Are there barriers to the intention of fish consumption in restaurants? Insights from Türkiye using an extension of the Theory of Planned Behaviour

Items	Extraction	Factor Loading	Item-total correlations	Total Variance
PB1	0.566	0.752	0.673	59.631
PB2	0.623	0.791	0.720
PB3	0.521	0.722	0.639
PB4	0.610	0.782	0.703
PB5	0.560	0.748	0.661
PB6	0.709	0.842	0.775
PB7	0.660	0.813	0.738
PB8	0.518	0.720	0.628

Table 2:

Correlation coefficients between variables

		Bivariate correlation					Descriptive statistics
		1	2	3	4	5	N	M	SD
1	Perceived barriers	-					529	2.58	.86
2	Attitude	-.21**	-				529	4.3	.57
3	Subjective norms	-.29**	.23**	-			529	3.79	.94
4	Perceived behavioural control	-.31**	.22**	.53**	-		529	3.09	.89
5	Intention of fish consumption	-.32**	.25**	.56**	.49**	-	529	2.96	1.01

1 *p < .05;

1** p < .01

The total effect of perceived barriers on intention of fish consumption

Table 3:

Regression coefficients and summary information for the model with mediating variables

Antecedent	Consequent
	M1 (ATD)				M2 (SN)				M3 (PBC)				Y (IFC)
		β	SE	p		β	SE	p		β	SE	p		β	SE	P
X (PB)	a₁	-.14	.03	< .01	a₂	-.31	.05	< .01	a₃	-.32	.04	< .01	c’	-.16	.05	< .01
M₁ (ATD)													b₁	.17	.07	< .01
M₂ (SN)													b₂	.25	.05	< .01
M₃ (PBC)													b₃	.35	.05	< .01
Constant	iM₁	4.63	.07	< .01	iM₂	4.56	.12	< .01	iM₃	3.86	.11	< .01	i_y	.58	.24	< .01
R²		.04				.09				.10				.33
F (df)	22.51*** (1;482)				46.29*** (1;482)				52.52*** (1;482)				58.09*** (4;479)
Indirect effect	K² = -.18 β= -.22 SE= .04 95% CI [-.29, -.15]

1 IFC = Intention of Fish Consumption; ATD = Attitude; SN = Subjective Norms; PBC = Perceived Behavioural Control, PB = Perceived Barriers a, b, c, and c’ represent unstandardized regression coefficients

1 SE = standard error

1 Bootstrap sample size = 5000

1*** p < .001