The logistics and delivery industry is currently undergoing a technology-driven transformation, as robotics, drones, and autonomous vehicles are poised to address the challenges of last-mile delivery. An earlier study in the United States (US) examined public receptiveness to automated parcel delivery methods, including autonomous vehicles, drones, sidewalk robots, and bipedal robots.
Study: Exploring Customer Preferences for Automated Parcel Delivery Modes. Image credit: Generated using DALL.E.3
In a recent publication in the journal Scientific Reports, researchers employed an Integrated Nested Choice and Correlated Latent Variable (INCLV) model to unveil substitution effects among these automated delivery modes among US participants.
Background
Last-mile logistics, representing the final stage of freight distribution, poses a critical challenge within the supply chain. Despite being the least efficient and often the costliest phase, it accounts for up to 28 percent of delivery and transportation costs. This inefficiency and negative impact call for immediate improvements.
The rise of e-commerce heightened consumer expectations, and ride-hailing services competing for curbside space exacerbated the challenge. Major retailers such as Amazon, Walmart, Einride, and Eliport are exploring autonomous freight delivery solutions. Automated delivery technologies promise efficiency, safety, and sustainability, although concerns about employment and regulation persist.
Public acceptance is crucial for these innovations. Customer attitudes toward automated delivery modes depend on perceived usefulness, convenience, and cost-effectiveness, while barriers include concerns about package handling, security, privacy, trust, familiarity, and environmental impact. These factors interact within a complex set of variables, shaping the future of last-mile logistics.
Analyzing Customer Preferences
For the current study, researchers employed a dataset with 692 respondents collected from a web survey using Qualtrics targeting contiguous US respondents through an online recruitment platform. The primary component of the survey is a discrete choice experiment (DCE), aiming to discern the factors influencing customer preferences for automated parcel delivery modes.
Participants evaluate various delivery attributes and item types before choosing their preferred home delivery option for an e-commerce purchase. The experiment presents six hypothetical choice scenarios, encompassing traditional trucks, autonomous vehicles, sidewalk robots, aerial drones, and bipedal robots, each with different shipping attributes. The choice experiment is carefully designed and accounts for various item-specific attributes.
The study utilizes a hybrid model combining nested logit and latent variable models, INCLV, to analyze the decision-making process. It groups similar technologies and considers latent attitudinal factors, demonstrating that small-scale automated delivery options tend to be grouped. The model accounts for the influence of attitudes, perceptions, and psychometric constructs on decision-making. Moreover, the study extends the model to include correlations among three latent constructs.
Results and Analysis
Researchers evaluated preferences for four emerging parcel delivery technologies and their associated decision-making intricacies based on 692 responses using the INCLV model. The study revealed that cost and time performance significantly influenced the acceptability of technology. High-performing delivery scenarios led to more even preferences among options, with a slight preference for drones. As costs and delivery times increase, traditional delivery modes become the dominant choice. This indicates a growing willingness to explore novel delivery automation when cost and time align. Generally, there was a positive preference for transformative automation technologies over traditional truck delivery. However, bipedal robots showed a lower innate preference, likely due to their significant technological leap. Smaller automated delivery methods, including drones, sidewalk robots, and bipedal robots, exhibit a substitution effect, with people mentally bundling them together.
The role of drop-off location was investigated, showing no substitution effects among modes with similar delivery locations. The value of time (VOT) is a strong driver for adoption across all modes, with autonomous vehicles and drones being more cost-sensitive. Time sensitivity emphasizes the importance of delivery convenience, particularly for autonomous vehicles and drones. The study finds a VOT of $1.42 per day for traditional deliveries and $2.92 per day for automated deliveries. The higher VOT for automated deliveries reflects the need for improved delivery performance to offset perceived risks.
The "Last steps" of drone and robot delivery are influenced by the presence requirement. For autonomous vehicles and drones, it is viewed as a guarantee of successful delivery, while for sidewalk and bipedal robots, it is seen as an inconvenience, mitigated by flexible delivery windows. Parcel content impacts acceptability, with trust in automated delivery being lower for fragile items. Self-driving cars are seen as more acceptable for delivering groceries. Individual differences play a role in automation acceptance, with age, gender, education level, and ethnicity having varying impacts. Technology affinity positively influences acceptance, while concerns about package handling negatively affect it.
Conclusion
In summary, researchers offered valuable insights into the potential adoption of emerging last-mile delivery technologies by customers. The research reveals that acceptance of these technologies is not based on evaluating individual alternatives in isolation. Rather, customers tend to view small-scale automation options, such as drones and robots, as a related group, leading to higher substitution rates between them. Future research explores the interplay between multiple stakeholders and customer reactions to innovative delivery services and understands the role of diverse delivery solutions, such as safe lockers and trunk delivery.
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