EMPIRICAL ANALYSIS AND MODEL TO ENHANCE EV AUTOMOBILE MARKET COMPETITIVENESS

Abstract

With the rapid development of China’s new energy vehicle (NEV) industry, the electric
vehicle (EV) market has become increasingly competitive, making customer loyalty and brand retention
critical for sustainable business growth. This study investigates EV consumers in mainland China and
constructs a structural equation model (SEM) in which Customer Perception and Innovation and
Technological Achievements serve as independent variables; Service Quality and Market
Competitiveness act as mediators; and Customer Loyalty and Retention function as the dependent
variable. Utilizing a questionnaire-based survey, data were collected from 437 respondents who either
had prior experience with or a strong purchase intention toward EVs. Empirical analysis using SEM
reveals that both customer perception and technological innovation exert significant positive effects on
service quality, which in turn enhances market competitiveness and indirectly fosters customer loyalty.
Among all paths, market competitiveness plays the most pivotal mediating role in influencing customer
retention intentions, with the highest path coefficient (β = 0.63, p < 0.001). The study further identifies
that service quality serves as a dual mediator within the model, acting as a vital bridge between internal
customer perceptions and external market performance. Theoretically, this research integrates Resource-
Based View (RBV) and Expectation Confirmation Theory (ECT) to innovatively propose and validate a
"dual mediation pathway" mechanism, thereby enriching the existing analytical framework on EV
consumer behavior. Practically, the findings offer empirical insights for EV companies in crafting
customer-centric brand strategies, service management approaches, and technological innovation
trajectories. Finally, the study suggests that future research could enhance model generalizability through
longitudinal tracking, multi-regional sampling, and the incorporation of affective or policy-related
variables, thus contributing to the continuous optimization and high-quality development of the EV
market.