NIRF 2016 Ranking Framework for Management Institutions

Organisation : National Institutional Ranking Framework NIRF
Announcement : Ranking Framework for Management Institutions

Notification : https://www.entrance.net.in/uploads/9922-Managment.pdf
Home Page : https://www.nirfindia.org/Home

Ranking Framework for Management Institutions :

The methodology draws from the overall recommendations broad understanding arrived at by a Core Committee set up by MHRD, to identify the broad parameters for ranking various universities and institutions.

Related : NIRF Ranking Framework for Engineering Institutions : www.entrance.net.in/9921.html

The parameters broadly cover “Teaching, Learning and Resources,” “Research and Professional Practices,” “Graduation Outcomes,” “Outreach and Inclusivity,” and “Perception”.

Summary of Ranking Parameters Finalized by MHRD :
Sr.No. |Parameter |Marks |Weightage
1 Teaching, Learning & Resources (TLR) 100 0.30
2 Research, Professional Practice & Collaborative Performance (RPC) 100 0.30
3 Graduation Outcome (GO) 100 0.15
4 Outreach and Inclusivity (OI) 100 0.15
5 Perception (PR) 100 0.10

Teaching, Learning & Resources (TLR) :
Teaching, Learning & Resources (TLR) – 100 Marks
Ranking Weight : 0.30
Overall Assessment Metric: TLR = (FSR + FQE + LI + SEC + TI)
The component metrics are explained on the following pages.

Faculty-Student Ratio with Emphasis on Permanent Faculty (FSR): 30 Marks
** Assessment will be based on the ratio of number of regular faculty members in the ** Institute and total sanctioned/approved intake considering full time Programs.

** Regular appointment means tenured or tenure-track faculty on full time basis with no time limit on their employment. However, full-time faculty on contract basis for a period of not less than 3 years, on gross salary similar to those who are permanent can also be included.

**Only faculty members with Ph.D qualifications should normally be counted here. Faculty with lower than MBA qualification can not be counted.
**Visiting faculty (with a Ph.D) who are visiting the institution on a full time basis for at least one year can be included in the count for that semester as explained below.
** Assessment metric will be the same for Category A and Category B Institutions.
FSR = 30 × Min [10 × (F/N), 1]
Here,
N: Total number of students studying in the institution considering all PG Programs, including the Ph.D program.
F1: Full time regular faculty of all PG Programs in the previous year.
F2: Eminent faculty (with Ph.D) visiting the institution for at least one year on a full time basis can be counted (with a count of 0.5 for each such visiting faculty for a semester) in the previous year.
F = F1 + 0.3F2
Benchmarks:
Expected ratio is 1:10 to score maximum marks.
For F/N < 1: 50, FSR will be set to zero.

Data Collection:
From the concerned Institutions in prescribed format on an On-line facility. As mentioned in the preamble, an institution will be eligible for ranking, if all relevant and updated data about the faculty members (in the previous three years) is available on a publicly visible website. The data will be archived and also duplicated by the ranking agency.
Data Verification:
By the Ranking Agency on a random sample basis.

Combined Metric for Faculty with Ph.D and Experience (FQE) : 30 Marks
It is proposed to give equal weightage (15 marks each) to both qualifications and experience.
Doctoral Qualification:
This will be measured on the basis of percentage of faculty with Ph.D in a relevant field. The expected benchmarks would be different for Category A and Category B Institutions to account for ground realities.

Assessment metric for Category A Institutions on Ph.D Qualification:
FQ = 15 × (F/95), for F = 95%
FQ = 15, for F > 95%.
Here,
F is the percentage of Faculty with Ph.D. averaged over the previous 3 years. (Implies that the expected percentage is a minimum of 95% to score maximum score, decreasing proportionately otherwise).

Experience Metric:
Experience would normally be assessed based on Average relevant experience of the faculty members. Relevance here pertains to experience in the subject area being taught by the faculty member.

To simplify, Ei may also be calculated from the age profile of the faculty members as follows:
Ei = Ai – 30, for Ai <= 45 years.
Ei = 15, for Ai > 45 years.
Assessment Metric for Experience:
FE = 15 × (E/15), for E <= 15 years;
FE = 15, for E > 15 years.
Here,
E is the average years of experience of all faculty members as calculated above.
This implies that the benchmark average experience is to be fifteen (15) years to score maximum marks, decreasing proportionately otherwise.

Data Collection:
Institutions to submit information in a tabular form indicating faculty name, age, qualifications (indicating the University attended for the qualifying degree) and experience under the categories academic and industrial. Updated data for the last 3 years should be available on a publicly available website, and suitably archived for consistency check in subsequent years.
Data Verification: On a random sampling basis.

Combined Metric for Faculty Qualifications and Experience:
FQE = FQ + FE

Metric for Library Facilities (LI) – 15 Marks
Library:
LI = 15 × (Percentile parameter on the basis of annual expenditure (EXLI) on library resources per student)
EXLI = EXLIPS + EXLIES
EXLIPS = EXLIP/N
EXLIES = 2×EXLIE/N
Here,
EXLIP: Actual Annual Expenditure on Physical Resources, Books, Journals, etc.
EXLIE: Actual Annual Expenditure on Electronic Resources, Books, Journals etc.
If this expenditure is below a threshold value to be determined separately for each category of institutions, EXLI = 0.

Metric for Sports and Extra-Curricular Facilities, Activities :(SEC) – 10 Marks
Extra-Curricular (EC) activities may typically include, but not limited to Clubs/Forums, NCC, NSS etc.
Parameters to be used:
– Sports facilities area per student (A);
– Actual expenditure per student on Sports and EC activities (B) and;
– Number of top positions in inter-college event (C).
Each parameter to be evaluated on a percentile basis to obtain the percentile parameter p(A), p(B) and p(C). Weights assigned to the 3 components are 0.5, 0.25 and 0.25, respectively.
SEC = 10 × [p(A)/2 + p(B)/4 + p(C)/4].
Data Collection: To be obtained from the institutions.
Data Verification: By Ranking Agency on a random sample basis.