Utrecht
Utrecht’s population is rising. In the last decade, the population of the city of Utrecht increased by roughly 70,000 and currently has a 1% growth rate per year. As the city grows, maintaining liveability is an important goal for city officials and policymakers.
Urban space is becoming scarcer and is therefore being redesigned to prioritise active mobility and increase car-free areas.
Starting in 2025, the city will implement a zero-emission zone in the inner city. As part of this plan, Utrecht aims to reduce the number of logistical vehicle movements. Restrictions will gradually apply to all conventional LDVs and starting in 2030 to HDVs.
Jumbo, the Dutch supermarket chain, acts as both retailer and transport operator in the Utrecht pilot. Their fleet includes nearly 650 vehicles carrying out home grocery deliveries spread across the Netherlands.
These vehicles are gradually being replaced by electric vehicles to align with Jumbo’s goal of zero-emission home deliveries and to meet the standard of Utrecht’s new zero-emission zone. Charging infrastructure is being installed at depots along with new planning software which will account for charging constraints.
As Jumbo improves its operational efficiency and sustainability, customer satisfaction remains a top priority and at times, a challenge. When customers choose narrow time delivery slots, lower stop density results in inefficient trips and multiple deliveries in the same area throughout the day as deliveries in the same area cannot be bundled.
To address this trade-off between keeping customers satisfied and operational efficiency and sustainability, customers must be nudged to choose a slot grid with wider time windows leading to more optimal routing, by maximising deliveries and decreasing the distance between customers in the same area.
Objectives
Assess the importance of different attributes of delivery options for customers and how they’re linked to customer behaviour such as amount and frequency of orders.
Map the characteristics of the urban zones affecting delivery operations, considering the diversity in delivery areas and local access regulations.
Explore and define techniques to nudge customers to choose the most optimal slot grid with the widest time window to ensure customer satisfaction and optimise operational efficiency.
Establish multiple delivery options and models based on the various attributes related to the customer value, operations and area characteristics.
Calculate the impact of different delivery options and models regarding operational efficiency for different customer profiles.
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