Business analytics and data maturity in logistics SMEs: A structured qualitative comparison between Australia and Vietnam
Xuất bản: tháng 8 26, 2026
doi:10.62831/nckh.2026.3587.v1
Tóm tắt
This study develops and applies a seven-dimensional data maturity framework to compare logistics small and medium-sized enterprises (SMEs) in Australia and Vietnam through a structured qualitative synthesis. The evidence indicates that Australian logistics SMEs are generally proactive, with more mature and systematically managed practices concentrated among better-connected firms and networks, whereas Vietnamese SMEs typically range from reactive to early proactive stages. Substantial within-country variation is observed in both contexts. The study contributes a transparent evidence hierarchy and a logistics-SME-specific maturity framework, while highlighting differences in data foundations, process integration, business intelligence, predictive analytics, and ecosystem-level data use across the two countries.
Từ khóa
business analyticsdata maturitydigital logisticslogistics SMEsAustraliaVietnam
Tài liệu tham khảo
1.
Abraham, R., Schneider, J., & vom Brocke, J. (2019). Data management: A conceptual framework, structured review, and research agenda. International Journal of Information Management, 49, 424-438. https://doi.org/10.1016/j.ijinfomgt.2019.07.008
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
Australian Government. (2019). National freight and supply chain strategy. Department of Infrastructure, Transport, Cities and Regional Development. https://www.freightaustralia.gov.au/a-closer-look/national-freight-supply-chain-strategy
4.
Australian Logistics Council. (2022). Annual report 2021. https://austlogistics.com.au/wp-content/uploads/2022/07/2022_04-ALC-annual-report-low-res.pdf
5.
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
Becker, J., Knackstedt, R., & Pöppelbuß, J. (2009). Developing maturity models for IT management: A procedure model and its application. Business & Information Systems Engineering, 1(3), 213-222. https://doi.org/10.1007/s12599-009-0044-5
Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of Things and supply chain management: A literature review. International Journal of Production Research, 57(15-16), 4719-4742. https://doi.org/10.1080/00207543.2017.1402140
Bureau of Infrastructure and Transport Research Economics. (2024). National Freight Data Hub. Australian Government. https://datahub.freightaustralia.gov.au/
9.
Cao, G., Duan, Y., & Li, G. (2015). Linking business analytics to decision making effectiveness: A path model analysis. IEEE Transactions on Engineering Management, 62(3), 384-395. https://doi.org/10.1109/TEM.2015.2441875
Caridi, M., Crippa, L., Perego, A., Sianesi, A., & Tumino, A. (2010). Do virtuality and complexity affect supply chain visibility? International Journal of Production Economics, 127(2), 372-383. https://doi.org/10.1016/j.ijpe.2009.10.016
Eller, R., Alford, P., Kallmünzer, A., & Peters, M. (2020). Antecedents, consequences, and challenges of small and medium-sized enterprise digitalization. Journal of Business Research, 112, 119-127. https://doi.org/10.1016/j.jbusres.2020.03.004
Ghasemaghaei, M. (2019). Does data analytics use improve firm decision making quality? The role of knowledge sharing and data quality. Decision Support Systems, 120, 14-24. https://doi.org/10.1016/j.dss.2019.03.004
Gupta, M., & George, J.F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049-1064. https://doi.org/10.1016/j.im.2016.07.004
Kane, G. C., Palmer, D., Phillips, A. N., Kiron, D., & Buckley, N. (2015). Strategy, not technology, drives digital transformation. MIT Sloan Management Review and Deloitte University Press. https://sloanreview.mit.edu/projects/strategy-drives-digital-transformation/
15.
Khatri, V., & Brown, C. V. (2010). Designing data management. Communications of the ACM, 53(1), 148-152. https://doi.org/10.1145/1629175.1629210
Ministry of Industry and Trade of Vietnam. (2023). Vietnam logistics report 2023: Digital transformation in logistics. Industry and Trade Publishing House.
17.
Ministry of Industry and Trade of Vietnam. (2025). Vietnam logistics report 2025: Smart logistics. Industry and Trade Publishing House.
18.
Montecchi, M., Plangger, K., & West, D. C. (2021). Supply chain transparency: A bibliometric review and research agenda. International Journal of Production Economics, 238, Article 108152. https://doi.org/10.1016/j.ijpe.2021.108152
Paulk, M. C., Curtis, B., Chrissis, M. B., & Weber, C. V. (1993). Capability maturity model, version 1.1. IEEE Software, 10(4), 18-27. https://doi.org/10.1109/52.219617
Pham Quang Hai, Phung Quang Phat & Do Hong Quan (2023). Digital transformation in Vietnamese logistics businesses. VNU Journal of Economics and Business, 3(1), 28-37. https://doi.org/10.57110/jebvn.v3i1.160
Popovič, A., Hackney, R., Coelho, P. S., & Jaklič, J. (2012). Towards business intelligence systems success: Effects of maturity and culture on analytical decision making. Decision Support Systems, 54(1), 729-739. https://doi.org/10.1016/j.dss.2012.08.017
Richey, R. G., Jr., Morgan, T. R., Lindsey-Hall, K., & Adams, F. G. (2016). A global exploration of big data in the supply chain. International Journal of Physical Distribution & Logistics Management, 46(8), 710-739. https://doi.org/10.1108/IJPDLM-05-2016-0134
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118-144. https://doi.org/10.1016/j.jsis.2019.01.003
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