Academic Reputation

The results are based on the responses to a survey distributed worldwide to academics from a number of different sources, including:

• Previous Respondents
• Submitted contact lists from institutions (see Survey Nominations Procedure)
• Sign-ups on our sign-up facility (see Survey Nominations Procedure)
• IBIS database - see IBIS

The Survey

The survey is sent to many thousands of global academics each year. It has largely followed the same principles since inception, with some variation depending on academic themes of interest over time. At the beginning of the survey, academics state their discipline area and their regional familiarity. The answers to this then guide the range of answers they can give in the remainder of the survey. We ask the following questions of each respondent:

Individual Characteristics

• Their name
• Their institution
• Their job
• The number of years they have been in academia

Knowledge Specification

• Which country/territory they are most familiar with, from an academic perspective. This will define the list of institutions from which the respondent can nominate domestically.
• Which region(s) they are most familiar with, from an academic perspective. Regional knowledge responses are grouped into three supersets that define the list of institutions from which the respondent can select when nominating internationally. These are Americas, APAC (Asia, Australia & New Zealand) and EMEA (Europe, Middle East & Africa).
• The faculty area in which they are most active and knowledgeable .
• The specific field (up to a maximum of two)* that they specialize in.

* Certain QS Subjects are not explicitly present in the survey form. This includes Geology, Geophysics and Petroleum Engineering. In such cases we derive their nominations and further transformations (see below) from the corresponding proxy field of study, which is available in the survey form: Geology and Geophysics are fully derived from Earth & Marine Sciences, while Petroleum Engineering is a weighted sum of Chemistry (5%), Environmental Sciences (5%), Earth & Marine Sciences (30%), Chemical Engineering (30%) and Electrical & Electronic Engineering (30%).

Top Domestic Institutions

• Academics are asked to nominate up to 10 institutions from their country/territory of knowledge that they think are demonstrating academic excellence. Their own institution is not available for selection.

Top International Institutions

• Academics are asked to nominate up to 30 institutions outside of their country/territory of knowledge that they think are demonstrating academic excellence. Their own institution is excluded. Although the main list consists solely of institutions from the region(s) with which they express familiarity with, academics are able to commend up to 10 institutions from other regions

Additional Questions

To answer certain higher education insight needs, or to receive feedback on our products, other additional questions may be asked. These questions necessarily vary from year to year, and are not shared in advance of our survey. 

If an academic respondent selects Business & Management, Accounting & Finance or Marketing as their field (narrow subject) of knowledge in the main track of the academic survey, then we ask what level of education they are primary focused on in their current role (Undergraduate, Masters, Doctoral, etc.). If Masters level is selected, then the business school track of the academic survey commences.

Top Business Schools

Academics are asked to identify up to 10 business schools, either domestic or international, that they regard as producing the best research in their field(s) of expertise. Their own institution is excluded. The list consists of all business schools (both standalone and child institutions), regardless of the region of knowledge selected in the main track of the survey. 

Data cleaning and validity checks

Once the survey has been collated, a variety of checks and balances are performed to ensure the responses are valid, useable and complete. As part of our normal data procedures, we can and do clean the data we use in the results analysis. This includes research data (removals of self-citations, high levels of affiliations), staff/student data (damping beyond certain thresholds, rejections of spurious data), and reputation data.  

As for QS Academic Reputation surveys, we evaluate nominations for approximately 7000 institutions each year and apply sophisticated and, importantly, non-manual processes to this cleaning. Over time, we improve the sophistication of these data science techniques, as one would hope from a company that prides itself on being a trusted data partner to the sector. One of the major iterations of such improvements took place in 2023, thus making our data validation techniques even more stringent for the upcoming ranking cycles. 

If an institution is following the protocol outlined below, then the reputation data should be captured in full by QS: 

1. Utilizing either the survey-sign up or contact list submission process for surveys. 
2. Ensuring that the people you nominate for surveys are eligible to take them, and that they are taking them in good-faith. 
3. Ensuring that the people you nominate to take the surveys are actually the people who go on to take them. 
4. Act independently in this process, i.e., not be seen to coach or solicit certain responses. 

We cannot comment on whether the above is or is not being followed by any specific institution, but suffice to say that if it is, then your institution should have no concerns. For reasons of data integrity and to prevent attempts to game the process, we do not publish a comprehensive list of our checks and validations, in line with good data governance protocols.

Step by Step Analysis

Once the responses have all been processed, we apply the following procedures for all of the nominations for each of our five broad faculty areas (in case of QS World University Rankings, QS University Rankings by Region or QS Rankings by Faculty) or for each of our individual narrow subject areas (in case of QS Rankings by Subject). 

• International Weighted Count
  Derive a weighted count of international nominations for each institution (excluding self-nominations), based on regional and country-level knowledge of a respondent, as well as a year of response.
  
