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Статті в журналах з теми "Big data in logistics"

Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 липня 2025

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1

Lekić, Matea, Kristijan Rogić, Adrienn Boldizsár, Máté Zöldy, and Ádám Török. "Big Data in Logistics." Periodica Polytechnica Transportation Engineering 49, no. 1 (2019): 60–65. http://dx.doi.org/10.3311/pptr.14589.

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Анотація:

With certainty, we can say that we are in the process of a new big revolution that has its name, Big Data. Though the term was devised by scientists from the area such as astronomy and genomics, Big Data is everywhere. They are both a resource and a tool whose main task is to provide information. However, as far as it can help us better understand the world around us, depending on how they are managed and who controls them, they can take us in some other direction. Although the figures that bind to Big Data can seem enormous at this time, we must be aware that the amount of what we can collect

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2

Vagapov, Shamil N., and Valentina M. Repnikova. "USING BIG DATA TO OPTIMIZE LOGISTIC OPERATIONS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 3/13, no. 156 (2025): 228–39. https://doi.org/10.36871/ek.up.p.r.2025.03.13.026.

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Анотація:

The article explores theoretical, methodological, and practical aspects of applying Big Data technologies to optimize enterprises’ logistic operations in the context of digital transformation. The relevance of the study is driven by the rapid development of Industry 4.0, the expansion of digitalization, and the growing need to improve the efficiency of transport and logistics processes through the integration of next-generation analytical tools. The role of Big Data as a key resource is substantiated, enabling the development of predictive management models, route optimization, demand forecast

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3

Gao, Fei, and Qilan Zhao. "Big Data Based Logistics Data Mining Platform: Architecture and Implementation." International Journal of Interdisciplinary Telecommunications and Networking 6, no. 4 (2014): 24–34. http://dx.doi.org/10.4018/ijitn.2014100103.

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Анотація:

With the development of intelligent logistics, enormous amount of logistics data are be-coming one of the sources of big data. Building the logistics information platform with big data mining and analysis capabilities to make full use of the huge logistics data is the inexorable trend for intelligent logistics. This paper studied the characteristics of the logistics big data, then, a big data based logistics data mining platform is designed and implemented by utilizing big data processing and storage techniques. The architecture and functions of the platform will be described in detail. This p

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4

Li, Zhuoyang. "Big Data Management: Empowering Sustainable Logistics with Data-Driven Operation Optimization." Advances in Economics, Management and Political Sciences 54, no. 1 (2023): 64–68. http://dx.doi.org/10.54254/2754-1169/54/20230878.

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Анотація:

Numerous disciplines, including logistics, have experienced a paradigm shift since the advent of big data. As the backbone of many industries, logistics has been significantly impacted by the expansion of big data. The purpose of this paper is to investigate the far-reaching effects of big data technology on the development of sustainable logistics, with a particular emphasis on the role of big data in various parts of the logistics process. Through a literature review and case analysis, this paper focuses on summarizing the application of big data in all aspects of logistics, and selecting an

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5

M, Mohamed Ali V. "Make logistics smarter: using big data." Journal of Management and Science 6, no. 3 (2016): 326–32. http://dx.doi.org/10.26524/jms.2016.34.

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Анотація:

Information and Communication Technology (ICT) has been providing effective and efficient path for the enhancement of each every business. ICT are now a days generating a rate that doubles the data every two years. In this VUCA (Volatility, Uncertainty, Complexity and Ambiguity) world, organizations are competing with each other for effective usage of logistics performance.

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6

Chen, Yitong. "Logistics Development in Laizhou under Big Data." Advances in Economics, Management and Political Sciences 77, no. 1 (2024): 251–56. http://dx.doi.org/10.54254/2754-1169/77/20241729.

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Анотація:

The extensive utilization of big data in logistics management is increasingly prevalent due to economic development and advancements in Internet technology. This research examines the present state and optimization method of big data utilization in logistics management, using Laizhou City as a case study. By examining the progress and current challenges of logistics in Laizhou City, this study proposes optimization solutions including the implementation of a big data platform, enhancement of logistics and transportation routes, allocation of resources, and risk management. As an example, we ex

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7

Ye, Yufan. "Intelligent Logistics under Artificial Intelligence and Big Data." Advances in Economics, Management and Political Sciences 62, no. 1 (2023): 277–82. http://dx.doi.org/10.54254/2754-1169/62/20231360.

