Developing A Sustainable and Effective Capacity Major Logistic Hubs in Indonesia
Keywords:
E-routing, logistic hub, effective capacity
Abstract
The study observed goals to degree the effective capability of logistics companies in Indonesia. Capacity is measured by the average load factor served per period with the queuing theory approach. The data used in this study were obtained from observations covering weekdays and weekends where the logistics company operates. The records compiled to seize versions in demand on the primary, middle, and quit of the working day with the item of studies divided into three regions, particularly western, crucial, and eastern Indonesia. The common load element information and the common ready time inside the queue are then used to degree the not unusual shipping of logistics merchandise served. The results showed that an effective logistics hub in the central part of Indonesia and other regions was less efficient due to the lack of routing development as well as demographic and geographical problems. The study concludes that logistics routes in Indonesia are categorized by region and hubs. Currently, not all operators implement e-routing due to the backbone of the technology infrastructure as well as financial reasons. There are significant differences regarding the area or scope of work logistics and distribution channels, the number of arrival units, the time spent in the waiting room when unloading goods, as well as the level of effective capacity in distribution infrastructure in Indonesia.
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Zhang, Z., & Zhang, C. (2020). An Empirical Study on the Impact of New Urbanization Pilot Policy on China’s Modern Logistics Development. Social and Economic Geography, 5(1). https://doi.org/10.12691/seg-5-1-3
Anderson, D. R., Sweeney, D. J., & William, T. A. (2011). Statistics for business and economics (11th ed.). Cengage Learning.
Charpin, R. (2022). The resurgence of nationalism and its implications for supply chain risk management. International Journal of Physical Distribution and Logistics Management, 52(1), 4–28. https://doi.org/10.1108/IJPDLM-01-2021-0019/FULL/XML
Chase, R. B., Jacobs, F. R., & Shankar, R. (2014). Operations and supply chain management.
Chukwudi Iwu, H., J. Ogbonna, C., Jude, O., & Georgina Onuma, K. (2014). Application of Inventory Model in Determining Stock Control in an Organization. American Journal of Applied Mathematics and Statistics, 2(5), 307–317. https://doi.org/10.12691/AJAMS-2-5-3
Duan, Y., Aloysius, J. A., & Mollenkopf, D. A. (2022). Communicating supply chain sustainability: transparency and framing effects. International Journal of Physical Distribution and Logistics Management, 52(1), 68–87. https://doi.org/10.1108/IJPDLM-04-2020-0107
Evan, J. ., & Collier, D. (2007). Operations Management: Processes and Supply Chains. Thomson. https://onesearch.id/Record/IOS2750.12.01.028/TOC
Evans, J. R., Evans, J. R., & Collier, D. A. (2007). Operations management : an integrated goods and services approach. Thomson/South-Western. http://books.google.es/books?id=PF78PAAACAAJ
Heizer, J., & Render, B. (2014). Operations management: sustainability and supply chain management. Pearson Education Limited. https://lib.ui.ac.id/detail?id=20418104
Kao, H. ., & Tsai, M. . (2022). Supply Chain Relationship, Earnings Management, and Operational Risks. Journal of Business and Management Sciences, 10(3), 147–156. https://doi.org/10.12691/jbms-10-3-6
Kliment, M., Trebuňa, P., & Straka, M. (2014). Tecnomatix Plant Simulation, Its Features and Its Integration into Business Processes in Logistics Systems. American Journal of Mechanical Engineering, 2(7), 286–289. https://doi.org/10.12691/AJME-2-7-24
Krajewski, Ritzman, L. J., Larry, P., & Malhotra, M. (2007). Operation. Management: Processesand Value Chains (eight). Pearson Prentice Hall.
