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This study provides a comprehensive analysis of the potential contagion of Bitcoin on financial markets and sheds light on the complex interplay between technological advancements, accounting regulatory and financial market stability.

The study employs a multi-faceted approach to analyze the impact of BTC systemic risk, technological factors and regulatory variables on Asia–Pacific financial markets. Initially, a single-index model is used to estimate the systematic risk of BTC to financial markets. The study then uses ordinary least squares (OLS) to assess the potential impact of systemic risk, technological factors and regulatory variables on financial markets. To further control for time-varying factors common to all countries, a fixed effect (FE) panel data analysis is implemented. Additionally, a multinomial logistic regression model is utilized to evaluate the presence of contagion.

Results indicate that Bitcoin's systemic risk to the Asia–Pacific financial markets is relatively weak. Furthermore, technological advancements and international accounting standard adoption appear to indirectly stabilize these markets. The degree of contagion is also found to be stronger in foreign currencies (FX) than in stock index (INDEX) markets.

This study has several limitations that should be considered when interpreting the study findings. First, the definition of financial contagion is not universally accepted, and the study results are based on the specific definition and methodology. Second, the matching of daily financial market and BTC data with annual technological and regulatory variable data may have limited the strength of the study findings. However, the authors’ use of both parametric and nonparametric methods provides insights that may inspire further research into cryptocurrency markets and financial contagions.

Based on the authors analysis, they suggest that financial market regulators prioritize the development and adoption of new technologies and international accounting standard practices, rather than focusing solely on the potential risks associated with cryptocurrencies. While a cryptocurrency crash could harm individual investors, it is unlikely to pose a significant threat to the overall financial system.

To the best of the authors knowledge, they have not found an asset pricing approach to assess a possible contagion. The authors have developed a new method to evaluate whether there is a contagion from BTC to financial markets. A simple but intuitive asset pricing method to evaluate a systematic risk from a factor is a single index model. The single index model has been extensively used in stock markets but has not been used to evaluate the systemic risk potentials of cryptocurrencies. The authors followed Morck et al. (2000) and Durnev et al. (2004) to assess whether there is a systemic risk from BTC to financial markets. If the BTC possesses a systematic risk, the explanatory power of the BTC index model should be high. Therefore, the first implied contribution is to re-evaluate the findings from Aslanidis et al. (2019), Dahir et al. (2019) and Handika et al. (2019), using a different method.

This study aims to explore consumer motivations to mitigate the contagion effect in access-based consumption after instances of prior customer misbehavior. Reverse contagion, demonstrated through customer citizenship behavior, entails using both firm-provided and personal resources to cocreate value, even in the presence of norm violations by others. The research delves into the influence of empathy, narrative appeal and past misbehavior severity on customer behavior, specifically in the context of reverse contagion.

Two scenario-based studies and a field study were used within the context of scooter-sharing to assess the conceptual model. Study 1 (n = 156) and Study 2 (n = 97) were conducted through surveys. Study 3 (n = 54) was a field study.

The results emphasize the crucial role of empathy in breaking the cycle of misbehavior contagion. Specifically, the findings suggest that narrative appeals have the potential foster greater empathy, encouraging customers to counteract the contagion. However, the intensity of prior misbehavior lessens the efficacy of narrative appeals in triggering reverse contagion, thereby moderating the mediating effect of empathy.

This study investigates reverse contagion stemming from customer misbehavior in accessed-based consumption. It delves into the impact of empathy, narrative appeal and previous misbehavior on the dynamics of value codestruction and cocreation. This comprehensive examination of these factors within a unified framework represents a new contribution to the literature. The results illuminate this intricate phenomenon, offering valuable insights for managers to address adverse customer behavior and harness the positive aspects of reverse contagion.

In the digital age, the spread of online behavior and real-world information leads to social contagion. This study aims to investigate the contagion phenomenon of online physician choice and then discuss its potential influence on the sub-specialization process in the healthcare service industry. In specific, this study aims to propose the basic mechanism of infection and immunity as follows – exposure to antigen may lead to an immune response, and the success of the immune response may depend on the provision of appropriate immune signaling.

Data collected from haodf.com including 4 disease types and 247 physicians from 2008 to 2015 were used to test the proposed hypotheses. Panel vector autoregression method was utilized to analyze the panel data.

