TY - JOUR
T1 - The effective factors on user acceptance in mobile business intelligence
AU - Bargshady, Ghazal
AU - Pourmahdi, Katayoon
AU - Khodakarami, Panteha
AU - Khodadadi, Touraj
AU - Alipanah, Farab
N1 - Publisher Copyright:
© 2015 Penerbit UTM Press. All rights reserved.
PY - 2015
Y1 - 2015
N2 - Mobile business intelligence used for business intelligence mobile service applications increasingly. According to Gartner (2011), global smartphone sales had arrived at 630 million in 2012, and are supposed to reach 1,105 million items in 2015. As a result, business intelligence users not only rely on desktop computers, while they as well want mobile access to joint and used data. Nevertheless, few studies have been consummate on mobile business intelligence services and the user acceptance rate of mobile BI is still moderately low. For these reasons, the current article centred on the significant of the factors and levels of mobile business intelligence user acceptance that affect the mobile business intelligence user Acceptance. The conceptual model planned and data collected between mobile business intelligence users and quantitative method used. The collected data, analysed by SPSS software. The result of data analysis exposed that how factors such as organization climate, information quality, system quality, society effect and individual effect were influenced user acceptance in mobile business intelligence applications.
AB - Mobile business intelligence used for business intelligence mobile service applications increasingly. According to Gartner (2011), global smartphone sales had arrived at 630 million in 2012, and are supposed to reach 1,105 million items in 2015. As a result, business intelligence users not only rely on desktop computers, while they as well want mobile access to joint and used data. Nevertheless, few studies have been consummate on mobile business intelligence services and the user acceptance rate of mobile BI is still moderately low. For these reasons, the current article centred on the significant of the factors and levels of mobile business intelligence user acceptance that affect the mobile business intelligence user Acceptance. The conceptual model planned and data collected between mobile business intelligence users and quantitative method used. The collected data, analysed by SPSS software. The result of data analysis exposed that how factors such as organization climate, information quality, system quality, society effect and individual effect were influenced user acceptance in mobile business intelligence applications.
KW - Individual effect and social effect
KW - Information quality
KW - Mobile business intelligence
KW - Organization climate
KW - System quality
KW - User acceptance
UR - http://www.scopus.com/inward/record.url?scp=84921879697&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84921879697
SN - 0127-9696
VL - 72
SP - 49
EP - 54
JO - Jurnal Teknologi
JF - Jurnal Teknologi
IS - 4
ER -