Driving SME Digital Transformation in Colombia: Analyzing Key Factors and Sustainable Development Goals (SDGs) Impact
DOI:
https://doi.org/10.4067/s0718-27242025000300059Keywords:
digitalization, SMEs, Artificial Neural Networks, Sustainable Development Goals, e-commerce, digital investmentAbstract
This study identifies key factors influencing digitalization investment decisions in Colombian SMEs and their alignment with Sustainable Development Goals (SDGs). Analyzing 4,600 surveys from 2023, we employed multilayer perceptron Artificial Neural Networks with backpropagation algorithms for predictive modeling, supported by validation through confusion matrices and ROC curves (average AUC: 0.94). Results revealed the most significant predictors: understanding digitalization's possibilities and advantages (20.87%), employees using ICT (14.77%), average workforce size (10.68%), and e-commerce marketplace participation (7.32%). The study's originality lies in precisely quantifying each factor's relative importance, providing an empirical foundation for prioritizing digitalization initiatives, and analyzing strategic alignment with SDGs, particularly SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 12 (Responsible Consumption and Production). These methodologically robust findings offer valuable guidance for policymaking, business strategies, and interdisciplinary theoretical frameworks promoting sustainable digital transformation of Colombian SMEs within broader socioeconomic contexts, while addressing critical technological adoption barriers, enhancing regional competitive advantage, and establishing comprehensive implementation pathways for digital ecosystem development. These insights directly inform practical digitalization policies for SMEs by providing evidence-based prioritization of educational initiatives over direct technology investments, with significant implications for sustainable development and competitive advantage in emerging economies.
Downloads
References
Alam, K., Ali, M. A., Erdiaw-Kwasie, M. O., Murray, P. A., & Wiesner, R. (2022). Digital transformation among SMEs: Does gender matter? Sustainability, 14(1), 535. https://doi.org/10.3390/su14010535
Anggraini, W., & Pranggono, B. (2022). Assessing digital readiness of small medium enterprises: intelligent dashboard decision support system. International Journal of Advanced Computer Science and Applications, 13(4).
Ardolino, M., Rapaccini, M., Saccani, N., Gaiardelli, P., Crespi, G., & Ruggeri, C. (2021). The role of digital technologies for the service transformation of industrial companies. International Journal of Production Research, 59(7), 2083-2107. https://doi.org/10.1080/00207543.2017.1324224
Barba-Sánchez, V., Martínez-Ruiz, M. P., & Jiménez-Zarco, A. I. (2019). Drivers, benefits and challenges of ICT adoption by small and medium sized enterprises (SMEs): A literature review. Problems and Perspectives in Management, 17(1), 20-34.
Becerra, J., Cotino-Hueso, L., León, I. P., Sánchez-Acevedo, M. E., Torres-Ávila, J., & Velandia-Vega, J. (2018). Derecho y big data. Universidad Católica de Colombia. https://publicacionesucatolica.publica.la/library/publication/derecho-y-big-data-1709929412
Bhuiyan, J., Asma, B., & Bhowmik, S. C. (2024). Digital procurement practices in SMES: Comparative cases of advanced and emerging economies. International Journal of Science and Technology Research Archive.
Bouwman, H., Nikou, S., & de Reuver, M. (2019). Digitalization, business models, and SMEs: How do business model innovation practices improve performance of digitalizing SMEs? Telecommunications Policy, 43(9), 101828. https://doi.org/10.1016/j.telpol.2019.101828
Bradley, A. P. (1997). The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition, 30(7), 1145-1159. https://doi.org/10.1016/S0031-3203(96)00142-2
Caloffi, A., Freo, M., Ghinoi, S., Rossi, F., & Russo, M. (2019). Is a policy mix more effective than individual policies for SME innovation? An exploratory analysis. fteval Journal for Research and Technology Policy Evaluation, (47), 72-77.
Caputo, F., Cillo, V., Candelo, E., & Liu, Y. (2019). The impact of digital transformation on the workforce: A framework for managing and developing human resources. In International Conference on Technology, Innovation, and Entrepreneurship (pp. 1-10). Springer.
