Research Article
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Year 2022, , 130 - 142, 30.09.2022
https://doi.org/10.17261/Pressacademia.2022.1633

Abstract

References

  • Anandhi, S., Anitha, R., & Sureshkumar, V., (2019). IoT enabled RFID authentication and secure object tracking system for smart logistics. Wireless Personal Communications, (104), 543-560. DOI: https://doi.org/10.1007/s11277-018-6033-6
  • Bashir, H., Lee, S., & Kim, K. H., (2019). Resource allocation through logistic regression and multicriteria decision making method in IoT fog computing. Emerging Telecommunications Technologies, 33(2), 1-14. DOI: https://doi.org/10.1002/ett.3824
  • Bokor, Z. (2012). Cost calculation model for logistics service providers. Promet - Traffic & Transportation, 24(6), 515-524. DOI: 10.7307/ptt.v24i6.1198
  • Byun, S. (2019). Reliable Resource Management for IoT based Logistic Services, 2019 IEEE Eurasia Conference on IOT. Communication and Engineering (ECICE), IEEE, 522-525, doi: 10.1109/ECICE47484.2019.8942731
  • Chen, X., Chen, R., & Yang, C. (2021). Research to key success factors of intelligent logistics based on IoT technology. The Journal of Supercomputing, 78(4), 1-35. DOI: https://doi.org/10.1007/s11227-021-04009-7
  • Chen, Y., Sun, E. W., Chang, M., & Lin, Y., (2021). Pragmatic real-time logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0. International Journal of Production Economics, 238, 1-27. DOI: https://doi.org/10.1016/j.ijpe.2021.108157
  • Chopra, A. (2020). Conceptual framework of IoT for transport logistics an approach to connecting material flow and IT in self-directing collaborating logistics progressions. International Journal of System Assurance Engineering and Management, 11(2), 258-266 . DOI: https://doi.org/10.1007/s13198-020-00997-6
  • Correa, J. S., Sampaio, M., Barros, R. C., & Hilsdorf, W. C. (2020). IoT and BDA in the Brazilian future logistics 4.0 scenario. Production, 30(4), 1-14. DOI:10.1590/0103-6513.20190102
  • Forcolin, M., E., F., Tumanischvili, F., & Lupieri, P. (2011). EURIDICE – IoT applied to Logistics using the Intelligent Cargo Concept, 2011 17th International Conference on Concurrent Enterprising, June 20-22, 2011, Aachen, Germany: Proceedings of the 2011, 1-9.
  • Globerman, S., & Storer, P. (2015). Transportation costs and trade clusters: Some empirical evidence from U.S. customs districts. Research in Transportation Business & Management, 16(5), 67-73. DOI: http://dx.doi.org/10.1016/j.rtbm.2015.05.004
  • Guo, Y., & Qu, J. (2015). Study on intelligent logistics management information system based on IOT and cloud computation in big data era. Open Cybernetics & Systemics Journal, 9(1), 934-941. DOI: http://dx.doi.org/10.2174/1874110X01509010934
  • Hopkins, J., & Hawking, P. (2018). Big data analytics and IoT in logistics: a case study. International Journal of Logistics Management, 29(2), 575-591. DOI: 10.1108/IJLM-05-2017-0109
  • Humayun, M., Jhanjhi, N., Hamid, B., & Ahmed, G. (2020). Emerging smart logistics and transportation using IoT and blockchain. IEEE Internet of Things Magazine, 3(2), 58-62. DOI: 10.1109/IOTM.0001.1900097
  • Kaya, E. (2018). Lojistik ve Maliyet Yönetimi. M. Nalçakan, & F. Er, Lojistik İlkeleri (s. 130). Eskişehir: Anadolu Üniversitesi Açıköğretim Fakültesi Yayını.
  • Liu, S., Zhang, G., & Wang, L. (2018). IoT-enabled dynamic optimisation for sustainable reverse logistics . Procedia CIRP 69, 662-667. DOI: https://doi.org/10.1016/j.procir.2017.11.088
  • Lopes, Y. M., & Moori, R. G., (2021). The role of IoT in the relationship between strategic logistics management and operational performance. Resources and Entrepreneurial Development, 22(3), 1-27. DOI: 10.1590/1678-6971/eRAMR210032
  • Özdemir, A. (2018). Lojistiğin Temel Kavramları. M. Nalçakan, & F. Er içinde, Lojistik İlkeleri (s. 16). Eskişehir: Anadolu Üniversitesi Açıköğretim Fakültesi Yayını.
  • Prasse, C., Nettstraeter, A., & Hompel, M. (2014). How IoT will change the design and operation of logistics systems. 2014 International Conference on the Internet of Things (IOT), IEEE, 1-6. DOI: https://doi.org/10.1109/IOT.2014.7030115
  • Sebestyén, T. (2017). Moving beyond the iceberg model: The role of trade relations in endogenizing transportation costs in computable general equilibrium models. Economic Modelling, 67, 159-174. DOI: https://doi.org/10.1016/j.econmod.2016.11.015
  • Sergi, I., Montanaro, T., Benvenuto, F. L., & Patrono, L. (2021). A Smart and Secure Logistics System Based on IoT and Cloud Technologies. Sensors, 21(6), 1-23. DOI: https://doi.org/10.3390/s21062231
  • Shah, S., Rutherford, R., & Menon, S. (2020). Emerging Technologies of IoT Usage in Global Logistics. 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM), IEEE, 251-257. DOI: 10.1109/ICCAKM46823.2020.9051530
  • Shine-Der, L., & Yen-Chen, F. (2014). Joint production and delivery loT sizing for a make-to-order producer–buyer supply chain with transportation cost. Transportation Research Part E (66), 23-35. DOI: https://doi.org/10.1016/j.tre.2014.03.002
  • Song, Y., Yu, F. R., Zhou, L., Yang, X., & He, Z. (2021). Applications of the Internet of Things (IoT) in smart logistics: a comprehensive survey. Internet of Things Journal, 8(6), 4250-4274. DOI: https://doi.org/10.1109/JIOT.2020.3034385
  • Stępień, M., Łęgowik-Świącik, S., Skibińska, W., & Turek, I. (2016). Identification and measurement of logistics cost parameters in the company. Transportation Research Procedia, (16), 490-497. DOI: http://dx.doi.org/10.1016/j.trpro.2016.11.046
  • Tu, M. (2018). An exploratory study of Internet of Things (IoT) adoption intention in logistics and supply chain management. The International Journal of Logistics Management, 29(1), 131-151. DOI:10.1108/IJLM-11-2016-0274
  • Tu, M., Lim, M. K., & Yang, M.-F. (2018). IoT-based production logistics and supply chain system – Part 1. Industrial Management & Data Systems, 118(1), 65-95. DOI:10.1108/IMDS-11-2016-0503
  • Turkensteen, M., & Klose, A. (2012). Demand dispersion and logistics costs in one-to-many distribution systems. European Journal of Operational Research, 223(2), 499-507. DOI: http://dx.doi.org/10.1016/j.ejor.2012.06.008
  • Wang, J., Lim, M. K., Zhan, Y., & Wang, X. F. (2020). An intelligent logistics service system for enhancing dispatching operations in an IoT environment. Transportation Research, Part E(135), 1-23. DOI: https://doi.org/10.1016/j.tre.2020.101886
  • Zhang, Y., Guo, Z., Lv, J., & Liu, Y. (2018). A Framework for Smart Production-Logistics Systems Based on CPS and Industrial IoT . Transactions On Industrial Informatics, 14(9), 4019-4032. DOI: https://doi.org/10.1109/TII.2018.2845683

