Big data en el desempeño financiero de las empresas peruanas: el rol mediador de la gestión
Resumen
En 2020, a raíz de la COVID-19, Perú experimentó un rápido crecimiento en la implementación de tecnología Big Data. El objetivo de este estudio es determinar la influencia del conocimiento en Big Data sobre el desempeño financiero de las empresas peruanas, mediado por la capacidad de gestión. Para ello, se empleó un enfoque cuantitativo correlacional con un diseño no experimental, en el que participaron 77 gerentes de grandes empresas peruanas incluidas en el ranking de las mejores empresas. La técnica de análisis utilizada fue el modelo de ecuaciones estructurales basado en varianzas. Los resultados indican que el conocimiento en Big Data tiene un impacto positivo en el desempeño financiero de las grandes empresas, siempre y cuando esté mediado por una sólida capacidad de gestión. La investigación concluye que la implementación, el uso y el conocimiento de Big Data en grandes empresas mejora significativamente cuando se complementa con una gestión eficaz, lo que influye positivamente en su desempeño financiero. Estos hallazgos tienen implicaciones importantes para las empresas que desean adoptar y aprovechar el potencial del Big Data para mejorar su desempeño financiero.
Citas
Akter, S., Gunasekaran, A., Wamba, S. F., Babu, M. M., & Hani, U. (2020). Reshaping competitive advantages with analytics capabilities in service systems. Technological Forecasting and Social Change, 159(120180), 120180. https://doi.org/10.1016/j.techfore.2020.120180
Arciénaga, A., Tuero, I., Salom, M., Arena, A., Villanueva, B., Tarcaya, H. R., Rodríguez, I., Jakúlica, R. (2021). Acciones de digitalización frente a la pandemia. [Objeto de conferencia]. Pontificia Universidad Católica del Perú. https://repositorio.pucp.edu.pe/index/handle/123456789/184730
Ateino, E. (2022). Financial Performance and Investment Decision Making in Kenya. African Journal of Commercial Studies, 1(2), 1–7. https://doi.org/10.59413/ajocs/v1.i2.1
Awan, U., Shamim, S., Khan, Z., Zia, N. U., Shariq, S. M., & Khan, M. (2021). Big Data Analytics Capability and Decision-making: The role of data-driven insight on circular Economy performance. Technological Forecasting and Social Change, 168. https://doi.org/10.1016/j.techfore.2021.120766
Bag, S., Wood, L. C., Xu, L., Dhamija, P., & Kayikci, Y. (2020). Big Data Analytics as an operational excellence approach to enhance sustainable supply chain performance. Resources Conservation and Recycling, 153, 104559. https://doi.org/10.1016/j.resconrec.2019.104559
CEPAL (20 de mayo de 2020). CEPAL y OIT analizan los desafíos laborales en América Latina y el Caribe tras la pandemia del COVID-19. Cepal. https://www.cepal.org/es/noticias/cepal-oit-analizan-desafios-laborales-america-latina-caribe-tras-la-pandemia-covid-19
Chen, L., Liu, H., Zhou, Z., Chen, M., & Chen, Y. (2022). IT-business alignment, big data analytics capability, and Strategic Decision-making: Moderating roles of event criticality and Disruption of COVID-19. Decision Support Systems, 161, 113745. https://doi.org/10.1016/j.dss.2022.113745
Cui, Y., Firdousi, S., Afzal, A., Awais, M., & Akram, Z. (2022). The influence of big data analytic capabilities building and education on business model innovation. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.999944.
Danielsen, F., Olsen, D., & Augustin, V. (2021). Toward an Understanding of Big Data Analytics and Competitive Performance. Scandinavian Journal of Information Systems, 33(1), 155-192. https://aisel.aisnet.org/sjis/vol33/iss1/6
Eleimat, D., Ebbini, M. M. A., Aryan, L. A., & Al-Hawary, S. I. S. (2023). The effect of big data on financial reporting quality. International journal of data and network science, 7(4), 1775–1780. https://doi.org/10.5267/j.ijdns.2023.7.015
Faroukhi, A. Z., El Alaoui, I., Gahi, Y., & Amine, A. (2020). An adaptable Big Data Value Chain framework for end-to-end Big Data monetization. Big Data and Cognitive Computing, 4(4), 34. https://doi.org/10.3390/bdcc4040034
Ferraris, A., Mazzoleni, A., Devalle, A., & Couturier, J. (2019). Big data analytics capabilities and knowledge management: impact on firm performance. Management Decision, 57(8), 1923–1936. https://doi.org/10.1108/md-07-2018-0825
Gao, J., Siddik, A. B., Khawar Abbas, S., Hamayun, M., Masukujjaman, M., & Alam, S. S. (2023). Impact of E-commerce and digital marketing adoption on the financial and sustainability performance of MSMEs during the COVID-19 pandemic: An empirical study. Sustainability, 15(2), 1594. https://doi.org/10.3390/su15021594
Gu, V. C., Zhou, B., Cao, Q., & Adams, J. (2021). Exploring the relationship between supplier development, big data analytics capability, and firm performance. Annals of Operations Research, 302(1), 151-172. https://doi.org/10.1007/s10479-021-03976-7
Hansen, J. & Quinon, P. (2023). The importance of expert knowledge in big dataand machine learning. Synthese, 201(2), 1 - 21. https://doi.org/10.1007/s11229-023-04041-5
Hasan, M. M., Popp, J., & Oláh, J. (2020). Current landscape and influence of big data on finance. Journal of Big Data, 7(1). https://doi.org/10.1186/s40537-020-00291-z
