درخت حوزه‌های تخصصی

Business Intelligence (BI) covers the tasks of collecting, processing, and analyzing large volumes of data. This includes internal systems and external resources, utilizing advanced high-speed analytics and forecasting tools enabling organizations to achieve organizational goals in a timely manner affording immediate decision-making. The main purpose of BI is to help companies improve their performance in the turbulent environment of business and enhance their competitive advantage in this immense data age. Research organizations need integrated information technologies such as business intelligence, perhaps more so than commercial companies need, given the highly competitive environment and increasing progress of various disciplines. The development of such a system, like other organizational information systems, requires the adoption of technology by its users. Various models, including behavioral models, have identified the acceptance factors of information technologies. The purpose of this study is the Interpretive Structural Modeling of factors affecting the adoption of business intelligence technology in research organizations. ISM is a systematic and interpretive process as it is formed based on group judgment and is structured and complemented by common relationships, and finally, depicts the overall structure of several complex elements in a graph model. The sample used in this study was experts of academic research institutes in Tehran. According to the findings, 20 main acceptance factors were modeled in four levels based on interactions between the categories of individual, organizational, and technological criteria.

Due to the dynamic nature of technology, capabilities related to production technologies that have been created for manufacturing new and unique products are constantly changing. Therefore it is essential to monitor the processes and techniques used to understand whether the production of a product fits future circumstances. Leaders of organizations must decide when to switch to a new technology, to maintain and increase competitive advantages. In such conditions, evaluating the maturity of the considered technologies is essential. This article with a conclusive view at various factors affecting the maturity of technology, examines the structuring of the factors affecting the aforementioned maturity. This model is based on Interpretive Structural Modelling (ISM) methodology. The ISM approach enables groups and individuals to identify complex relationships among a multitude of elements in a complex decision-making situation; and it works as a tool for organizing and directing complexities of relationships between variables. This technique starts with identifying variables that are related to the issue, then the contextual relations between the variables are determined using the knowledge and experience of the experts; finally, the multilevel structural model is formed.