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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 study aims to investigate the existence of contagion between liquid and illiquid assets in the credit default swap (CDS) market around the recent financial crisis. The authors perform analyses based on vector autoregression model and the dynamic conditional correlation model. The estimation of vector autoregression models reveals that changes in liquid CDS (LCDS) spreads lead to changes in illiquid CDS spreads at least one week ahead during the financial crisis period, whereas the leading direction is reversed during the post-crisis period. Moreover, the results are robust after controlling for structural variables which are proven as determinants of CDS spreads and are empirically supported. This study interprets that information was incorporated first into the LCDSs because of the flight-to-liquidity during the recent crisis period but there is a default contagion effect by reflecting illiquidity-induced credit risk after the crisis. Finally, the dynamic conditional correlation analysis also confirms the main results.

The purpose of this paper is to study the evolution of financial contagion between Eurozone banks, observing the credit default swaps (CDSs) market during the period 2009–2017.

The authors use a dynamic spatial Durbin model that enables to explore the direct and indirect effects over the short and long run and the transmission channels of the contagion.

The results show how contagion emerges through physical and financial market links between banks. This finding implies that a bank can fail because people expect other related financial institutions to fail as well (self-fulfilling crisis). The study provides statistically significant evidence of the presence of credit risk spillovers in CDS markets. The findings show that equity market dynamics of “neighbouring” banks are important factors in risk transmission.

The research provides a new contribution to the analysis of EZ banking risk contagion, studying CDS spread determinants both under a temporal and spatial dimension. Considering the cross-dependence of credit spreads, the study allowed to verify the non-linearity between the probability of default of a debtor and the observed credit spreads (credit spread puzzle). The authors provide information on the transmission mechanism of contagion and, on the effects among the largest banks. In fact, through the study of short- and long-term impacts, direct and indirect, the paper classify banks of systemic importance according to their effect on the financial system.

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.

In this paper, the authors use the balance sheet data to investigate the interconnectedness and risk contagion effects in China's banking sector. They firstly study the network structure and centrality of the interbank network. Then, they investigate how and to what extent the credit shock and liquidity shock can lead to the risk propagation in the banking network.

Referring to the theoretical framework by Haldane and May (2011), this paper uses the network topology theory to analyze the contagion mechanism of credit shock and liquidity shock. Centrality measures and log-log plot are used to evaluate the interconnectedness of China's banking network.

The network topology has shown clustering effects of large banks in China's financial network. If the Industrial and Commercial Bank of China (ICBC) is in distress, the credit shock has little impact on the Chinese banking sector. However, the liquidity shock has shown more substantial effects than that of the credit shock. The discount rate and the rollover ratio play significant roles in determining the contagion effects. If the credit shock and liquidity shock coincide, the contagion effects will be amplified.

The results of this paper reveal the network structure of China's interbank market and the resilience of banking system to the adverse shock. The findings are valuable for regulators to make policies and supervise the systemic important banks.

The balance sheet data of different types of banks are used to construct a bilateral exposure matrix. Based on the matrix, this paper investigates the knock-on effects of credit shock triggered by the debt default in the interbank market, the knock-on effects of liquidity effects, which is featured by “fire sale” of bank assets, and the contagion effects of combined shocks.

The purpose of this paper is to investigate the emotional contagion theory in print ads, and expand the literature of smiling to different type of smiles and gender congruency. Emotional contagion happens when an emotion is transferred from a sender to a receiver by the synchronization of emotions from the emitter. Drawing on emotional contagion theory, the authors expand this concept and propose that smiles in static facial expressions influence product evaluation. They suggest that false smiles do not have the same impact as genuine smiles on product evaluation, and the congruence between the model gender–product in a static ad and the gender of the viewer moderates the effects.

In Experiment 1, subjects were randomly assigned to view one of the two ad treatments to guard against systematic error (e.g. bias). In Experiment 2, it was investigated whether viewing a static ad featuring a model with a false smile can result in a positive product evaluation as was the case with genuine smiles (H3). In Experiment 3, it was assumed that when consumers evaluate an ad featuring a smiling face, the facial expression influences product evaluation, and this influence is moderated by the congruence between the gender of the ad viewer and the product H gender of the model in the ad.