Horng, J.-S., Liu, C.-H., Chou, S.-F., Yu, T.-Y., & Hu, D.-C. (2022). Role of big data capabilities in enhancing competitive advantage and performance in the hospitality sector: Knowledge-based dynamic capabilities view. Journal of Hospitality and Tourism Management, 51, 22–38. https://doi.org/10.1016/j.jhtm.2022.02.026
Huaman, J. (2021). Impacto económico y social de la COVID-19 en el Perú. Revista de Ciencia e Investigación en Defensa-CAEN, 2(1), 31-42. https://recide.caen.edu.pe/index.php/recide/article/download/51/38
Huang, T. C., Wang, T., & Huang, T. (2018). Initial evidence on the impact of big data implementation on firm performance. Information Systems Frontiers, 22(2), 475-487. https://doi.org/10.1007/s10796-018-9872-5
Huynh, M.-T., Nippa, M., & Aichner, T. (2023). Big data analytics capabilities: Patchwork or progress? A systematic review of the status quo and implications for future research. Technological Forecasting and Social Change, 197(122884), 122884. https://doi.org/10.1016/j.techfore.2023.122884
Islam, A. A., Ahmad, K., Rafi, M., & Zheng, J. (2021). Performance-based evaluation of academic libraries in the big data era. Journal of Information Science, 47(4), 458-471. https://doi.org/10.1177/0165551520918516
Jacková, A. (2021). Utilization of modern methods in measuring the financial performance of the company. AD ALTA: Journal of Interdisciplinary Research, 11(1), 114–116. https://doi.org/10.33543/1101114116
Ji-fan Ren, S., Fosso Wamba, S., Akter, S., Dubey, R., & Childe, S. J. (2017). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55(17), 5011–5026. https://doi.org/10.1080/00207543.2016.1154209
Karimi, J., Somers, T. M., & Gupta, Y. P. (2001). Impact of information technology management practices on customer service. Journal of Management Information Systems, 17(4), 125-158. https://doi.org/10.1080/07421222.2001.11045661
Kim, G., Shin, B., & Kwon, O. (2012). Investigating the value of sociomaterialism in conceptualizing IT capability of a firm. Journal of Management Information Systems, 29(3), 327-362. https://doi.org/10.2753/mis0742-1222290310
Liu, (claude) Chien-Hung, & Mehandjiev, N. (2020). The effect of big data analytics capability on firm performance: A pilot study in China. En Lecture Notes in Business Information Processing (pp. 594–608). Springer International Publishing.
Liu, J. & Fu, S. (2024). Financial big data management and intelligence based on computer intelligent algorithm. Scientific reports, 14(9395), 1-18. https://doi.org/10.1038/s41598-024-59244-8
Marcano, M. (2015). Internal Marketing: Analysis of theories and strategies that can be applied to reach competitive advantage and improve business performane in a telecommunication company. Unpublish thesis (Master’s), Dublin Business School. https://esource.dbs.ie/items/0a8b10fb-597f-4d14-9234-f90c297a2a00
Munodawafa, R. T., & Johl, S. K. (2019). Big Data Analytics Capabilities and Eco-Innovation: A study of Energy companies. Sustainability, 11(15), 4254. https://doi.org/10.3390/su11154254
Organización Internacional de Trabajo - Perú. (2020). Impacto de la COVID-19 en el empleo y los ingresos laborales. https://www.ilo.org/wcmsp5/groups/public/---americas/---ro-lima/documents/publication/wcms_756474.pdf
PwC Perú. (2024). Preparándonos para el impacto. Mine 2024. https://www.pwc.pe/es/esp-pwc-global-mine-2024-capitulo-peruano.pdf
Ren, S. (2022). Optimization of enterprise financial management and Decision-Making systems based on big data. Journal of Mathematics, 2022, 1-11. https://doi.org/10.1155/2022/1708506
Ringle, C., Wende, S., & Becker, J. (2015). SmartPLS 3. SmartPLS
Sadyrin, I., Syrovatskay, O., & Leonova, O. (2021). Prospects for Using Big Data in Financial Analysis. SHS Web of Conferences. https://doi.org/10.1051/SHSCONF/202111005004
Shawang, S., Indiran, L., Fu, C. & Abdullah, N. (2024). The Influence of Big Data Management Towards Big Data Decision-Making Capability in The Malaysian Public Sector. COMPENDIUM by paper ASIA, 40(4b), 132 – 144. https://doi.org/10.59953/paperasia.v40i4b.198
Superintendencia de Banca, Seguros y AFP - SBS. (2023). Informe de Estabilidad del Sistema Financiero. https://www.sbs.gob.pe/Portals/0/IESF-2023-2A.pdf
Tissot, B. (2019). Making the most of big data for financial stability purposes. En Advances in Knowledge Acquisition, Transfer, and Management (pp. 1–24). IGI Global.
Tong, D., & Tian, G. (2023). Intelligent financial decision support system based on big data. Journal of Intelligent Systems, 32(1). https://doi.org/10.1515/jisys-2022-0320
Zhou, G., Liu, L., & Luo, S. (2022). Sustainable development, ESG performance and company market value: Mediating effect of financial performance. Business Strategy and the Environment, 31(7), 3371–3387. https://doi.org/10.1002/bse.3089
Zraqat, O. (2020). The moderating role of business intelligence in the impact of big data on financial reports quality in Jordanian telecom companies. Modern Applied Science, 14(2), 71. https://doi.org/10.5539/mas.v14n2p71

Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0.