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Анотація:

With the development of science and technology, high-tech technologies such as artificial intelligence and big data are gradually being applied to daily life. Digitalization has become a new driving force for the transformation and upgrading of the logistics industry, and there are many problems in the current logistics market. The logistics industry has developed rapidly, but the problems of low inventory management and transportation efficiency have not been effectively solved. Research in the field of logistics should not be limited to certain aspects, but should take a holistic approach. I

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8

Chitta, Shyamsunder. "Leveraging Big Data for Third Party Logistics." Asian Journal of Research in Business Economics and Management 7, no. 1 (2017): 1. http://dx.doi.org/10.5958/2249-7307.2017.00001.9.

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9

Shaikh, Dr Sumaira. "Logistics Management System using Big Data Analytics." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (2023): 1–13. http://dx.doi.org/10.55041/ijsrem27750.

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Анотація:

Nowadays, the e-commerce sector has emerged as a significant player in the current financial landscape. It offers a wide range of advantages for global customers, and given the increasing demand for various services and products, there is a pressing need for the development of efficient Web applications. This e-commerce application serves as the bridge between small businesses and their clientele. The application harnesses the capabilities of various technologies, including MongoDB for data storage, Node.js and Express.js for a fast and efficient backend, and HTML CSS for constructing a user-f

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10

Chen, Zixuan, and Zishan Liao. "Impact of Data Technology on Logistics Industry Business Performance." Highlights in Business, Economics and Management 16 (August 2, 2023): 282–87. http://dx.doi.org/10.54097/hbem.v16i.10571.

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Анотація:

In the big data era, more and more people elect to conduct their business online, and logistics firms are expanding in tandem with the quick growth of e-commerce platforms. However, since the outbreak of the epidemic in 2020, it has dealt a heavy blow to the whole world. Despite the economic downturn and difficult development in this particular period, it has also brought challenges and opportunities for logistics companies. The study finds that the effectiveness of logistics companies in managing their warehouses can be improved through the use of AI-driven data analytics and machine learning

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11

Zhang, Li. "B/S-Based Construction of a Big Data Logistics Platform." Computational Intelligence and Neuroscience 2022 (July 13, 2022): 1–10. http://dx.doi.org/10.1155/2022/6873062.

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Анотація:

Due to the overwhelming characteristic of the Internet of Things, devices belonging to these networks are utilized in almost every domain of real life in order to improve the lifestyle of humans. However, these networks result in a huge amount of data related to different application domains, leading to another important research aspect, i.e., big data and cloud computing. Big data and cloud computing technologies in the logistics field have experienced initial contact, gradual penetration, and widespread application. Moreover, it supports traditional logistics to upgrade to smart logistics, a

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12

Zhao, Yingyan, Yihong Zhou, and Wu Deng. "Innovation Mode and Optimization Strategy of B2C E-Commerce Logistics Distribution under Big Data." Sustainability 12, no. 8 (2020): 3381. http://dx.doi.org/10.3390/su12083381.

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Анотація:

With the advent of big data era and rapid development of Internet technology, e-commerce has had a strong development tendency that causes many problems, such as redundant and complex business processes, low efficiency and a high cost for e-commerce logistics in the distribution sector. It is not difficult to conclude that the key to improving logistics distribution efficiency—and reduce logistics distribution costs—is to optimize logistics distribution under big data. In this study, the management model, influence factors and development status of B2C e-commerce logistics distribution under b

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13

Enache, Gabriela Ioana. "Logistics Security in the Era of Big Data, Cloud Computing and IoT." Proceedings of the International Conference on Business Excellence 17, no. 1 (2023): 188–99. http://dx.doi.org/10.2478/picbe-2023-0021.

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Анотація:

Abstract In the backdrop of the Fourth Industrial Revolution and the use of new technologies like the Internet of Things (IoT), 5G, big data and cloud computing, this research paper intends to analyze the many cybersecurity concerns encountered by the logistics industry. This paper will offer insights into the main cybersecurity concerns affecting the logistics industry and explain viable ways for reducing these risks through a thorough study of recent research. The Internet of Things (IoT) has made it possible to use smart devices that can gather and analyze massive volumes of data in real-ti

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14

Aubakirova, Dinara. "Directions for using big data analytics in logistics management." Development management 23, no. 1 (2024): 27–36. http://dx.doi.org/10.57111/devt/1.2024.27.

