A multicriteria quality evaluation method for organized scientific research considering heterogeneous information

Area of Science:

• Scientific research management
• Higher education quality assessment
• Information fusion

Background:

• Current multi-criteria quality evaluation methods for organized scientific research lack clarity in indicator construction and struggle with heterogeneous information.
• Existing approaches often neglect uncertainty in weight calculations and employ unscientific information fusion mechanisms.

Purpose of the Study:

• To propose a novel multi-criteria quality evaluation method for organized scientific research that effectively handles heterogeneous information.
• To improve the scientific rigor of quality evaluation by addressing limitations in indicator construction, data handling, and information fusion.

Main Methods:

• Developed evaluation indicators for organized scientific research based on systems-theoretic accident modeling and processes theory, incorporating contextual influences.
• Proposed a method involving heterogeneous information transformation, a weight determination model, an information fusion mechanism, and a quality evaluation approach.

Main Results:

• The proposed method demonstrated reasonable construction indicators and effectively handled uncertainty and fuzziness in data.
• The algorithm successfully managed heterogeneous evaluation information, showing superiority over existing methods.

Conclusions:

• The developed method offers a more scientific and robust approach to multi-criteria quality evaluation of organized scientific research.
• The findings suggest the method's applicability and effectiveness in real-world scenarios, particularly within university settings.