THE EFFECTS OF INTERNET OF THINGS ON THE TRANSPORTATION COST MANAGEMENT: A STUDY OF LOGISTICS COMPANY

Year 2022, , 130 - 142, 30.09.2022
https://doi.org/10.17261/Pressacademia.2022.1633

Abstract

Purpose- The purpose of this study is to examine the Internet of Things (IoT) conceptually and structurally. In this regard, the study will
examine the potential effects of the investments of the Internet of Things in the transportation operations of logistics, discuss the potential
effects of the transportation costs of the Internet of Things and investments on control and Management. This study also analyze and
evaluate such investments in a logistics company.
Methodology- In order to examine the potential effects of IoT investments on the management of transportation costs, an interview was
conducted with an Istanbul-centered company of logistics service provider in this study. The data were collected and evaluated by asking
open-ended questions within the scope of qualitative research with an interview technique.
Findings- It was determined that the company gained the advantage of real-time monitoring and controlling of the transportation operations,
real-time monitoring of vehicles and drivers, monitoring of the thermal conditions of loads, monitoring and controlling of the incidents of
losses and accidents through hardware and various technology like the Internet of Things (IoT) and integrated sensors to it. On the other
hand, the study received comprehensive support of data from the company about the transportation process and the control of vehicles,
loads, and drivers with IoT investments and the costs of transportation. Thus, the study obtained significant advantages for determining,
calculating, and controlling costs. However, since IoT investments are new, and R & D operations for some integrated technologies continue
in the company, the quantitative data that include cost advantages have not been formed yet. Therefore, a limited evaluation was conducted.
Conclusion- Technically, IoT is a technology that connects the vehicles in transportation operations in logistics with smart networks. IoT
enables complete control and real-time monitoring for transportation operations, and it can decrease setbacks and waiting during the
transportation process. In this regard, it can increase the management power for the transportation costs by offering advantageous qualities,
such as comprehensive data support and real-time monitoring for determining and calculating the transportation costs and controlling
expenses or spending. Hence, IoT can increase value-added for transportation operations and provide competitive pricing advantages with
its cost. Consequently, IoT investments can provide advantages like “offering a transportation service with high value-added to supply chains,
decreasing the costs of vehicles and drivers, and optimal pricing” to logistics companies against their opponents.

