View the archived 2022 results of the听色盒直播听Asia听University Rankings
罢丑别听Times Higher Education听World University Rankings are the only global performance tables that judge research-intensive universities across all their core missions: teaching, research, knowledge transfer and international outlook. The Asia University Rankings use the same 13 carefully calibrated performance indicators to provide the most comprehensive and balanced comparisons, trusted by students, academics, university leaders, industry and governments. However, the weightings are specially recalibrated to reflect the priorities of Asian institutions.
The performance indicators are grouped into five areas:听teaching听(the听learning environment);听research听(volume, income and reputation);听citations听(research influence);听international outlook听(staff, students and research); and听industry income听(knowledge transfer).

Teaching听(the learning environment): 25%
- Reputation survey听10%
- Staff-to-student ratio听4.5%
- Doctorate-to-bachelor鈥檚 ratio听2.25%
- Doctorates-awarded-to-academic-staff ratio 6%
- Institutional income 2.25%
The most recent Academic Reputation Survey (run annually) that underpins this category was carried out between November 2020 and February 2021. It examined the perceived prestige of institutions in teaching. The responses were statistically representative of the geographical and subject mix of academics globally. The 2021 data are combined with the results of the 2020 survey, giving听almost 22,000 responses.
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As well as giving a sense of how committed an institution is to nurturing the next generation of academics, a听high proportion of postgraduate research students also suggests the provision of teaching at the highest level that is thus attractive to graduates and effective at听developing them. This indicator is normalised to take account of a university鈥檚 unique subject mix, reflecting that the volume of doctoral awards varies by discipline.
Institutional income is scaled against academic staff numbers and normalised for purchasing-power parity. It indicates an institution鈥檚 general status and gives a broad sense of the infrastructure and facilities available to students and staff.
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Research听(volume, income and reputation): 30%
- Reputation survey听15%
- Research income听7.5%
- Research productivity听7.5%
The most prominent indicator in this category looks at a university鈥檚 reputation for research excellence among its peers, based on the responses to our annual Academic Reputation Survey (see above).
Research income is scaled against academic staff numbers and adjusted for purchasing-power parity (PPP). This is a controversial indicator because it can be influenced by national policy and economic circumstances. But income is crucial to the development of world-class research, and because much of it is subject to听competition and judged by peer review, our experts suggested that it was a valid measure. This indicator is fully normalised to听take account of each university鈥檚 distinct subject profile, reflecting the fact that research grants in science subjects are often bigger than those awarded for the highest-quality social science, arts and humanities research.
To measure productivity we count the number of papers published in the academic journals indexed by Elsevier鈥檚 Scopus database per scholar, scaled for institutional size and normalised for subject. This gives a sense of the university鈥檚 ability to get papers published in quality peer-reviewed journals. From the 2018 rankings, we devised a method to give credit for papers that are published in subjects where a university declares no staff.
Citations听(research influence): 30%
Our research influence indicator looks at universities鈥� role in spreading new knowledge and ideas. We examine research influence by capturing the average number of times a university鈥檚 published work is cited by scholars globally.
This year, our bibliometric data supplier Elsevier examined 108 million citations to 14.4 million journal articles, article reviews, conference proceedings and books and book chapters published over five years. The data include more than 24,600 academic journals indexed by Elsevier鈥檚 Scopus database and all indexed publications between 2016 and 2020. Citations to these publications made in the six years from 2016 to 2021 are also collected.
The citations help to show us how much each university is contributing to the sum of human knowledge: they tell us whose research has stood out, has been picked up and built on by other scholars and, most importantly, has been shared around the global scholarly community to听expand the boundaries of our understanding, irrespective of discipline.
The data are normalised by the overall number of papers produced to reflect variations in citation volume between different subject areas. This means that large institutions or those with high levels of research activity in subjects with traditionally high citation counts do not gain an unfair advantage.
We have blended equal measures of a country-adjusted and non-country-adjusted raw measure of citation scores.
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In 2015-16, we excluded papers with more than 1,000 authors because they were having a听disproportionate impact on the citation scores of a small number of universities. In 2016-17, we designed a method for reincorporating these papers. Working with Elsevier, we have developed a fractional counting approach that ensures that all universities where academics are authors of these papers will receive at least 5听per cent of the value of the paper, and where those that provide the most contributors to the paper receive a proportionately larger contribution.
International outlook听(staff, students, research): 7.5%
- International-to-domestic-student ratio听2.5%
- International-to-domestic-staff ratio听2.5%
- International collaboration 2.5%
The ability of a university to听attract undergraduates, postgraduates and faculty from all over the planet is key to its success on the world stage.
In the third international indicator, we calculate the proportion of a university鈥檚 total research journal publications that have at least one international co-author and reward higher volumes. This indicator is normalised to account for a听university鈥檚 subject mix and uses the same five-year window as the 鈥淐itations: research influence鈥� category.
Industry income听(knowledge transfer): 7.5%
A university鈥檚 ability to help industry with innovations, inventions and consultancy has become a core mission of听the contemporary global academy. This category seeks to capture such knowledge-transfer activity by looking at听how much research income an institution earns from industry (adjusted for PPP), scaled against the number of academic staff it听employs.
The category suggests the extent to which businesses听are willing to pay for research and a university鈥檚 ability to听attract funding in the commercial marketplace 鈥撎齯seful indicators of institutional quality.
Exclusions
Universities are excluded from the World University Rankings if they do not teach undergraduates or if their research output amounted to fewer than 1,000 relevant publications between听2016 and 2020听(and a听minimum of 150 a听year). Universities can also be excluded if 80听per cent or more of their research output is exclusively in one of our 11 subject areas.
Data collection
Institutions provide and sign off their institutional data for use in the rankings. On听the rare occasions when a particular data point is not provided, we enter a conservative estimate for the affected metric. By doing this, we avoid penalising an听institution too harshly with a听鈥渮ero鈥� value for data that it overlooks or听does not provide, but we do听not reward it for withholding them.
Getting to the final result
Moving from a series of specific data points to indicators, and finally to a total score for an institution, requires us to match values that represent fundamentally different data. To do this, we use a standardisation approach for each indicator and then combine the indicators in the proportions indicated to the right.
The standardisation approach we use is based on the distribution of data within a particular indicator, where we calculate a cumulative probability function, and evaluate where a particular institution鈥檚 indicator sits within that function.
For all indicators except the Academic Reputation Survey, we calculate the cumulative distribution function of a normal distribution using Z-scoring. The distribution of the data听in the Academic Reputation Survey requires us to add an exponential element.
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