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

3.3.4 H2: living condition has a positive effect on consumers green buying decision

3.3.4.1 H2a: The place of living is positively linked to green buying behavior

For this hypothesis the null hypothesis is:

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

Table 3.23 H2a: Model Summary

Récapitulatif des modèles

Modèle	R	R-deux	R-deux ajusté	Erreur standard de l'estimation
1 dimensi on0	,283^a	,080	,074	1,05686

a. Valeurs prédites : (constantes), 2

For this hypothesis, we could observe that the correlation between the variables, the place of living and the consumption of green products is 0.283. Moreover, R-square is equal to 0.080 this means that only 8% of the variance of green consumption could be explained by the place of living; therefore it seems that the consumption of green products is not dependent of the place of living.

Table 3.24 H2a ANOVA Table

ANOVA^b

Modèle	Somme des carrés	ddl	Moyenne des carrés	D	Sig.
1 Régression Résidu Total	14,364 165,309 179,673	1 148 149	14,364 1,117	12,860	,305^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, 165.309, than the part explain by the independent variable, 14.364. So it seems that the place of living doesn't have an effect upon the green consumption. In this case, the D (F) value is 12.860 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 place of living isn't useful as a predictor of green consumption. Therefore we keep the null hypothesis formulated above. So there isn't a statistically significant relationship between the green consumption and the place of living.

Table 3.25 H2a Coefficients Table

Coefficients^a

Modèle			Coefficients
	Coefficients non standardisés		standardisés
	A	Erreur standard	Bêta	T	Sig.
1 (Constante)	4,087	,197		20,777	,305
2	-,362	,101	-,283	-3,586	,010

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 = .010 therefore we get .010 > 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.

3.3.4.2 H2b: The household size is positively linked to green buying behavior

For this hypothesis the null hypothesis is:

H0 = the household size is not explaining the consumption of green products H1 = the household size permits to explain the consumption of green product

Table 3.26 H2b Model Summary

Récapitulatif des modèles

Modèle		R		R-deux	R-deux ajusté	Erreur standard de l'estimation
dimensio n^0	1		,090^a	,008	,001	1,09738

a. Valeurs prédites : (constantes), 2

For this hypothesis, we could observe that the correlation between the variables, the household size and the consumption of green products is 0.090. Moreover, R-square is equal to 0.008 this means that only 0.8% of the variance of green consumption could be explained by the household size; therefore it seems that the consumption of green products is not dependent at all of the household size.

Table 3.27 H2b ANOVA Table

ANOVA^b

Modèle	Somme des carrés	ddl	Moyenne des carrés	D	Sig.
1 Régression Résidu Total	1,447 178,226 179,673	1 148 149	1,447 1,204	1,201	,275^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, 178.226, than the part explain by the independent variable, 1.447. So it seems that the household size doesn't have an effect upon the green consumption. In this case, the D (F) value is 1.201 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 household size isn't useful as a predictor of green consumption. Therefore we keep the null hypothesis formulated above. So there isn't a statistically significant relationship between the green consumption and the household size.

Table 3.28 H2b Coefficients Table

Coefficients^a

Modèle			Coefficients
	Coefficients non standardisés		standardisés
	A	Erreur standard	Bêta	t	Sig.
1 (Constante)	3,728	,266		14,020	,000
2	-,187	,171	-,090	-1,096	,275

a. Variable dépendante : green_consump

For this hypothesis, the regression equation could be drawn as followed: Green consumption = 3.728-0.187*household size

For the p-value, in this case p = .275 therefore we get .275 > 0.05, as a consequence we keep H0 and we have to say that the household size can't explain the consumption of green products.