Sustainability assessment of last-mile logistics and distribution strategies: The case of local food networks

Ani Melkonyan, Tim Gruchmann, Fabian Lohmar, Vasanth Kamath, Stefan Spinler

Research output: Contribution to journalArticlepeer-review

64 Citations (Scopus)


Current trends related to increased sustainability requirements, the application of new digital technologies, and changes in consumer behavior have disrupted conventional food supply chains, entailing challenges for the last mile logistics and distribution of food products. The main aim of this study is to develop a toolset for exploring the sustainability potential of last mile logistics and distribution strategies, employing (1) a centralized distribution network with a click & collect option, (2) a decentralized distribution network with a home-delivery option, and (3) a distributed network based on a crowd logistics concept. For this, a system dynamics (SD) simulation and a multi-criteria decision aid (MCDA) were applied to assess the sustainability performance of these distribution channel options for a case study of a local food cooperative and a logistics service provider in Austria. The sustainability potential of developing a new logistics system in collaboration with these players has been estimated for the first time, while considering the dynamic interplay of all relevant sustainability elements within operational, tactical, and strategic planning. The results show that an integration of the two players into a distributed network strategy based on a crowd logistics concept is the most viable and sustainable option. This highlights the significant role of the logistics sector in proactively innovating services to make sustainable choices easier for the customer.

Original languageEnglish
Article number107746
JournalInternational Journal of Production Economics
Publication statusPublished - 10-2020

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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