The project describes the analysis of gap in the expected and delivered level of service in the college mess. It includes data collection from students and analysing the data by using SPSS tool.

1. Determining the gaps in the services
provided by BIMTECH Mess
Submittedto: Submittedby:
Dr. A.K. Dey Udit Jain
Sreevatsan Natarajan
Tarun Mangal
Sonakshi Govil
Vanshika Gupta
Shruti Mittal
13DM206
13DM209
13DM204
13DM186
13DM212
13DM180

2. INTRODUCTION
BIMTECH Mess is a type of food service location in which there is little or no waiting staff table
service, whether a restaurant or within an institution such as a large office building or school.
Instead of table service, there are food-serving counters, either in a line or allowing arbitrary
walking paths. Students take the food they require as they walk along, placing it on a tray. In
addition, there are often stations where students wait while food is prepared, particularly for
items such as chapattis, egg fried rice which must be served hot and can be quickly prepared.
PROBLEM STATEMENT
Measuring the quality of a service can be a very difficult exercise. Unlike product where there
are specific specifications such as length, depth, width, weight, color etc. a service can have
numerous intangible or qualitative specifications. In addition there are expectations of the
customer with regards the service, which can vary considerably based on a range of factors
such as prior experience, personal needs and what other people may have told them
RESEARCH OBJECTIVE
Determine the gaps in the service quality of BIMTECH Mess. To give recommendations and
suggest the changes that could be made in the mess services to improve their quality and to
overcome negative gap score.
SCOPE OF THE STUDY
The study would cover students in BIMTECH Campus and RCI Vidya Vihar. The expectations and
perceptions of the students towards the services of Mess will be studied.
LITERATURE REVIEW
Service Quality
Today, Food Services in Messes that are provided by almost all institutes across India are under
the scanner by the students and parents on if being in the institute for a residential program or
letting their children away from home assures they get nutritious and hygienic food. Many
institutes are ensuring the best possible service for their customers.

3. A. Parasuraman, Valarie A. Zeithaml, and Leonard L. Berry (PZB) suggested:
 Service quality is more difficult for the consumer to evaluate than goods quality
 Service quality perceptions result from a comparison of consumer expectations with
actual service performance
Quality evaluations are not made solely on the outcome of service; they also involve
evaluations of the process of service delivery.
Satisfaction
The design of service settings may have a powerful effect on customer feelings and
perceptions. Simply showing courtesy and a sincere interest toward a customer will gain their
satisfaction. When service quality increases, the satisfaction with the service and intentions to
reuse the service is also increase. Bailey and Pearson (1983) define satisfaction in any given
situation as the total of one’s feelings or attitudes toward a variety of factors affecting that
situation. However, they point out that user satisfaction is hard to measure accurately. They
also suggest that attitudes and perceptions are different measures than satisfaction, and as
such, should not be ignored in research.
SERVQUAL
The original SERVQUAL questionnaire was designed to measure both expectations (forecast)
and perceptions (what actually happens) within a firm, with respect to service quality. The
original SERVQUAL started with 10 original dimensions After several revisions by the authors,
the original 10 dimensions were reduced to five dimensions in the final instrument used for this
study.
Tangibles: Physical facilities, equipment, and appearance of personnel.
Reliability: Ability to perform the promised service dependably and accurately.
Responsiveness: Willingness to help customers and provide prompt service.
Assurance: Knowledge and courtesy of employees and their ability to inspire trust.
Empathy: Caring, individualized attention provide to its customers.
When SERVQUAL was originally administered in 1985 to 1990s the same question was asked
twice. The first time the users were asked what their ideal situation was; the second time the
users were asked to evaluate their service support. The need to ask the same question twice is
a common cause of criticisminvolving use of the SERVQUAL instrument.

