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Investigating antecedents that may affect the usage of electronic tax declaration platforms is not a new research topic. Nevertheless, investigating the antecedents that affect the continuance usage of these platforms beyond the COVID-19 pandemic is a relatively new research trend. Accordingly, the purpose of this study is to investigate the antecedent factors that directly influence electronic tax declaration platforms’ continuance usage in the post-pandemic era by integrating the Unified Theory of Acceptance and Use Technology Model with other related factors.

To achieve the main purpose of the study, an online questionnaire was used to gather data from 231 Jordanian taxpayers.

The findings revealed the positive and significant effects of performance expectancy, social influence, knowledge and trust in e-government services on continuance usage of electronic tax declaration platforms. Contrary to what is expected, effort expectancy is insignificant, and hence the related hypothesis (H2) was rejected.

The findings of current research provided theoretical and practical implications by using a well-established theoretical lens to investigate what factors affect the continuance usage of electronic tax declaration platforms within the context of a developing country, namely, Jordan.

The purpose of this study is to examine the effect of terrorist attacks on tax avoidance. Further, the authors identify the possible channel leading to our main result and examine the role of social pressure.

Data pertaining to terrorist attacks within the USA are procured from the Global Terrorism Database. The final sample consists of 45,524 firm-year observations from 1993 to 2017. The methodology uses ordinary least squares regressions.

The authors find that firms located in close proximity to terrorist attacks (i.e. impact firms) significantly decrease their tax avoidance practices after the attacks. The authors further find that these impact firms are willing to pay more taxes post attack when their headquarters are located in higher social capital regions.

Studies have mainly focused on the macroeconomic effects of terrorism, and only recently have researchers shifted their focus to firm-level impacts. The authors provide strong evidence that extends the second line of the literature by exploring corporate tax activities attributed to terrorist events.

This study aims to develop a maturity model designed for assessing the current state of digitization in accounting firms.

The authors have developed this index where the maturity levels are defined from the life cycle theory. For the items of a maturity measure, the authors have adopted a multimethodological approach. That approach allows to identify 27 measurement items to cover the three dimensions of audit, reporting and taxation.

This research proposes a diagnostic tool specific to accounting firms. The authors have tested this index in the Tunisian context. The results show that there are two types of accounting firms. This study found the first firm in the embryonic phase and the other in the growth phase. This points out the active role of Tunisian accounting firms in technology integration.

This study highlights the integration of technology in the accounting field. Specifically, it aims to address technology management in accounting firms by measuring the degree of digitization of accounting firms. This research projects the use of information technologies (artificial intelligence, cloud, big data, etc.) in auditing, reporting and taxation.

On a practical level, this research provides an organizational diagnostic tool to assess the status of their accounting firms in terms of digitization. This will motivate practitioners to make frequent assessments, thus contributing to continuous improvement toward digitization.

The theoretical foundation of this research is based on the theory of the life cycle of technologies. This study is using this theory to identify and describe the current phase of the organization. And that is by indicating the overall scores on the technological capabilities of the accounting firms.

This study aims to examine the Securities and Exchange Commission’s final rule in Modernization of Beneficial Ownership Reporting, which reduced the time for significant public company shareholders to file Schedule 13D (effective February 5, 2024). The authors corroborate prior results under the historic 10-day maximum reporting regime and provide updated academic analysis regarding how the five-day deadline between the “triggering” event, accumulating 5% of the outstanding shares and public disclosure of that event will affect abnormal returns.

This empirical archival study uses publicly available data.

The analyses show that changing from a 10-day to a 5-day Schedule 13 disclosure window will reduce activist investors’ opportunity to profit by legally delaying the filing of Schedule 13D. These excess returns for delay exist regardless of the profitability or size of the target firm or the shareholder’s disclosed reason for filing. The authors conclude that accelerating the timing of the disclosure window is an improvement that is in the best interest of the general investing public.

To the authors’ knowledge, this is the only academic study of Schedule 13D filings to include the postpandemic period. As such, the authors establish an updated “baseline projection” for expectations regarding how the Modernization final rule will impact activist investors and stock returns under a five-day reporting regime. In addition, the authors measure and test abnormal returns after considering differences between “triggering” events and filing dates of Schedule 13Ds in the sample rather than grouping all filings. This approach allows the authors to account for the time difference between the triggering event and the filing date.

This study uses a systematic review to explore the potential causes of previous findings related to e-government acceptance research. By identifying the most frequently used, best, promising or worst factors that affect the acceptance of e-government, this research presents a research agenda for e-government researchers.

Through conducting a systematic review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) procedure, this research first selected 109 papers. Subsequently, this research analyzed the predictors and linkages of e-government acceptance by adopting a weight-analysis method proposed by Jeyaraj et al. (2006).

The results first revealed the five most frequently used predictors and five best predictors of e-government acceptance at a comprehensive level. Furthermore, this study summarized the best predictors affecting the acceptance of e-government from the perspectives of adopter types and e-government stages. The results also illustrated the promising and the worst predictors influencing e-government acceptance.

The contribution of this research is twofold. First, this study identified the linkages between e-government acceptance at the individual and organizational levels and between different e-government development stages. Second, this research provided a research direction that could offer useful insights for future e-government studies.