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This study examines how bilateral international trade among mandatory International Financial Reporting Standards (IFRS) adopter countries moderates the relation between IFRS adoption and firms’ financial reporting quality.

The authors use data from 2007 to 2015 and focus on publicly listed firms from non-European Union countries that adopted IFRS on a mandatory basis.

The authors find that the interaction between mandatory IFRS adoption and a country’s bilateral trade with other countries using IFRS is negatively and significantly related to accruals-based earnings management, which is an inverse measure of financial reporting quality. This result is driven by firms in less developed countries. The improvement in accounting quality is for firms located in countries that both fully and partially adopt IFRS. The authors also find a significant and negative coefficient for the relation between real earnings management and the interaction between mandatory IFRS adoption and a country’s bilateral trade with other IFRS countries in the post-global financial crisis period.

Overall, the authors’ results are consistent with the notion that the mandatory adoption of IFRS creates a positive externality where firms improve their accounting quality because increased financial statement comparability means that foreign customers and suppliers can monitor the quality of earnings more easily.

Prior research on meeting or beating earnings thresholds documents that firms with earnings momentum are awarded with valuation premiums. However, it is unclear from this strand of literature why this is the case. Therefore, this study aims to investigate the effects of time-varying earnings persistence on earnings momentum and their pricing effects.

This study exploits a firm that reports earnings momentum as research setting to examine whether earnings persistence is significantly higher for firms with consecutive earnings increases. In addition, it investigates a relation between earnings momentum and fundamentals-driven earnings persistence and estimates return associations of earnings momentum conditional on economic-based persistence of earnings.

The empirical evidence suggests that firms with earnings momentum reflect higher time-varying earnings persistence. It further reveals that longer duration of earnings momentum is associated with higher fundamentals-driven earnings persistence. More importantly, valuation premiums are exclusively assigned to earnings momentum determined by strong firm fundamentals, not momentum itself.

This study provides new empirical evidence that valuation premiums accrued to firms with earnings momentum are conditional on time-varying earnings persistence. The research implications are relevant to investors, regulators and auditors, as the results bring conclusions that earnings momentum reflects successful business models not poor accounting quality. This leads to a more complete view of earnings momentum and helps allocate resources when evaluating earnings-momentum firms.

The worldwide imposition of lockdown measures to control the 2020 coronavirus disease 2019 (COVID-19) outbreak has shifted most executive communications with external stakeholders online, resulting in quick responses from stakeholders. This study aims to understand how presentational styles exhibited in online communication induce immediate audience responses and empirically test the effectiveness of reactive impression management tactics.

The authors analyze presentational styles using MP3 files containing executive utterances during earnings call conferences held by S&P 100-listed firms after June 2020, the quarter after the World Health Organization declared the COVID-19 outbreak a pandemic on March 11, 2020. Using timestamps, the authors link each utterance to a 1-minute interval change in the ask/bid prices of the stocks that occurs a minute after the corresponding utterance begins.

Exhibiting an informational presentation style in earnings calls leads to positive and immediate audience responses. Managers tend to increase their reliance on promotional presentation styles rather than on informational ones when quarterly earnings exceed market forecasts.

Drawing on organizational genre theory, this research identifies the discrepancy between the presentation styles that audiences positively respond to and those that managers tend to exhibit in earnings calls and provides a reactive impression management typology for immediate responses from online audiences.

This study aims to examine the impact of culture on earnings management after changing to International Financial Reporting Standards (IFRS).

The study’s sample selection comprises all publicly listed firms in 25 countries between 2000 and 2017 from DataStream database with cultural dimensions ratings from Hofstede et al. (2010). The initial sample contained 2,451 firms.

This study provides evidence that the interaction between national culture and IFRS adoption remains influential in explaining differences in the magnitude of earnings management behavior across countries.

This study higlights how IFRS and the cultural values interact with each other and affect earnings quality. In particular, the authors provide evidence on the relationship between individualism, uncertainty avoidance, power distance and masculinity of national culture and earnings management and, primarily, find that national culture significantly influences the decisions of managers after adopting IFRS.

Companies avoid taxes in a variety of ways and use different methods to do that, one of the most common being earnings management. The purpose of this paper is to investigate whether companies manipulate their financial data in order to reduce taxes paid.

We considered a sample of 63 listed Romanian companies for the period 2016–2021. The Beneish model was used for estimating earnings management, and the effective tax rate was used to measure tax avoidance. The analysis was carried out using regression analysis in Stata13 software.

The findings of the research indicate a negative and statistically significant association between effective tax rate and earnings management, implying that one of the main reasons why companies manipulate their earnings to reduce tax burden and avoid taxes. Moreover, our results show that return on assets (ROA) has a statistically significant negative influence on the effective tax rate. Furthermore, our analysis reveals that firm size, growth, and Big4 audit have no effect on effective tax rate.

Because it analyzes concrete cases using financial data and provides some recommendations for addressing the issue of tax avoidance, this work is useful in advancing both quantitative and qualitative research on this topic. This research is relevant for businesses, governments, regulators, audit professionals and investors.

The study, by analyzing concrete cases using reported financial data, contributes in filling the gap within the literature that results from a lack of scientific research on the relationship between tax avoidance and earnings management, and then it clarifies the nature of the causal connection between them. Moreover, it considers a combination of firm related variables including performance, size and also audit quality.

