Configurational Drivers of Digital Technology Adoption in Manufacturing SMEs: Evidence from Chile

Francisco Gatica - Neira; Mario Ramos - Maldonado

doi:10.4067/s0718-2724202600024993

Autores/as

Francisco Gatica - Neira Faculty of Business Sciences, Department of Economics and Finance, University of Bío-Bío , Concepción, Chile.
Mario Ramos - Maldonado Faculty of Engineering, Department of Engineering, University of Bío-Bío , Concepción, Chile.

DOI:

https://doi.org/10.4067/s0718-2724202600024993

Resumen

La transformación digital se ha convertido en un motor clave de la competitividad y la productividad de las pequeñas y medianas empresas (pymes). Sin embargo, los factores que permiten a las firmas profundizar la adopción de tecnologías digitales siguen siendo insuficientemente comprendidos, particularmente en regiones industriales emergentes. Este estudio analiza las configuraciones de factores tecnológicos y organizacionales que explican el nivel de adopción de tecnologías digitales en pymes manufactureras. Mediante análisis comparativo cualitativo de conjuntos difusos (fsQCA) y una muestra de 52 empresas ubicadas en la Región del Bío-Bío (Chile), la investigación se orienta por el marco Tecnología–Organización–Entorno (TOE). Los resultados identifican varias configuraciones que explican niveles más altos de adopción de tecnologías digitales y destacan la importancia de las capacidades internas. En particular, la presencia de profesionales TIC, el conocimiento tecnológico, una cultura organizacional favorable a la innovación digital y la motivación del liderazgo emergen como condiciones clave. Estos hallazgos sugieren que la adopción de tecnologías digitales se explica principalmente por capacidades tecnológicas y organizacionales, mientras que las condiciones del entorno analizadas desempeñan un papel más limitado. El estudio contribuye a la literatura sobre transformación digital y aporta implicancias para las políticas públicas orientadas a fortalecer las capacidades de innovación en pymes manufactureras.

Palabras clave:

transformación digital
adopción tecnológica
pymes
marco TOE
fsQCA
capacidades tecnológicas

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Biografía del autor/a

Francisco Gatica - Neira, Faculty of Business Sciences, Department of Economics and Finance, University of Bío-Bío , Concepción, Chile.

Citas

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T

Almeida, R., Fernandes, A., & Viollaz, M. (2020). Software adoption, employment, composition, and the skill content of occupations in Chilean firms. The Journal of Development Studies, 56(1), 169-185. https://doi.org/10.1080/00220388.2018.1546847

Battistoni, E., Gitto, S., Murgia, G., & Campisi, D. (2023). Adoption paths of digital transformation in manufacturing SMEs. International Journal of Production Economics, 255, 108675. https://doi.org/10.1016/j.ijpe.2022.108675

Bogliacino, F., & Pianta, M. (2016). The Pavitt taxonomy, revisited: Patterns of innovation in manufacturing and services. Economia Politica, 33(2), 153-180. https://doi.org/10.2139/ssrn.2579642

Cabrera-Sánchez, J., & Villarejo-Ramos, A. (2019). Fatores que afetam a adoção de análises de big data em empresas. Revista de Administração de Empresas, 59(6), 415-429. https://doi.org/10.1590/s0034-759020190607

Capello, R., & Lenzi, C. (2024). 4.0 technological transformations: Heterogeneous effects on regional growth. Economics of Innovation and New Technology, 33(5), 627-646. https://doi.org/10.1080/10438599.2023.2204523

Chauhan, C., Singh, A., & Luthra, S. (2021). Barriers to Industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy. Journal of Cleaner Production, 285, 124809. https://doi.org/10.1016/j.jclepro.2020.124809

Codara, L., & Sgobbi, F. (2023). Resilience, complexity and digital transformation: Three case studies in the valves industry. Journal of Manufacturing Technology Management, 34(9), 1-19. https://doi.org/10.1108/JMTM-05-2022-0214

Fiorini, N., Pucci, T., Casprini, E., & Zanni, L. (2022). The actors' role in industrial districts facing the challenge of technologies 4.0 between absorption and dissemination. European Planning Studies, 31(7), 1377-1396. https://doi.org/10.1080/09654313.2022.2161299

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley.

Gatica, F. (2022). Adoption and diffusion of technologies 4.0 based on the innovative trajectory and the scale of operation: The case of Chile. RAE - Revista de Administração de Empresas, 62(3), 1-25. https://doi.org/10.1590/S0034-759020220303x

Gatica-Neira, F., & Ramos-Maldonado, M. (2022). Differences in the capacity of adoption of the enabling ICTs for Industry 4.0 in Chile. E&M Economics and Management, 25(4), 180-195. https://doi.org/10.15240/tul/001/2022-4-012

Gatica-Neira, F., Ramos-Maldonado, M., Andrés Ascua, R., Revale, H., & Fernández, V. (2024). Digital technologies 4.0 in small and medium-sized manufacturing industries: Cases of the central region of Argentina and the Biobío Region of Chile. Sage Open, 14(2), 1-17. https://doi.org/10.1177/21582440241249285

Gentry, L., & Calantone, R. (2002). A comparison of three models to explain shop-bot use in the web. Psychology & Marketing, 19(11), 945-956. https://doi.org/10.1002/mar.10045