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Анотація:

Logistics operations are becoming increasingly complex and require accurate data for effective management. The use of big data in logistics management is a relevant issue due to the growing volume of data and the need to optimize delivery and inventory management processes to meet market demands. The purpose of the study was to develop ways to optimize the management of big data analysis in logistics. To achieve this goal, the methods of analysis, experimentation, and comparison were used. As a result of the study, strategies for optimizing logistics management of big data analysis were develo

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15

Zeng, Qian. "The Challenge and Approach of Improving the Big Data Analysis Ability of Logistics Professionals." Frontiers in Business, Economics and Management 5, no. 1 (2022): 116–18. http://dx.doi.org/10.54097/fbem.v5i1.1498.

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Анотація:

The development of the logistics industry has driven the explosive growth of logistics data. However, the market lacks skilled professionals to carry out source management, processing, analysis and mining of logistics data. Under the growing talent gap, the cultivation of big data talents has become a global realistic demand. This paper takes the logistics professionals trained in colleges and universities as the research object. We analyzes the difficulties of improving the big data analysis ability of logistics professionals from three aspects. A promotion approach for the big data analysis

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16

Dong, Hengyi. "Improving E-commerce User Satisfaction in Logistics System during the Big Data: A Case Study of JD.com." BCP Business & Management 48 (July 24, 2023): 218–27. http://dx.doi.org/10.54691/bcpbm.v48i.5270.

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Анотація:

Finding the unimaginably great value beneath the surface of big data, more and more industries have considered big data as a kind of strategic resource that can bring huge benefits, including logistics industry. JD.com is taken as an example in this paper to analyze the approaches to enhance logistics and improve the satisfaction of e-commerce users in the logistics system with the power of big data technology. This essay starts with the introduction and literature review of related topics, followed by an analysis of how JD.com leverages big data to improve logistics in areas like warehousing,

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17

Dragomirov, Nikolay, and Luben Boyanov. "Supply Chain Management and Logistics Big Data Challenges in Bulgaria." LOGI – Scientific Journal on Transport and Logistics 12, no. 1 (2021): 171–81. http://dx.doi.org/10.2478/logi-2021-0016.

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Анотація:

Abstract The article focuses on the challenges of applying big data approaches to logistics and supply chain management in Bulgaria, while also presenting the challenges, opportunities and problems from a broader perspective. This includes a review of big data in logistics and its subsystems in relation to integration and transformation processes, as well as the role of big data and the relevant technologies in supply chain management. The research framework for the study of Bulgarian companies focuses on their experiences, both positive and negative, with big data. Data was collected using an

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18

Mi, Jiale. "Reducing Costs to Enhance Profits for Logistics Companies: Strategies and Best Practices of JD Logistics." BCP Business & Management 48 (July 24, 2023): 213–17. http://dx.doi.org/10.54691/bcpbm.v48i.5269.

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Анотація:

With the development of big data and technology, the competition among e-commerce enterprises is becoming increasingly fierce. Reasonable integration of modern products into the operation of enterprises to obtain higher efficiency, and lower costs, will obtain greater competitive advantages. This paper studies how to reduce the enterprise supply chain's operation, transportation, and other costs. What can draw from the analysis is that enterprises need to progress with The Times. Apply big data to the supply chain management of enterprises. Moreover, use modern technology to replace part of th

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19

Duan, Huabin, Jie Yang, and Huanjun Yang. "A Blockchain-Based Privacy Protection Application for Logistics Big Data." Journal of Cases on Information Technology 24, no. 5 (2022): 1–12. http://dx.doi.org/10.4018/jcit.295249.

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Анотація:

Logistics business is generally managed by logistics orders in plain text, and there is a risk of disclosure of customer privacy information in every business link. In order to solve the problem of privacy protection in logistics big data system, a new kind of logistics user privacy data protection scheme is proposed. First of all, an access rights management mechanism is designed by combining block chain and anonymous authentication to realize the control and management of users' access rights to private data. Then, the privacy and confidentiality protection between different services is real

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20

Wang, Xinchun, and Dan Zhang. "Research on the Impact of Big Data on the Development of Supply Chain Logistics Management." E3S Web of Conferences 251 (2021): 01039. http://dx.doi.org/10.1051/e3sconf/202125101039.

