Abstract
This paper aims to propose a new trend in research which integrates the online customer relationship management through the perspectives of perceived value, satisfaction, and e-trust regarding the online restaurant in Chinese e-CRM business backgrounds. This study constructs a structural equation model to analyze the online restaurant marketing with the research perspective of the relationships among perceived value, satisfaction and e-Trust, corresponding to the cognitive belief, affective experiences and cognitive behavior of e-CRM. This model proposes six hypotheses concerning the relationships among perceived value, satisfaction and e-trust, aiming to demonstrate the predominant factors affecting the online restaurant sales and further to have a better understanding of the customers’ preferences on placing orders and purchases in the online context. The results show that there is a series of connections among perceived value, satisfaction and e-trust, and most of them are important. First, the perceived value has an incentive effect on satisfaction, e-trust, and customers’ commitment to a relationship. Second, satisfaction has a positive impact on e-trust and leads to the commitment to a relationship. Third, e-trust positively affects the consumer commitment to a relationship. In addition, production quality, service quality and price fairness have a significant impact on the perceived value.
References
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Articles in the same Issue
- Research on the Determinants of Government Investment Effect
- Connectedness Among Economic Policy Uncertainties: Evidence from the Time and Frequency Domain Perspectives
- Well-Posedness and Exponential Estimates for the Solutions to Neutral Stochastic Functional Differential Equations with Infinite Delay
- SCM Implementation Decisions Under Asymmetric Information: An Agency Approach
- Relationships Among Perceived Value, Satisfaction, and e-Trust: An e-CRM View of Online Restaurant Consumption
- Image Defogging Algorithm Based on Sky Region Segmentation and Dark Channel Prior