Business Intelligence technology implementation can bring capabilities to making decisions faster and better for organizations. It usually faces on significant rate of failure and leads to a large wasting of time and resources. Therefore, identifying critical readiness factors of it helps IT managers in implementation successfully and prevents from failure in this issue. This study conducted in Shahrvand retail company in Iran that wants to implement BI technology successfully. The purpose of this study is to recognize potential readiness factors of business intelligence technology implementation in this organization. On the base of previous study the most important factors were distinguished and one conceptual model was designed. The quantitative method was selected to evaluate factors and totally259 questionnaires were collected among respondents. The SPSS software used to analysis of data. The result shows that robust & extensible framework as a technology’s factor has positive and strong significant relationship with business intelligence technology readiness implementation. Therefore, The results show that the technology dimension factors are important in this implementation successfully. Also, findings demonstrated that the clear business visions and planning, committed management support and sponsorship, and map the solutions to the users were the important factors in this issue.

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.