Methodology for Prioritizing Best Practices Applied to the Sustainable Last Mile—The Case of a Brazilian Parcel Delivery Service Company

Sustainability

Mariane Gonzalez da Costa¹  Tássia Faria de Assis¹  Victor Hugo Souza de Abreu¹  Marcio de Almeida D’Agosto¹ 

[1] Program of Transportation Engineering, Instituto Alberto Luiz Coimbra de Pós Graduação e Pesquisa em Engenharia (COPPE), Federal University of Rio de Janeiro (UFRJ), Technology Center, Building H–Room 117, Rio de Janeiro 999074, Brazil;

关键词: sustainability;    last mile;    best practices;    parcel delivery;    SDG;    prioritization;   

DOI  :  10.3390/su14073812

来源: DOAJ

【 摘 要 】

The ever-increasing impacts of the last mile delivery sector on the environment and the quality of life of the urban population, such as increased congestion, demand best practices to be incorporated by companies to reduce impacts such as emission of air pollutants and Greenhouse Gases (GHG) and depletion of natural resources, among others. However, a myriad of strategies has been developed for this purpose but there is a lack of methodologies that allow the choice of the best ones for a specific case. Therefore, this study looks for those best practices to be employed through an innovative methodology that consists of SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats), a map of strategies of the delivery service, and using the Sustainability Balanced Scorecard (SBSC) and the Analytic Hierarchy Process (AHP), with the differential of considering the peculiarities of each company. The results applied in a Brazilian last mile delivery service company show that best practices such as route optimization, implementation of new infrastructure and business models for urban deliveries, and use of information systems for fleet tracking and monitoring contribute significantly to improving performance indicators and achieving the sector’s goal to become more sustainable, and especially meeting the Sustainable Development Goals (SDGs) 8, 9, 11, and 17.

【 授权许可】

Unknown