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Examining effective factors in initial acceptance of high-tech localized technologies: Xamin, Iranian localized operating system

Author

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  • Saghafi, Fatemeh
  • Noorzad Moghaddam, Ehsan
  • Aslani, Alireza

Abstract

An operating system (OS) is the most important software platform for secure electronic data transfer. Having an OS that is compatible with Iranian security applications and requirements is imperative. The first attempt to create local operating system in Iran was made some 10years ago, when pertinent technological research led to the development of Xamin as Iran's localized operating system. When the first version of the Xamin localized operating system was introduced in the market, some 250 small and medium-sized enterprises (SMEs) as well as 5 large organizations adopted the national operating system. This study analyzes the process of acceptance of Xamin localized open source server operating system technology in Iran. A technology acceptance model (TAM) has been used as the base model, and external variables have been determined based on surveying method. Moreover, two moderator variables have been introduced as new contributors in this study. The results are extracted using path analysis based on structural equation modeling. The statistical population is 250 Xamin users. Data collection tools consist of 200 questionnaires filled out by these users. The results show that subjective norm component and absorptive capacity moderator are two factors affecting the acceptance of this technology. Eventually, given Iran's special conditions, recommendations have been provided for strategic planning or policymaking for acceptance of Xamin operating system. The research also improves knowledge of conceptualization and policymaking for acceptance of high-tech software products.

Suggested Citation

  • Saghafi, Fatemeh & Noorzad Moghaddam, Ehsan & Aslani, Alireza, 2017. "Examining effective factors in initial acceptance of high-tech localized technologies: Xamin, Iranian localized operating system," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 275-288.
    • Handle: RePEc:eee:tefoso:v:122:y:2017:i:c:p:275-288
    DOI: 10.1016/j.techfore.2016.04.010
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