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Exploratory factor analysis (EFA) Sample paper.pdf


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RL4
RL3
RL2
RL8
Responsiveness
RE4
RE2
RE5
RE1
RE6


.719
.718
.709
.688

91.39

.756
.755
.725
.712
.573

94.10

Exploratory factor analysis (EFA) is a statistical technique used to reduce data to a smaller set of summary
variables and to explore the theoretical structure of the phenomena.
dimensions of multi-item measurement scales used in this study,

In order to determine underlying

Six items with inputs from

customers were loaded under Factor one with loading ranging from 0.826 to 0.875.
Hence it is named as “Tangibility” for functional quality.
 Five items were loaded under Factor Two with loading ranging from 0.935 to
0.977. Hence it is named as “Assurance” for functional quality.
 Five items were loaded under Factor Three with loading ranging from 0.718 to
0.819. Hence it is named as “Empathy” for functional quality.
 Six items were loaded under Factor Four with loading ranging from 0.688 to 0.745.
Hence it is named as “Reliability” for functional quality.
 Five items were loaded under Factor Five with loading ranging from 0.573 to
0.756. Hence it is named as “Responsiveness” for functional quality.
Table 2: Eigen values in the Functional Quality (n=43)
Factors
1
2
3
4
5

EIGENVALUE
S
9.244
5.129
4.685
3.822
2.426

%
TOTAL
VARIANCE
64.248
17.710
5.911
3.518
2.716

CUMULATIVE
EIGENVALUES
9.244
14.373
19.058
22.880
25.306

CUMULATIVE
PERCENTAGE
64.248
81.958
87.869
91.387
94.103

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