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. تفاصيل المقالة

Project-based organizations in upstream industries hold a large share of national resources and play an important role in the development of a country. Performance evaluation of project-based organizations can help managers to use inputs effectively and smooth their way to achieving goals. There are many qualitative and quantitative indices to performance evaluation of project-based organizations. Efficiency calculation through Data Envelopment Analysis (DEA) is a common index for performance assessment in such firms. In the traditional DEA model crisp data is needed while, in the real world, most of the data are imprecise and uncertain. A major cause of uncertainty related to the non-quantifiable, incomplete, and unachievable information that caused fuzzy logic and fuzzy sets merge in different models like DEA. The main idea of the present study is to combine quantitative and qualitative approaches in performance appraisal to take advantage of both and achieve more accurate results; therefore, in this paper, a hybrid model based on Fuzzy Data Envelopment Analysis (FDEA) and Project Excellence Model (PEM) is proposed for performance evaluation in project-based organizations. First, performance assessment by the PEM model of Fuzzy data is accomplished. Then, implementing Fuzzy DEA into the PEM model is performed in which the inputs and outputs of the FDEA model are the PEM model criteria. The proposed hybrid model is used to evaluate 30 petrochemical companies in Iran. The comparison of the results of both models indicates a correlation coefficient of almost 0.90 at the significance level of 0.01 that shows an appropriate correlation between the two models. تفاصيل المقالة