Pemanfaatan teknologi virtualisasi oleh operator telekomunikasi sudah bukan hal yang baru lagi karena teknologi virtualisasi terbukti memberikan efisiensi dalam menurunkan total cost ownership (TCO) pada pusat data yang besar dan kompleks. Meskipun demikian pemanfaatan teknologi virtualisasi dengan tugas dan fungsi yang berbeda dari sebelumnya, yaitu sebagai lingkungan simulasi infrastruktur teknologi informasi virtual akan mempengaruhi keputusan perilaku pengguna untuk mengadopsi dan memanfaatkan teknologi tersebut. Selain tiga faktor utama, yaitu perceived ease of use, perceived usefulness, dan behavior intention, model juga diperluas dengan menambahkan faktor computer self-efficacy dan task-technology fit sebagai variabel eksternal. Model ini juga diperluas dengan menambahkan commitment to system use sebagai faktor sosial yang mempengaruhi pengguna. Pengujian hipotesis dalam model penelitian ini menggunakan variance-based Partial Least Squares (PLS) dengan trimming model, dan terbukti hanya 6 hipotesis diterima dari total 14 hipotesis yang diajukan. Terdapat hubungan berikut yang terbukti signifikan yaitu: 1)computer self-efficacy dengan perceived ease of use, 2)task-technology fit dengan perceived ease of use, 3)identification dengan perceived ease of use, 4)perceived ease of use dengan perceived usefullness, 5)perceived ease of use dengan behavioral intention, 6)perceived usefullness dengan behavioral intention.

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Applied virtual technology is not uncommon system in the telecommunication operator since this technology has been used long time ago and shows highly efficiency in term of data center operational costs and as well able to decrease the total cost ownership (TCO) which is usually high and complex. However, the use of virtualization technology with different tasks and functions as virtual infrastructure simulation environment will be influencing user behavior decision to adopt and to utilize virtualization as the target technology. In addition to the primary three indigenous factors: perceived ease of use, perceived usefulness, and behavior intention, the model was also extended with computer self-efficacy and the task-technology fit constructs as external variables. The model was also expanded with commitment system of use to assess the degree to which social influences affect user. Data were collected using a survey questionnaire while the hypothesized relationships in the research model were tested employing the variance-based Partial Least Squares (PLS) with trimming model technique. This study showed there were only 6 of 14 hipothesis were significant accepted. Here below were the corelation was proof to be statisticaly significant: 1)computer self-efficacy and perceived ease of use, 2)task-technology fit and perceived ease of use, 3)identification and perceived ease of use, 4)perceived ease of use and perceived usefullness, 5)perceived ease of use and behavioral intention, 6)perceived usefullness and behavioral intention.