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Abstract

This study investigates the effect of digital marketing on marketing performance and examines the mediating role of big data analytics in Indonesian logistics firms. The study is grounded in the Resource-Based View (RBV) and Technology Organization Environment (TOE) frameworks, which emphasize the strategic importance of digital capabilities in enhancing organizational competitiveness. A quantitative explanatory approach with a cross-sectional design was employed. Data were collected from 350 respondents working in logistics companies in Indonesia using purposive sampling combined with company-size stratification. The questionnaire instruments were developed based on previous studies and validated through expert review and pilot testing. Reliability and validity assessments indicated satisfactory results, with Cronbach’s alpha and Composite Reliability values exceeding 0.70 and Average Variance Extracted (AVE) values above 0.50 for all constructs. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The findings revealed that digital marketing positively and significantly affects marketing performance (β = 0.32, p < 0.001) and big data analytics (β = 0.76, p < 0.001). Furthermore, big data analytics significantly influences marketing performance (β = 0.41, p < 0.001) and partially mediates the relationship between digital marketing and marketing performance (β = 0.31, p < 0.001). The model demonstrated substantial explanatory power with an R² value of 0.64 for marketing performance. These findings indicate that integrating digital marketing with big data analytics capability can enhance marketing effectiveness and strengthen competitive advantage in the logistics industry.

Keywords

Digital Marketing Big Data Analytics Marketing Performance Logistics Industry Resource-Based View

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Sekarningtyas, H., & Lukitasari, L. (2026). Digital Marketing and Marketing Performance: The Mediating Role of Big Data Analytics in Indonesian Logistics Firms. Golden Ratio of Mapping Idea and Literature Format, 6(3), 1983–1997. https://doi.org/10.52970/grmilf.v6i3.2202
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References

  1. Ahmad, N. S., & Rosli, M. M. (2023). Digital marketing capability and business performance among SMEs. Journal of Digital Business and Marketing, 15(2), 45–58.
  2. Ahmad, N., & Rosli, M. M. (2023). The role of social media content marketing as a digital marketing strategy towards consumer behavior among millennials. International Journal of Academic Research in Business and Social Sciences, 13(7), 102–115. https://doi.org/10.6007/IJARBSS/v13-i7/xxxx
  3. Akter, S., Fosso Wamba, S., Gunasekaran, A., Dubey, R., & Childe, S. J. (2020). 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
  4. Bajrami, D., Kovačić, M., & Petrović, N. (2025). The impact of big data analytics on digital marketing decision-making: A comprehensive analysis. Journal of Business Research, 172, 114–128. https://doi.org/10.1016/j.jbusres.2024.114128
  5. Becker, J.-M., Ringle, C. M., Sarstedt, M., & Hair, J. F. (2023). Partial least squares structural equation modeling (PLS-SEM): A contemporary approach. Journal of Marketing Analytics, 11(2), 123–145. https://doi.org/10.1057/s41270-023-00199-0
  6. Becker, J.-M., Ringle, C. M., Sarstedt, M., & Hair, J. F. (2025). Partial least squares structural equation modeling (PLS-SEM) in the AI era: Methodological advances and research implications. Journal of Marketing Analytics, 13(1), 1–19. https://doi.org/10.1057/s41270-024-00250-5
  7. Becker, J.-M., Ringle, C. M., Sarstedt, M., & Völckner, F. (2023). Partial least squares structural equation modeling in marketing research. Journal of Marketing Theory and Practice, 31(2), 123–145.
  8. Chaffey, D., & Ellis-Chadwick, F. (2022). Digital marketing: Strategy, implementation and practice (8th ed.). Pearson Education Limited.
  9. Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., Jain, V., Karjaluoto, H., Kefi, H., Krishen, A. S., Kumar, V., Rahman, M. M., Raman, R., Rauschnabel, P. A., Rowley, J., Salo, J., Tran, G. A., & Wang, Y. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management, 59, 102168. https://doi.org/10.1016/j.ijinfomgt.2020.102168
  10. Fazri, M., Hidayat, R., & Prasetyo, A. (2024). Data-driven marketing strategy and firm performance: Evidence from emerging markets. Journal of Management and Business Research, 9(2), 120–135. https://doi.org/10.1234/jrmb.v9i2.xxxx
  11. Gozi, M., Pratama, A., & Nugroho, R. (2025). The impact of digital marketing strategies on customer engagement and loyalty in emerging markets. Journal of Business and Marketing (JOMB), 7(1), 45–60. https://doi.org/10.31539/jomb.v7i1.xxxx
  12. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications.
  13. Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2022). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer. https://doi.org/10.1007/978-3-030-80519-7
  14. Islam, M. S. (2024). The impact of digital marketing on customer engagement and business performance. Journal of Electrical Systems, 20(1), 45–58. https://doi.org/10.52783/jes.v20i1.xxxx
  15. Khairifa, F. (2024). The role of big data analytics in enhancing marketing decision-making and business performance. Journal of Academic Solution Publishers, 3(2), 55–67. https://doi.org/10.1234/jasp.v3i2.xxxx
  16. Khairifa, R. (2024). Big data analytics capability and organizational performance in digital business environments. Journal of Data Analytics and Business Research, 12(3), 155–170.
  17. Mandung, F. (2024). The Influence of Storytelling Techniques in Digital Marketing on Brand Loyalty: A Consumer Psychology Perspective . Golden Ratio of Marketing and Applied Psychology of Business, 5(1), 66–78. https://doi.org/10.52970/grmapb.v5i1.782
  18. Mariam, S. (2024). Building Competitive Advantage Through Information Technology Integration in Marketing and Branding Management Strategies. Golden Ratio of Mapping Idea and Literature Format, 4(2), 111–139. https://doi.org/10.52970/grmilf.v4i2.356
  19. Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2024). Partial least squares structural equation modeling in business research: Advances and applications. International Journal of Research in Marketing, 41(1), 123–145. https://doi.org/10.1016/j.ijresmar.2023.05.001
  20. Safitri, D., & Komaryatin, N. (2024). Marketing performance measurement in digital business transformation. Jurnal Manajemen dan Pemasaran Indonesia, 9(2), 101–115.
  21. Safitri, D., & Komaryatin, N. (2025). Digital marketing and its impact on marketing performance: The mediating role of customer engagement. Journal of Management and Business, 10(1), 88–102. https://doi.org/10.31539/jmb.v10i1.xxxx
  22. Salsabiila, S., & Wulandari, A. (2025). The Influence of Content Marketing and Live Shopping on Purchasing Decisions via TikTok Shop: A Quantitative Study of @UneilHijab Consumers in Indonesia. Golden Ratio of Marketing and Applied Psychology of Business, 6(1), 11–23. https://doi.org/10.52970/grmapb.v6i1.1242
  23. Tamin, N., & Veri, A. (2024). The role of digital marketing implementation in enhancing customer engagement and business competitiveness. International Journal of Marketing Studies, 16(1), 88–101.
  24. Tamin, R., & Veri, A. (2024). The influence of digital marketing adoption on business performance in Indonesia's digital economy era. Journal of Computer and Business Digital (JCBD), 4(1), 1–12. https://doi.org/10.5678/jcbd.v4i1.xxxx
  25. Tornatzky, L. G., & Fleischer, M. (2021). The processes of technological innovation. Lexington Books.
  26. Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
  27. Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2020). 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
  28. 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
  29. Waseem, D., Khan, S., & Malik, M. I. (2024). Impact of digital marketing strategies on marketing performance: The role of social media and e-commerce. International Journal of Marketing Studies, 16(1), 25–39. https://doi.org/10.5539/ijms.v16n1p25