The Covid-19 pandemic appears to have engendered heterogeneous effects on individuals’ labour market prospects. This paper focuses on two possible sources of a heterogeneous exposition to labour market risks associated with the pandemic outbreak: the routine task content of the job and the teleworkability. To evaluate whether these dimensions played a crucial role in amplifying employment and wage gaps among workers, we focus on the case of Italy, the first EU country hit by Covid-19.

Investigating the actual effect of the pandemic on workers employed in jobs with a different degree of teleworkability and routinization, using real microdata, is currently unfeasible. This is because longitudinal datasets collecting annual earnings and the detailed information about occupations needed to capture a job’s routine task content and teleworkability are not presently available. To simulate changes in the wage distribution for the year 2020, we have employed a static microsimulation model. This model is built on data from the Statistics on Income and Living Conditions (IT-SILC) survey, which has been enriched with administrative data and aligned with monthly observed labour market dynamics by industries and regions.

We measure the degree of job teleworkability and routinization with the teleworkability index (TWA) built by Sostero et al. (2020) and the routine-task-intensity index (RTI) developed by Cirillo et al. (2021), respectively. We find that RTI and TWA are negatively and positively associated with wages, respectively, and they are correlated with higher (respectively lower) risks of a large labour income drop due to the pandemic. Our evidence suggests that labour market risks related to the pandemic – and the associated new types of earnings inequality that may derive – are shaped by various factors (including TWA and RTI) instead of by a single dimension. However, differences in income drop risks for workers in jobs with varying degrees of teleworkability and routinization largely reduce when income support measures are considered, thus suggesting that the redistributive effect of the emergency measures implemented by the Italian government was rather effective.

No studies have so far investigated the effect of the pandemic on workers employed in jobs with a different degree of routinization and teleworkability in Italy. We thus investigate whether income drop risks in Italy in 2020 – before and after income support measures – differed among workers whose jobs are characterized by a different degree of RTI and TWA.

This study aims to investigate the influence of digital transformation on the overall financial performance of firms, with a specific focus on Chinese-listed companies from 2010 to 2021. It seeks to understand the impacts on various accounting and financial indicators in emerging economies such as China.

This study employs a text-mining approach to construct a digital transformation index based on the data sample of 11,814 firm-year observations from China’s A-share listed companies. This index serves as a proxy to measure the extent of digital transformation and its impact on financial performance and health.

The findings indicate that digital transformation significantly enhances overall financial performance and health, as evidenced by increased profitability, reduced operational costs, and lowered financial risks. The study reveals a time-lagged effect, where the benefits of digital transformation become more apparent after about one year. Further analysis shows that the value of digital transformation is more evident in a firm’s asset items. This raises the possibility of recognising the by-product, such as data resources, in the digital transformation process.

This research offers a unique contribution by linking digital transformation to financial performance using a large dataset from China's A-share listed firms. Doing so enhances our understanding of the tangible effects of digital transformation on corporate performance. Furthermore, this research provides valuable insights for the advancement of future accounting practices and the development of standards.

This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country.

By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020.

The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance.

Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized.

Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

Corporate site visits increase labor investment efficiency.

Our empirical model for the baseline analysis follows those of Jung et al. (2014) and Ghaly et al. (2020).

We show that corporate site visits are associated with significantly higher labor investment efficiency; more specifically, site visits reduce both over-hiring and under-hiring of employees. The effect of site visits on labor investment efficiency is more pronounced for firms with higher labor adjustment costs, greater financial constraints, weaker corporate governance and lower financial reporting quality. We also find that site visits mitigate labor cost stickiness.

First, while the literature has suggested how the presence of institutional investors and analysts may affect labor investment decisions, we focus on institutional investors and analysts’ activities and interactions with firm executives. We provide direct evidence that institutional investors and analysts may use corporate site visits to improve labor investment efficiency. Second, our study adds to a line of recent studies on how corporate site visits reduce information asymmetry and agency conflicts. We show that corporate site visits allow institutional investors and analysts to influence labor investment efficiency. We also provide new evidence that corporate site visits reduce labor cost stickiness.

This study empirically demonstrates a contradiction between pillar 3 of Basel norms III and the designation of Systemically Important Banks (SIBs), also known as Too Big to Fail (TBTF). The objective of this study is threefold, which has been approached in a phased manner. The first is to determine the systemic importance of the banks under study; second, to examine if market discipline exists at different levels of systemic importance of banks and lastly, to examine if the strength of market discipline varies at different levels of systemic importance.

This study is based on all the public and private sector banks operating in the Indian banking sector. The Gaussian Mixture Model algorithm has been utilized to classify banks into distinct levels of systemic importance. Thereafter, market discipline has been observed by analyzing depositors' sentiments toward banks' risk (CAMEL indicators). The analysis has been performed by employing the system Generalized Method of Moments (GMM) to estimate models with different dependent variables.

The findings affirm the existence of market discipline across all levels of systemic importance. However, the strength of market discipline varies with the systemic importance of the banks, with weak market discipline being a negative externality of the SIBs designation.

By employing the Gaussian Mixture Model algorithm to develop a framework for categorizing banks on the basis of their systemic importance, this study is the first to go beyond the conventional method as outlined by the Reserve Bank of India (RBI).