Across three experiments, the authors found that the model’s facial expression influenced the product evaluation. Second, they supported the association between a model’s facial expression and mimicry synchronization. Third, they showed that genuine smiles have a higher impact on product evaluation than false smiles. This novel result enlarges the research on genuine smiles to include false smiles. Fourth, the authors supported the gender–product congruence effect in that the gender of the ad’s reader and the model have a moderating effect on the relationship between the model’s facial expression and the reader’s product evaluation.

Marketing managers would benefit from understanding that genuine smiles can encourage positive emotions on the part of consumers via emotional contagion, which would be very useful to create a positive effect on products. The authors improved upon previous psychological theory (Gunnery et al., 2013; Hennig-Thurau et al., 2006) showing that a genuine smile results in higher evaluation scores of products presented in static ads. The theoretical explanation for this effect is the genuine smile, which involves contraction of both zygomatic major and orbicularis oculi muscles. These facial muscles can be better perceived and transmit positive emotions (Hennig-Thurau et al., 2006).

This paper aims to determine the factors that influence the consumer’s online shopping intention in the current pandemic context (COVID-19). For this purpose, a conceptual model has been developed by introducing the constructs “attitude,” “perceived utility,” “intention” as well as the variable “perceived risk of contagion.”

After collecting data from the questionnaire diffused in Moroccan e-commerce websites, this study used various statistical analyses with the multiple regression model on the SPSS statistical software to confirm or refute the research hypotheses.

The results indicate that attitude and perceived utility positively affect online shopping intention. However, the variable “perceived risk of contagion” has a weak effect on such intention, which can be explained by the period in which the survey was started (a few months after the confinement).

The scientific contribution of this study lies in the insertion of a new factor that will be called “perceived risk of contagion” in the research model. This factor has been inspired by the perceived risk theory of Bauer (1960). Furthermore, all studies dealing with this topic have been carried out in developed countries, such as France, Great Britain, Germany and the USA. For this reason, the researcher believe that it is more appropriate to study the intention to buy online during the COVID-19 pandemic in one of the developing countries, such as Morocco. This is based on the fact that to develop theories, it is necessary to examine a given problem in several countries. The context plays a determining role in such situations.

The purpose of this paper is to address the following question: Can a bank capitalize on its well-established self-service technologies (SSTs) in order to entice customers to adopt a newly introduced SST, namely, mobile banking? More specifically, it proposes an integrative model that simultaneously investigates the transference effects of attitudes, trust and the contagious influences of social pressures on mobile banking adoption intentions.

Structural equation modeling is applied to data collected from banks’ clients who are actually non-users of mobile banking.

The results indicate that attitude toward and trust in mobile banking along with coercive, normative and mimetic pressures are key antecedents to mobile banking adoption intentions. In addition, attitudes toward automated teller machines (ATMs) and online banking significantly predict attitude toward mobile banking. The results also support the effects of trust in ATMs as well as trust in online banking on trust in mobile banking. Moreover, predicted differences in the relative effects of attitude and trust are supported. Particularly, attitude toward online banking has a stronger impact on attitude toward mobile banking compared to the impact of attitude toward ATMs. In the same vein, the effect of trust in online banking on mobile banking is significantly stronger than the effect of trust in ATMs.

The study’s results hint at some practical and worthwhile guidelines for banks that can be leveraged in communication campaigns aiming at boosting the adoption rates of mobile banking. Banks can take advantage of the transference effects of the established attitudes toward and trusting beliefs in their mature SSTs as well as the contagious social influences in inducing the adoption of a newly introduced SST.

The present study represents a first step toward generating new insights into the role of the joint effects of attitudes, trust and social influences in the adoption of a new SST.

This paper analyses emergency management in two regions of Italy – Emilia-Romagna and Veneto – in order (1) to understand whether they impact on the spread of local coronavirus disease 2019 (COVID-19) contagion and (2) evaluate which strategy works best.

A three-step method was developed consisting of (1) a regional incidence curve analysis; (2) a descriptive statistical analysis of the respective operational measures related to the COVID-19 curve stages; and (3) a dynamic Structural Equation Model.

The results show the effects of the models during the various stages of the local contagion, focussing both on the two individual regions and a comparison of the way they responded.

Three theoretical implications are highlighted: (1) Better results are not necessarily the outcome of increased expenditure; (2) The overall rigidity they both show does not work; (3) The decision to centralize was, to some extent, effective for both regions.

The article empirically tests the effectiveness of emergency management in tackling a single event. Instead of the widely-used normative approach, the authors adopted a descriptive one, which is not frequently discussed in the emergency management literature.

In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.

By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.

The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.

Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.

This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.