Abstract
Digital transformation refers to the change in all aspects of human society by the adoption of digital technologies. Different methodologies and measurements have been proposed to determine the level of digital transformation in regions or countries. In this work, we propose the creation of a digital transformation index for Mexican households using machine learning models for digital transformation measurement analysis and estimation. We include three dimensions in terms of the information and communication technologies infrastructure, availability of services, and usage. We also use a public dataset from the Mexican government to build and train three machine learning models. Experimental results validate that our methodology can deliver a digital transformation measurement using machine learning models consistently with \(84\%\) of accuracy and \(84\%\) of F1-score. We also prototype a simple web application using the best machine learning model found. We anticipate that measuring the digital transformation in companies, governments, and households allows better decisions in business intelligence and public policy.
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References
Baller, S., Dutta, S., Lanvin, B.: The Global Information Technology Report 2016. Innovating in the Digital Economy. World Economic Forum, 91–93 route de la Capite, CH-1223 Cologny/Geneva, Switzerland (2016)
Betancourt, G.A.: Las máquinas de soporte vectorial (svms). Scientia Et Technica (2005). https://www.redalyc.org/articulo.oa?id=84911698014
Bukht, R., Heeks, R.: Defining, conceptualising and measuring the digital economy. Dev. Inform. 1(68), 10–11 (2017)
Commission, E.: Digital economy and society index (desi) 2021 (2021). https://digital-strategy.ec.europa.eu/en/policies/desi. Accessed 11 June 2022
Heras, J.M.: Clustering (agrupamiento), k-means con ejemplos en python (2020). https://www.iartificial.net/clustering-agrupamiento-kmeans-ejemplos-en-python/. Accessed 11 June 2022
IBM: What is a decision tree? https://www.ibm.com/topics/decision-trees. Accessed 11 June 2022
INEGI: Nota sobre el cambio metodológico de la ENDUTIH (2020). https://www.inegi.org.mx/contenidos/programas/dutih/2020/doc/nota_tecnica_endutih_2020.pdf. Accessed 11 June 2022
Mishra, D., et al.: Digital Dividens, chap. Overview. The World Bank, 1818 H Street NW, Washington DC 20433 (2016)
Poland, E.: Digital transformation index (2020). https://www.ey.com/en_pl/technology/digital-transformation-index. Accessed 11 June 2020
Reinsdorf, M., Quirós, G., Group, S.: Measuring the digital economy. Policy Papers, pp. 9–11 (2018)
Sirimanne, S.N.: Digital economy report 2019. In: Value Creation and Capture: Implications for Developing Countries. 300 East 42nd Street, New York, New York 10017, USA (2019)
Technologies, D.: Measuring digital transformation progress around the world (2018). https://www.dell.com/en-us/dt/perspectives/digital-transformation-index.htm#scroll=off. Accessed 11 June 2022
Zaballos, A.G., Rodríguez, E.I.: Economía digital en América Latina y el Caribe. Situación actual y recomendaciones. Banco Interamericano de Desarrollo, 1300 New York Avenue, N.W. Washington, D.C. 20577 (2017)
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García, A., Salazar, V., Ponce, H. (2022). Machine Learning Model of Digital Transformation Index for Mexican Households. In: Pichardo Lagunas, O., Martínez-Miranda, J., Martínez Seis, B. (eds) Advances in Computational Intelligence. MICAI 2022. Lecture Notes in Computer Science(), vol 13613. Springer, Cham. https://doi.org/10.1007/978-3-031-19496-2_25
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DOI: https://doi.org/10.1007/978-3-031-19496-2_25
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