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Анотація:

In the era of big data, information sharing functions are of great significance. Moreover, under the effect of big data technology, information sharing can also avoid the problems of traditional supply chain logistics management, develop personalized service content for users, and fully control order risks. This article summarizes the current situation of traditional supply chain logistics services based on previous work experience. The author discusses the impact of big data on supply chain logistics management from how to improve the effect of high-tech management and control, how to shift f

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21

Cheng, Yusi, and Xinwei Pan. "Design of a Support System for Complicated Logistics Location Integrating Big Data." Advances in Civil Engineering 2021 (January 12, 2021): 1–16. http://dx.doi.org/10.1155/2021/6697755.

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Анотація:

Logistics location is an important component of logistics planning that affects traffic pressure and vehicle emissions. To date, there has not been an adequate study of the integration of big data into the location for a complicated logistics system. This study developed a decision support system that can address location problems for complicated logistics systems, e.g., a multilevel urban underground logistics system (ULS), using logistics big data. First, information needed in the logistics location, such as the traffic performance index (TPI) and the origin/destination (OD) matrix, was coll

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22

Vikaliana, Resista. "BIG DATA ON DIGITAL LOGISTICS IN SUPPLY CHAIN RISK PERSPECTIVE." Jurnal Logistik Indonesia 2, no. 1 (2018): 21–30. http://dx.doi.org/10.31334/jli.v2i1.215.

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Анотація:

In Industry 4.0, digital transformation moves quickly, flexibly and efficiently. Logistics and supply chains have transformed into web-based. Internet of things (IoT) and Big Data are important in the decision making process. The importance of big data doesn’t revolve around how much data you have, but what you do with it. In addition to the opportunities to use big data, there are possible risks that must be anticipated. The wide range of data that can be obtained, so that in practice key risk indicators will act as an early warning system for the entity. Key risk indicators and their paramet

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23

Wan, Fei, Rui Li, and Lei Qi. "Research on Military Logistics Ecosystem Based on Big Data." Journal of Physics: Conference Series 1813, no. 1 (2021): 012027. http://dx.doi.org/10.1088/1742-6596/1813/1/012027.

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24

Li, Na, and Wei Yao. "Research on Visual Logistics Big Data Information Service System." Journal of Physics: Conference Series 1820, no. 1 (2021): 012164. http://dx.doi.org/10.1088/1742-6596/1820/1/012164.

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25

Shin, Nala, and Yong Jin Kim. "Activating Strategies of Logistics Big Data through Case Studies." Korean Logistics Research Association 28, no. 2 (2018): 91–101. http://dx.doi.org/10.17825/klr.2018.28.2.91.

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26

Fosso Wamba, Samuel, Angappa Gunasekaran, Thanos Papadopoulos, and Eric Ngai. "Big data analytics in logistics and supply chain management." International Journal of Logistics Management 29, no. 2 (2018): 478–84. http://dx.doi.org/10.1108/ijlm-02-2018-0026.

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27

Guo, Xin. "Construction of Smart Logistics Model Based on Big Data." Journal of Physics: Conference Series 1533 (April 2020): 042036. http://dx.doi.org/10.1088/1742-6596/1533/4/042036.

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28

Gao, Xinyue, and Lei Liu. "Green Intelligent Logistics Sorting System in Big Data Environment." IOP Conference Series: Materials Science and Engineering 711 (January 7, 2020): 012040. http://dx.doi.org/10.1088/1757-899x/711/1/012040.

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29

Pan, Canhui. "Construction of Intelligent Logistics Model Based on Big Data." Journal of Physics: Conference Series 1648 (October 2020): 022014. http://dx.doi.org/10.1088/1742-6596/1648/2/022014.

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30

Wang, Yaxing, Lijie Feng, Heyu Chang, and Min Wu. "Research on the Impact of Big Data on Logistics." MATEC Web of Conferences 100 (2017): 02015. http://dx.doi.org/10.1051/matecconf/201710002015.

