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Knowledge-Driven Logistics Transformation: Complex Networks and UAVs in Distribution

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Abstract

In today’s rapidly evolving knowledge economy, the logistics landscape faces unprecedented challenges driven by the demands of e-commerce and takeaway services. Traditional logistics struggle with inefficiencies and escalating labor costs, prompting a paradigm shift toward leveraging uncrewed aerial vehicles (UAVs) for distribution. This paper explores the intersection of UAV technology, complex network theory, and the knowledge economy. The incorporation of UAVs into logistics networks offers a transformative solution to traditional challenges. However, a noticeable research gap exists in the strategic opening of distribution sites and optimizing flight paths. This study bridges this gap by introducing complex network evaluation indices into urban logistics UAV distribution networks. By applying complex network and innovation diffusion theories, we systematically assess the importance of distribution sites within the network, challenging conventional assumptions. Furthermore, we highlight the importance of knowledge management strategies in enhancing operational efficiency and adaptability within UAV distribution networks. Effective knowledge sharing and data analytics play a crucial role in informed decision-making and ongoing innovation. Our research pioneers the application of complex network evaluation indices, offering insights for logistics operators seeking to optimize their operations. This study advances our understanding of UAV logistics within the knowledge economy. It provides theoretical foundations for complex network analysis and practical recommendations for logistics managers. Embracing UAV technology presents economic and innovation implications, making it a driving force for efficiency and competitiveness in the logistics industry.

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Data Availability

Datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Funding

This research was supported by the Sichuan key research program (No. 2023YFG0054) and the Safety Foundation of Civil Aviation Administration of China (No. [2022]146).

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Authors and Affiliations

  1. College of Air Traffic Management, Civil Aviation Flight University of China, 618307, Guanghan, China

    Long-Yang Huang, Si-Yi Li, Bo-Zhi Zhao & Cheng-Long Li

  2. The Second Research Institute of Civil Aviation Administration of China, 610041, Chengdu, Sichuan, China

    Xiang Zou

  3. Civil Unmanned Aircraft Traffic Management Key Laboratory of Sichuan Province, Sichuan, China

    Xiang Zou

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  1. Long-Yang Huang
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Correspondence to Xiang Zou.

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Huang, LY., Li, SY., Zou, X. et al. Knowledge-Driven Logistics Transformation: Complex Networks and UAVs in Distribution. J Knowl Econ (2024). https://doi.org/10.1007/s13132-024-01984-z

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