Designing female-specific food delivery electric vehicles: a participatory and data-driven approach

Abstract

Delivery electric vehicles serve as essential work tools in platform-based food delivery, yet satisfaction-related design requirements for female riders remain insufficiently specified and are rarely translated into explicit design priorities with a traceable evidence chain. This study develops and quantifies a satisfaction-oriented requirement structure for female delivery electric vehicles using an integrated qualitative–quantitative pathway. Semi-structured interviews with 18 female riders were analyzed using grounded theory to derive indicators organized into five latent dimensions: applicability, safety, convenience, friendliness, and attractiveness. A subsequent survey was analyzed using structural equation modeling, yielding acceptable fit and unequal contributions of the five dimensions to self-reported satisfaction. Applicability and safety showed the largest standardized effects, followed by convenience, friendliness, and attractiveness. These estimates were translated into prioritized design directions and an illustrative design translation to demonstrate traceability from user evidence to design decisions; this translation is not presented as product-level validation. An XR-based System Usability Scale assessment is reported as exploratory and interpreted conservatively. Overall, the study provides an auditable pathway for requirement prioritization in delivery vehicle design under gig-work constraints and potential gender heterogeneity.