Research Topic

Advanced Analytics and Decision Making for Research Policy and Strategic Management

About this Research Topic

Processing large-scale data, recognizing uncertain and complex relationships, forecasting potential trend and investigating hidden mechanisms, and developing models with robustness and adaptability are all challenges that have risen due to the creation of increasingly complicated environments relevant to decision making in the real world. Bibliometrics, as an effective analytic tool, has provided systematic solutions for understanding the activities of science technology and innovation (ST&I). It has, thus, been supporting research policy and strategic management. The rapid development of information technologies - in particular, artificial intelligence techniques - has been bringing evolutionary changes to traditional bibliometrics as well as its applications. For example, natural language processing approaches, together with deep learning techniques, effectively encode semantic structures and identify sentimental elements from ST&I data sources. Similarly, large-scale network analytics leverage understandings on the topological structure of bibliometric networks to enable new angles for evaluating the dynamics of ST&I and to support science policy and entrepreneurship.

This Research Topic aims to explore the ways of fully facilitating the power of advanced analytics in order to enhance decision support for research policy and strategic management in scalable, uncertain, and complicated environments in the real world. Targeting broad issues in science, technology, and innovation policy, it emphasizes on the development and applications of advanced analytic approaches that provide transparent, explainable, and valuable evidence for decision making. This Research Topic spearheads a cross-disciplinary direction by covering information science, computer science, and business so as to present fundamental theories, conceptual methodologies, and practical toolkits for studies and practices in research policy and strategic management.

Driven by discipline-specific issues in research policy and strategic management, topics of interest include, but are not limited:

• Advanced bibliometric indicators and approaches
• Advanced network analytics for science maps
• Scholarly knowledge discovery and management
• Evidenced-based policy making in science, technology, and innovation policy
• Organizational methods and protocols in decision making for strategic management


Keywords: Bibliometrics, Data analytics, Decision making, Research policy, Strategic management


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Processing large-scale data, recognizing uncertain and complex relationships, forecasting potential trend and investigating hidden mechanisms, and developing models with robustness and adaptability are all challenges that have risen due to the creation of increasingly complicated environments relevant to decision making in the real world. Bibliometrics, as an effective analytic tool, has provided systematic solutions for understanding the activities of science technology and innovation (ST&I). It has, thus, been supporting research policy and strategic management. The rapid development of information technologies - in particular, artificial intelligence techniques - has been bringing evolutionary changes to traditional bibliometrics as well as its applications. For example, natural language processing approaches, together with deep learning techniques, effectively encode semantic structures and identify sentimental elements from ST&I data sources. Similarly, large-scale network analytics leverage understandings on the topological structure of bibliometric networks to enable new angles for evaluating the dynamics of ST&I and to support science policy and entrepreneurship.

This Research Topic aims to explore the ways of fully facilitating the power of advanced analytics in order to enhance decision support for research policy and strategic management in scalable, uncertain, and complicated environments in the real world. Targeting broad issues in science, technology, and innovation policy, it emphasizes on the development and applications of advanced analytic approaches that provide transparent, explainable, and valuable evidence for decision making. This Research Topic spearheads a cross-disciplinary direction by covering information science, computer science, and business so as to present fundamental theories, conceptual methodologies, and practical toolkits for studies and practices in research policy and strategic management.

Driven by discipline-specific issues in research policy and strategic management, topics of interest include, but are not limited:

• Advanced bibliometric indicators and approaches
• Advanced network analytics for science maps
• Scholarly knowledge discovery and management
• Evidenced-based policy making in science, technology, and innovation policy
• Organizational methods and protocols in decision making for strategic management


Keywords: Bibliometrics, Data analytics, Decision making, Research policy, Strategic management


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

About Frontiers Research Topics

With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author.

Topic Editors

Loading..

Submission Deadlines

05 June 2020 Abstract
03 October 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

Loading..

Topic Editors

Loading..

Submission Deadlines

05 June 2020 Abstract
03 October 2020 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

Loading..
Loading..

total views article views article downloads topic views

}
 
Top countries
Top referring sites
Loading..