Digital twins are among the most promising ideas in urban logistics, and among the most overhyped. The pitch is familiar: a live virtual copy of your delivery operation that lets you simulate, reroute, and optimize in real time. Fewer failed deliveries, fuller vans, lower emissions.
A new paper in Research in Transportation Business & Management by Mohammed, Naghshineh and colleagues (2026) asks a more useful question: under what conditions could digital twins actually support sustainable last-mile logistics?
What they did
The authors interviewed 16 experts from government, logistics companies, and academia, all based in the UAE and India. Fourteen of them then ranked eight barriers to digital twin implementation using the Analytic Hierarchy Process (AHP). The result is an expert-informed roadmap, which the authors explicitly describe as context-sensitive guidance and not a validated model.
A cleaner performance framework
One of the paper’s more useful contributions is conceptual. The literature often lumps together KPIs, goals and interventions. The authors separate them into three groups:
- six performance outcomes: on-time delivery, returns, CO₂ emissions, employee well-being and safety, cost per parcel, and customer satisfaction
- one operational objective: resource optimization, such as load factors and consolidation
- one sustainability intervention: electric-vehicle integration
This matters. An electric van is a means, not a result. Treating electrification as a KPI leads cities to count vehicles rather than measure outcomes.
Four drivers, all conditional
The experts saw potential in four digital twin functions: route optimization, real-time data integration, better customer communication, and data-driven decision-making. They were also candid about the limits. One academic put it simply: the technology is only as good as our ability to interpret the data. The interviewees also flagged familiar trade-offs, such as consolidation losing out to delivery windows. Several said they wanted to see a digital twin working in practice before believing the claims.
The barriers: data comes first
The AHP produced a clear top of the ranking:
- Data quality and availability (0.25)
- Cybersecurity (0.19)
- Implementation cost (0.19)
Lack of standards and organizational resistance came next. Regulation, skills and ethics ranked lowest. As one public-sector planner put it, without good data the twin becomes “a paperweight”.
The roadmap
The authors propose four parallel tracks, not sequential stages:
- Public–private data collaboration: formal agreements on which data are shared, in what format, at what quality and frequency. Rotterdam is cited as an example.
- Data governance: ownership, access, consent, audit trails and accountability for decisions informed by the twin.
- Cybersecurity: built into the design from the start, not added afterward.
- Targeted R&D: modular, affordable and interoperable tools, tested in joint pilots that assess not just cost and CO₂ but also working conditions and privacy.
The paper is admirably honest about its limits, and those limits are real. No digital twin was actually evaluated. The same small panel supplied both the interviews and the ranking.
What this means for city logistics
The key finding confirms what practitioners have long suspected: the bottleneck is not the technology but the institutions around it. A digital twin of a fragmented system is a fragmented twin. Cities and carriers that cannot share basic data on loading zones, delivery volumes or vehicle movements today will not solve that problem by buying a simulation platform tomorrow.
The lesson is to redesign governance before digitizing operations. First agree on who shares what, under which rules. The twin comes after.
Supported by ClaudeAI
Source: Mohammed, A., Naghshineh, B., Korathan Kandy, A., Alaya, A. & Siddique, A.A. (2026). Digital twins for sustainable urban last-mile logistics: an expert-informed implementation roadmap. Research in Transportation Business & Management, 69, 101884. https://doi.org/10.1016/j.rtbm.2026.101884