Cenamor, J., Parida, V., & Wincent, J. (2019). How entrepreneurial SMEs compete through digital platforms: The roles of digital platform capability, network capability and ambidexterity. Journal of Business Research, 100, 196-206. https://doi.org/10.1016/j.jbusres.2019.03.035
Chatterjee, S., Chaudhuri, R., Vrontis, D., & Thrassou, A. (2022). SME entrepreneurship and digitalization–the potentialities and moderating role of demographic factors. Technological Forecasting and Social Change, 179, 121648. https://doi.org/10.1016/j.techfore.2022.121648
Chawla, N. V., Bowyer, K. W., Hall, L. O., & Kegelmeyer, W. P. (2002). SMOTE: Synthetic minority over-sampling technique. Journal of Artificial Intelligence Research, 16, 321-357. https://doi.org/10.1613/jair.953
Choi, S. B., Kim, W. J., Yoo, T. K., Park, J. S., Chung, J. W., Lee, Y. H., ... & Kim, D. W. (2014). Screening for prediabetes using machine learning models. Computational and mathematical methods in medicine, 2014(1), 618976. https://doi.org/10.1155/2014/618976
Clemente-Almendros, J. A., Nicoara-Popescu, D., & Pastor-Sanz, I. (2024). Digital transformation in SMEs: Understanding its determinants and size heterogeneity. Technology in Society, 77, 102483. https://doi.org/10.1016/j.techsoc.2024.102483
Díaz Rodríguez, H. E., Sosa Castro, M. M., & Cabello Rosales, M. A. (2019). Financial performance and administrative practices in Mexican microenterprises: An analysis with artificial neural networks. Contaduría y administración, 64(3). https://doi.org/10.22201/fca.24488410e.2018.1622
Dörr, L., Fliege, K., Lehmann, C., Kanbach, D. K., & Kraus, S. (2023). A taxonomy on influencing factors towards digital transformation in SMEs. Journal of Small Business Strategy, 33(1), 53-69. https://doi.org/10.53703/001c.66283
Duran, J., & Castillo, R. (2023). Factors related to information and communication technologies adoption in small businesses in Colombia. Journal of Innovation and Entrepreneurship, 12(1), 55.
Eller, R., Alford, P., Kallmünzer, A., & Peters, M. (2020). Antecedents, consequences, and challenges of small and medium-sized enterprise digitalization. Journal of Business Research, 112, 119-127. https://doi.org/10.1016/j.jbusres.2020.03.004
Fareri, S., Tjahjono, B., & Koliousis, I. (2019). Unlocking the potential of digital transformation in manufacturing SMEs. Journal of Manufacturing Technology Management, 31(2), 226-248.
Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861-874. https://doi.org/10.1016/j.patrec.2005.10.010
Frau, M., Moi, L., & Cabiddu, F. (2022). Digital transformation through the lens of digital data handling: an exploratory analysis of agri-food SMEs. Journal of Small Business Strategy, 32(3), 84-97. https://doi.org/10.53703/001c.34642
Gašperlin, B., Pucihar, A., & Kljajić Borštnar, M. (2021). Influencing factors of digital transformation in SMEs–literature review. In Proceedings of the 40th International Conference on Organizational Science Development: Values, Competencies and Changes in Organizations (pp. 231-244).
Géron, A. (2022). Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. " O'Reilly Media, Inc.".
Ghobakhloo, M., Iranmanesh, M., Grybauskas, A., Vilkas, M., & Petraitė, M. (2021). Industry 4.0, innovation, and sustainable development: A systematic review and a roadmap to sustainable innovation. Business Strategy and the Environment, 30(8), 3211-3231. https://doi.org/10.1002/bse.2867
Gómez, J. A. U. (2021). El índice global de innovación en Colombia: un análisis y selección de los factores destacados mediante el uso de redes neuronales artificiales. Contaduría y administración, 66(4), 10. https://doi.org/10.22201/fca.24488410e.2021.2871
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
Gutiérrez Labrador, J. C., Pérez Ones, O., & Zumalacárregui de Cárdenas, L. (2021). Redes neuronales artificiales para estimar propiedades físicas, termodinámicas y de equilibrio de mezclas etanol-agua. Revista Universidad y Sociedad, 13(6), 514-525.
