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This study aimed to verify the impact of e-commerce live streaming interactivity on consumer engagement behavior. Specifically, the multiple dimensions of interactivity and tie strength together form a high-level consumer engagement behavior.

Data collection was carried out in the form of a questionnaire survey. Data from 416 respondents were analyzed by structural, followed by further test by fsQCA method.

Perceived controllability, perceived responsiveness and perceived mutuality positively influence tie strength, and tie strength promotes consumer engagement behavior. Moreover, we found a configuration effect between interactivity and tie strength and revealed four configurations that can affect high-level engagement behavior.

First, the SEM results show that the three dimensions of perceived interactivity positively impact tie strength: perceived controllability, perceived responsiveness, and perceived mutuality. And perceived personalization has no positive impact on tie strength. Second, the relevant results show that tie strength positively impacts consumer engagement behavior. Third, we find that the relationship between perceived interactivity and consumer engagement behavior may not be asymmetric, so the alternative combination of causal conditions may produce the same results. The fsQCA results revealed four configurations that can affect the level of consumer engagement behavior. And tie strength is the core condition.

This study provides specific solutions for e-retailers and live streaming platforms to promote consumers' participation in engagement behavior in e-commerce live streaming.

This study transforms the linear impact of interactivity on consumer engagement behavior into a configuration effect for the first time, and enriches the live streaming commerce and consumer engagement behavior literature.

To investigate the influence of vehicle operation speed, curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated optimization strategy to reduce wheel–rail contact fatigue damage.

Taking a small-radius curve of a high-speed railway as the research object, field measurements were conducted to obtain track parameters and wheel–rail profiles. A coupled vehicle-track dynamics model was established. Multiple numerical experiments were designed using the Latin Hypercube Sampling method to extract wheel-rail creepage indicators and construct a parameter-creepage response surface model.

Key service parameters affecting wheel–rail creepage were identified, including the matching relationship between curve geometry and vehicle speed and rail profile parameters. The influence patterns of various parameters on wheel–rail creepage were revealed through response surface analysis, leading to the establishment of parameter optimization criteria.

This study presents the systematic investigation of wheel–rail creepage characteristics under multi-parameter coupling in high-speed railway curves. A response surface-based parameter-creepage relationship model was established, and a multi-parameter coordinated optimization strategy was proposed. The research findings provide theoretical guidance for controlling wheel–rail contact fatigue damage and optimizing wheel–rail profiles in high-speed railway curves.