MAPPING DIGITAL TECHNOLOGIES IN LOGISTICS: EXPLORING TRENDS AND FUTURE DIRECTIONS

Öz

The rapid advancement of technology, the increasing interconnectedness between countries, and the evolving consumer demands have made logistics networks increasingly complex. Consequently, using digital technologies to analyze data sources within logistics networks has become significantly important. These technologies are critically important for minimizing costs, improving service quality, and enabling more flexible and faster decision-making through the digital tracking of every stage in logistics processes. Within this context, this study aims to examine studies on the use of digital technologies in the logistics sector through bibliometric analysis and to identify prominent topics and concepts in this field. Accordingly, a search was conducted in the Web of Science database using keywords related to logistics and digital technologies, and 1,597 publications from the period 1983–2024 were analyzed using the R program. The findings indicate a sharp increase in studies after 2017, coinciding with the rise of Industry 4.0. "Internet," "technology," and "challenges" emerged as the most frequent keywords. China and the USA were identified as leading contributors, while regions such as South America, Africa, and Australia showed weaker collaboration networks. The study contributes to literature by mapping the evolution of key themes and identifying underexplored topics such as ethics, data privacy, cybersecurity, government regulations, and human-centered approaches. Practically, it highlights the need for stronger international collaborations and more empirical research on real-life applications of digital technologies in logistics. By identifying trends and research gaps, this study provides insights that can guide both academics and practitioners in advancing the digital transformation of logistics.

Anahtar Kelimeler

• Digital Technologies
• Digitalization
• Logistics
• Supply Chain Management
• Bibliometric Analysis

LOJİSTİKTE DİJİTAL TEKNOLOJİLERİN HARİTALANDIRILMASI: EĞİLİMLERİN VE GELECEK YÖNELİMLERİN ARAŞTIRILMASI

Öz

Teknolojinin hızlı bir şekilde gelişmesi, ülkeler arasındaki bağlantıların artması ve farklılaşan tüketici talepleriyle birlikte lojistik ağlar da giderek karmaşık hale gelmektedir. Bu nedenle lojistik ağlarda yer alan veri kaynaklarının analizinde dijital teknolojilerin kullanımı önem kazanmıştır. Bu teknolojiler; maliyetlerin minimize edilmesi, hizmet kalitesinin artırılması, lojistik süreçlerde her aşamanın dijital olarak takibiyle daha esnek ve hızlı karar alabilme yeteneğinin sağlanması konusunda kritik öneme sahiptir. Bu kapsamda bu çalışmanın temel amacı dijital teknolojilerin lojistik sektöründe kullanımı ile ilgili çalışmaları bibliyometrik analiz yöntemiyle incelemek ve bu alanda öne çıkan konu ve kavramları tespit etmektir. Bu doğrultuda; Web of Science veri tabanında lojistik ve dijital teknolojilerle ilgili anahtar kelimeler ile arama yapılmış, 1983-2024 dönemindeki 1597 yayın R programıyla analiz edilmiştir. Bulgular, 2017 sonrasında çalışmaların hızlı bir şekilde artış gösterdiğini ve bunun Endüstri 4.0’ın yükselişiyle eşzamanlı olduğunu ortaya koymaktadır. En sık kullanılan anahtar kelimeler "internet," "teknoloji" ve "zorluklar" olarak belirlenmiştir. Çin ve ABD başlıca katkı sağlayan ülkeler olarak öne çıkarken, Güney Amerika, Afrika ve Avustralya gibi bölgelerde iş birliği ağlarının daha zayıf olduğu görülmüştür. Çalışma, etik, veri gizliliği, siber güvenlik, hükümet düzenlemeleri ve insan merkezli yaklaşımlar gibi yeterince araştırılmamış konuları tanımlayarak temel temaların evrimini haritalandırmak suretiyle literatüre katkı sağlamaktadır. Uygulama açısından ise, daha güçlü uluslararası iş birliklerine ve lojistikte dijital teknolojilerin gerçek yaşam uygulamaları üzerine daha fazla ampirik araştırmaya duyulan ihtiyacı vurgulamaktadır. Eğilimleri ve araştırma boşluklarını belirleyerek, bu çalışma lojistiğin dijital dönüşümünü ilerletmede hem akademisyenlere hem de uygulayıcılara yol gösterici nitelikte içgörüler sunmaktadır.

