An exploratory study to predict cloud computing adoption for Iranian companies for manufacturing electronic pieces

Nowadays, cloud computing is a hot topic attracted practitioners and researchers because of its indisputable benefits such as scalability, ease of use, the needlessness of internal resources and high quality of service. In this research, ten Iranian companies for manufacturing electronic pieces such as different types of transformers or various Plc Components which applied cloud computing are considered. Furthermore ten other companies in the same fields which still haven’t used this technology are examined. Then the effect of some already defined critical factors on the decision of cloud computing adoption is investigated by using data mining as a practical tool of data clustering. In the first step, the data have been grouped into two based on the introduced criteria. The next step is to determine the weight of each critical factor for all of the companies as a whole data set using logistic regression. At last, with respect to information from the clustering and the logistic regression the data set is cross validated and it is shown that a new company’s cloud computing adoption decision can be predicted by using the presented method.

Keywords:

Cloud computing adoption , Data mining , Clustering , Logistic Regression