Qualitative model of R&D management based on big data analytics

Purpose: This paper aims to identify and explain the dimensions and components of a qualitative model of research and development management, based on big data analytics.

Methodology: The current study is a qualitative research that was conducted using an exploratory approach. Data collection was done by semi-structured interview method. It is held through interviews with 12 R&D managers and experts, who are familiar by data science. Data analysis was done during the process of open, axcial and selective coding of grounded theory, using MAXQDA18 software, and finally the qualitative model was explained.

Findings: The findings of the research led to the identification of 8 dimensions (code axis) and 24 components (category) include: systematic management, ability to use big data analysis, application of data science, higher education, technical and non-technical infrastructure, government support, supply of resources, internal factors and external organization. It is organized in the form of the paradigm model of grounded theory, in six dimensions of causal factors, central category, strategies, intervening conditions, background conditions and consequences.

Conclusion: The qualitative model of research and development management was presented based on the process approach and integrated with the identified core components. In this model, data sources were added to the input part of the R&D management process. The ability to use big data analysis, research and development strategies, data science tools, system management and internal organizational factors are entered to the model processing part. While external organizational factors, higher education strategies and government support, technical infrastructure and organizational culture are mentioned as external effective components of the model.

Purpose: This paper aims to identify and explain the dimensions and components of a qualitative model of research and development management, based on big data analytics.

Methodology: The current study is a qualitative research that was conducted using an exploratory approach. Data collection was done by semi-structured interview method. It is held through interviews with 12 R&D managers and experts, who are familiar by data science. Data analysis was done during the process of open, axcial and selective coding of grounded theory, using MAXQDA18 software, and finally the qualitative model was explained.

Findings: The findings of the research led to the identification of 8 dimensions (code axis) and 24 components (category) include: systematic management, ability to use big data analysis, application of data science, higher education, technical and non-technical infrastructure, government support, supply of resources, internal factors and external organization. It is organized in the form of the paradigm model of grounded theory, in six dimensions of causal factors, central category, strategies, intervening conditions, background conditions and consequences.

Conclusion: The qualitative model of research and development management was presented based on the process approach and integrated with the identified core components. In this model, data sources were added to the input part of the R&D management process. The ability to use big data analysis, research and development strategies, data science tools, system management and internal organizational factors are entered to the model processing part. While external organizational factors, higher education strategies and government support, technical infrastructure and organizational culture are mentioned as external effective components of the model.

Purpose: This paper aims to identify and explain the dimensions and components of a qualitative model of research and development management, based on big data analytics.

Methodology: The current study is a qualitative research that was conducted using an exploratory approach. Data collection was done by semi-structured interview method. It is held through interviews with 12 R&D managers and experts, who are familiar by data science. Data analysis was done during the process of open, axcial and selective coding of grounded theory, using MAXQDA18 software, and finally the qualitative model was explained.

Findings: The findings of the research led to the identification of 8 dimensions (code axis) and 24 components (category) include: systematic management, ability to use big data analysis, application of data science, higher education, technical and non-technical infrastructure, government support, supply of resources, internal factors and external organization. It is organized in the form of the paradigm model of grounded theory, in six dimensions of causal factors, central category, strategies, intervening conditions, background conditions and consequences.

Conclusion: The qualitative model of research and development management was presented based on the process approach and integrated with the identified core components. In this model, data sources were added to the input part of the R&D management process. The ability to use big data analysis, research and development strategies, data science tools, system management and internal organizational factors are entered to the model processing part. While external organizational factors, higher education strategies and government support, technical infrastructure and organizational culture are mentioned as external effective components of the model.