درخت حوزه‌های تخصصی

There are many opportunities and threats in the decision-making environment for managers, and an organization must use research and information systems to change, monitor, and anticipate this environment. Futurism reflects how tomorrow reality gives birth to tomorrow's reality is. The purpose of this research; Analyzing the role of futures studies in the existing patterns of critical factors of multi-criteria decision-making techniques in operations research using the philosophical assumptions of the classical and critical paradigms and finally determining the appropriate strategy based on these components, to increase success and life expectancy. The present study intends to formulate exploratory scenarios of this knowledge by using the critical uncertainty approach. To develop credible scenarios of knowledge of decision techniques, the opinions of 15 experts in this field were collected using the fuzzy Delphi approach and through the critical uncertainty questionnaire. After extracting the most important uncertainties, plausible scenarios of decision-making techniques were determined with the help of experts. According to the results obtained from the opinion of experts from the critical uncertainty questionnaire, four research uncertainties were identified, identified and the scenario design criteria were used. Each of the four cases, which includes low attention to social issues versus high attention to social issues, low attention to ethical models versus high attention to ethical models, low attention to soft approaches versus high attention to soft approaches, Low attention to complex issues versus high attention to complex issues indicates a specific dual situation in the future. Each of these dual situations indicates uncertainty about the future of multi-criteria decision making. Based on these uncertainties, three scenarios were identified. These scenarios include Achilles heel, phoenix, and heel. Also, semi-structured interviews with the theme analysis approach were used, and the philosophy of past and future approaches in this field was reviewed and critiqued.

This study investigated the effects of information system (IS) integration on financial performance in Tehran Stock Exchange with an emphasis on the mediating role of cost performance and quality performance. This survey was carried out in 2018 by distributing 300 questionnaires among all CEOs, financial administrative vice-presidents, accounting managers, and accountants of manufacturing companies listed in the Tehran Stock Exchange. A total of 250 questionnaires were returned, and the data were analyzed in SmartPLS using structural equation modeling (SEM).The results confirmed the significant positive relationships of flexibility, completeness, and knowledge sharing with IS integration. In addition, IS integration affected corporate financial performance both directly and through the mediating variables of cost performance and quality performance. In other words, any increase in each of these three variables led to an improvement in corporate financial performance.

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.