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The purpose of this article is to explore the impression management practices in Covid-19 related discourses in the annual reports of the insurance companies in Bangladesh.

To fulfil this objective, the authors have conducted a discourse analysis of the Covid-19 related corporate narratives in the latest annual reports of listed insurance companies. The findings are then interpreted through the lens of impression management theory, following the impression management strategies identified by Caliskan et al. (2021).

It is found that companies tried to manage the impression of the stakeholders through the strategic use of language. There is evidence that the companies used assertive and performance-oriented tactics to impress their stakeholders. In few cases, defensive strategies were applied.

This study will facilitate improving the understanding of corporate communication during the Covid-19 crisis. Policymakers will be able to understand the current status of Covid-19 related disclosures and consider the necessity to provide guidance that may lead to better accountability during the crisis.

This study will contribute to the limited literature on Covid-19 related disclosure from the context of developing economies. This research is methodologically novel as it applies discourse analysis and interprets the findings through the lens of impression management.

This study aims to ascertain the intentions of risk managers to use artificial intelligence in performing their tasks by examining the factors affecting their motivation.

The study employs an integrated theoretical framework that merges the third version of the technology acceptance model 3 (TAM3) and the unified theory of acceptance and use of technology (UTAUT) based on the application of the structural equation model with partial least squares structural equation modeling (PLS-SEM) estimation on data gathered through a Likert-based questionnaire disseminated among Italian risk managers. The survey reached 782 people working as risk professionals, but only 208 provided full responses. The final response rate was 26.59%.

The findings show that social influence, perception of external control and risk perception are the main predictors of risk professionals' intention to use artificial intelligence. Moreover, performance expectancy (PE) and effort expectancy (EE) of risk professionals in relation to technology implementation and use also appear to be reasonably reliable predictors.

Thus, the study offers a precious contribution to the debate on the impact of automation and disruptive technologies in the risk management domain. It complements extant studies by tapping into cultural issues surrounding risk management and focuses on the mostly overlooked dimension of individuals.

Yet, thanks to its quite novel theoretical approach; it also extends the field of studies on artificial intelligence acceptance by offering fresh insights into the perceptions of risk professionals and valuable practical and policymaking implications.

This paper aims to explore how the phenomena of corruption and fraud in the public sector have been portrayed in the literature using the Audit Society Framework (Power, 1997).

The authors conducted a structured literature review (Massaro et al., 2016) to unveil relevant literature in the area of corruption and fraud in the public sector.

Results highlight that the literature using “The Audit Society” theory is still scant. Notwithstanding the call for a more decisive role of auditors in fighting corruption and fraud, much is still to be discovered about consequences of auditing and what “good quality” is.

The main limitation is that only literature in English has been included.

This paper helps practitioners and policymakers to take and implement informed decisions with regards to the fight against fraud and corruption.

In calling for more research in the domain of audit, fraud and corruption in the public sector, this paper promotes a higher focus of society on public interest and the common good.

This paper investigates one part of The Audit Society related to corruption and fraud, topics that are still very underdeveloped and unexplored by researchers. From the findings the authors suggest possible new avenues for further research.

This study aims to examine the relationship between the attributes of audit firms (Big 4, audit fees, busy season, audit firm tenure and audit partner gender) and the impact of these attributes on key audit matters (KAM) readability in Malaysia.

The auditor's reports and financial data were analysed from a sample of FTSE 100 Malaysia-listed companies for the fiscal years 2017–2019, consisting of 258 observations. Panel regression analyses were conducted to evaluate the possible associations between audit firm attributes and KAM readability. The Flesch reading ease score and Coleman–Liau index were applied to measure KAM readability.

The findings show that female audit partners significantly impact KAM readability; further analysis also revealed that companies audited by Big 4 audit firms and higher audit fees tend to report a more readable KAM disclosure in the FTSE 100 in Malaysia.

The regression results provide empirical evidence of the influence of audit firm attributes on KAM readability. This study also examined important corporate governance players, such as external auditors and those charged with governance, who form the audit committee's qualities when analysing the determinants of KAM reporting variations in Malaysia.

This paper examines whether financial distress is associated with tax avoidance and whether the COVID-19 pandemic moderates such association.

The sample covers 38,958 firm-year observations from 32 countries during the period 2015–2020. Financial distress is measured using the ZSCORE by Altman (1968), while tax avoidance is based on the book-tax difference.

Financially distressed firms exhibit low tax avoidance pre- and during the pandemic periods. The authors find higher tax avoidance during the pandemic compared to the pre-pandemic period, but the pandemic enhances the negative relationship between financial distress and tax avoidance.

