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Approaches to solving sustainability problems require a specific problem-solving mode, encompassing the complexity, fuzziness and interdisciplinary nature of the problem. This paper aims to promote a complex systems’ view of addressing sustainability problems, in particular through the tool of network science, and provides an outline of an interdisciplinary training workshop.

The topic of the workshop is the analysis of the Sustainable Development Goals (SDGs) as a political action plan. The authors are interested in the synergies and trade-offs between the goals, which are investigated through the structure of the underlying network. The authors use a teaching approach aligned with sustainable education and transformative learning.

Methodologies from network science are experienced as valuable tools to familiarise students with complexity and to handle the proposed case study.

To the best of the authors’ knowledge, this is the first work which uses network terminology and approaches to teach sustainability problems. This work highlights the potential of network science in sustainability education and contributes to accessible material.

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.