Innovation Mode and Optimization Strategy of B2C E-Commerce Logistics Distribution under Big Data

Ying-yan, Zhao; Zhou, Yanyan

doi:10.3390/su12083381

Cited by 34 publications

(21 citation statements)

References 61 publications

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“…e essence of e-commerce should be a set of complete network business management and management information system. More specifically, it is the use of existing computer hardware equipment, software, and network infrastructure, through a certain protocol connected with the electronic network environment to carry out a variety of business activities [12].…”

Section: Electronic Commerce Platform Systemmentioning

confidence: 99%

Big Data-Based E-Commerce Transaction Information Collection Method

Yan

et al. 2021

Complexity

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With the rapid development of e-commerce industry, online shopping has become a craze. With the rapid growth of transaction volume on e-commerce platforms, a large amount of transaction data has been accumulated. From the transaction information of these users, a lot of very valuable information can be mined, such as the defects of products and the actual needs of users. In view of the existing e-commerce transaction information collection method is not mature, in this paper, the electric business platform system architecture planning and design increases the function management module. In this paper, a new Naive Bayes model is established by using HBase distributed database instead of traditional database. Based on the optimization and extraction of the important transaction information in the product, the dataset of e-commerce transaction information is updated. Through the efficiency test of the collection method, the information scalability ability test, and the accuracy test, the important context was sorted out after integration, the sources of trading information were sorted out, and the data analysis of the collected information was conducted to optimize the information collection method and verify the feasibility of the method.

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Section: Electronic Commerce Platform Systemmentioning

confidence: 99%

Big Data-Based E-Commerce Transaction Information Collection Method

Yan

et al. 2021

Complexity

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“…Furthermore, congestion maps developed from truck data records (GPS locations and dates) and road data records (usage of roads and dates) were used to optimize the schedules and routes of trucks in order to reduce congestion. Zhao et al [28] analysed the management model, influencing factors, and development status of the B2C e-commerce logistics distribution, using big data, and optimized the resource allocation taking into consideration production sales and logistics distribution based on a big data platform. Shahparvari et al [29] identified the optimal location for a logistics hub at a larger geographical scale using GIS.…”

Section: Literature Reviewmentioning

confidence: 99%

Design of a Support System for Complicated Logistics Location Integrating Big Data

Cheng

Pan

2021

Advances in Civil Engineering

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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 collected and calculated using a big data platform, and this information was digitized and represented based on a geographic information system (GIS) tool. Second, a two-stage location model for a ULS was designed to balance the construction costs and traffic congestion. The first stage is establishing a set-covering model to identify optimum locations for secondary hubs based on the ant colony optimization algorithm, and the second stage is clustering of the secondary hubs to determine locations for primary hubs using the iterative self-organizing data analysis technique algorithm (ISODATA). Finally, the Xianlin district of Nanjing, China, was chosen as a case study to validate the effectiveness of the proposed system. The system can be used to facilitate logistics network planning and to promote the application of big data in logistics.

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“…An E-retailer, especially for an industry leader, such as JD, might readily have such data at its disposal. More detailed discussion of analyzing consumer big data has been addressed by the academic community [60].…”

Section: Insights and Conclusionmentioning

confidence: 99%

Optimal Internet of Things Technology Adoption Decisions and Pricing Strategies for High-Traceability Logistics Services

2021

Sustainability

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The Internet of Things (IoT) technology-based tracking system can reduce freight loss/damage during delivery, thereby avoiding wasting social resources. In this study, we address the issue of whether an E-retailer with a logistics arm should provide high-traceability logistics value-added service (based on IoT technology) in two customer segments and analyze their pricing decision. We found that companies always adopt IoT when equipment operation cost is low and not when the cost is high. Otherwise, the optimal IoT adoption strategy for a company depends on multiple factors, for example, the internal operation efficiency of a company. Providing high-traceability service as one kind of public service does not necessarily optimize social welfare even if the overall delivery failure is reduced. The customers’ preference for traceability significantly affects the company’s decision. Hence, we suggest that the company should implement a comprehensive investigation before launching a specific strategy.

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Innovation Mode and Optimization Strategy of B2C E-Commerce Logistics Distribution under Big Data

Abstract: 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.

Cited by 34 publications

References 61 publications

Big Data-Based E-Commerce Transaction Information Collection Method

Big Data-Based E-Commerce Transaction Information Collection Method

Design of a Support System for Complicated Logistics Location Integrating Big Data

Optimal Internet of Things Technology Adoption Decisions and Pricing Strategies for High-Traceability Logistics Services

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