Hypothesis Examination

8/13/2019 Hypothesis Examination

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PROPOSED CONCEPTUAL MODEL

H1

H6

H2

H7

H3

H8 H11

H12

H13

H4 H14

H9 H15 H16

H18 H17

H10 H19

H5 H20

Core

Human

System

Tangible

Social

Loyalty

Switching

Propensity

Pay

more

Ext & Int

Response

Service Quality Dimensions Behavioral Intention Dimensions


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Structural Equation ModellingTo test the efficacy of the proposed model, the researcher employed SEM. The major

advantages of the SEM was that it allowed simultaneous equation estimation that assess both

measurement issues and causal relationships in one model and the use of path analysis that

statistically and visually illustrates the system of complex relationships. A path diagram helps

clearly present the direction of each effect and the correlation or non correlation among all

variables in one complete picture (Bollen, 1989). Structural equation analysis includes

investigations of both structural and measurement models. The structural model is the path

model, which relates the independent to the dependent variables. Structural model analysis is

an essential tool for the identification of the causal relationship between several constructs in

which separate multiple regression equations are estimated simultaneously (Henderson, 1999).

The measurement model allowed the researcher to use several variables for a single

independent or dependent variable and assesses the contribution of each scale item as well as

incorporate how well the scale measures the concept into the estimation of the relationship

between the dependent and independent variables (Fassinger, 1986; Hair, et al., 1995).

Measurement Assessment

The measurement model describes the relationship between the measured variables or

indicators (i.e., specific items) and latent variables (i.e., dimension or sub-dimensions).

The results of the measurement model test determine how well the indicators capture their

specified constructs. In this study, the researcher tested nine separate sets of measurement

models. More specifically, a measurement was developed and tested for each of the primary

dimensions (i.e., Core Service, Human Element of Service Delivery, Systematization of

Service Delivery, Tangibles of Service Delivery and Social Responsibility) and the four

outcome variables (i.e., Loyalty, Switching Propensity, Pay more and External & Internal


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The values of CFI should be near to 0.9. (Rigdon, 1996). For a more thorough description of

the goodness-of-fit indices, please refer to the article written by Mulaik, and his colleagues

(1989). The more criteria the proposed model satisfies, the better is its fit (Kline, 1998).

When the proposed models satisfy the above criteria, descriptors of "good" and adequate"

were used (Kline, 1998).

INTEGRATED STRUCTURAL MODEL-BANKQUAL ON BI-HSBC FOREIGN

BANK.


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Examination of the Hypotheses:

H1-The customers perception of service quality dimension namely core service delivery

directly influence the customers behavioural intentions dimension namely Loyalty.

H2- The customers perception of service quality dimension namely Human Element of

service delivery directly influence the customers behavioural intentions dimension namely

Loyalty.

H3- The customers perception of service quality dimension namely systematization of


Loyalty.

H4- The customers perception of service quality dimension namely Tangibles of service

delivery directly influence the customers behavioural intentions dimension namelyLoyalty.

H5- The customers perception of service quality dimension namely Social Responsibility of


Loyalty.


directly influence the customers behavioural intentions dimension namely Switching

Propensity.

H7- The customers perception of service quality dimension namely Human Element ofservice delivery directly influence the customers behavioural intentions dimension namely

Switching Propensity.





delivery directly influence the customers behavioural intentions dimension namely


H10- The customers perception of service quality dimension namely Social Responsibility

of service delivery directly influence the customers behavioural intentions dimension namely



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directly influence the customers behavioural intentions dimension namely Pay More.



Pay More.



Pay More.


delivery directly influence the customers behavioural intentions dimension namelyPay More.


of service delivery directly influence the customers behavioural intentions dimension namelyPay More.


directly influence the customers behavioural intentions dimension namely External &

Internal Responses.



External & Internal Responses.





delivery directly influence the customers behavioural intentions dimension namelyExternal

& Internal Responses.


of service delivery directly influence the customers behavioural intentions dimension namely



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Hypotheses Path Path

Estimate

()

S.E. -

value

Hypotheses

support

status

H1 Core(C) Loyalty(L) .314 .146 .086 NotSupported

H2 Human(H) Loyalty (L) 1.263 .875 .043 Supported

H3 System(S) Loyalty(L) .634 .555 .035 Supported

H4 Tangible(T)Loyalty(L) -.245 .258 .183 Not

Supported

H5 Social(So) Loyalty(L) .432 .571 .501 Not

Supported

H6 Core(C) Switchingpropensity(SP)