Laith, W. H., Ali, S. S. A., & Mahmoud, M. A. (2017). Integrated Decision Making in Production Department inside Internal Supply Chain. American Journal of Industrial Engineering, Vol. 4, 2017, Pages 21-28, 4(1), 21–28. https://doi.org/10.12691/AJIE-4-1-4
Lantz, B., & Rosén, P. (2016). Measuring effective capacity in an emergency department. Journal of Health Organization and Management, 30(1), 73–84. https://doi.org/10.1108/JHOM-05-2014-0074
Lantz, B., & Rosén, P. (2017). Using queueing models to estimate system capacity. Http://Dx.Doi.Org/10.1080/09537287.2017.1329563, 28(13), 1037–1046. https://doi.org/10.1080/09537287.2017.1329563
Linda, D. A., Marchal, W. G., & Wathen, S. A. (2012). Statistical Techniques in Business and Economics. McGraw-Hill/Irwin. https://www.academia.edu/37003886/Statistical_Techniques_in_Business_and_Economics_by_Lind_Douglas_pdf
Mital, K. M. (2017). Queuing analysis for outpatient and inpatient services: A case study. https://doi.org/10.1108/00251741011037783
Mwamba, E., Masaiti, G., & Simui, F. (2021). Dynamic Effect of Rapid Urbanization on City Logistics : Literature Gleened Lessons for Developing Countries. 3(1), 37–47. https://doi.org/10.12691/jcd-3-1-5
Pekarčíková, M., Treburia, P., & Markovic, J. (2014). Time Structure Optimization of Logistics Chain during Assembly. American Journal of Mechanical Engineering, 2(7), 262–264. https://doi.org/10.12691/ajme-2-7-18
Rahman, A. U., & Zahura, M. T. (2018). A Grey Approach for the Prediction of Supply Chain Demand. American Journal of Industrial Engineering, Vol. 5, 2018, Pages 25-30, 5(1), 25–30. https://doi.org/10.12691/AJIE-5-1-4
Reid, R. D., & Sanders, N. (2007). Operations management : an integrated approach (3rd ed.). John Wiley & Sons, Inc.
Sadraoui, T., & Mchirgui, N. (2014). Supply Chain Management Optimization within Information System Development. International Journal of Econometrics and Financial Management, 2(2). https://doi.org/10.12691/ijefm-2-2-2
Sekaran, U., & Bougie, R. (2016). Research Method for Business : A Skill-Building Approach (Vol. 4, Issue 1). Wiley Publishing, Inc.
Shen, X., Feng, S., Li, Z., & Hu, B. (2016). Analysis of bus passenger comfort perception based on passenger load factor and in-vehicle time. SpringerPlus, 5(1), 1–10. https://doi.org/10.1186/S40064-016-1694-7/FIGURES/2
Stevenson, W. J., & Sum, C. C. (2014). Operations management. McGraw-Hill Education.
Tung, C. ., Chiu, S. ., & Yu, W. . (2020). Innovative Activities of a Logistics Company in the Global Value Chain. Journal of Business and Management Sciences, 8(3), 77–84. https://doi.org/10.12691/jbms-8-3-1
Wang, J., Zhang, J., & Li, J. (2014). A Scheduling Model of Coal Supply Chain Based on Supply Chain Management (SCM). American Journal of Industrial Engineering, 2(1), 15–20. https://doi.org/10.12691/ajie-2-1-4
Weeks, K., & Mileski, J. (2013). The Impact of Resource Commitment, Product Route Efficiency on Supply Chain Performance and Profitability: An Empirical Case Analysis. Journal of Business and Management Sciences, 1(5), 105–111. https://doi.org/10.12691/JBMS-1-5-4
Zhang, Z., & Zhang, C. (2020). An Empirical Study on the Impact of New Urbanization Pilot Policy on China’s Modern Logistics Development. Social and Economic Geography, 5(1). https://doi.org/10.12691/seg-5-1-3
Published
2022-08-05
How to Cite
Mohammad Annas, & Humairoh. (2022). Developing A Sustainable and Effective Capacity Major Logistic Hubs in Indonesia . Asian Journal of Management, Entrepreneurship and Social Science, 2(03), 245-260. Retrieved from https://ajmesc.com/index.php/ajmesc/article/view/136
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