Analysis of Cost Efficiency, Travel Time, Characteristics of Goods and Load Capacity on The Selection of Transportation Modes Through Route Optimization as a Mediating Variable
DOI:
https://doi.org/10.38035/sjtl.v4i1.874Keywords:
Cost Efficiency, Transit Time, Shipment Characteristics, Load Capacity, Route Optimization, Transportation Mode SelectionAbstract
The Influence of Cost Efficiency, Transit Time, Shipment Characteristics, and Load Capacity on Transportation Mode Selection through Route Optimization as a Mediating Variable at PT Pos Indonesia Regional III Bandung. The increasing complexity of logistics distribution and higher service demands require companies to improve transportation efficiency through effective management of cost efficiency, transit time, shipment characteristics, and load capacity. This study aims to analyze the influence of cost efficiency, transit time, shipment characteristics, and load capacity on transportation mode selection through route optimization as a mediating variable at PT Pos Indonesia Regional III Bandung. This research employed a quantitative approach using Structural Equation Modeling–Partial Least Squares analysis. Data were collected through questionnaires distributed to respondents involved in the company’s distribution and transportation activities. The results indicate that cost efficiency, transit time, shipment characteristics, and load capacity have a positive and significant effect on route optimization. Furthermore, route optimization has a positive and significant effect on transportation mode selection. Cost efficiency, transit time, shipment characteristics, and load capacity also positively influence transportation mode selection both directly and indirectly through route optimization. The study concludes that route optimization plays a crucial role in improving transportation mode selection decisions and enhancing distribution efficiency within the company.
References
Ahmed, M., & Roorda, M. J. (2022). Modeling freight vehicle type choice using machine learning and discrete choice methods. Transportation Research Record. https://doi.org/10.1177/03611981211044462
National Development Planning Agency. (2023). National logistics development and strategies to strengthen Indonesia's logistics system. Bappenas.
Central Statistics Agency. (2023). Indonesian e-commerce statistics 2023. BPS.
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173
Bowersox, D. J., Closs, D. J., Cooper, M. B., & Bowersox, J. C. (2013). Supply chain logistics management (4th ed.). McGraw-Hill Education.
Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge.
Cahoot. (2026). SLA meaning in logistics: What service level agreements actually guarantee (and what they don't). Cahoot. https://www.cahoot.ai/sla-meaning-in-logistics/
Chang, C. H., & Thai, V. V. (2017). Shippers' choice behaviour in choosing transport mode: The case of Southeast Asia region. Asian Journal of Shipping and Logistics, 33(4), 199–210. https://doi.org/10.1016/j.ajsl.2017.12.003
Chen, X. (2022). Logistics path decision optimization method of fresh product export cold chain considering transportation risk. Journal of Transportation Engineering. https://doi.org/10.1155/2022/8924938
Christopher, M. (2016). Logistics and supply chain management (5th ed.). Pearson Education Limited.
Civelek, M. E., Uca, N., & Çemberci, M. (2022). The mediator effect of logistics performance in the relationship between transportation activities and supply chain performance. Sustainability, 14(15), 9457. https://doi.org/10.3390/su14159457
de Jong, G., Baak, J., Ben-Akiva, M., & Yamada, H. (2021). Freight mode choice: Results from a nationwide qualitative and quantitative research effort. Transportation Research Part A: Policy and Practice, 143, 78–120.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2019). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage Publications.
