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This study aims to examine the determinants of ethical decision-making (EDM) of professional accountants in Sri Lanka, drawing on Rest’s (1986) four-component EDM model. The level of corporate collapses and fraud, coupled with the high level of corruption in Sri Lanka, has highlighted the importance and the timely nature of this research in the EDM processes of Sri Lankan accountants.

Data was collected from a sample of 315 accountants through a questionnaire survey that included four written ethical vignettes and was analysed using partial least square-structural equation modelling techniques.

The findings revealed a significant relationship between ethical awareness and ethical judgement, providing support for Rest’s model. However, the study does not support Rest’s model on the direct relationship between ethical judgement and ethical intention. Intrinsic religiosity and moral intensity significantly influenced the ethical awareness of accountants. Several determinants including accountants’ age, education, intrinsic religiosity, organisational ethical culture, familiarity with the professional ethical code and moral intensity influenced ethical judgement. However, the findings did not report any significant relationships between the study’s variables and ethical intention.

The study adds to the existing literature by providing a bigger picture of how various determinants work together in one EDM model and demonstrating that the EDM of accountants is multifaceted. The new finding on an insignificant relationship between ethical judgement and ethical intention implies that the Rest’s EDM process may be mediated and moderated by other constraints blocking accountants’ intention to act due to various pressures in a corrupt society, Sri Lanka, where accountants operate.

This study aims to objectively synthesize the volume of accounting literature on financial statement fraud (FSF) using a systematic literature review research method (SLRRM). This paper analyzes the vast FSF literature based on inclusion and exclusion criteria. These criteria filter articles that are present in the accounting fraud domain and are published in peer-reviewed quality journals based on Australian Business Deans Council (ABDC) journal ranking. Lastly, a reverse search, analyzing the articles' abstracts, further narrows the search to 88 peer-reviewed articles. After examining these 88 articles, the results imply that the current literature is shifting from traditional statistical approaches towards computational methods, specifically machine learning (ML), for predicting and detecting FSF. This evolution of the literature is influenced by the impact of micro and macro variables on FSF and the inadequacy of audit procedures to detect red flags of fraud. The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper chronicles the cluster of narratives surrounding the inadequacy of current accounting and auditing practices in preventing and detecting Financial Statement Fraud. The primary objective of this study is to objectively synthesize the volume of accounting literature on financial statement fraud. More specifically, this study will conduct a systematic literature review (SLR) to examine the evolution of financial statement fraud research and the emergence of new computational techniques to detect fraud in the accounting and finance literature.

The storyline of this study illustrates how the literature has evolved from conventional fraud detection mechanisms to computational techniques such as artificial intelligence (AI) and machine learning (ML). The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper contributes to the literature by providing insights to researchers about why the evolution of accounting fraud literature from traditional statistical methods to machine learning algorithms in fraud detection and prediction.

This paper aims to analyze the ethical responses of the fashion industry to the first wave of the COVID-19 pandemic when the entire world was shocked by the rapid spread of the virus. The authors describe lessons from emergency ethics of care in the fashion industry during the initial months of COVID-19, which can assist fashion managers in improving ethical decisions in future operations.

Rapid qualitative research methods were employed by conducting real-time, in-depth interviews with key informants from multinational fashion companies operating in Spain, a severely affected region. A content analysis of news articles published during the first months of 2020 was conducted.

Five critical disruptions in the fashion industry were identified: (1) changes in public needs, (2) transportation and distribution backlogs, (3) defective and counterfeit supplies, (4) stakeholder relationships at stake and (5) managers' coping challenges. Additionally, five business survival responses with a strong ethics of care component were identified, implemented by some fashion companies to mitigate the damage: (1) adapting production for public well-being, (2) enhancing the flexibility of logistic networks, (3) emphasizing quality and innovation, (4) reinventing stakeholder collaborations and (5) practicing responsible leadership.

Despite the well-documented controversies surrounding unethical practices within the fashion industry, even during COVID-19, our findings inform managers of the potential and capability of fashion companies to operate more responsibly. The lessons learned can guide fashion companies' operations in a post-pandemic society. Furthermore, they can address other grand challenges, such as natural disasters, geopolitical conflicts and climate change.

This paper aims to examine whether tax disclosure in Global Reporting Initiative (GRI)-based sustainability reporting mitigates aggressive tax avoidance.

This study uses a multiple regression method for 714 nonspecially taxed firms listed on the Indonesia Stock Exchange in 2014–2018.

The findings demonstrate that disclosing tax payments in GRI-based sustainability reports reduces aggressive tax avoidance. Additional analysis indicates that the number of GRI-based sustainability reports positively affects aggressive tax avoidance. However, disclosing tax payments in multiple GRI-based sustainability reports negatively affects aggressive tax avoidance.

