Abstract:

The objective of the study is to develop and test a model of cloud computing adoption by small and medium enterprises in an emerging market. The study uses the diffusion of innovation theory proposed by Rogers (1983) and seeks to investigate the factors that lead to or inhibit the adoption of cloud computing technology. Cloud computing is the shift of data and applications from local resources to remote Internet servers. This technology puts an end to several challenges those SMEs in developing countries face when trying to adopt information technology. These challenges include expensive hardware and software, lack of trained and skilled IT labor. This study will report the results from 110 questionnaires collected from small and medium enterprises in Morocco. Data mining techniques will be used to test the proposed research model and analyze the data. We will make use of the frequent itemsets mining to describe the characteristics of SMEs with intention to adopt cloud computing. Then we will create artificial contrasts and use the Random Forests learning algorithm to test how the questionnaire items discriminate adopters from non-adopters of the technology. Finally we will use association rules
mining to describe intentions of Moroccan SMEs as an interaction between the different components of the diffusion of innovation model. The results will help us determine the profile of cloud computing adopters. This research has several practical and theoretical implications. It will shed light on the attractiveness of cloud computing within SMEs and also provides another validation of the diffusion of innovation theory using data mining techniques.