References

  • Anandhi, S., Anitha, R., & Sureshkumar, V., (2019). IoT enabled RFID authentication and secure object tracking system for smart logistics. Wireless Personal Communications, (104), 543-560. DOI: https://doi.org/10.1007/s11277-018-6033-6
  • Bashir, H., Lee, S., & Kim, K. H., (2019). Resource allocation through logistic regression and multicriteria decision making method in IoT fog computing. Emerging Telecommunications Technologies, 33(2), 1-14. DOI: https://doi.org/10.1002/ett.3824
  • Bokor, Z. (2012). Cost calculation model for logistics service providers. Promet - Traffic & Transportation, 24(6), 515-524. DOI: 10.7307/ptt.v24i6.1198
  • Byun, S. (2019). Reliable Resource Management for IoT based Logistic Services, 2019 IEEE Eurasia Conference on IOT. Communication and Engineering (ECICE), IEEE, 522-525, doi: 10.1109/ECICE47484.2019.8942731
  • Chen, X., Chen, R., & Yang, C. (2021). Research to key success factors of intelligent logistics based on IoT technology. The Journal of Supercomputing, 78(4), 1-35. DOI: https://doi.org/10.1007/s11227-021-04009-7
  • Chen, Y., Sun, E. W., Chang, M., & Lin, Y., (2021). Pragmatic real-time logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0. International Journal of Production Economics, 238, 1-27. DOI: https://doi.org/10.1016/j.ijpe.2021.108157
  • Chopra, A. (2020). Conceptual framework of IoT for transport logistics an approach to connecting material flow and IT in self-directing collaborating logistics progressions. International Journal of System Assurance Engineering and Management, 11(2), 258-266 . DOI: https://doi.org/10.1007/s13198-020-00997-6
  • Correa, J. S., Sampaio, M., Barros, R. C., & Hilsdorf, W. C. (2020). IoT and BDA in the Brazilian future logistics 4.0 scenario. Production, 30(4), 1-14. DOI:10.1590/0103-6513.20190102
  • Forcolin, M., E., F., Tumanischvili, F., & Lupieri, P. (2011). EURIDICE – IoT applied to Logistics using the Intelligent Cargo Concept, 2011 17th International Conference on Concurrent Enterprising, June 20-22, 2011, Aachen, Germany: Proceedings of the 2011, 1-9.
  • Globerman, S., & Storer, P. (2015). Transportation costs and trade clusters: Some empirical evidence from U.S. customs districts. Research in Transportation Business & Management, 16(5), 67-73. DOI: http://dx.doi.org/10.1016/j.rtbm.2015.05.004
  • Guo, Y., & Qu, J. (2015). Study on intelligent logistics management information system based on IOT and cloud computation in big data era. Open Cybernetics & Systemics Journal, 9(1), 934-941. DOI: http://dx.doi.org/10.2174/1874110X01509010934
  • Hopkins, J., & Hawking, P. (2018). Big data analytics and IoT in logistics: a case study. International Journal of Logistics Management, 29(2), 575-591. DOI: 10.1108/IJLM-05-2017-0109
  • Humayun, M., Jhanjhi, N., Hamid, B., & Ahmed, G. (2020). Emerging smart logistics and transportation using IoT and blockchain. IEEE Internet of Things Magazine, 3(2), 58-62. DOI: 10.1109/IOTM.0001.1900097
  • Kaya, E. (2018). Lojistik ve Maliyet Yönetimi. M. Nalçakan, & F. Er, Lojistik İlkeleri (s. 130). Eskişehir: Anadolu Üniversitesi Açıköğretim Fakültesi Yayını.
  • Liu, S., Zhang, G., & Wang, L. (2018). IoT-enabled dynamic optimisation for sustainable reverse logistics . Procedia CIRP 69, 662-667. DOI: https://doi.org/10.1016/j.procir.2017.11.088
  • Lopes, Y. M., & Moori, R. G., (2021). The role of IoT in the relationship between strategic logistics management and operational performance. Resources and Entrepreneurial Development, 22(3), 1-27. DOI: 10.1590/1678-6971/eRAMR210032
