Main Article Content

Abstract

This study aims to examine the role of integrated logistics information in optimizing supply chain management within the e-commerce industry. Adopting a qualitative research approach based on a systematic literature study, this research synthesizes prior theoretical and empirical studies to develop a comprehensive understanding of how logistics information integration supports efficiency, coordination, and responsiveness in e-commerce supply chains. The analysis draws on peer-reviewed journal articles and authoritative sources to identify recurring patterns, key dimensions, and emerging trends related to digital logistics integration. The findings indicate that integrated logistics information significantly enhances supply chain visibility, operational efficiency, service performance, and agility, while also supporting resilience and sustainability objectives. Furthermore, the study reveals that the effectiveness of integration depends on technological readiness, data quality, organizational alignment, and inter-organizational collaboration. The main contribution of this research lies in positioning integrated logistics information as a strategic capability that underpins supply chain optimization in dynamic e-commerce environments and provides a foundation for sustainable and resilient supply chain development.

Keywords

Integrated Logistics Information Supply Chain Management E-Commerce Logistics Digital Integration Supply Chain Optimization

Article Details

How to Cite
Nurani, N., & Rajab, A. (2026). Integrated Logistics Information for Supply Chain Management Optimization in the E-Commerce Industry . Golden Ratio of Mapping Idea and Literature Format, 6(2), 1405–1415. https://doi.org/10.52970/grmilf.v6i2.1858

References

  1. Barratt, M., & Oke, A. (2007). Antecedents of supply chain visibility in retail supply chains: A resource-based theory perspective. Journal of Operations Management, 25(6), 1217–1233. https://doi.org/10.1016/j.jom.2007.01.003
  2. Baryannis, G., Dani, S., & Antoniou, G. (2021). Predicting supply chain risks using machine learning: The trade-off between performance and explainability. Supply Chain Management: An International Journal, 26(6), 654–669. https://doi.org/10.1108/SCM-07-2020-0342
  3. Cheng, Y., Chen, K., & Sun, H. (2021). The impact of logistics information integration on supply chain performance. International Journal of Logistics Management, 32(4), 1123–1145. https://doi.org/10.1108/IJLM-07-2020-0271
  4. Choi, T. M., Wallace, S. W., & Wang, Y. (2018). Big data analytics in operations management. Production and Operations Management, 27(10), 1868–1883. https://doi.org/10.1111/poms.12838
  5. Dubey, R., Gunasekaran, A., Childe, S. J., Papadopoulos, T., Blome, C., & Luo, Z. (2021). Antecedents of resilient supply chains: An empirical study. International Journal of Production Research, 59(6), 1684–1705. https://doi.org/10.1080/00207543.2020.1775912
  6. Flynn, B. B., Huo, B., & Zhao, X. (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of Operations Management, 28(1), 58–71. https://doi.org/10.1016/j.jom.2009.08.001
  7. Gunasekaran, A., Subramanian, N., & Rahman, S. (2017). Green supply chain collaboration and incentives: Current trends and future directions. International Journal of Production Economics, 181, 114–124. https://doi.org/10.1016/j.ijpe.2016.06.010
  8. Helo, P., & Hao, Y. (2024). Logistics 4.0: Digital transformation with smart connected applications. International Journal of Production Economics, 274, 109365. https://doi.org/10.1016/j.ijpe.2024.109365
  9. Hübner, A., Holzapfel, A., & Kuhn, H. (2016). Distribution systems in omni-channel retailing. International Journal of Retail and Distribution Management, 44(3), 296–318. https://doi.org/10.1108/IJRDM-03-2015-0039
  10. Ivanov, D., & Dolgui, A. (2020). Viability of intertwined supply networks: Extending the supply chain resilience angles. International Journal of Production Research, 58(10), 2904–2915. https://doi.org/10.1080/00207543.2020.1750727
  11. Kache, F., & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of big data analytics and supply chain management. International Journal of Operations and Production Management, 37(1), 10–36. https://doi.org/10.1108/IJOPM-02-2015-0078
  12. Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 1–25. https://doi.org/10.1002/j.2158-1592.2001.tb00001.x
  13. Patro, P. K., Mangla, S. K., Sahoo, S., & Dey, P. K. (2024). Blockchain-based solutions to enhance carbon footprint traceability in supply chains. International Journal of Production Research, 62(5), 1567–1584. https://doi.org/10.1080/00207543.2024.2441450
  14. Sahoo, S., Mangla, S. K., & Luthra, S. (2024). Blockchain for sustainable supply chain management: A systematic review and future research agenda. Environmental Monitoring and Assessment, 196(2), 1–25. https://doi.org/10.1007/s10660-022-09569-1
  15. Schoenherr, T., & Swink, M. (2012). Revisiting the arcs of integration: Cross-validations and extensions. Journal of Operations Management, 30(1–2), 99–115. https://doi.org/10.1016/j.jom.2011.09.001
  16. Wang, G., Gunasekaran, A., Ngai, E. W. T., & Papadopoulos, T. (2016). Big data analytics in logistics and supply chain management: A review and future directions. International Journal of Production Economics, 176, 98–110. https://doi.org/10.1016/j.ijpe.2016.03.014
  17. Zhang, C., Chen, X., & Liu, Y. (2024). Blockchain traceability adoption in low-carbon supply chains. Sustainability, 16(5), 1817. https://doi.org/10.3390/su16051817
  18. Zhao, X., Huo, B., Selen, W., & Yeung, J. H. Y. (2011). The impact of internal integration and supply chain integration on firm performance. Journal of Operations Management, 29(1–2), 17–32. https://doi.org/10.1016/j.jom.2010.05.001