The rapid growth of electric vehicles (EVs) is reshaping transport systems and accelerating the sustainable digital transformation of smart mobility. EV battery-swapping, delivered through platform-based, data-driven service networks, offers a low-carbon alternative to conventional refueling and plug-in charging by shortening replenishment time and enabling centralized battery management. However, the behavioral mechanisms driving user adoption of this digitally enabled infrastructure remain insufficiently understood. This study develops a socio-technical system (STS) model in which social and technical drivers influence users’ intention to adopt EV battery-swapping services via the dual mediation of perceived trust and perceived risk. Using a three-stage mixed-methods design that combines a PRISMA-based literature review, expert interviews with user-journey mapping, and a large-scale user survey, the study identifies six social and technical antecedents of EV battery-swapping adoption. Based on 565 valid responses from EV users in the Beijing–Tianjin–Hebei region, partial least squares structural equation modeling and multi-group analysis are employed to test the proposed framework. The results show that all six antecedents significantly affect perceived trust and perceived risk, which in turn mediate their impacts on adoption intention, with notable heterogeneity across income and usage-frequency groups. The findings provide a mechanism-based extension of STS theory for digitally mediated battery-swapping infrastructure by showing how socio-technical conditions shape adoption via trust and risk, and they offer actionable implications for operators and policymakers to build secure, user-centered swapping services within intelligent transport systems.

Exhibit texts are commonly presented as labels or information panels near artworks to provide visitors with direct access to key exhibit information. Digital museums offer flexible and diverse ways to present artworks and communicate their cultural meanings. They also allow exhibit texts to be displayed in different formats, which may shape users’ reading behavior and cognitive experience. This study used a repeated-measures, within-subject design (N = 38) to compare three types of exhibit text presentation: environment-based, object-based, and user-based. Eye tracking, the NASA Task Load Index, and semi-structured interviews were used to examine the users’ visual attention patterns and cognitive load. The results showed significant differences in cognitive load across presentation conditions (p < 0.05), with the object-based layout associated with relatively higher cognitive load and more active visual behavior. These findings provide empirical evidence on how exhibit text presentation affects visitors’ experience in digital museums and offer design implications for textual information in digital reading environments.