Exploring the customer e-loyalty of millennials when purchasing footwear online in South Africa

Figures & data

Figure 1. Proposed theoretical model. Source: Researchers’ own construct.

Table 1. Constructs and items.

Key constructs	Item count	Source
Efficiency	5	Türk et al. (2012)
Fulfilment	5	Türk et al. (2012)
Reliability	4	Ting et al. (2016)
Website design	5	Noorshella et al. (2015)
E-service experience	5	Chou et al. (2015)
E-security	5	Chou et al. (2015)
E-privacy	5	Chou et al. (2015)
E-trust	5	Chou et al. (2015)
E-satisfaction	5	Chou et al. (2015)
Attitudinal loyalty	5	Hong and Cho (2011)
Behavioural loyalty	5	Tankovic and Benazic (2018)

Source: Researchers’ own construct.

Table 2. Cronbach’s alpha scores per construct.

Key construct	Cronbach’s alpha value
Efficiency	0.869
Fulfilment	0.856
Reliability	0.929
Website design	0.900
E-service experience	0.925
E-security	0.927
E-privacy	0.910
E-trust	0.890
E-satisfaction	0.948
E-loyalty	0.900

Source: Researchers’ own construct.

Table 3. Measures for goodness of fit (measurement model).

CMIN	AGFI	CFI	TLI	RMSEA
2664	0.872	0.891	0.878	0.082

Source: Researchers’ own construct.

Table 4. Factor loadings, average variance extracted, mean, standard deviation and composite reliability.

Construct and items		Factor loadings	AVE	M	SD	CR
Efficiency	E1	0.887	0.741	5.81	1.474	0.934
	E2	0.910		5.74	1.450
	E3	0.734		5.74	1.577
	E4	0.855		5.59	1.582
	E5	0.906		5.80	1.469
Fulfilment	F3	0.916	0.826	5.52	1.478	0.935
	F2	0.916		5.73	1.443
	F1	0.895		5.61	1.521
Reliability	R3	0.752	0.659	5.30	1.509	0.852
	R2	0.890		5.30	1.479
	R1	0.787		4.94	1.624
Website design	WD5	0.871	0.800	5.47	1.561	0.942
	WD4	0.855		5.77	1.365
	WD3	0.896		5.75	1.401
	WD2	0.918		5.77	1.416
	WD1	0.833		5.79	1.419
E-service experience	ESE1	0.887	0.719	5.82	1.321	0.927
	ESE2	0.775		5.73	1.485
	ESE3	0.841		5.70	1.524
	ESE4	0.863		5.96	1.274
	ESE5	0.868		5.95	1.249
E-security	ES5	0.818	0.765	4.99	1.520	0.928
	ES3	0.874		5.25	1.504
	ES2	0.919		5.29	1.518
	ES1	0.884		5.31	1.436
E-privacy	EP5	0.790	0.669	4.77	1.649	0.910
	EP4	0.861		4.59	1.686
	EP3	0.889		5.00	1.514
	EP2	0.793		5.08	1.576
	EP1	0.748		4.88	1.696
E-trust	ET3	0.763	0.741	5.15	1.507	0.895
	ET4	0.904		5.43	1.485
	ET5	0.907		5.47	1.478
E-satisfaction	ES1	0.847	0.790	5.81	1.532	0.950
	ES2	0.920		5.99	1.298
	ES3	0.939		5.92	1.436
	ES4	0.870		5.85	1.492
	ES5	0.866		6.02	1.441
E-loyalty	AL1	0.711	0.709	5.49	1.664	0.906
	AL4	0.919		5.63	1.594
	AL5	0.946		5.69	1.594
	AL3	0.769		2.77	2.073

M: mean; SD: standard deviation; CR: composite reliability

Source: Researchers’ own construct.

Table 5. Component correlation matrix (discriminant validity).

EFF	0.861
FUL	0.716	0.909
REL	0.708	0.711	0.812
WD	0.819	0.671	0.683	0.894
ESE	0.790	0.738	0.704	0.881	0.848
ES	0.580	0.745	0.692	0.620	0.704	0.875
EP	0.535	0.588	0.625	0.617	0.648	0.768	0.818
ET	0.650	0.650	0.654	0.716	0.720	0.728	0.753	0.861
ES	0.750	0.750	0.631	0.800	0.797	0.593	0.556	0.713	0.889
EL	0.644	0.644	0.556	0.723	0.672	0.523	0.490	0.659	0.790	0.842

EFF: efficiency; FUL: fulfilment; REL: reliability; WD: website design; ESE: e-service experience; ES: e-security; EP: e-privacy; ET: e-trust; ES: e-satisfaction; EL: e-loyalty

The diagonal elements are the square root (√) of AVE and the off-diagonal variables are the inter-construct correlations.

Source: Researchers’ own construct.

Table 6. Measures for goodness of fit (structural model).

CMIN	AGFI	CFI	TLI	RMSEA
2550	0.872	0.996	0.978	0.082

Source: Researchers own’ construct.

Table 7. Hypothesis testing.

Hypothesis	Variable	Variable	β	Sig	Finding
H1	Efficiency	E	0.095	0.154	Not supported
H2	Fulfilment	F	0.156	0.005	Supported
H3	Reliability	R	0.038	0.541	Not supported
H4	Website design	WD	0.735	<0.001	Supported
H5	E-security	ES	0.349	<0.001	Supported
H6	E-privacy	EP	0.541	<0.001	Supported
H7	E-trust	ET	0.215	<0.001	Supported
H8	E-service experience	ESE	0.736	<0.001	Supported
H9	E-satisfaction	ES	0.836	<0.001	Supported

Source: Researchers’ own construct.

Figure 2. The path coefficients and beta value of the refined model, showing the relationship between factors influencing millennials’ e-satisfaction and e-loyalty towards online footwear purchases. Note:

indicates a significant path; indicates a non-significant path. Source: Researchers’ own construct.

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Data availability statement

The data set is available from the corresponding author on request.

New affiliation of co-author

Since the publication of this manuscript, Professor Mornay Roberts-Lombard have joined the Department of Management & Entrepreneurship at the University of the Western Cape in Bellville, Cape Town, South Africa. He can be contacted at [email protected]