Comprehensive Evaluation of E-business Satisfaction Variables and Indicators in B2C Model Using the Negotiation Decision Function Method

Introduction and Objectives: E-commerce has transformed traditional business behaviors, as consumers can easily make purchases through e-commerce platforms. The internet offers countless products and services, but consumers may struggle to choose their preferred products. In recent years, the B2C customer-seller model has gained significant popularity and is one of the best options for group-buying customers. However, users believe that this method increases the demand for services, which in turn leads to price increases.
Methods:
Using an intelligent agent in negotiations can effectively reduce the efforts spent on gathering buyer information and the costs of transactions and negotiations with sellers. This study applies an intelligent agent to the B2C e-commerce process and evaluates the system through testing. Additionally, a questionnaire is used to assess the benefits of the proposed intelligent system. The innovations of this research include identifying and categorizing variables affecting the business to customer purchase, designing a negotiation mechanism, and evaluating business satisfaction. A key limitation of this research is the data collection process and the sample size studied.
Results and discussion: Analytical results indicate that the proposed intelligent system can reduce operational risk while increasing user satisfaction and perceived fairness. Fifty participants, aged 23 to 27, were involved in this experiment. The most common method for estimating the reliability of such scales is the α coefficient. Based on the minimum acceptable criterion, if α is greater than 0.7, it has higher reliability, and if α is less than 0.35, it has lower reliability and should be rejected. The analysis shows that α in this study is 0.844, which indicates higher reliability. In this study, the perceived value shows no significant difference before and after using this system, indicating that the intelligent agent can enhance the value of the business to customer trading system. When participants engage with the platform, shared value may not be the primary concern. The user can receive assistance from this experimental system, but participants did not have a specific goal for using the system, likely due to the limited time of the experiment. In such a short period, participants were unable to form clear objectives or expectations for using the system. Therefore, the analytical results suggest that the system offers higher satisfaction, greater perceived fairness, and lower perceived risk, but users have a neutral attitude toward the perceived value and use of the system.
 Conclusion: The value of this system is not yet fully understood, indicating that it requires more promotion in today's commerce to better reveal its benefits to consumers. From a practical perspective, it is recommended that e-commerce practitioners implement negotiation processes through intelligent systems to identify customer satisfaction aspects, which can then be used for re-engineering and redesigning processes and products. Moreover, this system is not only applicable to the B2C, but can also be extended to other e-commerce models, as the agent can facilitate negotiations between sellers and buyers.