Understanding customer preferences for autonomous delivery vehicles in instant delivery: exploring the impact of delivery and personal attributes

• Instant delivery services face several challenges, including high labor costs, low efficiency, and courier accidents. • Despite the increasing popularity of ADVs, there is a paucity of research on customer preferences for ADVs. • A random parameter logit model with interactions is utilized to investigate the heterogeneous preferences of customers. • This study is the first to consider cargo damage as an attribute in instant delivery mode preference studies. • The significant interaction effects on delivery price associated with income and use frequency are revealed. Various issues confront instant delivery, such as elevated labor expenses, low efficiency, and courier accidents. Consequently, e-commerce and logistics providers have turned their attention towards autonomous delivery vehicles (ADVs). There are no studies on customers who use instant delivery that focus on their preferences for ADVs in relation to cargo damage in conjunction with other delivery attributes such as instant delivery service use frequency and price of orders. The objective of this study is to examine customers’ preferences for ADVs in comparison to traditional courier delivery. To account for the heterogeneity of customers, this study employs the random parameter logit (RPL) model with interactions to quantify the relevance of attributes and their interaction effects. This study is the first to consider cargo damage as an alternative-specific attribute (ASA) in the context of preference studies for instant delivery modes. We also examine the interaction effects between delivery price and personal and delivery attributes, considering the significance and notable preference variations regarding delivery price across different populations. For data collection, a survey employing stated-preference (SP) approach was conducted in China, resulting in 309 effective surveys. The findings indicate that customer preference heterogeneity regarding delivery price and cargo damage both follow normal distributions. And gender, privacy, instant delivery service use frequency, and price of orders all show significant effects on customers’ preferences for ADVs. Analysis of the survey answers also revealed statistically significant positive interaction effects on delivery price associated with income and instant delivery service use frequency. This study contributes to understanding customer preferences for ADVs, thereby assisting logistics providers in identifying target customers for ADVs.