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Research on Evaluation of courier efficiency based on information entropy and data envelopment analysis

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Published:13 July 2023Publication History

ABSTRACT

Measuring the efficiency of couriers in the last kilometre and determining the key factors affecting the efficiency of couriers are of great significance to the courier industry in solving the last kilometre problem. According to the distribution process, the indexes affecting the delivery efficiency of couriers before, during and after dispatch are established, the weights of each index are determined by using information Entropy, and DEA model is established to calculate the delivery efficiency of couriers in express outlets. The differences of sorting, dispatching and service ability during the delivery process of couriers are analyzed, the improvement direction of couriers is defined, and the distribution areas and routes are re-divided. The result of optimization is brought into DEA evaluation model. The example shows that the distribution route and time after optimization are less than before, and the distribution efficiency of most couriers is significantly improved.

References

  1. Caggiani Leonardo, Colovic Aleksandra, Prencipe Luigi Pio, Ottomanelli Michele. 2021. A green logistics solution for last-mile deliveries considering e-vans and e-cargo bikes[J]. Transportation Research Procedia, 2021, 52.Google ScholarGoogle Scholar
  2. Wang Yang,Bi Mengyu, Chen Yanyan. 2020. A Scheduling Strategy of Mobile Parcel Lockers for the Last Mile Delivery Problem[J]. Promet - Traffic&Transportation, 2020, 32(6).Google ScholarGoogle Scholar
  3. González Varona José M., Villafáñez Félix,Acebes Fernando, Redondo Alfonso, Poza David. 2020. Reusing Newspaper Kiosks for Last-Mile Delivery in Urban Areas[J]. Sustainability, 2020, 12(22).Google ScholarGoogle Scholar
  4. Rougès J F, Montreuil B. 2014. Crowdsourcing Delivery: New Interconnected Business Models to Reinvent Delivery[C]//1st International Physical Internet Conference. 2014: 28-30Google ScholarGoogle Scholar
  5. Hribernik Marko, Zero Kathrin, Kummer Sebastian, Herold David M.. 2020. City logistics: Towards a blockchain decision framework for collaborative parcel deliveries in micro-hubs[J]. Transportation Research Interdisciplinary Perspectives, 2020, 8.Google ScholarGoogle Scholar
  6. Khalid Aljohani, Russell G. 2020. Thompson. An Examination of Last Mile Delivery Practices of Freight Carriers Servicing Business Receivers in Inner-City Areas[J]. Sustainability, 2020, 12(7):Google ScholarGoogle Scholar
  7. Wen H. , Yun Q. , Liu D. , Fan X. , & Su W. 2020. The Impact of Personality Traits, Group Identification on Courier Turnover Intention: Social Support as a Moderator. 2020 9th International Conference on Industrial Technology and Management (ICITM).Google ScholarGoogle ScholarCross RefCross Ref
  8. Dong Seok Shin, Jong Han Byun,Byung Yong Jeong. 2019. Crashes and Traffic Signal Violations Caused by Commercial Motorcycle Couriers[J]. Safety and Health at Work, 2019, 10(2):Google ScholarGoogle Scholar
  9. Wei Li, Le Xia, Ying Huang, Soroosh Mahmoodi. 2021. An ant colony optimization algorithm with adaptive greedy strategy to optimize path problems[J]. Journal of Ambient Intelligence and Humanized Computing, 2021(prepublish):Google ScholarGoogle Scholar
  10. Qitong Zhao, Chenhao Zhou, Giulia Pedrielli. 2020. A Decision Support System for Data-Driven Driver-Experience Augmented Vehicle Routing Problem[J]. Asia-Pacific Journal of Operational Research, 2020, 37(05):Google ScholarGoogle Scholar
  11. Lele Zhang, Russell G. Thompson. 2019. Understanding the benefits and limitations of occupancy information systems for couriers[J]. Transportation Research Part C, 2019, 105:Google ScholarGoogle ScholarCross RefCross Ref
  12. Fabio Sgarbossa, Eric H. Grosse, W. Patrick Neumann, Daria Battini, Christoph H. 2020. Glock. Human factors in production and logistics systems of the future[J]. Annual Reviews in Control, 2020, 49:Google ScholarGoogle Scholar
  13. De Bruecker, P. , Van den Bergh, J. , Beliën, J. , & Demeulemeester, E. (2015). Workforce planning incorporating skills: State of the art. European Journal of Operational Research, 243 (1), 1–16 .Google ScholarGoogle ScholarCross RefCross Ref
  14. Chandrasekar K. 2011. Workplace environment and its impact organizational performance in public sector organizations. Int. J. Enterp. Comput. Bus. Syst. 2011, 1, 1–19.Google ScholarGoogle Scholar
  15. Kim, Ji-Hoon Kim, Minkyun. 2021. A Study on the Effect of Technology Acquisition and Employee Welfare on Job Satisfaction and Customer Satisfaction - For Parcel delivery worker of Three parcel delivery service company in the Capital area[J].Management & Information Systems Review. 2021, 40(2)Google ScholarGoogle Scholar
  16. Mariana Strenitzerová, Karol Achimský. 2019. Employee Satisfaction and Loyalty as a Part of Sustainable Human Resource Management in Postal Sector[J]. Sustainability, 2019, 11(17):Google ScholarGoogle Scholar
  17. Eric H. Grosse, Christoph H. Glock. 2015. The effect of worker learning on manual order picking processes[J]. International Journal of Production Economics, 2015, 170:Google ScholarGoogle Scholar
  18. Sang-Bing Tsai, Kai Wang. 2019. Using a Novel Method to Evaluate the Performance of Human Resources in Green Logistics Enterprises[J]. Ecological Chemistry and Engineering S, 2019, 26(4):Google ScholarGoogle ScholarCross RefCross Ref
  19. Chen Quan, Tsai Sang-Bing, Zhai Yuming, Zhou Jie, Yu Jian, Chang Li-Chung, Li Guodong, Zheng Yuxiang, Wang Jiangtao. 2018 .An Empirical Study on Low-Carbon: Human Resources Performance Evaluation.[J]. International journal of environmental research and public health, 2018, 15(1):Google ScholarGoogle Scholar
  20. Yu-Jen >Wu, Jiang-Liang Hou. 2009. An employee performance estimation model for the logistics industry[J]. Decision Support Systems, 2009, 48(4):Google ScholarGoogle Scholar
  21. Longxiao Li , Xu Wang ,1and Jafar Rezaei. 2020. A Bayesian Best-Worst Method-Based Multicriteria Competence Analysis of Crowdsourcing Delivery Personnel[J].Complexity, 2020Google ScholarGoogle Scholar

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    • Published in

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      ICIIT '23: Proceedings of the 2023 8th International Conference on Intelligent Information Technology
      February 2023
      310 pages
      ISBN:9781450399616
      DOI:10.1145/3591569

      Copyright © 2023 ACM

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      Publication History

      • Published: 13 July 2023

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