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31

Kim, Seung Wook. "Last Miles Logistics Model based on Big Data Analytics." E-Business Studies 20, no. 4 (2019): 241–54. http://dx.doi.org/10.20462/tebs.2019.8.20.4.241.

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32

AlShaer, Mohammed, Yehia Taher, Rafiqul Haque, Mohand-Saïd Hacid, and Mohamed Dbouk. "IBRIDIA: A hybrid solution for processing big logistics data." Future Generation Computer Systems 97 (August 2019): 792–804. http://dx.doi.org/10.1016/j.future.2019.02.044.

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33

Mitroshin, Pavel, Yulia Shitova, Yury Shitov, Dmitry Vlasov, and Anton Mitroshin. "Big Data and Data Mining Technologies Application at Road Transport Logistics." Transportation Research Procedia 61 (2022): 462–66. http://dx.doi.org/10.1016/j.trpro.2022.01.075.

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34

Wen, Long. "Development Analysis of Cross-Border E-Commerce Logistics Based on Big Data Technology Under Safety Law Protection." International Journal of Information Systems in the Service Sector 14, no. 2 (2022): 1–14. http://dx.doi.org/10.4018/ijisss.290547.

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Анотація:

To improve logistics level of cross-border e-commerce, big data technology can effectively enhance its logistics level. Firstly, difficulties existing in international logistics management and the necessity of international logistics supply chain management are discussed. Secondly, challenges and opportunities of big data technology to cross-border E-commerce are analyzed respectively. Big data logistics and its characteristics are studied in depth. The cross-border e-commerce sales forecast model is established based on GM(1,1), and the proposed model is verified based on case study, simulati

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35

Ma'arif, Muhammad Rifqi, and Andika Bayu Saputra. "RANCANGAN ARSITEKTUR SISTEM INFORMASI LOGISTIK BERBASIS CYBER-PHYSICAL SYSTEMS DENGAN TEKNOLOGI BIG DATA DAN INTERNET OF THINGS." J@ti Undip : Jurnal Teknik Industri 16, no. 2 (2021): 143–52. http://dx.doi.org/10.14710/jati.16.2.143-152.

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Анотація:

Era Industri 4.0 sangat dipengaruhi oleh perkembangan teknologi informasi khususnya teknologi big data dan internet of things. Dua teknologi tersebut membangun sebuah paradigma baru yang disebut dengan Cyber-Physical System (CPS). CPS didefinsikan sebagai interkoneksi antara lingkungan fisik dengan program komputer melalui teknologi sensor/ IoT. Penerapan CPS di berbagai bidang bisnis/ industri akan semakin memperkuat nilai bisnis yang ditawarkan kepada customer. Salah satu bidang industri yang akan mengalami peningkatan signifikan dengan penerapan CPS adalah bidang logistik. Pengembangan Sist

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36

Runtuk, Johan Krisnanto, Filson Sidjabat, Jsslynn, and Felicia Jordan. "Big Data in Supply Chain Management: A Systematic Literature Review." Green Intelligent Systems and Applications 2, no. 2 (2022): 108–17. http://dx.doi.org/10.53623/gisa.v2i2.115.

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Анотація:

Big data analytics (BDA) have the potential to improve upon and change conventional supply chain management (SCM) techniques. Using BDA, organisations need to build the necessary skills to use big data effectively. Since BDA is relatively new and has few practical applications in SCM and logistics, a systematic review is needed to emphasise the most significant advancements in current research. The objectives are to evaluate and categorise the literature that addresses the big data potential in SCM and the current practises of big data in SCM. The Systematic Literature Review (SLR) was conduct

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37

Zhou, Lei. "The Convergence of IoT, Big Data, and International Logistics: Enhancing Supply Chain Efficiency." Law and Economy 2, no. 9 (2023): 35–40. http://dx.doi.org/10.56397/le.2023.09.05.

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Анотація:

This paper explores the transformative convergence of the Internet of Things (IoT) and Big Data within the realm of international logistics, focusing on their collective potential to enhance supply chain efficiency. We delve into the IoT's foundational technology, its role in international logistics, and its adoption within China's logistics networks. Additionally, we examine the significance of Big Data analytics, its applications in supply chain management, and its specific utilization in China's international logistics operations. The paper also highlights the convergence of these technolog

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38

Chen, Wei, and Candido Perez. "A Brief Analysis of Logistics Customer Service Management." LOGI – Scientific Journal on Transport and Logistics 14, no. 1 (2023): 309–16. http://dx.doi.org/10.2478/logi-2023-0028.

