final report

1. Customer Perception about Coaching
Institutes for MBA
Group 7
Charan Kamal Singh (7)
Maneesha Gautam (15) Manjalika Raj (16)

2. Index
S. No. Contents Page No.
1. Conceptual Model

3. Research Objectives:
 To study the impact of Service Performance parameters on Customer’s (student) Perception.
 To study the effect of demographics on relationship between Service Performance and Customer
Perception.
Research Hypothesis:
From the research objectives we define our null research hypothesis as follows:
H1: Service Performance factors have no significant impact on the custome r’s perception
about coaching institutes.
H1.1: Reliability has no significant impact on customer’s perception.
H1.2: Responsiveness has no significant impact on customer’s perception.
H1.3: Assurance has no significant impact on customer’s perception.
H1.4: Empathy has no significant impact on customer’s perception.
H1.5: Tangibles has no significant impact on customer’s perception.
.
H2: Service Performance parameters are independent of demographics.
H2.1: Service Performance parameters are independent of Age.
H2.2: Service Performance parameters are independent of Gender.
H2.3: Service Performance parameters are independent of Family Income.
H2.4: Service Performance parameters are independent of Educational background.
H2.5: Service Performance parameters are independent of Work Experience.
H3: Customer Perception is independent of demographics.
H3.1: Customer Perception is independent of Age.
H3.2: Customer Perception is independent of Gender.
H3.3: Customer Perception is independent of Educational background.
H3.5: Customer Perception is independent of Work Experience.

4. Independent Variables: Reliability, Responsiveness, Assurance, Empathy, Tangibles
Dependent Variable: Customer Perception
Conceptual Model
SERVICE PERFORMANCE
PARAMETERS
DEMOGRAPHICS
H1 H2
RELIABILITY
RESPONSIVENESS
ASSURANCE
EMPATHY
TANGIBLES
AGE
SEX
FAMILY INCOME
EDUCATIONAL
BACKGROUND
WORK EXPERIENCE
CUSTOMER
PERCEPTION

5. Research Objectives:
 To study the impact of Service Performance parameters on Customer’s (student) Perception.
 To study the effect of demographics on relationship between Service Performance and Customer
Perception.
Research Hypothesis:
From the research objectives we define our null research hypothesis as follows:
H1: Service Performance factors have no significant impact on the custome r’s perception
about coaching institutes.
H1.1: Reliability has no significant impact on customer’s perception.
H1.2: Responsiveness has no significant impact on customer’s perception.
H1.3: Assurance has no significant impact on customer’s perception.
H1.4: Empathy has no significant impact on customer’s perception.
H1.5: Tangibles has no significant impact on customer’s perception.
.
H2: Service Performance parameters are independent of demographics.
H2.1: Service Performance parameters are independent of Age.
H2.2: Service Performance parameters are independent of Gender.
H2.3: Service Performance parameters are independent of Family Income.
H2.4: Service Performance parameters are independent of Educational background.
H2.5: Service Performance parameters are independent of Work Experience.
H3: Customer Perception is independent of demographics.
H3.1: Customer Perception is independent of Age.
H3.2: Customer Perception is independent of Gender.
H3.3: Customer Perception is independent of Educational background.
H3.5: Customer Perception is independent of Work Experience.

6. Independent Variables: Reliability, Responsiveness, Assurance, Empathy, Tangibles
Dependent Variable: Customer Perception
Demographic variables: Age, Gender, Family income, Educational background, Work experience
3. Data Analysis
3.1 Descriptive Analysis of the Sample:
3.1.1 Frequency analysis with respect to Age.
Table: Frequency distribution of sample with respect to Age
Indicate your age bracket
Frequency Percent Val id Percent
Cumulative
Percent
Val id BELOW 20 8 6.7 6.7 6.7
20-25 109 90.8 90.8 97.5
26-30 3 2.5 2.5 100.0
Tota l 120 100.0 100.0
Figure: Graphical representation of sample with respect to Age

7. Inte rpretation: Above graph shows that 6.67% of the respondents are in age group below 20,
90.83% of the respondents are in age group 20-25 and 2.5% of the respondents are in age group
26-30.
3.1.2 Frequency analysis with respect to Gender.
Table: Frequency distribution of sample with respect to Gender
Gender: Male or Female
Frequency Percent Val id Percent Cumulative Percent
Val id Male 62 51.7 51.7 51.7
Female 58 48.3 48.3 100.0
Tota l 120 100.0 100.0
Figure: Graphical representation of sample with respect to Gender
Interpretation: Above graph shows that 48.33% of the respondents are females, 51.67% of the
respondents are males.

8. 3.1.3 Frequency analysis with respect to Family income.
Table: Frequency distribution of sample with respect to Family income.
Indicate your family income bracket
Frequency Percent Val id Percent
Cumulative
Percent
Val id LESS THAN 1,00,000 3 2.5 2.5 2.5
1,00,000 - 2,00,000 9 7.5 7.5 10.0
2,00,001- 5,00,000 39 32.5 32.5 42.5
5,00,001 -10,00,000 36 30.0 30.0 72.5
Above 10,00,000 33 27.5 27.5 100.0
Tota l 120 100.0 100.0
Figure: Graphical representation of sample with respect to Family income.
Inte rpretation: Above graph shows that 2.5% of the respondents have annual income of family
less than Rs 100000, 7.5% of the respondents have annual income of family between Rs 100000-
200000, 32.5% of the respondents have annual income of family between Rs 200000 - 500000,
30% of the respondents have annual income of family between Rs 500000 - 1000000 and
27.5% of the respondents have annual income of family more than Rs 1000000.

