A Holistic Human-Based Approach to Last-Mile Delivery: Stakeholder-Based Evaluation of Logistics Strategies

Background: The growing complexity of last-mile logistics (LML) in urban environments has created an urgent need for sustainable, efficient, and stakeholder-inclusive solutions. This study addresses these challenges by exploring a holistic, human-centered approach to evaluating LML strategies, recognizing the diverse expectations of logistics service providers, delivery personnel, customers, and local authorities. Methods: To capture both subjective and objective factors influencing decision-making, the study employs a Multi-Criteria Decision-Making (MCDM) framework that integrates the Fuzzy Analytic Hierarchy Process (FAHP) and Evaluation based on Distance from Average Solution (EDAS). Evaluation criteria encompass operational efficiency, environmental impact, social acceptance, and technological feasibility. Results: Six LML solutions were assessed and ranked using this approach. The results indicate that the cargo bike (A2) emerged as the most favorable alternative, while electric freight vehicles (A5) ranked lowest. These findings reflect significant trade-offs between stakeholder priorities and the varying performance of different delivery strategies. Conclusions: The proposed methodology offers practical guidance for designing balanced and socially responsible urban logistics systems. By emphasizing inclusivity in decision-making, this approach supports the development of LML solutions that are not only operationally effective but also environmentally sustainable and broadly accepted by stakeholders.

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Publication Details

Journal
Logistics
Published
2025-09-23
DOI
https://doi.org/10.3390/logistics9040135
Citations
3
Primary Topic
Urban and Freight Transport Logistics
Type
article
Field-Weighted Citation Impact
3.02
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article

A Holistic Human-Based Approach to Last-Mile Delivery: Stakeholder-Based Evaluation of Logistics Strategies

Milan Andrejić, Vukašin Pajić, Aleksa Maravić
3 citations
Logistics
Urban and Freight Transport Logistics
3.02
article

A Holistic Human-Based Approach to Last-Mile Delivery: Stakeholder-Based Evaluation of Logistics Strategies

Milan Andrejić, Vukašin Pajić, Aleksa Maravić
article en
3 citations

Abstract

Background: The growing complexity of last-mile logistics (LML) in urban environments has created an urgent need for sustainable, efficient, and stakeholder-inclusive solutions. This study addresses these challenges by exploring a holistic, human-centered approach to evaluating LML strategies, recognizing the diverse expectations of logistics service providers, delivery personnel, customers, and local authorities. Methods: To capture both subjective and objective factors influencing decision-making, the study employs a Multi-Criteria Decision-Making (MCDM) framework that integrates the Fuzzy Analytic Hierarchy Process (FAHP) and Evaluation based on Distance from Average Solution (EDAS). Evaluation criteria encompass operational efficiency, environmental impact, social acceptance, and technological feasibility. Results: Six LML solutions were assessed and ranked using this approach. The results indicate that the cargo bike (A2) emerged as the most favorable alternative, while electric freight vehicles (A5) ranked lowest. These findings reflect significant trade-offs between stakeholder priorities and the varying performance of different delivery strategies. Conclusions: The proposed methodology offers practical guidance for designing balanced and socially responsible urban logistics systems. By emphasizing inclusivity in decision-making, this approach supports the development of LML solutions that are not only operationally effective but also environmentally sustainable and broadly accepted by stakeholders.

LogisticsVol. 9(4)
University of Belgrade (RS)
Openalex Percentile: Top 9%
Urban and Freight Transport Logistics
3.02
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A Holistic Human-Based Approach to Last-Mile Delivery: Stakeholder-Based Evaluation of Logistics Strategies — Milan Andrejić, Vukašin Pajić, et al. · Logistics (2025) | TGRS Research Map | TGRS