The obtained result shows that social contagion of physician choice over disease type is salient on e-consultation platforms, indicating that physicians associated with/on haodf.com are concentrating on an even narrower type of disease. Disclosing more simple signals (physician history orders) results in more disease concentration for that physician in the future. In contrast, disclosing more detailed signals (physician-contributed knowledge or physician reviews) leads to less disease concentration.

This finding implies that physician-contributed knowledge and physician reviews may act as immune signal which will tend to trigger a success immune response. This study not only suggests managers should be careful about the double-edged sword effect of online physician choice contagion but also provides the useful approaches to promote or restrain such a contagion in a flexible way.

Corruption is a major social problem, and scholars have devoted considerable attention to this phenomenon. However, less attention has been paid to how corruption spreads among organizations and what factors can make its spread more likely. This study aims to fill the gap by modelling corruption as an interorganizational contagion.

The authors used social contagion theory to model corruption as an interorganizational contagion, influenced by the susceptibility of organizations and the strength of contagion sources. The study analysed 736 medium and large Italian municipalities over a five-year period, with 3,146 observations (excluding missing data). The authors conducted a longitudinal analysis using panel logistic regression techniques and performed robustness and endogeneity checks through a dynamic panel data model.

The authors found that municipalities with a higher percentage of corrupt neighbouring municipalities were more likely to experience corruption. The probability of experiencing corruption was also significantly higher for municipalities with weaker organizational resistance to corruption contagion.

Previous studies have not clearly explained the organizational mechanisms behind the spread of corruption at the interorganizational level. The study suggests that corruption contagion at the municipal level occurs via reduced uncertainty in decision-makers and is influenced by the prevalence of corruption locally. The spread can be driven by conscious or unconscious mechanisms. This study challenges the idea that corruption contagion is immediate and inevitable. Organizational resistance to corruption can affect the risk of contagion, highlighting the importance of anti-corruption controls and ethical systems in preventing it.

This paper explores whether the Euro-area sovereign credit default swap market is prone to contagion effects. It investigates whether the sharp increase in sovereign CDS spread of a given country is due to a deterioration of the macroeconomic variables or some form of contagion.

For this purpose, the authors use an innovative approach, i.e. spatial econometrics. Although modeling spatial dependence is an attractive challenge, its application in the field of finance remains limited.

The empirical findings show strong evidence of spatial dependence highlighting the presence of pure contagion. Furthermore, evidence of wake-up call contagion-increased sensitivity of investors to fundamentals of neighboring countries and shift contagion-increased sensitivity to common factors are well recorded.

This study aims to study a crucial financial issue that gained increased research interest, i.e. financial contagion. A methodological contribution is made by extending the standard spatial Durbin model (SDM) to analyze and differentiate between several forms of contagion. The results can be used to understand how shocks are spreading through countries.

This study addresses the COVID-19 infection and its relationship with the city’s constructive intensity, commuting time to work and labor market dynamics during the lockdown period.

Microdata from formal workers in Recife was used to adjust a probability model for disease contraction.

The authors' results indicate that greater distance to employment increases the probability of infection. The same applies to constructive intensity, suggesting that residences in denser areas, such as apartments in buildings, condominiums and informal settlements, elevate the chances of contracting the disease. It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others. The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

The research shows important causal relationships, making it possible to think about public policies for the health of individuals both when commuting to work and in living conditions, aiming to control contagion by COVID-19.

The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others.

The authors identified positive and significant relationships between these urban characteristics and increased contagion, controlling for neighborhood, individual characteristics, comorbidities, occupations and economic activities.

As the application of crowdsourcing contests grows, leveraging the participation of superstars (i.e. solvers who have outstanding performance records in a crowdsourcing platform) becomes an emergent approach for managers to solve crowdsourced problems. Although much is known about superstars’ performance implications, it remains unclear whether and how their participation affects the size of a contest crowd for a crowdsourcing contest. Based on social contagion theory, this paper aims to examine the impact of superstars’ participation on the crowd size and studies how this impact varies across solvers with different heterogeneity in terms of skills, exposure and cultural proximity with superstars in crowdsourcing contests.

This paper uses secondary data from one crowdsourcing platform that includes 6,587 innovation contests to examine superstars’ main and contextual effects on the crowd size of a contest.

