A fuzzy conjoint analysis (FCA: Turksen, 1992) model for enhancing management decision in the technology adoption domain was implemented as an extension to the UTAUT model (Venkatesh, Morris, Davis, & Davis, 2003). Additionally, a UTAUT-based Usage Intention Framework Model (UIFM) introduced a closed-loop feedback system. The empirical evidence depicted in this dissertation research's UIFM supported most of the UTAUT's findings and explained 68% of the variance in behavioral intention (BI) to use the technology. As such, the classical data analysis (CDA) proved that performance expectancy was a direct determinant of BI. The FCA model affirmed this finding. The CDA found effort expectancy to be a direct determinant of BI. The FCA also affirmed this finding. The CDA confirmed social influence as a direct determinant of BI. The FCA did not fully support this finding. The CDA found facilitating conditions to be a direct determinant of BI. The FCA concurred with this finding. For the attitude towards using technology, the CDA rejected the null hypothesis. The FCA supported this finding. The CDA also rejected the null hypothesis of self efficacy. The FCA method partially supported this finding. Although the anxiety construct was significant, it was confirmed by the FCA and the CDA not to be a direct determinant of BI. Therefore, based on the evidence, the FCA methodology provided additional insight into the technology adoption paradigm and should provide management with additional guidelines to better understand the potential impact of adoption or rejection of a deployed technology. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]