Anahtar Kelimeler

• Dijital Teknolojiler
• Dijitalleşme
• Lojistik
• Tedarik Zinciri Yönetimi
• Bibliyometrik Analiz

Kaynakça

1. Abdulrashid, I., Zanjirani Farahani, R., Mammadov, S., Khalafalla, M., & Chiang, W.-C. (2024). Explainable artificial intelligence in transport logistics: risk analysis for road accidents. Transportation Research Part E: Logistics and Transportation Review, 186, 103563. https://doi.org/10.1016/j.tre.2024.103563
2. Admoko, D. A., Darmawan, B., Ana, A., & Dwiyanti, V. (2024). A cluster-based bibliometric analysis of the emerging technological landscape in logistics using Vosviewer. Journal of Advanced Research in Applied Sciences and Engineering Technology, 42(2), 234–249. https://doi.org/10.37934/araset.42.2.234249
3. Albrecht, T., Baier, M.-S., Gimpel, H., Meierhöfer, S., Röglinger, M., Schlüchtermann, J., & Will, L. (2024). Leveraging digital technologies in Logistics 4.0: insights on affordances from intralogistics processes. Information Systems Frontiers, 26(2), 755–774. https://doi.org/10.1007/s10796-023-10394-6
4. Alnasser, A., Al Ghofaili, A. Y. R., Almushaiti, M. A., & AlZaidan, Z. I. (2024). Navigating digital transformation in alignment with Vision 2030: a review of organizational strategies, innovations, and implications in Saudi Arabia. Journal of Knowledge Learning and Science Technology, 3(2), 21–29. https://doi.org/10.60087/jklst.vol3.n2.p29
5. Atzeni, G., Vignali, G., Tebaldi, L., & Bottani, E. (2021). A bibliometric analysis on collaborative robots in Logistics 4.0 environments. Procedia Computer Science, 180, 686–695. https://doi.org/10.1016/j.procs.2021.01.291
6. Autore, D., Chen, H. (Amy), Clarke, N., & Lin, J. (2024). Blockchain and earnings management: evidence from the supply chain. The British Accounting Review, 56(4), 101357. https://doi.org/10.1016/j.bar.2024.101357
7. Aziz, G., Strielkowski, W., Sarwar, S., & Tiwari, A. K. (2024). Implications of circular economy, digitalization and technological innovation to achieve sustainable environmental goal: pre and post-vision 2030. Heliyon, 10(10), e30978. https://doi.org/10.1016/j.heliyon.2024.e30978
8. Benatiya Andaloussi, M. (2024). A bibliometric literature review of digital supply chain: trends, insights, and future directions. Sage Open, 14(2), 21582440241240340. https://doi.org/10.1177/21582440241240340

