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The purpose of this paper is to examine whether managers of bankrupt firms are more or less conditionally conservative in their financial reporting relative to non-bankrupt firms. The study further examines the cross-sectional differences in conditional conservatism among bankrupt and non-bankrupt firms.

The study employs a sample of US firms to investigate conditional conservatism in firms that experience financial distress and go bankrupt relative to non-stressed non-bankrupt firms. The study also uses switching regression models to identify the drivers of the cross-sectional difference in conditional conservatism among bankrupt and non-bankrupt firms.

Empirical results show that bankrupt firms are timelier in recognizing bad news than good news when compared to non-bankrupt firms. The higher level of conditional conservatism in bankrupt firms is mainly driven by their higher levels of leverage and tax-reduction incentives. The cross-sectional analyses show that these results largely hold for more leveraged firms and firms with higher tax costs. Taken together, these results suggest that the conservative tendency of managers of bankrupt firms can stem from the agency problem between lenders and managers and from tax-decreasing motivations.

The novelty of the authors’ research stands in studying the drivers of the cross-sectional differences in conditional conservatism between bankrupt and non-bankrupt firms and specifically, the demonstration that taxation also induces conditional conservatism in the setting of ex post bankrupt firms.

The present study seeks to shed further light on the effectiveness of Basu (1997) and Khan and Watts' (2009) differential timeliness metrics in detecting predictable differences in conservatism following corrections of restated earnings.

Using cross-sectional and time-series analyses for companies listed on the Tehran Stock Exchange during 2009–2013, the results indicate lower conservatism for restating firms as compared to their counterparts during prerestatement period.

Using cross-sectional and time-series analyses for companies listed on the Tehran Stock Exchange during 2009–2013, the results indicate lower conservatism for restating firms as compared to their counterparts during prerestatement period. In contrast, our findings are indicative of higher conservatism among these restating firms during the years of restatements. Moreover, the time-series approach captures a higher conservatism for the restating firms during restatement years than prerestatement periods. Overall, these results provide insight into the usefulness of the metrics used in the restatement setting.

Similar to recent papers, the present study seeks to shed further light on the ability of Basu-based coupled with Khan–Watts-based measures of conservatism to detect situations in which companies' earnings are known to be significantly restated.

CEOs’ (chief executive officer) term of office may explain discretionary accruals as a result of opportunistic behavior arising during certain periods of the term of office. Therefore, CEOs, in their early years of office, have incentives to report results that meet market expectations. In turn, CEOs in their senior year may be motivated to use discretionary accruals to gain private benefits. In this scenario, corporate governance mechanisms play an important role in monitoring relationships. Hence, the purpose of this study is to verify the influence of monitoring mechanisms on the relationship between CEOs’ term of office and discretionary accruals.

Descriptive statistics, multiple cross-sectional regression to estimate the accruals and regression of panel data to test the hypotheses were used. The sample comprised 195 companies listed on BM&FBovespa.

The results indicated that CEOs’ long term of office has a negative impact on the level of discretionary accruals, and thus, Brazilian CEOs with a longer term of office tend to establish a certain reputation in the stock market. On the other hand, it is concluded that CEOs’ intentions, in the first years of term, are positively related to the use of accruals and that the monitoring mechanisms can minimize these CEOs’ opportunistic practices.

The results broaden the literature on corporate governance, pointing that different systems of variable remuneration may influence CEOs’ willingness to manage results in their last year of term.

The purpose of this paper is to examine the impact of debt maturity structure and types of institutional ownership on accounting conservatism by using different financial variables and proxies.

Employing panel data analysis in the R programming language, the authors test their hypotheses on a sample of 143 (858 firm-year observations) companies listed on the Tehran Stock Exchange during 2011–2016.

Using Basu (1997) and Beaver and Ryan (2000) models as proxies for accounting conservatism, the findings suggest a non-significant relationship between accounting conservatism and debt maturity structure. Contrary to the primary expectation, the results indicate that short-maturity debts are also non-significantly and negatively associated with accounting conservatism in financially distressed firms. Finally, using both conservatism measures, the authors document that there is no significant relationship between both active and passive institutional ownership and accounting conservatism as well as debt maturity structure.

The current study is the first study conducted in a developing country like Iran, and the outcomes of the study may be helpful to other developing nations.

The purpose of this paper is to achieve effective governance of online rumors through the proposed rumor propagation model and immunization strategy.

The paper leverages the agent-based modeling (ABM) method to model individuals from two aspects, behavior and attitude. Based on the analysis and research of online data, we propose a rumor propagation model, namely the Untouched view transmit removed-Susceptible hesitate agree disagree (Unite-Shad), and devise an immunization strategy, namely the Gravity Immunization Strategy (GIS). A graph-based framework, namely Pregel, is used to carry out the rumor propagation simulation experiments. Through the experiments, the rationality of the Unite-Shad and the effectiveness of the GIS are verified.

The study discovers that the inconsistency between human behaviors and attitudes in rumor propagation can be explained by the Unite-shad model. Besides, the GIS, which shows better performance in small-world networks than in scale-free networks, can effectively suppress rumor propagation in the early stage.

This paper provides an effective immunization strategy for rumor governance. Specifically, the Unite-Shad model reveals the mechanism of rumor propagation, and the GIS provides an effective governance method for selecting immune nodes.

The inconsistency of human behaviors and attitudes in real scenes is modeled in the Unite-Shad model. Combined with the model, the definition of diffusion domain is proposed and a novel immunization strategy, namely GIS, is designed, which is significant for the social governance of rumor propagation.

This research explores the spillovers and portfolio implications for green bonds and environmental, social and governance (ESG) assets in the context of the rapidly expanding trend in green finance investments and the need for a green recovery in the post-COVID-19 era.

This study utilizes Diebold and Yilmaz’s (2014) spillover method and portfolio strategies (hedge ratio, optimal weights and hedging effectiveness) for the data starting from February 29, 2012, to March 14, 2022.

The study’s findings reveal that the lower volatility spillover is evidenced between the green bonds and ESG stocks during tranquil and turbulent periods (e.g. COVID-19 and Russia-Ukraine War). Furthermore, hedging costs are lower both in normal times and during economic slumps. Investing the bulk of the funds in green bonds makes it possible to achieve maximum hedging effectiveness between the S&P green bond (GB) and the S&P 500 ESG.

Both investors and policymakers may use these findings to make wise investment and policy choices to achieve post-COVID environmental sustainability.

Unlike previous research, this is the first to explore the interconnectedness among the major global and country-specific green bonds and ESG assets. The major findings of this study about the lower volatility spillovers and hedging costs between green bonds and ESG assets during the tranquil and turbulent periods may contribute to the post-COVID investment portfolio for environmental sustainability.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.