Table 4. Discriminant validity...

Table 4.

Discriminant validity assessment using Fornell–Larcker criterion

Variables	AI adoption	Collaborative partnership	Cultural context	Employee empowerment	Motivation to protection	Regulatory framework	Sustainability development
AI adoption	0.839
Collaborative partnership	0.476	0.790
Cultural context	−0.163	−0.251	0.858
Employee empowerment	0.362	0.521	−0.410	0.848
Motivation to protection	0.125	0.248	−0.567	0.333	0.900
Regulatory framework	0.108	0.017	−0.156	−0.012	0.003	0.842
Sustainability development	0.370	0.502	−0.167	0.612	0.442	−0.185	0.927

Variables	AI adoption	Collaborative partnership	Cultural context	Employee empowerment	Motivation to protection	Regulatory framework	Sustainability development
AI adoption	0.839
Collaborative partnership	0.476	0.790
Cultural context	−0.163	−0.251	0.858
Employee empowerment	0.362	0.521	−0.410	0.848
Motivation to protection	0.125	0.248	−0.567	0.333	0.900
Regulatory framework	0.108	0.017	−0.156	−0.012	0.003	0.842
Sustainability development	0.370	0.502	−0.167	0.612	0.442	−0.185	0.927

Note(s):

The diagonal values (in italics) represent the square root of the AVE (Average Variance Extracted) for each construct. These values must be higher than the corresponding interconstruct correlations shown in the off-diagonal cells. This test follows Fornell and Larcker’s (1981) criterion for establishing discriminant validity

Source(s): Authors’ own creation

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