Effects of service quality and customer satisfaction on loyalty of bank customers

Figures & data

Figure 1. Theoretical model of the effect of service quality on customer satisfaction and customer loyalty

Table 1. Research instrument grid

Variable	Indicator	Item	Symbol
Service quality	1.Tangibility	a. Completeness of property	SQ11 SQ12
		b. The grandeur of the building	SQ13 SQ14
		c. Employee appearance	SQ15
	2. Reliability	a. Service accuracy	SQ21 SQ22
		b. Consistency of service	SQ23
		The accuracy of service information	SQ24
	3. Responsiveness	Response speed in responding	SQ31
		b. Ethics in service	SQ32
		c. Simplicity/ease of service	SQ33
	4. Assurance	Giving customer trust	SQ41
		Ability to provide warranty	SQ42
		c. Providing security to customers	SQ43
	5. Empathy	a. Concern	SQ51
		b. Individual attention to customers.	SQ52
Customer satisfaction	1. Customer attitude	a. customer attitude towards the product	CS11
		b. customer attitudes towards the organization’s brand	CS12
		c. Attitudes of customers to organizational service	CS13
	2. Customer happiness	a. security services	CS21
		b. Reassuring service	CS22
		c. Pleasant service	CS23
	3. Customer Satisfaction	a. Service stability	CS31
		b. Harmonious relationship	CS32
		c. Trust in each other	CS33
		d. Communication in service	CS34
Customer loyalty	1. Cognitive Loyalty	a. Rational to the organization	CL11
		b. Rating is better than others	CL12
		c. The frequency increases	CL13
		d. Long time	CL14
	2. Affective Loyalty	a. Pride in being a customer	CL21
		b. Commitment to the organization	CL22
		Feeling of belonging to an organization	CL23
	3.Conative Loyalty	a. Keep abreast of organizational developments	CL31
		b. Willing a lot for the organization	CL32
		c. Wish you success in joining the organization	CL33
	4.Action Loyalty	a. Increased frequency of participating in organizational activities	CL41
		b. Has a long time for organization	CL42
		Demonstrate self-success to the organization.	CL43

Table 2. Criteria for data interpretation

Index	Criteria	Conclusion
CFI (McDonald & Marsh, 1990)	0–1	Poor to Good fit
TLI (Bentler & Bonett, 1980)	0–1	Poor to Good fit
PCFI (James et al., 1982)	>0.06	Good fit
RMSEA (Browne & Cudeck, 1993)	≤0.05	Close fit
	0.05 ≥ RMSEA ≤ 0.08	Good fit

Figure 2. Final model the influence of service quality and customer satisfaction on customer loyalty with measurement error

Table 3. Measurement of the final model direct, indirect, and total effect

Standardized Direct Effects
	QServ	CSatisfy	CLoyal
CSatisfy	,957	,000	,000
CLoyal	-,257	1,140	,000
Standardized Indirect Effects
	QServ	CSatisfy	CLoyal
CSatisfy	,000	,000	,000
CLoyal	1,091	,000	,000
Standardized Total Effects
	QServ	CSatisfy	CLoyal
CSatisfy	,957	,000	,000
CLoyal	,834	1,140	,000

Source: Research data, processed.

Information

QServ: Quality service

CSatisfy: Customer satisfaction

CLoyal: Customer loyalty

Table 4. Fit model summary

CMIN
Model	NPAR	CMIN		DF			P		CMIN/DF
Default model	123	5983.656		737			.000		8.119
Saturated model	860	.000		0
Independence model	40	56,300.159		820			.000		68.659
Baseline Comparisons
Model	NFI Delta1	RFI rho1		IFI Delta2			TLI rho2		CFI
Default model	.894	.882		.906			.895		.905
Saturated model	1.000			1.000					1.000
Independence model	.000	.000		.000			.000		.000
Parsimony-Adjusted Measures
Model	PRATIO					PNFI			PCFI
Default model	.899					.803			.814
Saturated model	.000					.000			.000
Independence model	1.000					.000			.000
RMSEA
Model	RMSEA		LO 90		HI 90			PCLOSE
Default model	.075		.073		.077			.000
Independence model	.231		.229		.233			.000

