Optimalisasi Manajemen Sistem Informasi melalui Big Data Analytics untuk Keberhasilan Transformasi Digital

Iska Asri Agustin

doi:10.37150/jimat.v6i1.3914

Authors

Iska Asri Agustin Program Studi Informatika, Universitas Linggabuana PGRI Sukabumi

DOI:

https://doi.org/10.37150/jimat.v6i1.3914

Keywords:

Big Data Analytics, Management Information Systems, Digital Transformation, Organizational Readiness, PLS-SEM

Abstract

This study aims to analyze the influence of Big Data Analytics (BDA) and Management Information Systems (MIS) on Digital Transformation (DT) and Organizational Readiness (OR) in facing the digital era. Employing a quantitative approach using Partial Least Squares - Structural Equation Modeling (PLS-SEM), data were collected from 30 organizations in Sukabumi City and Regency that have implemented or are in the process of implementing digital transformation. The results show that MIS has a significant and positive effect on both DT and OR, directly and indirectly through the mediation of digital transformation. In contrast, BDA does not exhibit a significant impact on either DT or OR, indicating that BDA implementation has yet to be strategically integrated within the organizations. Digital transformation is proven to be a significant mediator between MIS and OR but not between BDA and OR. The managerial implications highlight the importance of strengthening information systems, digital culture, and human resource capabilities in preparing organizations to face technological disruption. Theoretically, this study contributes to the development of a technology-based organizational readiness model and provides a foundation for more effective digital transformation strategies. Future research is recommended to expand the sectoral scope and include additional mediating or moderating variables for a more comprehensive understanding.

References

Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment? International Journal of Production Economics, 182, 113–131. https://doi.org/10.1016/j.ijpe.2016.08.018

Ansari, K., & Ghasemaghaei, M. (2023). Big Data Analytics Capability and Firm Performance: Meta-Analysis. Journal of Computer Information Systems, 63(6), 1477–1494. https://doi.org/10.1080/08874417.2023.2170300

Appio, F. P., Frattini, F., Petruzzelli, A. M., & Neirotti, P. (2021). Big data analytics and business model innovation: A systematic literature review. Journal of Business Research, 130, 83–101. https://doi.org/10.1016/j.jbusres.2021.03.063

Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Quarterly, 24(1), 169–196.

Chen, D. Q., Mocker, M., Preston, D. S., & Teubner, A. (2010). Information systems strategy: reconceptualization, measurement, and implications. MIS Quarterly, 34(2), 233–259.

Chen, Y., Wang, Y., Nevo, S., Jin, J., Wang, L., & Chow, W. S. (2020). IT capability and organizational performance: The roles of business process agility and environmental factors. European Journal of Information Systems, 29(3), 1–20. https://doi.org/10.1080/0960085X.2019.1705191

Chuang, H. M., & Lin, H. N. (2017). Performance implications of information-value offering in e-service systems: Examining the resource-based perspective and innovation strategy. Journal of Strategic Information Systems, 26(1), 22–38.

Deloitte Insights. (2023). Realizing Value from Digital Transformation Investments. https://deloitte.wsj.com/cio/realizing-value-from-digital-transformation-investments-780a29aa

Grover, V., Chiang, R. H. L., Liang, T.-P., & Zhang, D. (2018). Creating strategic business value from big data analytics: A research framework. Journal of Management Information Systems, 35(2), 388–423. https://doi.org/10.1080/07421222.2018.1451951

Günther, W. A., Mehrizi, M. H. R., Huysman, M., & Feldberg, F. (2017). Debating big data: A literature review on realizing value from big data. Journal of Strategic Information Systems, 26(3), 191–209. https://doi.org/10.1016/j.jsis.2017.07.003

Kim, E. S., Choi, Y., & Byun, J. (2019). Big Data Analytics in Government: Improving Decision Making for R&D Investment in Korean SMEs. Sustainability, 12(1), 202. https://doi.org/10.3390/su12010202

Laudon, K. C., & Laudon, J. P. (2020). Management Information Systems: Managing the Digital Firm. Pearson.

Lutfi, A., et al. (2023). Drivers and impact of big data analytic adoption in the retail industry: A quantitative investigation applying structural equation modeling. Journal of Retailing and Consumer Services, 70, 103129. https://doi.org/10.1016/j.jretconser.2022.103129

Madhala, P., Li, H., & Helander, N. (2024). Developing data analytics capabilities: integrating the information systems success model and the resource-based view. Industrial Management & Data Systems, 124(7), 2364–2387. https://doi.org/10.1108/IMDS-09-2023-0653

Mikalef, P., Krogstie, J., Pappas, I. O., & Giannakos, M. (2018). Investigating the effects of big data analytics capabilities on firm performance: The mediating role of dynamic capabilities. Information & Management, 55(8), 103207. https://doi.org/10.1016/j.im.2018.03.004

Rumman, A. A., Alsmairat, M. A. K., Alshawabkeh, R., & Al-Abbadi, L. (2024). Digital transformation in SMEs: Assessing the impact of big data capabilities on project success, business continuity, and sustainability. International Journal of Data and Network Science, 8(4), 2701–2712. https://doi.org/10.5267/j.ijdns.2024.4.009

Sindarov, A., Vafaei-Zadeh, A., Syafrizal, S., & Chanda, R. C. (2023). Big data analytical capability and firm performance: moderating effect of analytics capability business strategy alignment. International Journal of Applied Decision Sciences, 16(6), 663–685. https://doi.org/10.1504/IJADS.2023.134188

TechRadar. (2025). Transforming dark data into AI-driven business value. https://www.techradar.com/pro/transforming-dark-data-into-ai-driven-business-value

Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.

Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144.

Waller, M. A., & Fawcett, S. E. (2013). Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2), 77–84. https://doi.org/10.1111/jbl.12010

Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J.-F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365. https://doi.org/10.1016/j.jbusres.2016.08.009

Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading Digital: Turning Technology into Business Transformation. Harvard Business Review Press.

Wided, R. (2023). IT Capabilities, Strategic Flexibility and Organizational Resilience in SMEs Post-COVID-19: A Mediating and Moderating Role of Big Data Analytics Capabilities. Global Journal of Flexible Systems Management, 24(1), 123–142. https://doi.org/10.1007/s40171-022-00327-8

Xu, J., Naseer, H., Maynard, S., & Filippou, J. (2024). Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework. Australasian Journal of Information Systems, 28. https://doi.org/10.3127/ajis.v28.4215