References
Armstrong, J. S., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396–402. https://doi.org/10.2307/3150783 Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022- 3514.51.6.1173 Becker, G. S. (1968). Crime and punishment: An economic approach. Journal of Political Economy, 76(2), 169–217. https://doi.org/10.1086/259394 Buczak, A. L., & Guven, E. (2016). A survey of data mining and machine learning methods for cyber security intrusion detection. IEEE Communications Surveys & Tutorials, 18(2), 1153–1176. https://doi.org/10.1109/COMST.2015.2494502 Casey, E. (2011). Digital evidence and computer crime: Forensic science, computers, and the Internet (3rd ed.). Academic Press. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Lawrence Erlbaum Associates. Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44(4), 588–608. https://doi.org/10.2307/2094589 Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications. Cybersecurity Ventures. (2023). Cybercrime to cost the world $8 trillion in 2023. Cybersecurity Ventures Annual Report. https://cybersecurityventures.com Dilek, S., Cakir, H., & Aydin, M. (2015). Applications of artificial intelligence techniques to combating cyber crimes: A review. International Journal of Artificial Intelligence & Applications, 6(1), 21–39. https://doi.org/10.5121/ijaia.2015.6102 Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An ethical framework for a good AI society. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5 Garfinkel, S. L. (2010). Digital forensics research: The next 10 years. Digital Investigation, 7(Suppl.), S64–S73. https://doi.org/10.1016/j.diin.2010.05.009 GSMA. (2022). The mobile economy: Sub-Saharan Africa 2022. GSM Association. https://www.gsma.com/mobileeconomy/sub-saharan-africa Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning. Hayes, A. F., & Cai, L. (2007). Using heteroscedasticity-consistent standard error estimators in OLS regression. Behavior Research Methods, 39(4), 709–722. https://doi.org/10.3758/BF03192961 International Telecommunication Union. (2023). Measuring digital development: Facts and figures 2023. ITU Publications. https://www.itu.int Milgrom, P., & Roberts, J. (1990). The economics of modern manufacturing: Technology, strategy, and organization. American Economic Review, 80(3), 511–528. National Institute of Standards and Technology. (2018). Framework for improving critical infrastructure cybersecurity, Version 1.1. https://doi.org/10.6028/NIST.CSWP.04162018 Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill. Pratt, T. C., Holtfreter, K., & Reisig, M. D. (2010). Routine online activity theory and internet fraud targeting. Journal of Research in Crime and Delinquency, 47(3), 267–296. https://doi.org/10.1177/0022427810365903 Quick, D., & Choo, K. R. (2014). Impacts of increasing volume of digital forensic data: A survey and future research challenges. Digital Investigation, 11(4), 273–294. https://doi.org/10.1016/j.diin.2014.09.002 Scientific Working Group on Digital Evidence. (2014). SWGDE core competencies for digital and multimedia evidence examiners. SWGDE. Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290–312. https://doi.org/10.2307/270723 Sommer, R., & Paxson, V. (2010). Outside the closed world: On using machine learning for network intrusion detection. Proceedings IEEE Symposium on Security and Privacy, 305– 316. https://doi.org/10.1109/SP.2010.25 Taddeo, M., McCutcheon, T., & Floridi, L. (2019). Trusting artificial intelligence in cybersecurity is a double-edged sword. Nature Machine Intelligence, 1(12), 557–560. https://doi.org/10.1038/s42256-019-0109-1 Von Solms, R., & Van Niekerk, J. (2013). From information security to cyber security. Computers & Security, 38, 97–102. https://doi.org/10.1016/j.cose.2013.04.004 Wall, D. S. (2007). Cybercrime: The transformation of crime in the information age. Polity Press. Yamane, T. (1967). Statistics: An introductory analysis (2nd ed.). Harper & Row. Yar, M. (2005). The novelty of 'cybercrime': An assessment in light of routine activity theory. European Journal of Criminology, 2(4), 407–427. https://doi.org/10.1177/147737080556056