Table

			Estimate	S.E.	C.R.	P	Label
CSatisfy	<—-	QServ	5.426	.454	11.952	***	par_40
CLoyal	<—-	QServ	−1.471	.409	−3.599	***	par_38
CLoyal	<—-	CSatisfy	1.149	.075	15.263	***	par_39
SQ11	<—-	QServ	1.000
SQ12	<—-	QServ	5.217	.445	11.733	***	par_1
SQ13	<—-	QServ	5.185	.439	11.803	***	par_2
SQ14	<—-	QServ	5.274	.447	11.798	***	par_3
SQ15	<—-	QServ	5.422	.454	11.933	***	par_4
SQ21	<—-	QServ	5.765	.480	11.998	***	par_5
SQ22	<—-	QServ	5.897	.488	12.088	***	par_6
SQ23	<—-	QServ	5.982	.494	12.107	***	par_7
SQ24	<—-	QServ	5.870	.485	12.112	***	par_8
SQ31	<—-	QServ	5.949	.497	11.966	***	par_9
SQ32	<—-	QServ	6.032	.500	12.064	***	par_10
SQ33	<—-	QServ	5.979	.495	12.081	***	par_11
SQ41	<—-	QServ	6.033	.498	12.114	***	par_12
SQ42	<—-	QServ	5.963	.491	12.137	***	par_13
SQ43	<—-	QServ	6.043	.499	12.098	***	par_14
SQ51	<—-	QServ	5.852	.487	12.011	***	par_15
SQ52	<—-	QServ	2.750	.268	10.247	***	par_16
CS11	<—-	CSatisfy	1.000
CS12	<—-	CSatisfy	1.014	.026	38.884	***	par_17
CS13	<—-	CSatisfy	1.049	.026	39.778	***	par_18
CS21	<—-	CSatisfy	1.065	.024	43.606	***	par_19
CS22	<—-	CSatisfy	1.031	.025	40.766	***	par_20
CS23	<—-	CSatisfy	1.048	.024	43.822	***	par_21
CS31	<—-	CSatisfy	1.054	.024	43.529	***	par_22
CS32	<—-	CSatisfy	1.029	.026	40.084	***	par_23
CS33	<—-	CSatisfy	1.047	.027	38.823	***	par_24
CS34	<—-	CSatisfy	1.054	.026	39.966	***	par_25
CL11	<—-	CLoyal	1.000
CL12	<—-	CLoyal	1.050	.029	36.376	***	par_26
CL13	<—-	CLoyal	1.046	.029	35.547	***	par_27
CL14	<—-	CLoyal	1.042	.026	39.833	***	par_28
CL21	<—-	CLoyal	1.058	.028	37.433	***	par_29
CL22	<—-	CLoyal	1.099	.027	40.914	***	par_30
CL23	<—-	CLoyal	1.106	.029	37.608	***	par_31
CL31	<—-	CLoyal	1.070	.030	35.146	***	par_32
CL32	<—-	CLoyal	1.041	.029	35.565	***	par_33
CL33	<—-	CLoyal	1.056	.031	33.952	***	par_34
CL41	<—-	CLoyal	1.042	.041	25.172	***	par_35
CL42	<—-	CLoyal	1.067	.039	27.620	***	par_36
CL43	<—-	CLoyal	1.054	.040	26.431	***	par_37

