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Economic geographies of the illegal: the multiscalar production of cybercrime

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Abstract

Economic geographers have traditionally been reluctant to extend their analysis to illicit and illegal markets despite their being significant in their global economic extent and displaying highly uneven geographies. By contrast, the geographies of licit, legal industries have produced multiple traditions of empirically rich, theoretically diverse accounts. Our understandings of the spatialities of illicit and illegal ‘industries’ derive from a different set of intellectual traditions for whom space is a less explicit, central concern. This paper aims to advance our understanding of the geographies of illegal economic activities by exploring the spatialities of one illegal industry, cybercrime (online for-profit fraud), through the lens of economic geography. It considers the spaces within which cybercrime is embedded, exploring it as the product of factors operating at multiple scales. It reviews cybercrime scholarship focused, variously, at the local, national and transnational scales and examines factors salient to the production of cybercrime through case studies at these scales. It examines national level drivers of cybercrime, local cybercrime agglomerations in Europe and transnational asymmetries, connections and opacities and the production of cybercrime. In each case, it reflects upon the potentials for the development of more spatially informed readings of cybercrime specifically, and illegal economic activities more generally, and considers how this might be mobilised to inform anti-cybercrime policy. The paper speaks to both theme I of this special edition ‘the interactions, the norms, the rituals, the behaviours of OCGs in physical spaces’ and theme III ‘the interactions between OCGs and institutions such as the political and economic field’.

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Authors and Affiliations

  1. Faculty of Humanities and Social Sciences, University of Winchester, Winchester, UK

    Tim Hall

  2. Department of Digital Futures, University of Winchester, Winchester, UK

    Ben Sanders

  3. Department of Accounting, Finance, Mathematics and Economics, University of Winchester, Winchester, UK

    Mamadou Bah

  4. School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK

    Owen King

  5. Department of Geography, Faculty of Arts and Social Sciences, The Open University, Milton Keynes, UK

    Edward Wigley

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Additional information

1. Recent history of economic transition / liberalisation: Macroeconomic stability at pillar level. World Economic Forum, (WEF) Global Competitiveness Report (GCR), 2018.

2. Economic uncertainty / downturn: World Uncertainty Index, year average for 2018.

3. Poverty / lack of opportunities in legitimate economy (particularly affecting young people with IT skills): World Bank Unemployment with Advanced Education (% of total labour force with advanced education. 2017 (Nigeria 2016, Ghana 2015).

4. Blurring of licit and illicit economic practices: International Labour Organization Women and Men in the Informal Economy: A Statistical Picture, Share of informal employment in non-agricultural employment by urban location (2018).

5. Unbalanced economy / revenues inaccessible to the majority: Legatum Prosperity Index, 2018. (% of the population living below the national poverty lines).

6. High levels of education: Quality of math and science education from WEF Global Information Technology Report (GITR), 2016.

7. IT literacy / skills amongst young people: Digital skills amongst among population. WEF GCR, 2018.

8. Normative influence of consumerism / materialism: Post-materialist Index (4 item), World Values Survey, 2010-2014.

9. High internet penetration: WEF GITR, 2018. Internet users as a % of population.

10. Appropriate technical infrastructure: WEF GITR, 2018 3rd pillar infrastructure score.

11. High levels of corruption: Transparency International Corruption Perception Index, 2018.

12. State and institutional weakness: World Bank World Governance Indicators - Rule of law 2018.

13. Government indifference towards cybercrime / not a government priority: ITU Global Cybersecurity Index, 2017.

14. Internal legal and regulatory shortcomings: WEF GITR, 2016 – 1st pillar ‘Political and regulatory environment’.

15. Traditions of illicitness / normative influence of gangsterism: Legatum Prosperity Index, 2018 (Social capital pillar)

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National predictors of cybercrime – statistical sources.

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Hall, T., Sanders, B., Bah, M. et al. Economic geographies of the illegal: the multiscalar production of cybercrime. Trends Organ Crim 24, 282–307 (2021). https://doi.org/10.1007/s12117-020-09392-w

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