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Анотація:

Abstract The quality of customer service determines the survival and development of logistics enterprises. In the highly competitive e-commerce field, it is necessary to continuously improve the customer service management level of logistics enterprises, and the application of big data can optimize customer service management of logistics enterprises in e-commerce. This paper analyzes the reasons for the low customer service satisfaction with domestic logistics enterprises in China, and then puts forward how to optimize customer service management of logistics enterprises in ecommerce based on

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39

Jin, Dong-Hui, and Hyun-Jung Kim. "Integrated Understanding of Big Data, Big Data Analysis, and Business Intelligence: A Case Study of Logistics." Sustainability 10, no. 10 (2018): 3778. http://dx.doi.org/10.3390/su10103778.

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Анотація:

Efficient decision making based on business intelligence (BI) is essential to ensure competitiveness for sustainable growth. The rapid development of information and communication technology has made collection and analysis of big data essential, resulting in a considerable increase in academic studies on big data and big data analysis (BDA). However, many of these studies are not linked to BI, as companies do not understand and utilize the concepts in an integrated way. Therefore, the purpose of this study is twofold. First, we review the literature on BI, big data, and BDA to show that they

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40

Zhang, Yingting, and Yanyi Deng. "Construction of green logistics evaluation index system based on big data." Journal of Computational Methods in Sciences and Engineering 24, no. 4-5 (2024): 2629–42. http://dx.doi.org/10.3233/jcm-247491.

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With the improvement of environmental awareness, green logistics, as a kind of logistics mode that can realize the unity of economic benefits and environmental benefits, has been paid more and more attention by the academia and the industry. However, how to effectively evaluate the operation effect of green logistics is still a problem to be solved. To solve this problem, this paper proposes a green logistics evaluation index system based on factor analysis, and verifies its effectiveness through simulation data. In the process of building and validating the model, rigorous mathematical modeli

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Li, Wenjing, Shiaofang Liang, Yinjiao Jiang, and Qiuxia Pan. "Road condition prediction and logistics distribution path optimization algorithm based on traffic big data." Journal of Algorithms & Computational Technology 13 (January 2019): 174830261987419. http://dx.doi.org/10.1177/1748302619874197.

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In view of the complex road conditions in today’s cities, the traditional prediction methods for road conditions are not so accurate, and the optimization algorithm for the logistics distribution path is not sensitive to changes in the road conditions so that its application in an actual logistics distribution system is not effective. This article proposes a road condition prediction and logistics distribution path optimization algorithm based on traffic big data. First, it analyses the characteristics of the road condition information of traffic big data. By combining the powerful feature ext

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Kopec, Ján, Miriam Pekarcíková, Michal Dic, and Laura Lachvajderová. "Analysis of the big data concept and its use for logistics processes." Advanced Logistic Systems - Theory and Practice 16, no. 1 (2022): 85–91. http://dx.doi.org/10.32971/als.2022.008.

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This article deals with Big Data analysis and subsequently the application itself for logistics. Today, it is possible to consider various opportunities to improve Big Data analysis and its logistics applications. The research is conducted by examining monitoring strategies based on, for example, technologies and relationships to financial performance. This article contains the attributes of big data, their effective forms of implementation,and the implementation methods themselves.Big data is a benefit to the industry, and nowadays it is inconceivable that a business should not work with a la

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Łukasik, Zbigniew, Bartłomiej Ulatowski, and Łukasz Łukasik. "The usage of RFID technology using Big Data in logistics processess." AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe 19, no. 12 (2018): 780–82. http://dx.doi.org/10.24136/atest.2018.497.

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The following article shows how to use large data sets using logistic data using radio frequency identification (RFID) technology. First of all, the so-called RFID-Cuboids processors are introduced to create a data warehouse so that logistics data managed via RFID technology can be highly integrated in terms of specific logic and operations. Second, the tables are used to combine r data to increase information quality and reduce the data set volume.

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Zhu, Suming. "How Does E-commerce Industry Benefit from Big Data." SHS Web of Conferences 181 (2024): 01029. http://dx.doi.org/10.1051/shsconf/202418101029.

