Transforming Urban Logistics 2024

City archetypes FIGURE 1 Population density Scale of transport network Congestion levels Car-centricity Population density Scale of transport network Congestion levels Car-centricity Population density Scale of transport network Congestion levels Car-centricityPopulation density Scale of transport network Congestion levels Car-centricityPopulation density Scale of transport network Congestion levels Car-centricityDense inner-city metropolises Dense cities that typically suffer traffic jams due to limited space availability Low For example: London, New York, Bangkok, Mexico City, Seoul Population density Scale of transport network Congestion levels Car-centricityHistoric city centres Typically, older cities with a narrow streetscape not originally designed for motor vehicles Low For example: Rome, Prague, Valencia, Istanbul, JerusalemEmerging cities Cities with rapidly growing population but limited infrastructure development Low For example: Bengaluru, Lagos, Lima, Jakarta, Bogotá Eco-efficient cities Cities with sustainable and efficient transport infrastructure Low For example: Strasbourg, Amsterdam, Copenhagen, Cologne, Antwerp Regional hub cities Typically, cities that are a significant population centre, which acts as a hub for surrounding rural areas Low For example: Winnipeg, Rosario, Adelaide, Daegu, MedanSuburban sprawling metropolitan areas Cities with extensive road network and many suburban neighbourhoods Low For example: Sydney, Miami, Calgary, Gaborone, Riyadh HighHigh High HighHigh High Notes: These archetypes are used to generalize city models. The challenges and impact experienced by cities will also depend on factors such as their geographies, local climates or politics, which might limit the adoption of recommendations. Source: Accenture City Archetype Framework Transforming Urban Logistics: Sustainable and Efficient Last-Mile Delivery in Cities 8