.146 .035 .533 Not

Supported

H7 Human(H) Switchingpropensity(SP)

.577 .214 .472 NotSupported

H8 System(S) Switching

propensity(SP)

-.413 .130 .267 Not

Supported

H9 Tangible(T)Switching

propensity(SP)

-.389 .075 .168 Not

Supported

H10 Social(So) Switching

propensity(SP)

.432 .157 .432 Not

Supported

H11 Core(C) Pay more(P) -1.392 .487 .043 SupportedH12 Human(H) Pay more(P) 5.352 2.971 .025 Supported

H13 System(S) Pay more(P) .781 1.681 .448 NotSupported

H14 Tangible(T)Pay more(P) .965 .890 .179 Not

Supported

H15 Social(So) Pay More (P) -5.224 2.190 .001 Supported

H16 Core(C) External & Internal

response(EI)

.983 .365 .182 Not

Supported

H17 Human(H)External & Internal

response(EI)

-4.368 2.281 .094 Not

Supported

H18 System(S)External &Internal

response(EI)

1.619 1.123 .098 Not

Supported

H19 Tangiable(T)External &Internal

response(EI)

-.038 .444 .941 Not

Supported

H20 Social(So) External &Internal

response(EI)

2.882 1.394 .040 Supported


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According to the results (Table), Core (C) is not significantly related to Loyalty, thus H1 is

not supported. The results show that Human (H) is positively and significantly related to

Loyalty (L) ( =+1.263; = 0.043), hence H2 is supported. Similarly, the results show that

System (S) is positively and significantly related to Loyalty (L) ( =+.634; = 0.035) and

thus H3 is supported. It is observed that Tangible is not significantly related to loyalty; Social

(SO) is not significantly related to Loyalty (L),Core(C) is not significantly related to

Switching propensity(SP),Human(H) is not significantly related to Switching

Propensity(SP),System(S) is not significantly related to Switching Propensity(SP),Tangible

(T) is not significantly related to Switching Propensity(SP),Social(SO) is not significantly

related to Switching Propensity(SP) and Hence ,H4,H5,H6,H7,H8,H9,H10 is not supported.

Further results show that Core (c) is negatively and significantly related to Pay more (P) ( =

-1.392; = 0.043), hence H11 is not supported. The results also show that Human (H) is

positively and significantly related to Pay more (P) ( =+5.352; = 0.035) and thus H12 is

supported. System (S) is not significantly related to Pay More (P), Tangible (T) is not

significantly related to pay more (P) and their H13 & H14 is not supported. The results show

that Social (SO) is negatively and significantly related to Pay more (p) ( =-5.224; = 0.001),

hence H15 is supported. It is observed that Core(C) is not significantly related to External and

Internal Response (EI), Human (H) is not significantly related to External and Internal

Response (EI), System(S) is not significantly related to External and Internal Response(EI),

Tangible(T) is not significantly related to External and Internal Response(EI),H16,H17,H18

and H19 is not supported. Finally, Social (SO) is positively and significantly related to

External and Internal Response (EI) ( =+2.882; = .04), hence H20 is supported. To

Conclude from the above hypotheses table value examinations ,specific dimensions of

Service quality (SQ) namely Human Element of Service delivery got positive significant

relationship with Loyalty dimension of Behavioural intentions construct with p-value


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of .043.The systematization of service delivery of SQ dimensions have positive significant

relationship with loyalty dimension of BI dimensions with p-value .035.Similarly,the core

service or service product dimension of SQ dimensions got positive significant relationship

with Pay More dimension of BI Dimensions with p-value of .043.And the Human element of

service

delivery got

positive

significant

relationship

with Pay

more dimension of BI Dimensions. The most positive significant relationship found between

social responsibility of SQ Dimensions and Pay more dimension of BI Dimensions with p-

value of .001.Finally,the social responsibility dimension of SQ dimensions got positive

significant relationship with External & Internal response dimension of BI Dimensions.

Service Scale Un- Standardized S.E C.R. p-


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Table XVII.

ShowingStandardize

d

Loadings ,S.

