By shifting the marketing paradigm from transactions to customers, it has been recognized that models for customer satisfaction have to include marketing relational components as a human factor. The studies of customer satisfaction have focused on transactional components such as the perceived quality and the perceived value of products/services. This has limitations as an explanation for dynamic marketing flow which reflects the complicated interaction in the customer-firm dyad. That is why the customer relationship, as a human and relational factor, can play a crucial role in improving the customer retention and loyalty. Thus, this study aims to examine the effects of customer satisfaction and relationship marketing on behavior intention. Specifically, we proposed an extended model for predicting customer satisfaction through the connection of the perceived quality (transactional factor) and the relationship quality(relational factor). For this study, a survey was conducted with 95 male and 275 female customers visiting large discount stores. The hypothesized model was tested by using structural equation modeling with the Maximum Likelihood Method. We first tested the measurement model to identify the constructs of research variables and then analyzed the structural relationships of the constructs. We also examined the effect of common method variance(CMV) in order to control the response bias since the measurement of predictors and criteria variables was obtained from the same source. Results reveal that the measurement model is a reasonable fit to the data with GFI=.93, RMR=.021, RMSEA=.048, IFI=.95, and CFI=.95. The structural model also fits to the data reasonably well(GFI=.93, AGFI=.90, RMR=.023, IFI=.95, CFI=.95) and transactional and relational components both have significant effects on customer satisfaction. In particular, the perceived quality influenced the perceived value and the relationship quality, and then they had strong effects on satisfaction and behavior intention, although the effect of relational management on relationship quality was not statistically significant when the common method variance was controlled. The results also indicate that the explained variance of customer satisfaction in the hypothesized model is 74% and the explained variance of behavior intention is 48%. This implies that relational variables such as relationship quality can effectively explain customer satisfaction and loyalty through the connection of the perceived quality and the perceived value of products/services. Our findings suggest that an integration of customer satisfaction and relationship marketing can be developed as an extended model of customer satisfaction to explain ultimate organizational outcomes including customer loyalty and repeat purchasing. The improvement of product/service quality can increase the exchange value of products and services as well as build high quality customer relationships. As a result, high quality marketing relationships positively affect customer satisfaction and long-term loyalty. This implies that the competitive advantage of customer satisfaction in the current market will be achieved by building the beneficial marketing relationships with the product/service quality. Furthermore, this study provides an insight into how customer-centered management can strengthen the connection of quality → satisfaction → repeat purchasing intention. In other words, the management of customer relationships can be very important to manage customers who are satisfied with the specific product/service but do not purchase it.