Table

			Estimate
CSatisfy	<—-	QServ	.957
CLoyal	<—-	QServ	−.257
CLoyal	<—-	CSatisfy	1.140
SQ11	<—-	QServ	.339
SQ12	<—-	QServ	.752
SQ13	<—-	QServ	.774
SQ14	<—-	QServ	.773
SQ15	<—-	QServ	.820
SQ21	<—-	QServ	.846
SQ22	<—-	QServ	.885
SQ23	<—-	QServ	.894
SQ24	<—-	QServ	.896
SQ31	<—-	QServ	.833
SQ32	<—-	QServ	.874
SQ33	<—-	QServ	.882
SQ41	<—-	QServ	.897
SQ42	<—-	QServ	.908
SQ43	<—-	QServ	.890
SQ51	<—-	QServ	.851
SQ52	<—-	QServ	.476
CS11	<—-	CSatisfy	.856
CS12	<—-	CSatisfy	.844
CS13	<—-	CSatisfy	.855
CS21	<—-	CSatisfy	.896
CS22	<—-	CSatisfy	.866
CS23	<—-	CSatisfy	.898
CS31	<—-	CSatisfy	.895
CS32	<—-	CSatisfy	.858
CS33	<—-	CSatisfy	.844
CS34	<—-	CSatisfy	.857
CL11	<—-	CLoyal	.821
CL12	<—-	CLoyal	.849
CL13	<—-	CLoyal	.837
CL14	<—-	CLoyal	.897
CL21	<—-	CLoyal	.864
CL22	<—-	CLoyal	.911
CL23	<—-	CLoyal	.867
CL31	<—-	CLoyal	.831
CL32	<—-	CLoyal	.837
CL33	<—-	CLoyal	.812
CL41	<—-	CLoyal	.654
CL42	<—-	CLoyal	.702
CL43	<—-	CLoyal	.679

Table

	Correlation
		Total
SQ11	Pearson Correlation	.327**
SQ12	Pearson Correlation	.746**
SQ13	Pearson Correlation	.768**
SQ14	Pearson Correlation	.770**
SQ15	Pearson Correlation	.784**
SQ21	Pearson Correlation	.820**
SQ22	Pearson Correlation	.852**
SQ23	Pearson Correlation	.863**
SQ24	Pearson Correlation	.866**
SQ31	Pearson Correlation	.814**
SQ32	Pearson Correlation	.825**
SQ33	Pearson Correlation	.837**
SQ41	Pearson Correlation	.864**
SQ42	Pearson Correlation	.877**
SQ43	Pearson Correlation	.852**
SQ51	Pearson Correlation	.820**
SQ52	Pearson Correlation	.502**
CS11	Pearson Correlation	.845**
CS12	Pearson Correlation	.846**
CS13	Pearson Correlation	.831**
CS21	Pearson Correlation	.867**
CS22	Pearson Correlation	.845**
CS23	Pearson Correlation	.867**
CS31	Pearson Correlation	.872**
CS32	Pearson Correlation	.855**
CS33	Pearson Correlation	.829**
CS34	Pearson Correlation	.851**
CL11	Pearson Correlation	.834**
CL12	Pearson Correlation	.811**
CL13	Pearson Correlation	.802**
CL14	Pearson Correlation	.875**
CL21	Pearson Correlation	.842**
CL22	Pearson Correlation	.856**
CL23	Pearson Correlation	.800**
CL31	Pearson Correlation	.779**
CL32	Pearson Correlation	.809**
CL33	Pearson Correlation	.777**
CL41	Pearson Correlation	.593**
CL42	Pearson Correlation	.645**
CL43	Pearson Correlation	.622**
Total	Pearson Correlation	1

Table

Reliability statistics
Cronbach’s Alpha	Cronbach’s Alpha Based on Standardized Items	N of Items
.985	.985	40

Table

Tests of normality
	Kolmogorov-Smirnov^a			Shapiro-Wilk
	Statistic	df	Sig.	Statistic	df	Sig.
QServe	.129	1190	.000	.864	1190	.000
Satisf	.196	1190	.000	.842	1190	.000
CLoyalty	.129	1190	.000	.893	1190	.000
a. Lilliefors Significance Correction

McDonald, R., & Marsh, H. W. (1990). Choosing a multivariate model: Noncentrality and goodness of fit. Psychological Bulletin, 107(2), 247–255. https://doi.org/https://doi.org/10.1037/0033-2909.107.2.247

 Google Scholar

Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–17. https://doi.org/https://doi.org/10.1037/0033-2909.88.3.588

 Google Scholar

James, L. R., Mulaik, S. A., & Brett, J. M. (1982). Causal analysis: Assumptions, models, dan data. SAGE Publications. https://www.scholars.northwestern.edu/en/publications/causal-analysis-assumptions-models-and-data

 Google Scholar

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Bollen KA, Long JS, eds. Testing structural equation models. Sociological Methods & Research, SAGE Publications Inc. 136–162. https://doi.org/https://doi.org/10.1177/0049124192021002005

 Google Scholar