, within and between individuals, wider communities and a variety of authorities using online media. We present qualitative findings from the CASCADE knowledge exchange project and a case study, from a flood risk area, on the role of social networks using such ‘new’ media as engagement tools in building resilience to flooding. The data emerged from a workshop held in 2018, together with a study into changing communication practice in the Thames Valley near Windsor, UK. It was found that engagement is occurring both during events, as an emergency management tool, and between events, often linked to strategic management such as flood defense and related planning. The qualitative findings were analyzed to investigate whether knowledge and information sharing in emergencies may lead to co-operative sharing between emergencies. According to evidence from workshop discussions across the seminars, and empirical evidence from the flood risk zone, social networks formed and/or enhanced using new media can help promote consensus but also have the potential to accentuate distrust and divide managers and the community at risk. Relevant factors were the nature of the risk faced, nature of event-related protection activity, whether extreme weather events were occurring or had occurred in the recent past, and sociocultural aspects such as the degree of general engagement of civil society, linked to location. There is a possibility that new media may thus reinforce existing power structures, including acknowledged paternalistic attitudes by management authorities and pre-conceived ideas from at-risk communities. In terms of the contribution that social media can make toward the goal of social learning for resilience, the specific role of online social media as a communication tool continues to evolve. It was noted from the workshop that there is a potential for producers of information to act also as consumers (the ‘prosumer effect’), but gaining benefit from this trend requires some changes to existing interaction patterns within and between risk management authorities and communities. More investment may be required in forms of engagement that build relationships of trust, using ‘traditional’ (face-to-face) approaches.

Privacy and trust of biomedical solutions that capture and share data is an issue rising to the center of public attention and discourse. While large-scale academic, medical, and industrial research initiatives must collect increasing amounts of personal biomedical data from patient stakeholders, central to ensuring precision health becomes a reality, methods for providing sufficient privacy in biomedical databases and conveying a sense of trust to the user is equally crucial for the field of biocomputing to advance with the grace of those stakeholders. If the intended audience does not trust new precision health innovations, funding and support for these efforts will inevitably be limited. It is therefore crucial for the field to address these issues in a timely manner. Here we describe current research directions towards achieving trustworthy biomedical informatics solutions.

Crowd-powered telemedicine has the potential to revolutionize healthcare, especially during times that require remote access to care. However, sharing private health data with strangers from around the world is not compatible with data privacy standards, requiring a stringent filtration process to recruit reliable and trustworthy workers who can go through the proper training and security steps. The key challenge, then, is to identify capable, trustworthy, and reliable workers through high-fidelity evaluation tasks without exposing any sensitive patient data during the evaluation process. We contribute a set of experimentally validated metrics for assessing the trustworthiness and reliability of crowd workers tasked with providing behavioral feature tags to unstructured videos of children with autism and matched neurotypical controls. The workers are blinded to diagnosis and blinded to the goal of using the features to diagnose autism. These behavioral labels are fed as input to a previously validated binary logistic regression classifier for detecting autism cases using categorical feature vectors. While the metrics do not incorporate any ground truth labels of child diagnosis, linear regression using the 3 correlative metrics as input can predict the mean probability of the correct class of each worker with a mean average error of 7.51% for performance on the same set of videos and 10.93% for performance on a distinct balanced video set with different children. These results indicate that crowd workers can be recruited for performance based largely on behavioral metrics on a crowdsourced task, enabling an affordable way to filter crowd workforces into a trustworthy and reliable diagnostic workforce.