University of Qom Sciences and Techniques of Information Management 2476-6658 10 4 2024 12 21 Qualitative Model of R&D Management Based on Big Data Analytics Qualitative Model of R&D Management Based on Big Data Analytics 285 315 3158 10.22091/stim.2023.9444.1965 FA Saleh Achak PhD., Candidate of Technology Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran. 0000-0003-0948-426X Reza Radfar Professor, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran 0000-0002-3951-9905 Abbas Toloie Ashlaghi Professor, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran 0000-0001-6050-1016 Abbas Khamseh Associate Professor, Department of Industrial Management, Karaj Branch, Islamic Azad University, Karaj, Iran 0000-0002-1263-919X Journal Article 2023 06 07 <strong>Purpose:</strong> This paper aims to identify and explain the dimensions and components of a qualitative model for research and development management, based on big data analytics. <strong>Method</strong>: The current study is a qualitative research design utilizing an exploratory approach. Data collection was conducted through semi-structured interviews with 12 R&D managers and experts who are knowledgeable in data science. Data analysis was performed using open, axial, and selective coding techniques from grounded theory, facilitated by MAXQDA 18 software. Ultimately, a qualitative model was developed and presented. <strong>Findings</strong>: The research findings identified eight dimensions (code axes) and twenty-four components (categories), which include: systematic management, the ability to utilize big data analysis, the application of data science, higher education, technical and non-technical infrastructure, government support, resource availability, internal factors, and external organizations. These findings are organized within the framework of a paradigm model based on grounded theory, encompassing<br />six dimensions: causal factors, the central category, strategies, intervening conditions, background conditions, and consequences. <strong>Conclusion</strong>: The qualitative model of research and development management was presented based on a process-oriented approach and integrated with the identified core components. In this model, data sources were incorporated into the input phase of the R&D management process. The model processing phase includes the ability to utilize big data analysis, research and development strategies, data science tools, system management, and internal organizational factors. Additionally, external organizational factors, higher education strategies, government support, technical infrastructure, and organizational culture are identified as influential external components of the model. <strong>Purpose:</strong> This paper aims to identify and explain the dimensions and components of a qualitative model for research and development management, based on big data analytics. <strong>Method</strong>: The current study is a qualitative research design utilizing an exploratory approach. Data collection was conducted through semi-structured interviews with 12 R&D managers and experts who are knowledgeable in data science. Data analysis was performed using open, axial, and selective coding techniques from grounded theory, facilitated by MAXQDA 18 software. Ultimately, a qualitative model was developed and presented. <strong>Findings</strong>: The research findings identified eight dimensions (code axes) and twenty-four components (categories), which include: systematic management, the ability to utilize big data analysis, the application of data science, higher education, technical and non-technical infrastructure, government support, resource availability, internal factors, and external organizations. These findings are organized within the framework of a paradigm model based on grounded theory, encompassing<br />six dimensions: causal factors, the central category, strategies, intervening conditions, background conditions, and consequences. <strong>Conclusion</strong>: The qualitative model of research and development management was presented based on a process-oriented approach and integrated with the identified core components. In this model, data sources were incorporated into the input phase of the R&D management process. The model processing phase includes the ability to utilize big data analysis, research and development strategies, data science tools, system management, and internal organizational factors. Additionally, external organizational factors, higher education strategies, government support, technical infrastructure, and organizational culture are identified as influential external components of the model. https://stim.qom.ac.ir/article_3158_c8682b84401d3c6a7aaee819da1340d0.pdf