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This paper develops novel proxies for labour tax avoidance (LTAV) and tests their validity within a sample of 189 labour tax-avoidant offending firms (LTAOFs) accused of evading social security contributions (SOCs) by public authorities.

LTAV proxies are based on abnormal values of SOCs paid, reported in the income statements of a sample of 857,790 Spanish firm-years for the period 2001–2015, estimated through two-stage least square panel data regressions with firm fixed effects.

The results reveal that proxies specifically built to signal both conforming and non-conforming LTAV can provide evidence of abnormally low SOCs as expenses within the sample of LTAOFs. Furthermore, firm-specific financial variables as well as macroeconomic variables significantly influence LTAV.

This study could foster further research on the efficacy of the LTAV proxies and on the drivers and sustainability implications of LTAV for firms and their stakeholders in different socio-economic and institutional contexts.

These LTAV proxies could integrate other methods applied to estimate the undeclared work and its trends. Furthermore, they may assist tax authorities to direct their inspections, detect labour tax evasion and then strengthen the social protection of the employees from employers' illegal exploitation practices, as well as reducing tax revenue shortfalls and related sustainability concerns in the social security systems.

This study proposes a novel methodology to examine LTAV and its determinants through accounting information. This methodology may support researchers to provide a more comprehensive picture of tax planning strategies pursued by companies, that include LTAV, and in this way integrate the extant mature literature on income tax avoidance.

This study aims to explore the Facebook communication strategies of Spanish hospitals during health emergencies, focusing on their role in crisis management and public information dissemination.

Automatic topic modelling and deep learning sentiment analysis were applied to analyse 151,738 posts from 274 hospital Facebook pages (March 2020–Feb 2022). Regression analyses were used to explore the relationships between topics, sentiment scores and hospital characteristics.

The analysis revealed nine main topics, with the three most prevalent related to COVID-19: vaccine information, security measures and situational updates. This indicates that Spanish hospitals significantly relied on Facebook to manage the emergency. The communication strategies dynamically adapted to the intensity of the pandemic and varied across hospital types. Sentiment analysis showed a negative tone for posts about security measures and situational updates. These findings align with the Agenda-Setting Theory, suggesting that hospitals influenced public discourse. Vaccine information posts were more positive, resonating with the Uses and Gratifications Theory by fulfilling the audience’s need for reassurance and guidance.

Using replicable machine learning techniques, this study elucidates the communication strategies employed by Spanish hospitals to manage healthcare emergencies, such as the COVID-19 pandemic. It highlights factors that potentially influence these strategies and provides theoretical justifications for them. The variation in communication strategies on Facebook among different hospital categories underscores the imperative for stricter guidelines and regulations to guarantee consistent and reliable communication during emergencies. This research provides valuable insights for practitioners and policymakers aimed at developing effective health communication strategies on social media.

This study aims to investigate whether chief executive officer (CEO) demographics are associated with gender diversity in senior management in the Scandinavia region.

The research design draws on multivariate cross-sectional analysis. The demographic characteristics examined are gender, age and education. A total of six hypotheses are developed and tested. The sample includes the largest 106 public firms from Denmark, Finland, Norway and Sweden.

Results show that firms with female CEOs have more women in senior management than other firms. However, neither age nor level of formal education of CEOs shows significant results, with the exception of CEOs holding MBA degrees, who are associated with fewer women in these positions. Interestingly, the association between educational background and gender diversity is principally driven by study-abroad experiences. Finally, results show that gender diversity in senior management has an important country component, whereas the industry component is negligible.

The relationship between managers’ demographics and gender diversity among subordinates is a relatively unexplored research issue, as previous works have focused on general comparisons between male and female managers. Furthermore, the Scandinavian context is particularly interesting as this region leads gender equality rankings.

This study aims to investigate how the village government implements internal control, accountability, transparency and participation in the good governance practice for corruption prevention and detection in Indonesia.

This study is qualitative research by conducting a semi-structured interview with village staff, village consultative council members and auditors.

The findings highlight three major issues contributing to poor governance and the failure to prevent and detect corruption.

The regulator should urgently provide accounting standards, audit standards and internal control regulations for the village to create good governance for eradicating corruption.

This paper is a ground-breaking study that investigates the governance practice in the village as an anchor to solve the chronic corruption problem and offers a new direction of research in the village government.

The purpose of this paper is to investigate how accounting is used to disguise and carry out money laundering activities in specific socio-economic and political contexts and whether discretionary accruals can provide evidence of such illicit practices performed through legally registered Mafia firms (LMFs).

The study is based on a sample of 224 Italian firms identified as LMFs, due to having been confiscated by judicial authorities because of their owners being accused of Mafia-type association. Using a multivariate regression model, specifically developed discretionary accrual proxies for LMFs are compared with those of a population of lawful firms (LWFs).

The results reveal that in the pre-confiscation years, LMFs manage aggregate, revenue and expense accruals more than LWFs do, in order to smooth earnings and disguise/carry out money laundering. In contrast, in the post-confiscation years, there is no significant difference in the level of accrual management between LMFs and LWFs, as a consequence of the effective intervention of legal administrators.

This study adopts discretionary revenue and expense accrual proxies that provide additional insight into the simultaneous manipulation of revenues and expenses, linked to money laundering, which may not be fully detected by traditional aggregate accrual models. Furthermore, it suggests that the incentive for LMFs to manage accruals may be fostered by the irrelevance of their financial statements to trades with stakeholders. Finally, this paper may provide regulators with financial accounting signals which could be included in risk assessment models aiming to detect money laundering activities within firms.

The purpose of this study is to review the literature on money laundering and its related areas. The main objective is to identify any gaps in the literature and direct attention towards addressing them.

A systematic review of the money laundering literature was conducted with an emphasis on the Pro-Quest, Scopus and Science-Direct databases. Broad research themes were identified after investigating the literature. The theme about the detection of money laundering was then further investigated. The major approaches of such detection are identified, as well as research gaps that could be addressed in future studies.

The literature on money laundering can be classified into the following six broad areas: anti-money laundering framework and its effectiveness, the effect of money laundering on other fields and the economy, the role of actors and their relative importance, the magnitude of money laundering, new opportunities available for money laundering and detection of money laundering. Most studies about the detection of money laundering have focused on the use of innovative technologies, banking transactions or real estate- and trade-based money laundering. However, the literature on the detection of shell companies being explicitly used to launder funds is relatively scarce.

This paper provides insights into an area related to money laundering where research is relatively scant. Shell companies incorporated in the UK alone were identified to be associated with laundering £80bn of stolen money between 2010 and 2014. The use of these entities to launder billions of dollars as witnessed through the laundromat schemes and several data leaks clearly indicate the need to focus on illicit financial flows through such entities.