  • Özdemir, A. (2018). Lojistiğin Temel Kavramları. M. Nalçakan, & F. Er içinde, Lojistik İlkeleri (s. 16). Eskişehir: Anadolu Üniversitesi Açıköğretim Fakültesi Yayını.
  • Prasse, C., Nettstraeter, A., & Hompel, M. (2014). How IoT will change the design and operation of logistics systems. 2014 International Conference on the Internet of Things (IOT), IEEE, 1-6. DOI: https://doi.org/10.1109/IOT.2014.7030115
  • Sebestyén, T. (2017). Moving beyond the iceberg model: The role of trade relations in endogenizing transportation costs in computable general equilibrium models. Economic Modelling, 67, 159-174. DOI: https://doi.org/10.1016/j.econmod.2016.11.015
  • Sergi, I., Montanaro, T., Benvenuto, F. L., & Patrono, L. (2021). A Smart and Secure Logistics System Based on IoT and Cloud Technologies. Sensors, 21(6), 1-23. DOI: https://doi.org/10.3390/s21062231
  • Shah, S., Rutherford, R., & Menon, S. (2020). Emerging Technologies of IoT Usage in Global Logistics. 2020 International Conference on Computation, Automation and Knowledge Management (ICCAKM), IEEE, 251-257. DOI: 10.1109/ICCAKM46823.2020.9051530
  • Shine-Der, L., & Yen-Chen, F. (2014). Joint production and delivery loT sizing for a make-to-order producer–buyer supply chain with transportation cost. Transportation Research Part E (66), 23-35. DOI: https://doi.org/10.1016/j.tre.2014.03.002
  • Song, Y., Yu, F. R., Zhou, L., Yang, X., & He, Z. (2021). Applications of the Internet of Things (IoT) in smart logistics: a comprehensive survey. Internet of Things Journal, 8(6), 4250-4274. DOI: https://doi.org/10.1109/JIOT.2020.3034385
  • Stępień, M., Łęgowik-Świącik, S., Skibińska, W., & Turek, I. (2016). Identification and measurement of logistics cost parameters in the company. Transportation Research Procedia, (16), 490-497. DOI: http://dx.doi.org/10.1016/j.trpro.2016.11.046
  • Tu, M. (2018). An exploratory study of Internet of Things (IoT) adoption intention in logistics and supply chain management. The International Journal of Logistics Management, 29(1), 131-151. DOI:10.1108/IJLM-11-2016-0274
  • Tu, M., Lim, M. K., & Yang, M.-F. (2018). IoT-based production logistics and supply chain system – Part 1. Industrial Management & Data Systems, 118(1), 65-95. DOI:10.1108/IMDS-11-2016-0503
  • Turkensteen, M., & Klose, A. (2012). Demand dispersion and logistics costs in one-to-many distribution systems. European Journal of Operational Research, 223(2), 499-507. DOI: http://dx.doi.org/10.1016/j.ejor.2012.06.008
  • Wang, J., Lim, M. K., Zhan, Y., & Wang, X. F. (2020). An intelligent logistics service system for enhancing dispatching operations in an IoT environment. Transportation Research, Part E(135), 1-23. DOI: https://doi.org/10.1016/j.tre.2020.101886
  • Zhang, Y., Guo, Z., Lv, J., & Liu, Y. (2018). A Framework for Smart Production-Logistics Systems Based on CPS and Industrial IoT . Transactions On Industrial Informatics, 14(9), 4019-4032. DOI: https://doi.org/10.1109/TII.2018.2845683
There are 29 citations in total.

Details

Primary Language English
Subjects Economics, Behaviour-Personality Assessment in Psychology, Finance, Business Administration
Journal Section Articles
Authors

Mehmet Cakmak This is me 0000-0002-6128-5607

Yildiz Ozerhan This is me 0000-0002-1589-2692

Publication Date September 30, 2022
Published in Issue Year 2022

Cite

APA Cakmak, M., & Ozerhan, Y. (2022). THE EFFECTS OF INTERNET OF THINGS ON THE TRANSPORTATION COST MANAGEMENT: A STUDY OF LOGISTICS COMPANY. Journal of Business Economics and Finance, 11(3), 130-142. https://doi.org/10.17261/Pressacademia.2022.1633

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