9. Bendary, M. G., & Rajadurai, J. (2024). Emerging technologies and public innovation in the Saudi public sector: an analysis of adoption and challenges amidst Vision 2030. Innovation Journal, 29(1), 1–42.
10. Boute, R. N., & Udenio, M. (2023). AI in logistics and supply chain management. In R. Merkert & K. Hoberg (Eds.), Global logistics and supply chain strategies for the 2020s: vital skills for the next generation (pp. 49–65). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-95764-3_3
11. Büyükkıdık, S. (2022). A bibliometric analysis: a tutorial for the bibliometrix package in R using IRT literature. Journal of Measurement and Evaluation in Education and Psychology, 13(3), 164–193.
12. Çağlar, M. B. & Karagöz Taşkın, B. (2023). The effects of using artificial intelligence and robotic in logistics service production: an application in 3PLs and 4PLs. Logforum, 19(3), 347-360. https://doi.org/10.17270/J.LOG.2023.856
13. Chen, Y., Wang, W., Yang, Z., Deveci, M., & Delen, D. (2024). Evaluating risk of IoT adoption in the food supply chain using an integrated interval-valued spherical fuzzy generalised TODIM method. International Journal of Production Economics, 277, 109386. https://doi.org/10.1016/j.ijpe.2024.109386
14. Derviş, H. (2019). Bibliometric analysis using bibliometrix an R package. Journal of Scientometric Research, 8(3), 156–160.
15. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: an overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
16. Dreyfus, D. (2024). Blockchain technology in the supply chain management classroom: proof of attendance protocols. Journal of Innovation Education, 22(4), 260–269. https://doi.org/10.1111/dsji.12312
17. Fan, Q., Wang, Y., & Liang, S. (2024, May 7). Study on the development and future of Hong Kong trade logistics. 634–652. Atlantis Press. https://doi.org/10.2991/978-94-6463-408-2_71
18. Fareed, A. G., De Felice, F., Forcina, A., & Petrillo, A. (2024). Role and applications of advanced digital technologies in achieving sustainability in multimodal logistics operations: a systematic literature review. Sustainable Futures, 8, 100278. https://doi.org/10.1016/j.sftr.2024.100278
19. He, X., Hu, W., Li, W., & Hu, R. (2023). Digital transformation, technological innovation, and operational resilience of port firms in case of supply chain disruption. Marine Pollution Bulletin, 190, 114811. https://doi.org/10.1016/j.marpolbul.2023.114811
20. Hejazi, M. T. (2024). The impact of digitalization practices on supply chain sustainability and organizational sustainability. WSEAS Transactions on Business and Economics, 21, 35-43. https://doi.org/10.37394/23207.2024.21.4
21. Hiatt, B., Hong, S.-J., Kwon, I.-W., & Savoie, M. (2024). Digitalization and the medical supply chain management: systematic literature review and bibliometric analysis. Operations and Supply Chain Management: An International Journal, 17(3), 128–140. https://doi.org/10.31387/oscm0580431
22. Iftikhar, A., Ali, I., Arslan, A., & Tarba, S. (2024). Digital innovation, data analytics, and supply chain resiliency: a bibliometric-based systematic literature review. Annals of Operations Research, 333(2), 825–848. https://doi.org/10.1007/s10479-022-04765-6
23. Indradevi, R., Natarajan, S., & Sathyamoorthy, V. K. P. (2024). Does disruptive technology and AI (Artificial Intelligence) influence logistics management? Multidisciplinary Science Journal, 6(12), e2024259. https://doi.org/10.31893/multiscience.2024259
24. Institute for Security and Development Policy. (2018). Made in China 2025. Retrieved December 15, 2024, from https://www.isdp.eu/wp-content/uploads/2018/06/Made-in-China-Backgrounder.pdf
25. International Trade Administration. (2024). Information and communication technology—overview. Retrieved December 2, 2024, from https://www.trade.gov/country-commercial-guides/india-information-and-communication-technology