Hastie, T., Tibshirani, R., Friedman, J. H., & Friedman, J. H. (2009). The elements of statistical learning: data mining, inference, and prediction (Vol. 2, pp. 1-758). New York: springer. https://doi.org/10.1007/978-0-387-21606-5
Holl, A., & Rama, R. (2024). Spatial patterns and drivers of SME digitalisation. Journal of the Knowledge Economy, 15(2), 5625-5649. https://doi.org/10.1007/s13132-023-01257-1
Huang, S., Han, F., & Chen, L. (2023). Can the digital economy promote the upgrading of urban environmental quality?. International Journal of Environmental Research and Public Health, 20(3), 2243. https://doi.org/10.3390/ijerph20032243
Kulathunga, K. M. M. C. B., Ye, J., Sharma, S., & Weerathunga, P. R. (2020). How does technological and financial literacy influence SME performance: Mediating role of ERM practices. Information, 11(6), 297. https://doi.org/10.3390/info11060297
Lee, C. Y., Wen, C. R., & Thi-Thanh-Nguyen, B. (2024). Board expertise background and firm performance. International Journal of Financial Studies, 12(1), 17. https://doi.org/10.3390/ijfs12010017
Li, L., Su, F., Zhang, W., & Mao, J. Y. (2018). Digital transformation by SME entrepreneurs: A capability perspective. Information Systems Journal, 28(6), 1129-1157. https://doi.org/10.1111/isj.12153
Lokuge, S., & Duan, S. X. (2023). Exploring the enablers of digital transformation in small and medium-sized enterprises. Handbook of research on business model innovation through disruption and digitalization, 136-156.
Lousã, E. (2020). Comparing the effects of leadership and organizational culture on innovation in technology-based organizations and other industries. IBIMA Business Review, Vol. 2020. https://doi.org/10.5171/2020.315185
Mia, M. A., Hossain, M. I., & Sangwan, S. (2024). Determinants of digitalization: Evidence from Asia and the Pacific countries. Digital Transformation and Society, (ahead-of-print).
Mohammadi, F., Teiri, H., Hajizadeh, Y., Abdolahnejad, A., & Ebrahimi, A. (2024). Prediction of atmospheric PM2. 5 level by machine learning techniques in Isfahan, Iran. Scientific Reports, 14(1), 2109. https://doi.org/10.1038/s41598-024-52617-z
Okfalisa, O., Anggraini, W., Nawanir, G., Saktioto, S., & Wong, K. Y. (2021). Measuring the effects of different factors influencing on the readiness of SMEs towards digitalization: A multiple perspectives design of decision support system. Decision Science Letters, 10(3), 425-442.
Omrani, N., Rejeb, N., Maalaoui, A., Dabić, M., & Kraus, S. (2022). Drivers of digital transformation in SMEs. IEEE Transactions on Engineering Management. https://doi.org/ 10.1109/TEM.2022.3215727
Packmohr, S., Paul, F. H., & Brink, H. (2024). Considering company size, level of responsibility, and employee age for analysing countermeasures against barriers to digital transformation. Journal of Telecommunications and the Digital Economy, 12(1), 172-195. https://doi.org/10.3316/informit.T2024040300009601537672089
Papadopoulos, T., Baltas, K. N., & Balta, M. E. (2020). The use of digital technologies by small and medium enterprises during COVID-19: Implications for theory and practice. International Journal of Information Management, 55, 102192. https://doi.org/10.1016/j.ijinfomgt.2020.102192
Philbin, S., Viswanathan, R., & Telukdarie, A. (2022). Understanding how digital transformation can enable SMEs to achieve sustainable development: A systematic literature review. Small Business International Review, 6(1), e473.
Plečko, S., Tominc, P., & Širec, K. (2023). Digitalization in Entrepreneurship: Unveiling the Motivational and Demographic Influences towards Sustainable Digital Sales Strategies. Sustainability, 15(23), 16150. https://doi.org/10.3390/su152316150
Puyol, J. M. (2014). Una aproximación a Big Data. Revista de Derecho UNED, 14, 471-506.
Romo, J. F. M., & Muñoz, J. M. (2021). Predicción de efectos fisiológicos causados por el estrés académico mediante redes neuronales artificiales. Revista Iberoamericana de Psicología, 14(3), 25-37. https://doi.org/10.33881/2027-1786.rip.14303
Rupeika-Apoga, R., & Petrovska, K. (2022). Barriers to sustainable digital transformation in micro-, small-, and medium-sized enterprises. Sustainability, 14(20), 13558. https://doi.org/10.3390/su142013558
Rusly, F. H., Talib, Y. Y. A., Hussin, M. R. A., & Abd Mutalib, H. (2021). Modelling the Internal Forces of SMEs digital adaptation strategy towards industry Revolution 4.0. Polish Journal of Management Studies, 24(1), 306-321. https://doi.org/10.17512/pjms.2021.24.1.18
Sadati, S. H., Kaklar, J. A., & Ghajar, R. (2011). Application of artificial neural networks in the estimation of mechanical properties of materials. Artificial Neural Networks ͳ Industrial and Control Engineering Applications, 117.
