Table AI. Discriminant validity of...

Table AI.

Discriminant validity of construct pairs

	Involvement	CE affect	CE cognition	CE behaviour	Ne affect	NE cognition	NE behaviour	WOM
Involvement	0.928
CE affect	0.642	0.939
CE cognition	0.502	0.598	0.916
CE behaviour	0.631	0.666	0.787	0.814
NE affect	−0.194	−0.229	−0.030	0.016	0.914
NE cognition	−0.083	−0.044	0.210	0.088	0.530	0.816
NE behaviour	0.005	0.026	0.167	0.222	0.672	0.590	0.784
CD	−0.511	−0.522	−0.448	−0.381	0.567	0.353	0.469
WOM	0.521	0.499	0.580	0.644	0.177	0.284	0.338	0.916

	Involvement	CE affect	CE cognition	CE behaviour	Ne affect	NE cognition	NE behaviour	WOM
Involvement	0.928
CE affect	0.642	0.939
CE cognition	0.502	0.598	0.916
CE behaviour	0.631	0.666	0.787	0.814
NE affect	−0.194	−0.229	−0.030	0.016	0.914
NE cognition	−0.083	−0.044	0.210	0.088	0.530	0.816
NE behaviour	0.005	0.026	0.167	0.222	0.672	0.590	0.784
CD	−0.511	−0.522	−0.448	−0.381	0.567	0.353	0.469
WOM	0.521	0.499	0.580	0.644	0.177	0.284	0.338	0.916

Notes:

The calculated values of the squared structural path coefficients between all possible pairs of constructs are presented in the upper triangle of the matrix. The average variance extracted is shown on the diagonal (shaded). Discriminant validity was established for all construct pairs since the average variance extracted was greater than the squared structural path coefficient. AVE figures are rounded up to the nearest tenth.

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