  • Regional Familiarity and Faculty Knowledge Weights
    Devise and apply weightings based on the regional and faculty familiarity of respondents. This is done to balance the representation of three regional super sets (see above) in our surveys. Respondents are able to relate to more than one region. The aim here is to ensure that over-represented regions and faculty areas are not obscuring nominations from less represented regions and faculty areas. If a respondent commends an institution out of their regional familiarity, such a nomination is weighted lower (20% of a regular international nomination). 
  • Country Weights *
    Devise weightings based on the location with which respondents consider themselves familiar. Here we look at the number of well recognized institutions in the location per response originated from it, such that high denominator values would tend to have high nominator values (we largely expect the volume of responses from a country to correlate with its international recognition). Locations with a low participation rate are exempted from this to avoid small number effects.
    * Currently, not applicable for QS World University Rankings and QS University Rankings by Region
    
  • Year Weights
    Here, we use a 5 year aggregation of nominations, where the earlier two years count for 25% (year 5) and 50% (year 4), and the most recent three years at full 100% weight. 
• Domestic Weighted Count
  Derive a weighted count of domestic nominations for each institution (excluding self-nominations).  This is adjusted against the number of institutions from that country with a certain level of international nominations and the total volume of responses from that country. Larger countries with more recognized institutions naturally face more competition in terms of gaining nominations, and this is designed to reflect and reward this. 
• Normalize both domestic and international count to achieve a score out of 100.
• Combine the two scores with the relevant weights (see the table below)
• Various transformation techniques applied to minimize the impact of outliers and scale the numbers to present a score out of 100 for the given faculty area.

QS World University Rankings and QS University Rankings by Region

The scores across the five faculty areas are then combined with an equal weighting to produce the final score per institution for Academic Reputation. The adopted assumption here is that, in a typical international comprehensive university, each of these faculty areas represents a roughly equitable share of activity. Looking at the distribution of students might inspire a great emphasis on Arts & Humanities and Social Sciences in many countries, whilst looking at the allocation of research funding would lean towards medicine and sciences where research is, typically, more expensive. Thus, equalizing these faculty areas for Academic Reputation seems a fair and balanced approach. In other words, institutions that see a skewed distribution of nominations across faculty areas may perform less well than those with a flatter distribution.

QS Subject Rankings

In our Subject Rankings, there is a possibility that institutions with well-known strengths in a given discipline may be undervalued with respect to comprehensive institutions with a strong overall reputation and research profile. An example could be a specialized Art & Design institution vs. a large multidisciplinary university. To address this, and better identify institutions with key strengths in a particular area, we apply the following adjustments where relevant. 

• We look at the divergence between academic reputation in the specific subject and academic reputation in the corresponding broad subject area (or between the academic reputation in the broad subject area and overall academic reputation, for broad subject area rankings). This means that the academic reputation scores of institutions that fare better in the specific discipline than in the associated broad faculty area are given a proportional boost, while those that fare worse have those shortfalls proportionally amplified. The result is that the key strengths of institutions shine brighter and less credit is attributed to overall reputation and strength in adjoining disciplines.
• An extra boost may be applied to institutions identified as Specialists (see QS Institution Classification), if they offer academic programs in the relevant subject area (for QS Rankings by Subject) or faculty area (for QS Rankings by Faculty).
• Responses from academics expressing knowledge of a single specific discipline are given additional weight.

Domestic and international nomination weights used in various rankings

* As a general principle, we expect the volume of responses from a country/territory to correlate with the number of institutions available in our ranking, and particularly the number of high-performing institutions (impact). If, however, an anomalous number of responses are showing from a country/territory that does not achieve this 'volume by impact' measure, we inspect the nominations more thoroughly. If the highest nominating country is a neighboring country/territory, which, in turn, provides more than 10% of all the international nominations received by that neighbor, we adjust these mutual nominations to the corresponding 'domestic' weight in the analysis. 

In Business School Rankings, the analysis follows the same step-by-step procedure, with the following caveats: 

• We do not break down our analysis by faculty area 
• A regional weighting (step 1) is not applied 
• Standalone business schools that receive nominations are boosted to combat the advantage that affiliate/child schools have due to the halo effect that may exist from the parent institution.
• If a business school or its parent institution (any) was nominated in the main track of the survey in one of the business-related subject areas (see below), then the business school is rewarded additionally, to reflect its broader brand awareness.

Mapping between subject areas available for selection in the QS Academic Survey and QS Global MBA Rankings (MBA); QS Business Masters Rankings: Masters in Management (MIM), Masters in Finance (MIF), Masters in Business Analytics (MSB), Masters in Marketing (MMK), Masters in Supply Chain Management (MSM); QS Online MBA Rankings (OMBA); QS Executive MBA Rankings (EMBA)