The determinants of green consumption: a study of socio-demographics factors as determinants

3.3.3.4 H1d: employment status is positively linked to the

consumption of green product

For this hypothesis the null hypothesis is:

H0 = the employment status is not explaining the consumption of green products H1 = the employment status has an effect on the consumption of green product

Table 3.17 H1d Model Summary

Récapitulatif des modèles

Modèle	R	R-deux	R-deux ajusté	Erreur standard de l'estimation
1 dimensi on^0	,228^a	,052	,046	1,07279

a. Valeurs prédites : (constantes), 2

For this hypothesis, we could observe that the correlation between the variables, the employment status and the consumption of green products is 0.228, so it is a weak correlation. Moreover, R-square is equal to 0.052 this means that only 5.2% of the variance of green consumption could be explained by the employment status; therefore it seems that the consumption of green products is not dependent of the employment status.

Table 3.18 H1d ANOVA Table

ANOVA^b

Modèle	Somme des carrés	ddl	Moyenne des carrés	D	Sig.
1 Régression Résidu Total	9,345 170,329 179,673	1 148 149	9,345 1,151	8,120	,007^a

a. Valeurs prédites : (constantes), 2

b. Variable dépendante : green_consump

The part of variance none explain by the independent variable is much more important, 170.329, than the part explain by the independent variable, 9.345. So it seems that the employment status don't have an effect upon the green consumption.

In this case, the D (F) value is 8.120 and is significant at p <0.0005. In other words, at the p = 0.05 level of significance, there exists enough evidence to conclude that the slope of the population regression line is close to zero and, hence, that the employment status isn't useful as a predictor of green consumption. In this case, we keep the null hypothesis formulated above. So there isn't a statistically significant relationship between the green consumption and the employment status.

Table 3.19 H1d Coefficients Table

Coefficients^a

Modèle			Coefficients
	Coefficients non standardisés		standardisés
	A	Erreur standard	Bêta	T	Sig.
1 (Constante)	3,026	,174		17,436	,000
2	,244	,086	,228	2,850	,007

a. Variable dépendante : green_consump

For this hypothesis, the regression equation could be drawn as followed: Green consumption = 3.026+0.244*employment status

For the p-value, in this case p = .007 therefore we get .007 > 0.05, as a consequence we keep H0 and we have to say that the employment status can't explain the consumption of green products.

3.3.3.5 H1e: the legal status is positively linked to green purchasing

behavior

For this hypothesis the null hypothesis is:

H0 = the legal status is not explaining the consumption of green products H1 = the legal status has an effect on the consumption of green product

Table 3.20 H1e Model Summary

Récapitulatif des modèles

Modèle	R	R-deux	R-deux ajusté	Erreur standard de l'estimation
1 dimensi on0	,170^a	,029	,022	1,08584

a. Valeurs prédites : (constantes), 2

For this hypothesis, we could observe that the correlation between the variables, the legal status and the consumption of green products is 0.170. Moreover, R-square is equal to 0.029 this means that only 2.9% of the variance of green consumption could be explained by the legal status; therefore it seems that the consumption of green products is not dependent of the legal status.

Table 3.21 H1e ANOVA Table

ANOVA^b

Modèle	Somme des carrés	ddl	Moyenne des carrés	D	Sig.
1 Régression Résidu Total	5,176 174,498 179,673	1 148 149	5,176 1,179	4,390	,038^a

a. Valeurs prédites : (constantes), 2

b. Variable dépendante : green_consump

The part of variance none explain by the independent variable is much more important, 174.498, than the part explain by the independent variable, 5.176. So it seems that the legal status doesn't have an effect upon the green consumption.

In this case, the D (F) value is 4.390 and is significant at p < 0.0005. In other words, at the p = 0.05 level of significance, there exists enough evidence to conclude that the slope of the population regression line is close to zero and, hence, that the legal status isn't useful as a predictor of green consumption. In this case, we keep the null hypothesis formulated above. So there isn't a statistically significant relationship between the green consumption and the legal status.

Table 3.22 H1e Coefficients Table

Coefficients^a

Modèle			Coefficients
	Coefficients non standardisés		standardisés
	A	Erreur standard	Bêta	T	Sig.
1 (Constante)	3,056	,209		14,587	,000
2	,159	,076	,170	2,095	,038

a. Variable dépendante : green_consump

For this hypothesis, the regression equation could be drawn as followed: Green consumption = 3.056+0.159*legal status

For the p-value, in this case p = .038 therefore we get .038 > 0.05, as a consequence we keep H0 and we have to say that the legal status can't explain the consumption of green products.