E, C.R and

P-Value of

Service

Quality

Construct.

quality

Dimensions

Items standardized

Regression

Weights

Regression

loading

Weights()

Value

Core(C) C1 1.000 .857

C2 .586 .656 .034 17.442 ***

C3 .480 .522 .036 13.259 ***C4 .276 .297 .038 7.173 ***

C5 .346 .319 .045 7.744 ***

Human(H) H6 1.000 .488

H7 1.171 .574 .109 10.751 ***

H8 .817 .461 .087 9.359 ***

H9 .669 .381 .082 8.158 ***

H10 .876 .472 .092 9.513 ***

H11 .660 .368 .083 7.946 ***

H12 .910 .504 .092 9.938 ***

H13 .740 .399 .088 8.450 ***

H14 .848 .471 .089 9.503 ***

H15 .873 .484 .090 9.671 ***

H16 .744 .410 .086 8.625 ***

H17 .975 .512 .097 10.030 ***

H18 .725 .406 .085 8.554 ***

H19 .588 .328 .081 7.254 ***

H20 1.466 .728 .120 12.169 ***

H21 .709 .504 .071 9.927 ***

H22 .484 .292 .073 6.605 ***

System(S) S23 1.000 .412

S24 1.368 .573 .143 9.574 ***S25 1.236 .499 .138 8.964 ***

S26 1.303 .526 .142 9.199 ***

S27 1.205 .490 .136 8.885 ***

S28 1.117 .473 .128 8.722 ***

Tangible(T) T29 1.000 .518

T30 .789 .435 .079 9.938 ***

T31 .966 .514 .086 11.190 ***

T32 .770 .452 .075 10.226 ***

T33 .690 .402 .074 9.343 ***

T34 .941 .508 .085 11.102 ***

Social(SO) SO35 1.000 .506SO36 1.089 .538 .103 10.615 ***

SO37 .967 .452 .103 9.430 ***

SO38 .936 .464 .097 9.609 ***

SO39 .710 .392 .084 8.481 ***

SO40 1.110 .568 .101 10.979 ***

SO41 .881 .514 .085 10.308 ***


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From the above table, it is inferred by looking at the standardized regression loading weights

Note: Three asterisks (***) indicate that the p-value is smaller than .01.Which denotes the

significance level.

It is inferred that the un-standardized weights are highly sensitive to model constraints,

whereas the standardized regression weights ()provide more intuitive information about the

strength of loadings of the indicator(Measured variable) on the factor(Latent Variable).A lowstandardized loadings of indicator on a specific factor suggesting that it is an unreliable

indicator . The p-value less than .05 denote that the indicator is having positive significant

relationship.

For Example, Core, C1 = 1C+e1--------------1

C2 = 2C+e2-------------2

C3= 3C+e3------------3

C4= 4C+e4------------4

C4=5C+e5------------5.

The above equations 1, 2, 3, 4, and 5 are the measurement equations for calculating the factor

equations.e1,e2, e3, e4 and e5 are the measurement errors of the model. Equation 1 describes

that, on an average if the unobserved core service delivery changes by one standard

deviation ,there will be .857 standard deviation increase in the C1 and the similar formula is

used for equation 2,3,4 and 5.The critical ratio reveals that the calculated significance of the

standardised regression weight are valid at one percent level.

Correlation Table, Showing the estimated correlation between Service qualityDimensions

Estimate

Core Human .883

Core Tangible .809

System Tangible 1.143


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For Example, Loyalty, L1 = 1L+e1--------------1

L2 = 2L+e2-------------2

L3= 3L+e3--------------3

L4= 4L+e4---------------4

L4=5L+e5---------------5.

Intention

Dimensions

Items Standar

dized

regressi

on

loading

Weights

d regression

Loading

Weights ()

Loyalty(L) L1 1.000 .797

L2 .587 .588 .040 14.679 ***

L3 .415 .370 .046 8.936 ***

L4 .411 .336 .051 8.065 ***

L5 .428 .353 .050 8.490 ***

Switching

Propensity(SP)

SP6 1.000.149

SP7 4.578 .711 1.671 2.740 .006

Pay More(P) P8 1.000 .718

P9 .712 .513 .064 11.140 ***EI10 1.000 .488

External

&Internal

Response(EI)

EI11 .734

.364

.094 7.825 ***

EI12 1.081 .547 .104 10.372 ***

EI13 .603 .360 .078 7.749 ***


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The above equations 1, 2, 3, 4, and 5 are the measurement equations for calculating the factor

equations.e1,e2, e3, e4 and e5 are the measurement errors of the model. Equation 1 describes

that, on an average if the unobserved Loyalty changes by one standard deviation ,there will

be .857 standard deviation increase in the L1 and the similar formula is used for equation

2,3,4 and 5.The critical ratio reveals that the calculated significance of the standardisedregression weight are valid at one percent level.

Hypothesis Examination

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