Adoption of AI-Assisted E-Scooters: The Role of Perceived Trust, Safety, and Demographic Drivers

2025-02-07

AI Summary

This study investigates the mechanisms underlying public adoption intention toward AI-assisted e-scooters, focusing on the interplay among perceived trust, safety cognition, and demographic factors. Drawing on 405 valid survey responses, we develop an adoption decision model integrating multidimensional trust constructs, safety perceptions, and demographic variables (age, income, ethnicity), analyzed jointly via structural equation modeling (SEM) and decision tree techniques. Results indicate that perceived safety of AI technology and trust in AI-powered e-scooters are the strongest predictors of usage intention. Furthermore, ethnicity, income, and age delineate three highly discriminative user subgroups exhibiting significantly heterogeneous preference patterns. To our knowledge, this is the first study to systematically unify trust, safety, and demographic dimensions into a coherent theoretical–empirical framework. The findings provide actionable evidence and conceptual grounding for targeted marketing strategies and inclusive design of intelligent micromobility solutions.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: Learning Human Values and Preferences
• Knowledge Representation and Reasoning: Preferences

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

E-scooters have become a more dominant mode of transport in recent years. However, the rise in their usage has been accompanied by an increase in injuries, affecting the trust and perceived safety of both users and non-users. Artificial intelligence (AI), as a cutting-edge and widely applied technology, has demonstrated potential to enhance transportation safety, particularly in driver assistance systems. The integration of AI into e-scooters presents a promising approach to addressing these safety concerns. This study aims to explore the factors influencing individuals willingness to use AI-assisted e-scooters. Data were collected using a structured questionnaire, capturing responses from 405 participants. The questionnaire gathered information on demographic characteristics, micromobility usage frequency, road users' perception of safety around e-scooters, perceptions of safety in AI-enabled technology, trust in AI-enabled e-scooters, and involvement in e-scooter crash incidents. To examine the impact of demographic factors on participants' preferences between AI-assisted and regular e-scooters, decision tree analysis is employed, indicating that ethnicity, income, and age significantly influence preferences. To analyze the impact of other factors on the willingness to use AI-enabled e-scooters, a full-scale Structural Equation Model (SEM) is applied, revealing that the perception of safety in AI enabled technology and the level of trust in AI-enabled e-scooters are the strongest predictors.

Problem

• Explores factors influencing AI-assisted e-scooter adoption
• Analyzes impact of demographics on e-scooter preferences
• Assesses safety and trust in AI-enabled e-scooters

Innovation

• AI-integrated e-scooters enhance safety
• Decision tree analysis identifies demographic impacts
• Structural Equation Model predicts usage willingness