9. 3.1.4 Frequency analysis with respect to Education background.
Table: Frequency distribution of sample with respect to Educational Background.
Indicate your Education Background
Frequency Percent Valid Percent
Cumulative
Percent
Valid ENGINEERING 77 64.2 64.2 64.2
SCIENCE 7 5.8 5.8 70.0
COMMERCE 27 22.5 22.5 92.5
MANAGEMENT 3 2.5 2.5 95.0
OTHERS 6 5.0 5.0 100.0
Total 120 100.0 100.0
Figure: Graphical representation of sample with respect to Educational Background
Inte rpretation: Above graph shows that 64.17% of the respondents are engineering students,
5.83% of the respondents are science students, 22.5% of the respondents are commerce students,
2.5% of the respondant are management students and 5% of the respondents are with other
preference students.

10. 3.1.5 Frequency analysis with respect to Work experience.
Table: Frequency distribution of sample with respect to Work experience.
Indicate your Work Experience
Frequency Percent Val id Percent
Cumulative
Percent
Val id NIL 101 84.2 84.2 84.2
0-12 MONTHS 11 9.2 9.2 93.3
13-24 MONTHS 5 4.2 4.2 97.5
25-36 MONTHS 1 .8 .8 98.3
ABOVE 36 MONTHS 2 1.7 1.7 100.0
Tota l 120 100.0 100.0
Figure: Graphical representation of sample with respect to Work Experience.
Inte rpretation: Above graph shows that 84.17% of the respondents are having no work
experience, 9.17% of the respondents are having work experience 0-12 months, 4.17% of the
respondents are having work experience 13-24 months, 0.82% of the respondents are having work
experience 25-36 months, 1.67% of the respondents are having work experience above 36moths.

11. 3.3 Tests of normality
Table: Normality values for different variable.
Interpretation: For each of the variables mentioned above significant value (p) is ≤ 0.05, that
means data is not normally distributed.
3.4 Correlation Analysis
Table: Correlation between parameters of Service Performance, Average Service Performance and Customers
Perception.

12. Results of Correlation Analysis:
1. The correlation coefficient between Customer perception and Reliability is 0.622, with p= 0.00. Thus
there is a significant positive association between Customer perception and Reliability. Hence, we
reject our Hypothesis H1.1.
2. The correlation coefficient between Customer perception and Responsiveness is 0.634, with p= 0.00.
Thus there is a significant positive association between Customer perception and Responsiveness.
Hence, we reject our Hypothesis H1.2.
3. The correlation coefficient between Customer perception and Assurance is 0.595, with p= 0.00. Thus
there is a significant positive association between Customer perception and Assurance. Hence, we
reject our Hypothesis H1.3.
4. The correlation coefficient between Customer perception and Empathy is 0.627, with p= 0.00. Thus
there is a significant positive association between Customer perception and Empathy. Hence, we
reject our Hypothesis H1.4.
5. The correlation coefficient between Customer perception and Tangibility is 0.638, with p= 0.00. Thus
there is a significant positive association between Customer perception and Reliability. Hence, we
reject our Hypothesis H1.5.
Hence, from above we find that all the five service performance parameters are significantly
affecting the Customer Perception.
3.5 Regression Analysis
Applying the regression test between all the five service performance parameters factors and
Customer Perception.
Table: Summary of the regression model
Model Summary
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate
1 .757a .573 .554 .538
a. Predictors: (Constant), AVG_TAN, AVG_REL, AVG_ASU,
AVG_EMP, AVG_RES
Inte rpretation: We got the value of R = 0.757 and R square = 0.573. The value of R square tells
us what percent of the variance in the dependent variable has been explained by the considered
independent variables. Thus, in our research, service performance parameters i.e. Reliability,
Responsiveness, Assurance, Empathy, Tangibles can explain 75.7% of the variance in the
Customer Perception.

13. Table: ANOVA table giving the p value
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 44.278 5 8.856 30.596 .000a
Residual 32.996 114 .289
Total 77.274 119
a. Predictors: (Constant), AVG_TAN, AVG_REL, AVG_ASU, AVG_EMP, AVG_RES
b. Dependent Variable: AVG_CP
Interpretation: We got the value of p = 0.000. Since, p value is less than 0.05, thus the relationship is
significant at 100 % confidence level which is very high.
Table: Coefficients of the significant factors in the regression equation

14. ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 44.278 5 8.856 30.596 .000a
Residual 32.996 114 .289
Total 77.274 119
a. Predictors: (Constant), AVG_TAN, AVG_REL, AVG_ASU, AVG_EMP, AVG_RES
Interpretation: The above table gives us the coefficients of the independent variables in the required
regression equation. We get, Y = -0.004 + 0.320*X1 + 0.186*X2+0.251*X3+0.100*X4+0.164*X5
Where, Y = Customer Perception
X1= Average Reliability
X2 = Average Responsiveness
X3= Average Assurance
X4= Average Empathy
X5= Average Tangibles