An Application of ANFIS in Business to Customer Electronic Commerce Transactions

Abstract

This study aims to prototype a fuzzy logic-based system (FLS) for supporting the decision-making process of business to customer (B2C) electronic commerce (e-commerce) transactions. An adaptive-network-based fuzzy inference system (ANFIS) is employed to activate this study. The architecture of MFs is revealed and displayed in the content. Related algorithm of ANFIS is illustrated to demonstrate how the model proposed works out in B2C E-commerce Transaction. This study contributes to current literature by exploring the characteristics of FLS in B2C e-commerce transactions and ANFIS. Followed by it, ANFIS to facilitate FLS with various membership functions (MF) are investigated from the aspects of their implementation and engagement with customers. Insights into managing B2C e-commerce can be used for duplication and scaling up similar studies. Consequently, the findings could help to more than likely facilitate diverse users or membership engagement for the field of e-commerce.