Social network multiple-criteria decision-making approach for evaluating unmanned ground delivery vehicles under the Pythagorean fuzzy environment

With the rapid development of instant delivery, the shrinking labor population and prevailing contact-free economy, companies have launched unmanned ground delivery vehicles (UGDVs) to replace human distribution with machines. To meet the requirements for selecting UGDVs and achieve better applications in community delivery, a multi-criteria decision-making (MCDM) framework, combining the self-confidence aggregation approach and social trust network, is proposed in this study. Based on the internal characteristics of UGDVs, a multi-criteria comprehensive evaluation system for UGDVs is constructed. Then, a trust propagation and aggregation mechanism to yield expert weights based on a social trust network is suggested. Further, a self-confidence Pythagorean fuzzy aggregation operator is proposed to enhance the credibility of the decision results and compensate for the defects of existing methods. Finally, a practical case is considered to demonstrate the complete process of the MCDM model and to conduct a comparative analysis and sensitivity analysis of the model.

• Record URL:
  https://doi.org/10.1016/j.techfore.2021.121414
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0040162521008453
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00401625
• Supplemental Notes:
  • © 2021 Elsevier Inc. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zeng, Shouzhen
  • Zhang, Na
  • Zhang, Chonghui
  • Su, Weihua
  • Carlos, Llopis-Albert
• Publication Date: 2022-2

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: 121414
• Serial:
  • Technological Forecasting and Social Change
  • Volume: 175
  • Issue Number: 0
  • Publisher: Elsevier Science Publishing Company, Incorporated
  • ISSN: 0040-1625
  • Serial URL: http://www.sciencedirect.com/science/journal/00401625

Subject/Index Terms

• TRT Terms: Autonomous land vehicles; Delivery service; Psychological trust; Social factors
• Subject Areas: Highways; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01832022
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 29 2021 2:43PM