Online Shopping Adoption Factors in Kuwait Market based on Data Mining Rough Set Approach
Author(s) -
A. Luai
Publication year - 2018
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2018916832
Subject(s) - computer science , rough set , data mining , set (abstract data type) , data set , data science , artificial intelligence , programming language
This study applied data mining process to provide an insight about factors which led to the adoption of online shopping in medium and Large-sized shopping centers (MLShCs) in Kuwait. This research is focused on proposing the high quality environmental factors which affect the success of online shopping among (MLShCs) in Kuwait and ignoring the low impact factors that may cost a lot of money. It also researches the behavior of the customers and their desire to buy directly from the physical store, the online shopping website, or both. This was achieved by distributing a questionnaire, collecting the data in dataset, cleaning the data, minimizing the dimension of the dataset vertically by applying the rough set feature selection technique, and building a classification model. The result of the previous process is the key to examine the success of online shopping in MLShCs. This study could work as the decision maker for those new investors in Kuwait who are thinking of establishing new shopping business and advise them to go for physical store, online shopping website, or both. It also advices current online shopping business to improve their infrastructure, website’s design and availability, and security issues. The proposed approach performs effectively and generates interested results.
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