Understanding the performance of universities to promote technological innovation and transformation
An application to China based on a new network data envelopment analysis cross‐efficiency model
Bibliographic Data
| ID | 21592455 |
|---|---|
| Authors | Yaotian Sun (The Center for Economic Research, Shandong School of Development Shandong University Jinan China), Ruchuan Zhang (0000-0002-6049-8993, The Center for Economic Research, Shandong School of Development Shandong University Jinan China), Liqi Hu (0009-0005-6289-2926, The Center for Economic Research, Shandong School of Development Shandong University Jinan China), Aijun Li (0000-0003-2654-5781, The Center for Economic Research, Shandong School of Development Shandong University Jinan China, corresponding author) |
| Year | 2023 |
| Volume | 77 |
| Issue | 4 |
| Pages | 932-968 |
| Publication date | 2023-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Higher Education Quarterly (JOURNAL) |
| Journal identifiers | ISSN: 0951-5224 • E-ISSN: 1468-2273 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/hequ.12442 |
| OpenAlex | W4379932671 |
| Language | EN |
| References cited | 87 |
When evaluating the performance of Research and Development (R&D) and Scientific and Technological (S&T) transformation activities in universities, the existing studies do not contain prior strategy analysis and inequality analysis. In this regard, prior strategy reflects the relative attention paid by universities to R&D and S&T transformation activities, while inequality analysis assists us in better understanding technological inequality in efficiency across universities. Additionally, this study contributes to the existing literatures by proposing new concepts of window‐based cross‐efficiency, window‐based relative weights and a network Data Envelopment Analysis model. Our framework is able to evaluate the efficiency, perform priority analysis and identify the sources of technological inequality. Empirically, this study focuses on universities in Chinese provinces from 2007 to 2019. This study is of high policy practice, since it provides policy makers with how each university has performed during the examined period and what are the underling factors driving efficiency changes
Business · China · Data envelopment analysis · Economics · Efficiency · Inequality · Political science · Statistics · Computer Science · Efficiency Analysis Using DEA · Energy, Environment, Economic Growth · Innovation Policy and RD · Mathematics
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| Highly cited | No |
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