Recent prior studies demonstrate that aggressive tax avoidance does not indicate an organizational culture that devalues corporate social responsibility. This paper argues that firms cannot find the link between tax and corporate social responsibility when tax payments are not incorporated in sustainability reports. GRI considers tax a sustainability issue and seeks to institutionalize this concept by recommending that firms disclose taxes in their sustainability reports. This research analyses whether disclosing taxes in GRI-based sustainability reports may serve as a form of soft law by convincing firms that tax is a sustainability issue, thereby reducing their tax avoidance. This topic has received little attention in previous research.

Using attribution theory, this study examined the effects of situational factors [time budget pressure (TBP), organisational ethical culture (OEC) and quality control procedures (QCPs)] and dispositional factors [auditor professional commitment (APC) and internal locus of control (ILOC)] on audit quality threatening behaviour (AQTB). In addition, it observed the moderating role of religiosity in the relationship between situational and dispositional factors and AQTB.

A total of 189 external auditors responded to the survey questionnaire. This study employed structural equation modelling via SmartPLS to analyse the proposed model.

The results documented that the OEC and QCPs situational factors were negatively related to the incidence of AQTB, whilst TBP was positively linked to the incidence of AQTB. Dispositional factors APC and ILOC were negatively connected to AQTB. Furthermore, the findings recorded the moderating effect of religiosity on most of the situational and dispositional factors related to AQTB.

Regulators and accounting firms' efforts to promote high audit quality (AQ) may consider the theological/religious lens and reinforce ethical culture and quality control to reduce AQTB.

The findings provide further insights into situational and dispositional factors that may cause or impede the incidence of AQTB in auditing practices, as well as the moderating role of religiosity in curbing AQTB.

This paper aims to develop a conceptual framework that jointly considers Environmental, Social and Governance (ESG) factors and organisational resilience (OR) components to ameliorate organisations' understanding of sustainability’s overall requirements and related decision-making processes.

This paper combines ESG and OR through a 3x3 conceptual matrix, where ESG factors are listed along the vertical axis and OR components along the horizontal axis. This results in nine quadrants, which have been read according to two arrangements: (1) static, looking at the specific characteristics of each single quadrant, and (2) dynamic, investigating the relationships between the different quadrants according to the system theory (ST) lens.

The integration between ESG and OR results in nine organisational typologies, each characterised by a specific focus: (1) green visioning, (2) eco ethos, (3) climate guard, (4) inclusive strategy, (5) empathy ethos, (6) community shield, (7) ethical blueprint, (8) integrity ethos and (9) compliance guard. These typologies and related focuses determine the different strategic options of organisations, the decision-making emphasis concerning ESG factors and OR components and the organisation’s behaviour concerning its internal and external environment. According to ST, the nine typologies interact with each other, emphasising the existence of interconnectedness, interdependence and cascading effects between ESG and OR.

The paper represents a unique attempt to interrelate ESG factors and OR components according to a ST lens, emphasising the dynamic nature of their interactions and organisations’ need for continuous adaptation and learning to make decisions that create sustainable long-term value.

Most research on tax evasion focused on microeconomic variables revolving around perceptions and decisions of individual taxpayers. However, a new wave of research is now investigating the role of macroeconomic variables in inducing tax evasion. This study adds to the limited studies in this new direction of research. Previous studies found that inflation, low gross domestic product (GDP) growth and gross fixed capital formation causes recession, increases unemployment, raise interest rates, hurts both domestic and foreign direct investments. This study examined the relationship between these variables and estimated tax evasion in Sub-Saharan Africa.

The study adopts a correlation research design with 2,300 data points collected from 23 countries in Sub-Saharan Africa. Specifically, tax to GDP ratio, gross fixed capital formation per GDP and the GDP annual growth report from each country for the period 2011–2020 was retrieved. Generalised least square regression technique was employed to analyse the data due to the presence of heteroskedasticity in the model and random effect was utilized based on the Hausman test. To avoid misspecification and biased result; therefore, all relevant test was conducted including the multicollinearity test.

The results indicate that GDP annual growth and gross fixed capital formation have a significant negative impact on estimated tax evasion in Sub-Saharan Africa. The findings further indicate a negative but insignificant relationship between inflation and estimated tax evasion in Sub-Saharan Africa. The study concludes that both GDP annual growth rate and gross fixed capital formation negatively influence estimated tax evasion and the policy implications in the African continent were discussed.

The new findings on the effects of GDP annual growth, growth fixed capital formation and inflation on estimated tax evasion provide novel knowledge that is currently lacking in the current literature, specifically Sub-Saharan African continent.