26. Ivanova, T., & Shkrobot, M. (2023). Digitalization in the reverse supply chain: a bibliometric analysis. LogForum, 19(4), 683–702. https://doi.org/10.17270/J.LOG.2023.865
27. Jackson, I., Ivanov, D., Dolgui, A., & Namdar, J. (2024). Generative artificial intelligence in supply chain and operations management: a capability-based framework for analysis and implementation. International Journal of Production Research, 62(17), 6120–6145. https://doi.org/10.1080/00207543.2024.2309309
28. Jiang, Z., & Xu, C. (2024). Disrupting the technology innovation efficiency of manufacturing enterprises through digital technology promotion: an evidence of 5g technology construction in China. IEEE Transactions on Engineering Management, 71, 6918–6928. https://doi.org/10.1109/TEM.2023.3261940
29. Kayikci, Y. (2018). Sustainability impact of digitization in logistics. Procedia Manufacturing, 21, 782–789. https://doi.org/10.1016/j.promfg.2018.02.184
30. Khanra, S., Kaur, P., Joseph, R. P., Malik, A., & Dhir, A. (2022). A resource‐based view of green innovation as a strategic firm resource: present status and future directions. Business Strategy and the Environment, 31(4), 1395–1413. https://doi.org/10.1002/bse.2961
31. Larsen, M. H., & Lund, M. S. (2021). Cyber risk perception in the maritime domain: a systematic literature review. IEEE Access, 9, 144895–144905. https://doi.org/10.1109/ACCESS.2021.3122433
32. Latif, M. N. A., Aziz, N. A. A., Hussin, N. S. N., & Aziz, Z. A. (2021). Cyber security in supply chain management: A systematic review. LogForum, 17(1), 49–57. https://doi.org/10.17270/J.LOG.2021.555
33. Lee, K. L., Teong, C. X., Alzoubi, H. M., Alshurideh, M. T., Khatib, M. E., & Al-Gharaibeh, S. M. (2024). Digital supply chain transformation: the role of smart technologies on operational performance in manufacturing industry. International Journal of Engineering Business Management, 16, 18479790241234986. https://doi.org/10.1177/18479790241234986
34. Li, X., Krivtsov, V., Pan, C., Nassehi, A., Gao, R. X., & Ivanov, D. (2024). End-to-end supply chain resilience management using deep learning, survival analysis, and explainable artificial intelligence. International Journal of Production Research, 1–29. https://doi.org/10.1080/00207543.2024.2367685
35. Liu, K. P., & Chiu, W. (2021). Supply Chain 4.0: The impact of supply chain digitalization and integration on firm performance. Asian Journal of Business Ethics, 10(2), 371–389. https://doi.org/10.1007/s13520-021-00137-8
36. Liu, Q., Ma, Y., Chen, L., Pedrycz, W., Skibniewski, M. J., & Chen, Z.-S. (2024). Artificial intelligence for production, operations and logistics management in modular construction industry: a systematic literature review. Information Fusion, 109, 102423. https://doi.org/10.1016/j.inffus.2024.102423
37. Liu, Z., Zhao, Y., Guo, C., & Xin, Z. (2024). Research on the impact of digital-real integration on logistics industrial transformation and upgrading under Green Economy. Sustainability, 16(14), 6173. https://doi.org/10.3390/su16146173
38. Lotfi, R., Hazrati, R., Aghakhani, S., Afshar, M., Amra, M., & Ali, S. S. (2024). A data-driven robust optimization in viable supply chain network design by considering Open Innovation and Blockchain Technology. Journal of Cleaner Production, 436, 140369. https://doi.org/10.1016/j.jclepro.2023.140369
39. Ma, L., & Chang, R. (2024). How big data analytics and artificial intelligence facilitate digital supply chain transformation: the role of integration and agility. Management Decision, ahead-of-print(ahead-of-print). (world). https://doi.org/10.1108/MD-10-2023-1822
40. Masoomi, B., Sahebi, I. G., Gholian-Jouybari, F., Mejia-Argueta, C., & Hajiaghaei-Keshteli, M. (2024). The role of internet of things adoption on the sustainability performance of the renewable energy supply chain: a conceptual framework. Renewable and Sustainable Energy Reviews, 202, 114610. https://doi.org/10.1016/j.rser.2024.114610
