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This study aims to contribute to the existing literature by empirically investigating the impact of digital competitiveness and technology on corruption under the moderating effect of some cultural and economic control variables and providing evidence on the links between corruption and various cultural dimensions at the country level.

The cross-sectional sample covers 61 countries (41 high-income and 20 lower-income countries) during the 2016–2020 period, and the analysis was carried out for both the full sample and the subsamples.

The results provide clear evidence supporting the hypothesis that digitalisation and technology significantly affect the perceived level of corruption under the moderating role of cultural framework and economic development. Furthermore, the most significant cultural dimensions of corruption are individualism versus collectivism, uncertainty avoidance, long-term orientation and indulgence versus restraint, even if, in some cases, its influence might be felt differently when the results are estimated on subsamples. Thus, in the case of indulgence versus restraint, high-income countries with higher indulgence scores would register higher scores for the corruption perception index and thus a better control of corruption, while for lower-income countries, the more indulgent these countries are, the weaker the corruption control will be. Furthermore, our results validate a powerful and significant correlation between the index of economic freedom and corruption in both digitalisation and technology.

This study may have relevant implications for policymakers who need to recognise the role of digitalisation and technology in the fight against corruption but considering the cultural and economic characteristics specific to each country.

To the authors' knowledge, the relationship between digital competitiveness, technology and corruption within an economic and cultural framework, while highlighting the differences between high-income and lower-income countries, has not been previously documented in the literature. Thus, this article argues that the level of digital competitiveness and the adoption of technology would significantly impact the level of perceived corruption, although this impact could be felt differently by countries in the high-income category compared to countries in the lower-level income category.

The purpose of this study is to provide a detailed demonstration of how artificial intelligence (AI) can be used to potentially generate valuable insights and recommendations regarding the role of accounting in addressing key sustainability-related issues.

The study offers a novel method for leveraging AI tools to augment traditional scoping study techniques. The method was used to show how the authors can produce recommendations for potentially enhancing organisational accountability pertaining to seasonal workers.

Through the use of AI and informed by the knowledge base that the authors created, the authors have developed prescriptions that have the potential to advance the interests of seasonal workers. In doing so, the authors have focussed on developing a useful and detailed guide to assist their colleagues to apply AI to various research questions.

This study demonstrates the ability of AI to assist researchers in efficiently finding solutions to social problems. By augmenting traditional scoping study techniques with AI tools, the authors present a framework to assist future research in such areas as accounting and accountability.