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

Introduction:
E-commerce has changed traditional business behaviors, as consumers can easily buy through e-commerce platforms. The Internet offers countless products and services, but consumers find it difficult to choose their favorite products. In recent years, the B2C customer-seller model has become very popular and is one of the best options for customers who buy in groups. However, the users of this method believe that this method increases the demand for services, as a result, the price increases.
Methods:
Therefore, the use of an intelligent agent in negotiation can effectively reduce the efforts spent on collecting buyer information, transaction costs and negotiation with sellers. This study applies an intelligent agent in the B2C e-commerce process and evaluates the system through testing. In addition, a questionnaire is used to examine the benefits of the proposed intelligent operating systems. The innovations of the current research include identifying and categorizing the variables affecting the business to customer purchase, designing the negotiation mechanism, and evaluating business satisfaction. The important limitation in this research is focused on the collection of data and the size of the studied sample.
Results and discussion:
Analytical results show that the proposed intelligent system can increase user satisfaction, reduce performance risk, and increase fairness. There are 50 participants from 23 to 27 years old in this experiment. The most common method of estimating the reliability of these types of scales is with a coefficient . According to the minimum acceptable criterion, if is more than 0.7, it has more credibility, and if is less than 0.35, it has less credibility and should be rejected. The results of the analysis show that  is 0.844 in this study and hence has more validity. In this study, the perceived value has no significant difference between before and after using this system. This shows that the intelligent agent can increase the value of the business to customer trading system. Shared value may not be the customer's primary concern when participants use the involved operating system. The user can get help from this test system, but the participants have no specific purpose to use this system. This must be due to the limited testing time. In such a short time using the proposed system, the participants cannot have a specific goal or desire to use this system. Therefore, the analytical results show that this system has higher satisfaction, more perceived fairness and less perceived risk, but users have a neutral attitude towards the perceived value and use of this system.
Conclusion:
But the value of this system is still not understood and this shows that this system needs more promotion in today's business to make its value to more consumers. From a practical point of view, it is also suggested to the e-commerce activists to implement the negotiation process to convince users through intelligence so that they can identify aspects of customer satisfaction and based on that implement re-engineering and re-design of processes and products. In addition, this system is not only applicable to B2C, but can also be transferred to other e-commerce models, as the agent can help negotiate between sellers and buyers.