41. Miah, M. T., Lakner, Z., & Fekete-Farkas, M. (2024). Addressing poverty through social entrepreneurship for sustainable development: a comprehensive bibliometric analysis. Administrative Sciences, 14(1), 16. https://doi.org/10.3390/admsci14010016
42. Moldabekova, A., Philipp, R., Reimers, H. E., & Alikozhayev, B. (2021). Digital technologies for improving logistics performance of countries. Transport and Telecommunication, 22(2), 207-216. https://doi.org/10.2478/ttj-2021-0016
43. Neilson, A., Indratmo, Daniel, B., & Tjandra, S. (2019). Systematic review of the literature on big data in the transportation domain: concepts and applications. Big Data Research, 17, 35–44. https://doi.org/10.1016/j.bdr.2019.03.001
44. Nour, R. (2022). Enhancing the Logistics 4.0 firms through information technology. Sustainability, 14(23), 15860. https://doi.org/10.3390/su142315860
45. OECD. (2024). Digital Economy Outlook 2024 (Volume 1). Retrieved November 25, 2024, from https://www.oecd.org/content/dam/oecd/en/publications/reports/2024/05/oecd-digital-economy-outlook-2024-volume-1_d30a04c9/a1689dc5-en.pdf
46. Oğuz, S., Alkan, G., Yilmaz, B., & Kocabaş, C. (2024). The use of blockchain technology in logistics and supply chain management (SCM): a systematic review. IEEE Access, 12, 166211–166224. https://doi.org/10.1109/ACCESS.2024.3494674
47. Oršič, J., Jereb, B., & Obrecht, M. (2022). Sustainable operations of last mile logistics based on machine learning processes. Processes, 10(12), 2524. https://doi.org/10.3390/pr10122524
48. Oubrahim, I., Sefiani, N., & Happonen, A. (2023). The influence of digital transformation and supply chain integration on overall sustainable supply chain performance: an empirical analysis from manufacturing companies in Morocco. Energies, 16(2), 1004. https://doi.org/10.3390/en16021004
49. Overvelde, R. M. (2021). Digitalization in logistics: Small, medium and large-sized organizations (a comparison study in the Dutch logistics sector). 35th Twente Student Conference on IT, Enschede, The Netherlands.
50. Park, M., & Singh, N. P. (2022). Predicting supply chain risks through big data analytics: Role of risk alert tool in mitigating business disruption. Benchmarking: An International Journal, 30(5), 1457–1484. (world). https://doi.org/10.1108/BIJ-03-2022-0169
51. Passas, I. (2024). Bibliometric analysis: the main steps. Encyclopedia, 4(2), 1014–1025.
52. Pasupuleti, V., Thuraka, B., Kodete, C. S., & Malisetty, S. (2024). Enhancing supply chain agility and sustainability through machine learning: optimization techniques for logistics and inventory management. Logistics, 8(3), 73. https://doi.org/10.3390/logistics8030073
53. Patro, P. K., Acquaye, A., Jayaraman, R., & Salah, K. (2024). Blockchain, IoT, and AI-based framework for traceability in carbon capture utilization storage (CCUS) supply chain. Proceedings of the 2024 6th Blockchain and Internet of Things Conference, 67–73. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3688225.3688234
54. Patrucco, A. S., Marzi, G., & Trabucchi, D. (2023). The role of absorptive capacity and big data analytics in strategic purchasing and supply chain management decisions. Technovation, 126, 102814. https://doi.org/10.1016/j.technovation.2023.102814
55. Ran, J., Ma, H., & Ran, R. (2024). The role of big data and IoT in logistics supply chain management of e-commerce. Journal of Computational Methods in Sciences and Engineering, 24(2), 813–822. https://doi.org/10.3233/JCM-237067
56. Rashid, A., Rasheed, R., Ngah, A. H., & Amirah, N. A. (2024). Unleashing the power of cloud adoption and artificial intelligence in optimizing resilience and sustainable manufacturing supply chain in the USA. Journal of Manufacturing Technology Management, 35(7), 1329–1353. (world). https://doi.org/10.1108/JMTM-02-2024-0080