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In this paper, the benefits of applying big data in the industry of online retailing, with a focus on logistics distribution and precision marketing. The findings indicate that big data plays a crucial role in revolutionizing logistics distribution, enabling e-commerce companies to optimize their inventory management, delivery routes, and customer demand forecasting. This results in cost savings, improved efficiency, and enhanced customer satisfaction. Moreover, big data empowers precision marketing by providing deep customer insights, enabling effective segmentation, supporting dynamic pricin

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Fu, Fang, and Wanyang Zhou. "The Application of Order Scheduling Algorithm for Food Delivery Logistics Based on Historical Data." Journal of Physics: Conference Series 2074, no. 1 (2021): 012081. http://dx.doi.org/10.1088/1742-6596/2074/1/012081.

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Abstract With the improvement of China’s social and economic development, the requirements for delivery efficiency of foreign logistics orders are becoming more and more stringent. Big data technology is the current direction of vigorous development. With the development of the Chinese era, in order to better promote the development of China’s urbanization. With the continuous innovation of big data technology, various industries are undergoing industrial upgrading and format conversion. This article mainly discusses the order scheduling algorithm of takeaway logistics based on historical data

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Chen, Lingling, Yuanyuan Zhang, and Zhiping Wang. "Logistics Service Supply Chain Model Applying Artificial Intelligence and Big Data Analysis." Security and Communication Networks 2022 (June 21, 2022): 1–12. http://dx.doi.org/10.1155/2022/1575813.

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The logistics service chain is a specialized service chain produced along with the continuous update and development of the logistics industry. It is an inevitable direction choice that is naturally formed when the degree of logistics specialization continues to increase. This paper aims to study how to analyze and study the logistics service supply chain model based on artificial intelligence and big data analysis, and describe the data mining algorithm. This paper puts forward the problem of logistics service supply chain, which is based on big data analysis, and then elaborates around its r

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Meier, Thomas, Helena Makyšová, and Alena Pauliková. "Evaluation of the Economic, Ecological and Ethical Potential of Big Data Solutions for a Digital Utopia in Logistics." Sustainability 15, no. 6 (2023): 5088. http://dx.doi.org/10.3390/su15065088.

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In the context of digital transformation and the use of big data technologies, this study shows the potential and possible applications associated with using big data, depending on the respective logistics area. The evaluation of this potential follows a logistical target system, which has been expanded to include ethical and sustainable aspects in line with the challenges of the 21st century. Furthermore, the status quo of the degree of digitization is determined, problems in understanding the terminology are shown, and cognitive and technical prerequisites and recommendations for action conc

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Li, Na, and Wei Yao. "Research on Application of Cold Chain Logistics Management Based on Big Data Technology." E3S Web of Conferences 253 (2021): 02056. http://dx.doi.org/10.1051/e3sconf/202125302056.

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Compared with developed countries, the cold chain logistics of agricultural products in china is wasteful, which not only consumes a lot of labor and natural resources, but also reduces the domestic and international competitiveness of agricultural products. The paper analyzes outstanding issues such as cold chain "broken chain", "information islands", and cold chain "food safety". Through the integration of advanced information technologies such as big data and mobile internet, a cold chain logistics engineering management technology platform is established to establish a national The data an

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DANG, SHUO, Jing Shi, and Yang Li. "Big Data Management in Transport Logistics Industry: A Literature Review." Turk Turizm Arastirmalari Dergisi 2, no. 3 (2019): 56–62. http://dx.doi.org/10.26677/tr1010.2019.78.

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Hopkins, John, and Paul Hawking. "Big Data Analytics and IoT in logistics: a case study." International Journal of Logistics Management 29, no. 2 (2018): 575–91. http://dx.doi.org/10.1108/ijlm-05-2017-0109.

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Purpose Advances in technology enable companies to collect and analyse data, which were previously not accessible, to either enhance existing business processes or create new ones. The purpose of this paper is to document the role and impact of Big Data Analytics (BDA), and the Internet of Things (IoT), in supporting a large logistics firm’s strategy to improve driver safety, lower operating costs, and reduce the environmental impact of their vehicles. Design/methodology/approach A single case with embedded units intrinsic case study method was adopted for this research and data were collected

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