Condition N 268 268 Purchase intention Pearson Correlation

Condition 1: Independent and
Dependent Variables (IV-DV) Correlation

            The correlation
measurements / values as shown in table 4.7 above mentioned that all
consumption motives (included all independent variables and dimensions values)
are significantly correlated with food purchase intention (The dependent
variable) showing the values of correlation coefficient as 0.442; 0.483; 0.528;
0.335; 0.419; 0.513; 0.582; 0.495.

 

Condition
2: Correlation of Mediator with all identified
factors (IV-MV)

In order to identify the mediation role
played by consumer involvement in buying decision towards food products to influence
the purchase intention or buying behavior in food industry to enhance level of
consumer involvement and competitive position in purchase decision of food, a
correlation analysis was performed to find out the association/correlation
between the consumer involvement and the five consumptions motives such as
health consciousness, food safety concern, personal consumer traits with
dimensions (self efficiency, need for
interaction and inherent novelty seeking), situational factors (peer influence
and time pressure) and ecological motives (ethical concern and environmental
protection) for enhancing customer purchase intention in food industry, as
showing the values of correlation coefficient; 0.474; 0.551; 0.665; 0.510;
0.496; 0.598; 0.747; 0.609, mentioned in Table 4.7 results fulfill the second
condition necessary to examine whether the effect of mediation has occurred.

Condition 3: Correlation Analysis
between Dependent Variable and Mediator (MV-DV)

            As
mentioned above the results in Table 4.7 confirmed the completion and
contentment of second mediation condition according to which there is
correlation between mediator and independent variables exist with value 0.596.
Therefore, it stimulated the need to precede further correlation analysis and
check/examines the mediating effect of consumer involvement in buying food
item. The strong correlation analysis between mediator (consumer involvement)
and dependent variable (purchase intention of consumer in food industry) was
performed, as results shown in table 4.8 to confirm or verify the third
condition of Pearson’s correlation analysis.

Table 4.8 Correlation between Mediating Variable
and Dependent Variables (MV-DV)

Correlations

 

Consumer Involvement

Purchase intention

Consumer Involvement

Pearson Correlation

1

.596**

Sig. (2-tailed)

 

.000

N

268

268

Purchase intention

Pearson Correlation

.596**

1

Sig. (2-tailed)

.000

 

N

268

268

**. Correlation is
significant at the 0.01 level (2-tailed).

 

The results of correlation analysis as
shown in Table 4.8 confirmed the fulfillment of third condition of mediating
effect to verify that there is correlation or significance association between
mediator (Consumer involvement in buying food) and dependent variable
(intention to buying food/purchase intention) exist. Therefore, it confirmed
that the initial conditions for mediation analysis are accomplished. Thus, the
analysis further continued to verify the mediating effect of consumer
involvement through regression analysis.

4.5 Regression analysis to Measuring the Mediator Effect

The all hypothesis of this
study have been scrutinized by multiple linear regression analysis for each
variable and the values of measurements shown in given below tables. R value, R
square value, beta value under standardized coefficient, beta under
standardized coefficient and significance (p-value) are some essential
parameters to be focused. The correlation coefficient’s values represent an
association between all variables of this survey for every single path which is
statistically significant. Therefore, this has validate that the regression
analysis test for recognizing and identifying the key function/role of
mediating variable can be preceded all required necessary conditions at their
level of bivariate are met.

According to the
suggestion of Baron and Kenny (1986), the analysis of mediation fulfill in four
necessary steps. The first step is that the forecasting of DV-dependent
variable ought to be significant using the IV-independent variables. The second
step is that the MV-mediating variable ought to be significantly forecasted by
the IV-independent variable and the third step of analysis is that the DV-dependent
variable should be significantly forecasted by the MV-mediating variable. At last
and final fourth step, the dependent variable-DV ought to be forecasted
significantly by both independent variable-IV and mediator-MV collectively. In case
the four step criteria are met, then the direct effect of independent variable
absolutely be minimized or reduced from the individual effect of independent
and mediator variables. In case the analysis results of independent variable-IV
become significant, it shows that partial mediation is occurring and if when the
independent variable’s-IV values become insignificant, it predicts that there
is perfect mediation has occurred. The statistical significance of the
mediation model will be analysed by using a Sobel test (MacKinnon and Dwyer, 1993; Soper,
2011).   Through ‘Sobel test’, this will
be further confirmation and validation where the effect of independent variable
reduction that reached to zero, fulfillment mediation analysis has been
confirmed.

These following
instructions presented by Baron and Kenny (1986), the analysis is proceeding to
identify if consumer involvement in buying food product act as a mediator.
Therefore, the researcher followed the procedure of four step mediation
analysis below. The mediation analysis for each variable and dimension are
presented separately to understand the mediating effect of each variable or
factors.

In the first step, the
influence/impact of five identified components (independent variables) with
dimensions is measured on purchase intention of food products-DV. In the second
step, the influence/impact of five identified components (independent
variables) with dimensions on Mediator as consumer involvement in buying food
items is calculated and the third step, the purchase intention of food item is
influenced by consumer involvement in buying food items is measured. And at the
end, the fourth step, the purchase intention of food is influenced by both five
identified variables-IVs and Mediator-MV collectively has been examined. In
case, if the independent component’s influence on the dependent component-DV is
decreased because of the inclusion of a mediator, it will verify that mediating
effect is happened and vice versa.

The value of regression
measurement for all constructs, which depict and characterize a statistically
significant link between variables. Hence, this has validate that the analysis
for recognizing the consequence of mediating variable between dependent
variable and independent variable. The regression analysis result performed are
shown in Tables 4.10-4.17 and the list of the variables that used in the
analysis are given below in table 4.9