Our results reveal that superstars’ participation positively affects the crowd size of a contest in general. This finding suggests that social contagion is a fundamental mechanism underlying crowd formation in crowdsourcing contests. Our results also indicate that in contests that involve multiple superstars, superstars’ effect on crowd size becomes negative when we simultaneously consider other solvers’ heterogeneity in terms of skills, exposure and cultural background, and this negative effect will be intensified by increases in the skill gap, extent of exposure and cultural proximity between superstars and other solvers in the same contest.

Our research enhances the understanding of the influence of superstars and the mechanism underlying the emergence of contest crowds in crowdsourcing contests and contributes knowledge to better understand social contagion in a competitive setting. The results are meaningful for sourcing managers and platform supervisors to design contests and supervise crowd size in crowdsourcing contests.

Considering the frequency of extreme events, enhancing the global financial system's stability has become crucial. This study aims to investigate the contagion effects of extreme risk events in the international commodity market on China's financial industry. It highlights the significance of comprehending the origins, severity and potential impacts of extreme risks within China's financial market.

This study uses the tail-event driven network risk (TENET) model to construct a tail risk spillover network between China's financial market and the international commodity market. Combining with the characteristics of the network, this study employs an autoregressive distributed lag (ARDL) model to examine the factors influencing systemic risks in China's financial market and to explore the early identification of indicators for systemic risks in China's financial market.

The research reveals a strong tail risk contagion effect between China's financial market and the international commodity market, with a more pronounced impact from the latter to the former. Industrial raw materials, food, metals, oils, livestock and textiles notably influence China's currency market. The systemic risk in China's financial market is driven by systemic risks in the international commodity market and network centrality and can be accurately predicted with the ARDL-error correction model (ECM) model. Based on these, Chinese regulatory authorities can establish a monitoring and early warning mechanism to promptly identify contagion signs, issue timely warnings and adjust regulatory measures.

This study provides new insights into predicting systemic risk in China's financial market by revealing the tail risk spillover network structure between China's financial and international commodity markets.

This study aims to investigate the busy season contagion effects on other clients of the Big 4 auditor’s local office associated with the non-timely (NT) filing(s) by large accelerated filer (LAF) client(s) of the office. Specifically, the authors examine the influence such events have on the audit quality and timeliness of other clients of that office.

Using panel data of annual NT filings of LAF clients between 2006 and 2019, the authors apply the ordinary least squares regression technique to model audit reporting lag (ARL) and the logistic regression technique to model the probability of restatements.

Controlling for audit firm, industry and year-fixed effects, the authors find that a LAF NT filing reduces audit quality and audit timeliness of other clients of the office, as measured by restatement risk and ARL. The impact on ARL is most pronounced on the medium and small clients within the office. The deteriorated audit quality is observed for medium clients.

The results of this study have practical implications for auditors and regulators. They reveal the contagion effect in the auditor’s local office with the NT LAF client. The main limitation of the study is the lack of staffing utilization data to allow for drawing conclusions on causality.

To the best of the authors’ knowledge, this is the first study to document the contagion effect of NT filings of LAF clients conducted at the auditor’s local office level.

The main objective on this research is providing evidence of the contagion effect of decreasing audit's quality. Audit failure affects the quality of the financial analysis that has been carried out and has a big impact on the accuracy of decision making due to the material information bias. Findings of this research will urge the Public Accounting Firm (PAF) to design a quality control of the audit services. This action is taken with the consideration of maintaining the quality of audit services and the reputation of auditors.

Utilizing manufacturing data listed on Bursa Efek Indonesia (BEI), the researchers developed a model to explain the audit failure which is seen from restatement of financial statement in the subsequent period.

This research indicates that audit failure to detect the misstatement will decrease the audit's quality of other companies audited by the same auditor. There is also an insight that contagion effect of decreasing auditor quality was stronger for non-big four and non-industry specialist auditors.

Audit failure still has the potential to occur. There is the potential that a failure in an audit of a particular client entity has an impact on defects of other clients served. If this allegation is proven, there are big challenges faced by the public accounting profession and PAF to pay special attention in order to maintain the professional reputation.

Professional body and government need to develop a robust standard and operating procedures as well as quality control on audit engagement.

Due to the intention of fraud occurred in Indonesia, namely SNP Finance and Garuda Indonesia case. It is important to learn from that cases. This research gives fruitful insights to prevent the same case in the future.