Heizer, J., Render, B., & Munson, C. (2020). Operations management: Sustainability and supply chain management (13th ed.). Pearson.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Kaewfak, K., Ammarapala, V., & Huynh, V. N. (2021). Multi-objective optimization of freight route choices in multimodal transportation. International Journal of Computational Intelligence Systems, 14(1), 794–807. https://doi.org/10.2991/ijcis.d.210308.001
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
Leffler, D., Burghout, W., Cats, O., & Jenelius, E. (2022). An adaptive route choice model for integrated fixed and flexible transit systems. Transportation Research Record. https://doi.org/10.1177/03611981221114250
Liu, Y., et al. (2022). Logistics distribution route optimization based on genetic algorithm. Journal of Logistics Systems. https://doi.org/10.1155/2022/8468438
Lu, X., & Wang, Y. (2022). Optimization of joint decision of transport mode and path in multimode freight transportation network. Sustainability, 14(18), Article 11658. https://doi.org/10.3390/su141811658
Masudin, I., Hanifah, Y. K. P., Dewi, S. K., Restuputri, D. P., & Handayani, D. I. (2022). Customer perception of logistics service quality using SIPA and modified Kano: Case study of Indonesian e-commerce. Logistics, 6(3), 51. https://doi.org/10.3390/logistics6030051
Meixell, M. J., & Norbis, M. (2008). A review of the transportation mode choice and carrier selection literature. The International Journal of Logistics Management, 19(2), 183–211. https://doi.org/10.1108/09574090810895951
Park, D., Kim, N. S., Park, H., & Kim, K. (2012). Estimating trade-off among logistics cost, CO₂ and time: A case study of container transportation systems in Korea. International Journal of Urban Sciences, 16(1), 85–98. https://doi.org/10.1080/12265934.2012.662973
Patil, R. A., Patange, A. D., & Pardeshi, S. S. (2023). International transportation mode selection through total logistics cost-based intelligent approach. Logistics, 7(3), 60. https://doi.org/10.3390/logistics7030060
Rodrigue, J. P. (2022). The geography of transport systems (5th ed.). Routledge.
RXO. (2025). Logistics KPI benchmarks: Research from 1,000 shippers & carriers. RXO. https://rxo.com/resources/research/kpi-research-study/
Santoso, S., Nurhidayat, R., Mahmud, G., & Arijuddin, A. M. (2021). Measuring the total logistics costs at the macro level: A study of Indonesia. Logistics, 5(68), 1–17. https://doi.org/10.3390/logistics5040068
Sharma, S., van Lint, H., Tavasszy, L., & Snelder, M. (2022). Estimating route choice characteristics of truck drivers from sparse automated vehicle identification data through data fusion and bi-objective optimization. Transportation Research Record, 2676(12), 378–392. https://doi.org/10.1177/03611981221109143
Shin, S., Roh, H. S., & Hur, S. H. (2019). Characteristics analysis of freight mode choice model according to the introduction of a new freight transport system. Sustainability, 11(4), 1209. https://doi.org/10.3390/su11041209
Shoukat, A., & Xiaoqiang, Z. (2023). Sustainable logistics network optimization from dry ports to seaport. Sustainability. https://doi.org/10.1177/03611981221115121
Slack, N., Brandon-Jones, A., & Johnston, R. (2019). Operations management (9th ed.). Pearson Education.
Stanković, M., et al. (2023). Optimizing utilization of transport capacities in the cold chain by introducing dynamic allocation of semi-trailers. Sustainability, 15(4), 3180. https://doi.org/10.3390/su15043180
Tagawa, H., Kawasaki, T., & Hanaoka, S. (2021). Conditions influencing the choice between direct shipment and transshipment in maritime shipping network. Journal of Shipping and Trade, 6(4), 1–18. https://doi.org/10.1186/s41072-021-00092-8
Toth, P., & Vigo, D. (2014). Vehicle routing: Problems, methods, and applications (2nd ed.). Society for Industrial and Applied Mathematics.
United Nations Conference on Trade and Development. (2024). Review of maritime transport 2024. United Nations.
World Bank. (2023). Connecting to compete 2023: Trade logistics in the global economy. World Bank.
Yakovlev, A., Korablev, P., Tsoy, Y., & Fedorov, A. (2022). Process optimization for last mile logistics. Transportation Research Procedia, 63, 1700–1707. https://doi.org/10.1016/j.trpro.2022.06.184
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Christin M, Maniah Maniah, Erna Mulyati

This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright :
Authors who publish their manuscripts in this journal agree to the following conditions:
- Copyright in each article belongs to the author.
- The author acknowledges that the Siber Journal of Transportation and Logistics (SJTL) has the right to be the first to publish under a Creative Commons Attribution 4.0 International license (Attribution 4.0 International CC BY 4.0).
- Authors can submit articles separately, arrange the non-exclusive distribution of manuscripts that have been published in this journal to other versions (for example, sent to the author's institutional repository, publication in a book, etc.), by acknowledging that the manuscript has been published for the first time at SJTL.






