4. METHODOLOGY
Overview
This study used an online survey posted on a secure Web site which provided one selection per
item using the radio button force-completion method. This method avoided multiple invalid
answers, improved the accuracy of responses, and increased the valid response rate.
There are also other rationales for using an online survey:
No time limit: Subjects can take all the time they need and work at their own pace without a
time limit.
Short survey: The entire survey normally took about 10 minutes to complete. This discouraged
boredom and helped to prevent fatigue
Statistical Hypotheses
Five specific hypotheses were identified, which are stated below. The null hypothesis is simply
the hypothesis of “no difference” or “no relationship” existing between variables.
Ho1: There is no significant difference between Expectations and Perceptions in Tangibility.
Ho2: There is no significant difference between Expectations and Perceptions in Reliability.
Ho3: There is no significant difference between Expectations and Perceptions in
Responsiveness.
Ho4: There is no significant difference between Expectations and Perceptions in Empathy.
Ho5: There is no significant difference between Expectations and Perceptions in Assurance.
Instrument DesignandValidation
Framework
The SERVQUAL model has been widely used to study the service industry in general and
education customer service, the SERVQUAL method is a technique that can be used for
performing a gap analysis of an organization’s service quality performance against customer
service quality needs.
Reliability and Validity
SERVQUAL is a generic instrument with good reliability, validity, and broad applicability in the
original study of SERVQUAL.

5. Population
The population in this study involves all students in BIMTECH. According to the Institute there
are about 350 Students.
Sample
The research sample consisted of voluntary participants from all departments within the
college. The survey instrument was distributed through a secure web site and an invitation was
sent to everyone within the college. At the end of the five week data collection period, 105
participants responded.
Data Collection
Data for this study were collected using an online survey. We sent out e-mail with a link to the
online survey and asked the subjects to participate in the study. When the subjects clicked on
the hyperlink sent to them in the e-mail, they were taken to the secure Web site. This online
survey included 21 satisfaction questions. The whole process was expected to take about 20
minutes.
Analysis of Data
The results of this survey were stored on the secure web server. The data was easily exported
to a spreadsheet and transferred to the Statistical Package for the Social Sciences (SPSS) for
analysis.
Gap Analysis and Correlation: We performed GAP Analysis using t-test to check for any
difference between Expectations and Perceptions for each of the 21 variables. We would also
find the Co-relation between all the 5 dimensions of Expectations and Perceptions each done
separately. This would reveal if the participants of the survey were able to comprehend the
questions easily and were able to mark the answers accordingly.
Composite and Total Factor Analysis: After this a composite analysis by reducing them to 5
factors is done for Expectations and Perceptions separately. This will prove more accurate
check if our dimensions are loaded properly or if there is any overlapping. Now we would
merge the 10 factors (5 each) of expectation and perception into one single sheet and analyze
them to see if we are able to load perception and expectation separately into 2 factors.
At last, an analysis is done with all the data to analyze the number of components in which our
42 factors are being loaded.

6. Summary
Population: All BIMTECH Students.
Sample: Voluntary participants from above group.
Instrument: SERVQUAL instrument
Data Collection: Survey posted on secure Web site.
Procedures: Subjects remained totally anonymous
Data Analysis: Gap Analysis, Partial Correlation, Factor Analysis.
FINDINGS
Gap Analysis
Factor Analysis
After applying factor analysis on Expectations and perceptions separately, we found that in
expectation analysis only three variables are explaining 71.68 % of the results and in perception
analysis only four variables are explaining71.56 % of the results.
On applying factor analysis, using five factors on expectations and perception together having
all the 21 variables of each, there were four variables which explain 65.08 % of the results and if
we include fifth variable, 69.45 % of the results could be explained. So we do not take the fifth
variable as it does not contribute much.
On applying factor analysis, using Eigen plotting on expectations and perception together, there
were seven variables explaining 74.23 % of the results, which is almost same as that of
expectation and perception individually. If we reduce our dimension to seven, having three
variables of expectations and four of perception, it will explain around 71.68 % of the results in
case of expectations, 71.56 % in case of perception and 74.23 % of total results.