RESEARCH
METHODOLOGY:

This
project assesses the efficiency of the universities that offer master courses
in business analytics based on following inputs and outputs. DEA analysis is
used to measure the efficiencies of different universities based on inputs and
outputs. Some of the most common inputs are number of faculty, number of
students enrolled, investment, course fee, student to faculty ratio and number
of research faculty. Common outputs are graduation rate, university ranking,
number of researches published, freshmen retention rate and average salary of
the graduate placed on campus. According to the results obtained from the
survey conducted among the students who aspires to graduate following inputs
and outputs were considered. Inputs are Course fee and Number of faculty
members and Number of students graduated and Average salary of the graduated
student are considered as outputs for this study.

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Data
Envelopment Analysis (DEA)

For
DEA analysis on measuring the efficiencies, outputs vary mostly on the decision
for taking inputs and outputs.

Inputs:

The
inputs are Course fee and Number of faculty members

Course
Fee: Course fees is considered as the input to the University for task
performance. In this research course fee is considered as an input. A
university is considered efficient if the University is charging low course fee
and providing more quality of education or university is considered inefficient
when it is charging high tuition fee, providing less quality of education.

Student
to faculty ratio: Availability of faculty members is also considered as an
input. The main aim of the university is to serve students with sufficient
faculty members. It will more or less indicate the number of students under the
guidance of each faculty. Efficiency is achieved when more output is achieved
with less number of faculty. This also reflects the faculty strength of the
university.

Outputs:

The
outputs considered are Number of students graduated and Average salary of the
graduated student are considered as outputs.

Number
of students graduated: Number of students graduated can also be termed as
graduation rate from that university. It usually refers to percentage or number
of students who has entered and completed the graduation. It is also an
important performance indicator.

Averages
salary of the graduated student: It is considered as an output, higher the
average salary indicates the student position in an organization. It is also a
performance indicator. It will let us know how many students are placed on
campus. Higher rate of on campus placement will indicate the university
efficiency.

 Table 1 lists the inputs and outputs
considered for the DEA.

Input

Output

Course
fee

Number
of students graduated

Number
of faculty members

Average
salary of the graduate student

Table 1: Inputs and outputs of DEA

Relative
ratios are calculated for sample units known as DMUs after the inputs and
outputs were determined. 20 decision making units are considered for the study.
These can be generally defined as an entity which is responsible for converting
inputs into outputs and evaluating their performances (Chuen & Kuan, 2011).
This study focuses on the 20 universities that are rated as top 20 universities
for master’s in business analytics by some of the reputed research and sites
such as U.S. News, organization of masters in science and analytics and Tech
republic. So, efficiency is determined among the top list of universities that
offer business analytics course.  This
study will stand as a sample study for many students who wants to graduate in
business analytics and aspire a career as business analytics.

The
study has collected the data from various university ranking websites and sites
of the universities which provides the recent data of their university and
performance. 4

While
taking the inputs and outputs for analysis data available in websites and
universities is taken into consideration. Furthermore, research can be done to
define the efficiency using all the available measures.

Number
of DMU’s condition is verified against inputs and outputs.

 i.e.

20

 3*(2+2). Hence DMU condition is satisfied.

Before
conducting the data envelopment analysis for the data, inputs and outputs are
checked with the basic assumption of DEA. The assumption of inputs and outputs
should be positively correlated. The correlation analysis of inputs and outputs
are shown in the table 2 below.

Correlation
Analysis

 

Graduation rate

Average
salary of the graduate student

Tuition Fee

0.371193488

0.032120628

Student to faculty ratio

0.021519923

0.145157127

Table 2: Correlation analysis of inputs
and outputs.

 

After
verifying all the measures of DEA. The DEA analysis is run in a software “DEA
frontier”.

The
results after the analysis are as follow:

Fig 1: Efficiency list of universities

After
calculating the DEA analysis, in the efficiency tab of the output shows the
list of all the universities which were found to be efficient. DMU’s 4,9 and 15
are found to be efficient with a maximum score of 1. After considering all the
inputs and outputs the universities that were found efficient are University of
southern California, New York university and University of Iowa.

In
the efficiency tab universities that are found to be inefficient are also
listed and they were benchmarked against the efficient universities with a
weighted value as shown in the below figure.

Fig 2: Efficiency tab of DEA analysis.

 

From
the above figure we can analyze that inefficient universities are benchmarked
against the efficient universities with a weighted value.

For
example:  University of Texas Austin is
verified against and should reference two efficient universities with their
given weights (New York university and University of Iowa)

It
is also represented in a simple equation:

University
of Texas at Austin 0.75868= 0.501 New York University + 0.548 University of
Iowa

DEA
analysis not only measure the efficiency it also explains how the inefficient
university can achieve the targets to become efficient university. In the
target tab, targets usually represent the amount of changes that the university
need to make to their inputs and outputs to achieve maximum efficiency.

This
analysis will also clearly explain how the respective inefficient universities
can become more efficient by achieving their targets. These targets usually
represent the amount of changes that they need to make to their inputs and
outputs to achieve maximum efficiency as shown in the below figure.

Fig 3: Target values for universities.

For
example: For university of Texas at Austin, if the university decrease the
tuition fee from $ 43000 to 32624 and decrease the student faculty ratio from
18:1 to 10:1 than the university can achieve efficiency.

In
appendix tab, data related to inputs and outputs can be found.

Thus,
by using the data envelopment methodology students will be able to define the
efficient universities among the list of the universities of their interest.