ANTECEDENTS OF ONLINE PURCHASING BEHAVIOR FOR PRODUCTS MARKETING IN CONTEMPORARY WORLD: AN INTEGRATED APPROACH WITHDEEP LEARNING, MACHINE LEARNING AND DATA MINING

Abstract

In the last decade as a result of the developments in Information systems and information technologies, payment systems, structural reforms implemented in several geographies and regions, new retail and commerce approaches evolved and entered into our lives. Today many consumers prefer online commerce and retail options, whereas some think of switching to online channels because of their popularity and distinct advantages it provides. On the other hand number of consumers using traditional sales channels remains important. In this research some of the characteristics and antecedents of online purchasing behavior, which is known to be one of the consumer behavior types, are analyzed with the help of deep learning, supervised and unsupervised machine learning forms of data mining. Some predictive rules discovered as part of the analysis process with the performance evaluations.