Salcedo, L. O. G., Zúñiga, A. P. G., Arjona, S. D., & Will, A. L. E. (2017). Redes neuronales artificiales para estimar propiedades en estado fresco y endurecido, para hormigones reforzados con fibras metálicas. Cuaderno activa, 9, 95-107. https://doi.org/10.53995/20278101.423
Sándor, Á., & Gubán, Á. (2021). A measuring tool for the digital maturity of small and medium-sized enterprises. Management and Production Engineering Review, 14.
Schmitt, C., & Baldegger, R. (2020). Digitalization and internationalization. Technology Innovation Management Review, 10(4), 3-4.
Sharabati, A. A. A., Ali, A. A. A., Allahham, M. I., Hussein, A. A., Alheet, A. F., & Mohammad, A. S. (2024). The Impact of Digital Marketing on the Performance of SMEs: An Analytical Study in Light of Modern Digital Transformations. Sustainability, 16(19), 8667.
Silva, J., Hernandez, L., Hernandez, A. E., Varela, N., Palma, H. H., Bilbao, O. R., & Guliany, J. G. (2020). Measuring the financial performance of MSMEs through artificial neural networks. In International Conference on Communication, Computing and Electronics Systems (pp. 185-192). Springer. https://doi.org/10.1007/978-981-15-2612-1_17
Srivastava, N., Hinton, G., Krizhevsky, A., Sutsever, I., & Salakhutdinov, R. (2014). Dropout: a simple way to prevent neural networks from overfitting. The Journal of Machine Learning Research, 15(1), 1929-1958. https://doi.org/10.5555/2627435.2670313
Stephenson, M., Hamid, M. F. S., Peter, A., Sauvant, K. P., Seric, A., & Tajoli, L. (2021). More and better investment now! How unlocking sustainable and digital investment flows can help achieve the SDGs. Journal of International Business Policy, 4(1), 152.
Sudirman, I. D., Astuty, E., & Aryanto, R. (2025). Enhancing Digital Technology Adoption in SMEs Through Sustainable Resilience Strategy: Examining the Role of Entrepreneurial Orientation and Competencies. Journal of Small Business Strategy, 35(1), 97–114. https://doi.org/10.53703/001c.124907
Ta, V. A., & Lin, C. Y. (2023). Exploring the determinants of digital transformation adoption for SMEs in an emerging economy. Sustainability, 15(9), 7093. https://doi.org/10.3390/su15097093
Taiminen, H. M., & Karjaluoto, H. (2015). The usage of digital marketing channels in SMEs. Journal of Small Business and Enterprise Development, 22(4), 633-651. https://doi.org/10.1108/JSBED-05-2013-0073
Tarutė, A., Duobienė, J., Klovienė, L., Vitkauskaitė, E., & Varaniūtė, V. (2018). Identifying factors affecting digital transformation of SMEs. In Proceedings of the 18th International Conference on Electronic Business (pp. 373-381). ICEB.
Teng, X., Wu, Z., & Yang, F. (2022). Research on the relationship between digital transformation and performance of SMEs. Sustainability, 14(10), 6012.
Thomä, J. (2023). An urban-rural divide (or not?): Small firm location and the use of digital technologies. Journal of Rural Studies, 97, 214-223. https://doi.org/10.1016/j.jrurstud.2022.12.020
Valdés, E., Castillo, R., & Duran, J. (2019). Tecnologías de información y teletrabajo; su estado en Colombia. In: García C, Astudillo R (compiladores). Investigaciones en Gestión Empresarial, Ambiental y Competitividad. (pp. 75–100). Cali: Editorial Universidad Santiago de Cali.
Wang, J., Ma, Y., Zhang, L., Gao, R. X., & Wu, D. (2018). Deep learning for smart manufacturing: Methods and applications. Journal of Manufacturing Systems, 62, 177-193. https://doi.org/10.1016/j.jmsy.2018.01.003
Yao, W., Chen, X., Zhao, Y., & van Tooren, M. (2011). Concurrent subspace width optimization method for RBF neural network modeling. IEEE transactions on neural networks and learning systems, 23(2), 247-259. https://doi.org/10.1109/TNNLS.2011.2178560
Zahar Djordjevic, M., Djordjevic, A., Klochkova, E., & Misic, M. (2022). Application of modern digital systems and approaches to business process management. Sustainability, 14(3), 1697. https://doi.org/10.3390/su14031697
Zennouche, M., & Zhang, J. (2014). Evolution of leadership and organizational culture research on innovation field: 12 years of analysis. Open Journal of Social Sciences, 2(4), 388-392. https://doi.org/10.4236/jss.2014.24044
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Journal of Technology Management and Innovation

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



