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The continuance behavioral intention to adopt electrified ride-sourcing: Empirical evidence from China

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  • Lu, Ke
  • Xu, Yuan

Abstract

Despite the emphasis on traveler-related factors in electrified ride-sourcing, few studies have investigated travelers' long-term behavior. Therefore, this study aims to examine determinants affecting continuance behavioral intention towards electrified ride-sourcing. A conceptual framework integrating Expectation Confirmation Model and Technology Acceptance Model is developed. Additionally, factors of environmental awareness and subjective norm are included. Based on a survey in Nanjing, empirical analysis was conducted using partial least squares structural equation modeling and fuzzy set qualitative comparative analysis. Further, a multi-group analysis was employed to examine behavioral differences. The results indicate that expectation confirmation, perceived usefulness, and perceived ease of use are significant predictors of continuance behavioral intention towards electrified ride-sourcing. In addition, attitude and satisfaction serve as predictive mediators. Besides, subjective norm indirectly affects travelers' intention. Notably, both direct and indirect effects of environmental awareness confirm its importance in continuance intention towards electrified ride-sourcing. Furthermore, travelers' continuance intention is associated with age, income, and educational level. The findings identify the determinants of continuance behavioral intention, and validate the explanatory and predictive power of the conceptual framework, thereby broaden the understanding of electrified ride-sourcing. Moreover, the findings provide valuable insights for policymakers and platforms to enhance the promotion of electrified ride-sourcing.

Suggested Citation

  • Lu, Ke & Xu, Yuan, 2024. "The continuance behavioral intention to adopt electrified ride-sourcing: Empirical evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:tefoso:v:209:y:2024:i:c:s0040162524006036
    DOI: 10.1016/j.techfore.2024.123805
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