Open Access

Methods and Practices for Institutional Benchmarking based on Research Impact and Competitiveness: A Case Study of ShanghaiTech University


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Purpose

To develop and test a mission-oriented and multi-dimensional benchmarking method for a small scale university aiming for internationally first-class basic research.

Design/methodology/approach

An individualized evidence-based assessment scheme was employed to benchmark ShanghaiTech University against selected top research institutions, focusing on research impact and competitiveness at the institutional and disciplinary levels. Topic maps opposing ShanghaiTech and corresponding top institutions were produced for the main research disciplines of ShanghaiTech. This provides opportunities for further exploration of strengths and weakness.

Findings

This study establishes a preliminary framework for assessing the mission of the university. It further provides assessment principles, assessment questions, and indicators. Analytical methods and data sources were tested and proved to be applicable and efficient.

Research limitations

To better fit the selective research focuses of this university, its schema of research disciplines needs to be re-organized and benchmarking targets should include disciplinary top institutions and not necessarily those universities leading overall rankings. Current reliance on research articles and certain databases may neglect important research output types.

Practical implications

This study provides a working framework and practical methods for mission-oriented, individual, and multi-dimensional benchmarking that ShanghaiTech decided to use for periodical assessments. It also offers a working reference for other institutions to adapt. Further needs are identified so that ShanghaiTech can tackle them for future benchmarking.

Originality/value

This is an effort to develop a mission-oriented, individually designed, systematically structured, and multi-dimensional assessment methodology which differs from often used composite indices.

eISSN:
2543-683X
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Information Technology, Project Management, Databases and Data Mining