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Applications of structural equation modeling and mathematical statistics to the triggering mechanism of a class of liquors consumer behaviors in Sichuan province

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  • Ruofeng Rao

Abstract

Structural Equation Modeling (SEM) systematically validated hierarchical pathways among multiple factors by constructing a dual framework integrating latent variable measurement and path analysis, utilizing covariance matrices derived from online questionnaires of Wuliangye consumers in Sichuan Province. Statistical analysis quantified path coefficient significance through maximum likelihood estimation, revealing via factor loadings and goodness-of-fit tests that consumer ethnocentrism directly promotes purchase intention, while simultaneously refuting the null hypothesis regarding perceived behavioral control-thus deconstructing the "trigger-transmission" causal chain among variables. Crucially, SEM findings revealed environmental stimuli as the predominant factor, indirectly influencing purchasing behavior through perceived value, contrary to existing literature asserting equal impacts from consumer ethnocentrism, environmental stimuli, and perceived behavioral control. Statistical evidence further demonstrated higher online purchase frequency for premium Wuliangye liquor, aligning with Generation Z's e-commerce preferences. By implementing stricter website-based participant screening than prior studies, this research optimized the analytical model, yielding data-driven strategic recommendations: strengthening e-commerce platforms, enhancing promotional expertise, leveraging cultural localization, and prioritizing premium product development. These actionable insights significantly advance sales optimization strategies for Wuliangye products in Sichuan's dynamic market.

Suggested Citation

  • Ruofeng Rao, 2026. "Applications of structural equation modeling and mathematical statistics to the triggering mechanism of a class of liquors consumer behaviors in Sichuan province," Papers 2602.02956, arXiv.org.
  • Handle: RePEc:arx:papers:2602.02956
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