57. Rejeb, A., Simske, S., Rejeb, K., Treiblmaier, H., & Zailani, S. (2020). Internet of Things research in supply chain management and logistics: a bibliometric analysis. Internet of Things, 12, 100318. https://doi.org/10.1016/j.iot.2020.100318
58. Seyedghorban, Z., Tahernejad, H., Meriton, R., & Graham, G. (2020). Supply chain digitalization: past, present and future. Production Planning & Control, 31(2–3), 96–114.
59. Sharma, V. (2023). Impact of automation on retail logistics: AI-powered solutions for efficient supply chains. International Journal of Scientific Research in Engineering and Management, 7(9), 1–17. https://doi.org/10.55041/IJSREM25850
60. Shi, Y., Zheng, X., Venkatesh, V. G., Humdan, E. A., & Paul, S. K. (2023). The impact of digitalization on supply chain resilience: an empirical study of the Chinese manufacturing industry. Journal of Business & Industrial Marketing, 38(1), 1-11. https://doi.org/10.1108/JBIM-09-2021-0456
61. Shoomal, A., Jahanbakht, M., Componation, P. J., & Ozay, D. (2024). Enhancing supply chain resilience and efficiency through internet of things integration: challenges and opportunities. Internet of Things, 27, 101324. https://doi.org/10.1016/j.iot.2024.101324
62. Srivastava, S. K., Routray, S., Bag, S., Gupta, S., & Zhang, J. Z. (2024). Exploring the potential of large language models in supply chain management: a study using big data. Journal of Global Information Management (JGIM), 32(1), 1–29. https://doi.org/10.4018/JGIM.335125
63. Statista. (2024). Digital investment – United States. Retrieved November 28, 2024, from https://www.statista.com/outlook/dmo/fintech/digital-investment/united-states
64. Tavana, M., Sohrabi, M., Rezaei, H., Sorooshian, S., & Mina, H. (2024). A sustainable circular supply chain network design model for electric vehicle battery production using internet of things and big data. Expert Systems, 41(7), e13395. https://doi.org/10.1111/exsy.13395
65. Transport and Logistics Bureau. (2024). Action on modern logistics development. Retrieved November 18, 2024, from https://www.tlb.gov.hk/doc/Action%20Plan%20on%20Modern%20Logistics%20Development_e.pdf
66. United Nations. (2024). Digital economy report. Retrieved December 22, 2024, from https://unctad.org/system/files/official-document/der2024_en.pdf
67. World Bank (2023). Logistics performance index. Retrieved August 08, 2025, from https://lpi.worldbank.org/index.php/international/global
68. Yavas, V., & Ozkan-Ozen, Y. D. (2023). Bibliometric analysis of the transformation in air logistics operations in terms of digitalization and sustainability. Visions for Sustainability, 19, 321–342. https://doi.org/10.13135/2384-8677/6991
69. Yılmaz, B. (2025). Determining the digitalization levels of leading countries in Logistics Performance Index: an application with CRITIC-TOPSIS approach. Journal of Productivity, 59(2), 431-450. https://doi.org/10.51551/verimlilik.1541480
70. Yilmaz, B. (2025). Cybersecurity applications in the maritime industry: A scientometric approach. Scientific Journal of Maritime Research-Pomorstvo, 39(2), 254-278. https://doi.org/10.31217/p.39.2.6
71. Zhang, J., Yang, Z., & He, B. (2024). Empowerment of digital technology for the resilience of the logistics industry: mechanisms and paths. Systems, 12(8), 278. https://doi.org/10.3390/systems12080278
72. Zhao, Q., Fan, Z.-P., & Sun, M. (2024). Sales mode selection and blockchain technology adoption decisions in a platform supply chain. International Journal of Production Economics, 272, 109255. https://doi.org/10.1016/j.ijpe.2024.109255
73. Zheng, J., Alzaman, C., & Diabat, A. (2023). Big data analytics in flexible supply chain networks. Computers & Industrial Engineering, 178, 109098. https://doi.org/10.1016/j.cie.2023.109098