Hietala, J., Hänninen, R., Kniivilä, M., & Toppinen, A. (2019). Networks in international opportunity recognition among Finnish wood product industry SMEs. Silva Fennica, 53(4), 10151. https://doi.org/10.14214/sf.10151

Horváth, D., & Szabó, R. Z. (2019). Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? Technological Forecasting and Social Change, 146, 119-132. https://doi.org/10.1016/j.techfore.2019.05.021

Ingaldi, M., & Ulewicz, R. (2020). Problems with the implementation of Industry 4.0 in enterprises from the SME sector. Sustainability, 12, 217. https://doi.org/10.3390/su12010217

Kent, R. (2008). Using fsQCA: A brief guide and workshop for fuzzy-set qualitative comparative analysis. Department of Marketing, University of Stirling. https://hummedia.manchester.ac.uk/institutes/cmist/archive-publications/working-papers/2008/2008-10-teaching-paper-fsqca.pdf

Kiraz, A., Canpolat, O., Özkurt, C., & Taşkın, H. (2020). Analysis of the factors affecting the Industry 4.0 tendency with the structural equation model and an application. Computers & Industrial Engineering, 150, 106911. https://doi.org/10.1016/j.cie.2020.106911

Li, F., Long, J., & Zhao, W. (2023). Mining braces of innovation linking to digital transformation grounded in TOE framework. Sustainability, 15, 301. https://doi.org/10.3390/su15010301

Luo, S., Yimamu, N., Li, Y., Wu, H., Irfan, M., & Hao, Y. (2022). Digitalization and sustainable development: How could digital economy development improve green innovation in China? Business Strategy and the Environment, 1-25. https://doi.org/10.1002/bse.3223

Maggi, C., Ramos, M., & Vergara, R. (2020). Adopción de tecnologías digitales 4.0 por parte de pequeñas y medianas empresas manufactureras en la Región del Biobío (Chile) (Documentos de Proyectos LC/TS.2020/133). Comisión Económica para América Latina y el Caribe (CEPAL).

Margherita, E. G., & Braccini, A. M. (2021). Exploring the socio-technical interplay of Industry 4.0: A single case study of an Italian manufacturing organisation. International Workshop on Socio-Technical Perspective in IS Development.

Marrucci, A., Rialti, R., & Balzano, M. (2025). Exploring paths underlying Industry 4.0 implementation in manufacturing SMEs: A fuzzy-set qualitative comparative analysis. Management Decision, 63(6), 1936-1959. https://doi.org/10.1108/MD-05-2022-0644

Motta, J., Moreno, H., & Ascúa, R. (2019). Industria 4.0 en MIPYMES manufactureras de la Argentina (Documentos de Proyectos LC/TS.2019/93). Comisión Económica para América Latina y el Caribe (CEPAL).

Pappas, I., & Woodside, A. (2021). Fuzzy-set qualitative comparative analysis (fsQCA): Guidelines for research practice in Information Systems and marketing. International Journal of Information Management, 58, 102310. https://doi.org/10.1016/j.ijinfomgt.2021.102310

Ragin, C., Patros, T., Strand, S., & Rubinson, C. (2017). User's guide to fuzzy-set/qualitative comparative analysis. Department of Sociology, University of California. https://sites.socsci.uci.edu/~cragin/fsQCA/download/fsQCAManual.pdf

Rogers, E. M. (1995). Diffusion of innovations. The Free Press.

Saridakis, C., Zaefarian, G., Ganotakis, P., & Angelidou, S. (2022). A step-by-step guide of (fuzzy set) qualitative comparative analysis: From theory to practice via an implementation in a B2B context. Industrial Marketing Management, 107, 92-107. https://doi.org/10.1016/j.indmarman.2022.09.026

Shalahuddin, M., Sunindyo, W. D., Effendi, M. R., & Surendro, K. (2024). Fuzzy-set qualitative comparative analysis (fsQCA) for validating causal relationships in system dynamics models. Engineering Reports, e12855, 1-14. https://doi.org/10.1002/eng2.12855

Song, Q., Chen, X., & Gu, H. (2023). How technological, organizational, and environmental factors drive enterprise digital innovation: Analysis based on the dynamic fsQCA approach. Sustainability, 15, 12248. https://doi.org/10.3390/su151612248

Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. K. (1990). Processes of technological innovation. Lexington Books.

Venkatesh, V., Thong, J., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412

Wang, Q., Gao, Y., Cao, Q., Li, Z., & Wang, R. (2023). What kind of configuration can facilitate the digital transformation? A fsQCA and NCA study of SMEs. Journal of Organizational and End User Computing, 35(1), 1-20. https://doi.org/10.4018/JOEUC.334110

Xu, K. (2025). Promotion path of digital transformation in China's manufacturing industry based on technology-organisation-environment framework. Journal of Business Economics and Management, 26(5), 1090-1111. https://doi.org/10.3846/jbem.2025.24959

Zhang, X., Zhao, H., & Zhou, W. (2024). Antecedent configuration pathways for manufacturing-enterprise digital servitization: Based on a technology-organization-environment theoretical framework. PLoS ONE, 19(5), e0301789. https://doi.org/10.1371/journal.pone.0301789