The study offers evidence on how financial distress drives firms to engage in more tax avoidance when firms globally encountered various levels of financial difficulty sparked by the economic challenges of the COVID-19 pandemic.

The findings provide insights to policymakers on the need to monitor and incentivise financially distressed firms, especially during economic challenges due to pandemic.

This study adds to the limited, albeit important, evidence on the joint effect of the COVID-19 pandemic and financial distress on tax avoidance.

The purpose of this study is to examine the relationship between auditing/non-auditing and accounting timeliness among Swedish private firms.

This paper uses regression analysis to test the relationship between auditing and two measurements of timeliness; lead time and late filing. The sample consists of Swedish private firms.

This paper finds that audited firms, when compared with unaudited firms, are significantly less timely. Moreover, greater profitability was associated with more timeliness but only for audited firms. The results of this paper also show that firms being audited by a big 4 auditor are significantly timelier than firms being audited by a non-big 4 auditor.

The findings in this paper suggests that one aspect of accounting quality, timeliness, does not seem to benefit from auditing in a Swedish context. There is a debate about whether the threshold levels in Sweden should be raised so that more firms voluntarily can opt out of audit. Those opposing a raised threshold level claim that auditing has positive effects on accounting quality and consequently that a raised level would have adverse effects. The findings in this paper do not support such a claim.

Little is known about timeliness in private firms compared to public firms and this paper fills that void. Contrary to prior research, findings show that unaudited firms in a Swedish regulatory setting actually are timelier than their audited counterparts. This questions one of the (presumed) benefits of auditing and should stimulate more research on this issue.

The main objective of this study is to examine the impact of audit data analytics (ADA) on audit quality (AQ) and audit review continuity (ARC).

Using 452 CPAs in Thailand as samples, mail questionnaires were used and sent to collect the data. Descriptive analysis, correlation matrix and path analysis were used to analyze the data.

The results of this study indicated that audit data analytics had a positive impact on AQ and ARC. Cybersecurity, used as a moderator in this study, was found to be the interaction between ADA, AQ and review continuity.

Auditors and audit firms can consider using big data in their data analytics to improve AQ and ARC.

Resource advantage theory has been used in this study to explain the impact of ADA on AQ and ARC in Thailand.

This article aims to investigate the financial constraints and nonlinearity of farm size growth.

Farm size growth is measured with land, labor and output using data from the Farm Accountancy Data Network (FADN) for Hungary and Slovenia. A dynamic panel model is applied to assess financial constraints and nonlinearity of farm size growth.

Results show that, except for land in Slovenia and output in Hungary, liquidity constraints are less important for farm size growth than endogenous factors based on farm size growth expectations and steady farm size restructuring. Smaller farms are growing faster than larger ones. The hypothesis that a higher level of subsidies would increase farm size is not supported for Hungary. When farms reach a certain size, the land area of the largest farms increases. Farm debts in Hungary are linked with land growth and in Slovenia with output growth.

Further research on the impact of liquidity constraints and subsidies can be conducted at a disaggregate farm-type level to examine whether there is variability in the underlying interlinkages at the farm-type specialization level.

The implication that farm size growth is dependent on initial size and that smaller farms are growing faster than bigger ones indicates that it is not necessary to favor the fastest growing smaller farms thus supports the application of a non-discriminatory farm size policy for observing farm size structural changes.

The dynamic panel econometric model that incorporates cash flow as a measure of financial constraints provides insight into farm size growth in cross-country comparison in relation to potential farm liquidity constraints, farm debt and the nonlinearity of farm size, which information is of relevance to policy makers and practitioners.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

The purpose of this study is to examine the relationship between the corporate social responsibility (CSR) performance of job-hopping executives at their former and subsequent firms.

We conduct regression analyses using a sample of firms listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2020 to examine whether CSR performance is similar from one firm to the next as executives switch jobs.

We find a positive relationship between the CSR performance of former and subsequent firms under job-hopping executives. This relationship is the strongest in the year of the job switch; it weakens in the second year and eventually disappears in the third year. In addition, we show that this relationship benefits different CSR stakeholder groups and is contingent on executive and subsequent firm attributes and job-hopping characteristics. Furthermore, we demonstrate that firms that hire a new chief executive officer from a firm with a strong track record in CSR, the new firm experiences a significant surge in CSR performance compared with firms that do not experience such a shock.

This study has implications for executive hiring decisions.

This study extends the understanding of CSR determinants through the lens of inter-organisational ties associated with job-hopping executives.