Addressing the challenges of using autonomous robots for last-mile delivery

AYYILDIZ E., Erdogan M.

Computers and Industrial Engineering, vol.190, 2024 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 190
  • Publication Date: 2024
  • Doi Number: 10.1016/j.cie.2024.110096
  • Journal Name: Computers and Industrial Engineering
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Keywords: Autonomous delivery robots, Intuitionistic fuzzy sets, Multi-criteria decision-making, PIPRECIA, Sustainability
  • Karadeniz Technical University Affiliated: Yes


The importance of last-mile delivery (LMD) in today's logistics networks has increased recently due to the rising popularity of e-commerce and home delivery. Various LMD modes, such as drones and autonomous vehicles, have emerged to solve the problems encountered during LMD activities and to reduce human intervention in the process. The purpose of this paper is to determine the challenges that arise when using autonomous delivery robots (ADRs) in LMD. Throughout the research, the challenges have been revealed, categorized into six titles and their significance has been calculated via the intuitionistic fuzzy (IF) pivot pairwise relative criteria importance assessment (PIPRECIA) method in conjunction with PESTEL Analysis. IF-PIPRECIA is employed for the first time in the literature with PESTEL Analysis to evaluate the challenges for the implementation of ADRs in LMD. According to the proposed methodology results, challenges related to “Energy consumption,” “Battery life and energy management,” “Cybersecurity,” “Air pollution,” and “Uncertain return on investment” are the most critical factors to consider when implementing ADRs in LMD.