Data analysis

 

Collected data was analysed conducting a confirmatory factor analysis (CFA) and structural equation modeling (SEM) in AMOS 21 statistical software. The validity and reliability of the adapted measurements were analyzed through CFA. The research model was evaluated testing the direction and significance of the proposed paths via SEM.

 

Results

 

Convergent and discriminant validity of the measured constructs

Validity was tested using confirmatory factor analysis (CFA) based on structural equation modeling (SEM). For the six constructs in the scale Cronbach’s α ranged from 0.50 to 0.–. The lowest value had Culture and traditions subscale. The next lowest one was for Consumer’s willingness to purchase (0.–). The internal consistency coefficients were exceeding the recommended value of 0.70 for five of six scales. For evaluating convergent validity, average variance extracted (AVE) was calculated, along with the evaluation of standardized factor loadings. For costruct Culture and traditions the AVE estimate was lower than the recommended value of 0.50 for the Culture and traditions construct (0.–). For the remaining five construct AVE was within the range of acceptability, ranging from 0.– to 0.–. Standardized factor loadings were above the treshold value of 0.–, except the loading of CT2 on the Culture and traditions construct (0.–). For evaluation of the convergent validity of each construct, the composite reliability (CR) was used as measure. CR values were ranging between 0.– and 0.–, except for Culture and traditions(0.–) which was below the treshold of 0.60. These results revealed that the instrument had a good convergent validity for all construct except for Culture and traditions.

 

Testing the measurement model

The overall measurement model was improved and within the recommended values after excluding the fifth item (RD5) of the Rural development scale, which showed to have several problematic modification indicies (M.I.)and excessive standardized residual covariances. The ratio χ2/df (1.–) was much lower than the recommended treshold value of 5.0. The root mean square error of approximation (RMSEA) coefficient (0.–) was lower than the treshold of 0.08, while the standardized root mean residual (–) value (0.–) was less than 0.–, as recommended. Adjusted goodness of fit index (–, 0.–) was higher than the treshold of 0.80. The recommendations (above 0.90)for indicies such as NFI, TLI and CFI were met as well. All the recommended model fit values were met, so the measurement model fit was evaluated as adequate.

 

Structural equation analysis and hypotheses testing

The overall fit of the hypothesized structural model was adequate. The ratio χ2/df (1.948) was lower than the treshold value of 5.0. RMSEA (0.063), SRMR (0.042), and fit indicies such as NFI (0.931) and CFI (0.965) were within the recommended values.

To assess the effects of four indicators culture and traditions, health benefits, perceived quality and safety, and rural development on trust in ……. / ……. logo, as well as their effects and the effect of trust on consumers’ willingness to purchase cheese with ……. / ……. logo, the measurement items to measure all six dimensions were adapted from several studies (Caputo et al, 2011; Teuber, 2011; Mazodier, 2015; Lai, & Cheng, 2016). The questionnaire is shown in Table I.

 

Table I. Items for the presumed dimensions of — and -, —, —-, perceived – and -, -, and consumers’ willingness to purchase

Construct Item Statement
CT1
CT2
CT3
HB1
HB2
HB3
HB4
RD1
RD2
RD3
RD4  
PQS1  
PQS2  
PQS3  
PQS4  
T1  
T2  
T3  
Consumers’ willingness to purchase CWP1  
CWP2  

For the hypotheses testing, the path analysis was applied via SEM.

H1 predicts that (a) culture and traditions, (b) health benefits, (c) perceived quality and safety, and (4) rural development indicators of GI have a positive effect on trust in ……. / ……. logo. This hypothesis is partially supported by the results. Perceived – and – (b = 0.-, p < 0.001) and culture and traditions (b = 0.-, p = 0.-) positively affect trust in ……. / ……. logo. However, health benefits (b = 0.-, p = 0.-), and rural development (b = 0.-, p = 0.582) do not affect -. 65.4% of the variance of – is explained by the predictors.

H2 predicts that (a) culture and traditions, (b) health benefits, (c) perceived quality and safety, and (d) rural development indicators of GI have a positive effect on consumers’ willingness to purchase cheese with ……. / ……. logo. This hypothesis is partially supported by the results. Health benefits (b = 0.23, p = 0.018) positively affect consumers’ willingness to purchase. However, culture and traditions (b = -0.01, p = 0.967), perceived quality and safety (b = 0.03, p = 0.807) and rural development (b = 0.13, p = 0.212) do not predict consumers’ willingness to purchase.

H3 predicts that consumers’ trust in ……. / ……. logo positively influence their willingness to purchase ……. / ……. with logo. This hypothesis is fully suported by the obtained results (b = 0.51, p < 0.001). Trust is a statistically significant predictor of consumers’ willingness to purchase cheese with ……. / ……. logo. 55.3% of the variance of consumers’ willingness to purchase is explained by its predictors health benefits and trust.

H4 predicts that trust mediates the influence of GI indicators (a) culture and traditions, (b) health benefits, (c) perceived quality and safety, (d) rural development on consumers’ willingness to purchase ……. / ……. with the logo. Mediation was first tested using Baron & Kenny’s approach (1986)[1], as shown in Table II. The hypothesis is partially supported by the results according to this approach. There is full mediation effect of trust on the relationship between perceived quality and safety and consumers’ willingness to purchase (direct effect is PQS on CWP is significant without mediator, and insignificant with mediator included in the model). There is partial mediation effect of trust on the relationship between health benefits and consumers’ willingness to purchase (direct effect of HB on CWP is significant both with and without the mediator included in the model). There are mediating effects of trust neither on the relationship between culture and traditions with consumers’ willingness to buy, nor on the relationship between rural development and consumers’ willingness to purchase.

After that, the mediation was futher evalueted using the bias-corrected bootstrap method with 10.000 samples at 95% confidence intervals. Column Standardized indirect effects of Table II shows the results. The full mediation effect of trust on the relationship between perceived quality and safety and consumers’ willingness to purchase was confirmed. There was also full mediation effect of trust on the relationship between culture and traditions and consumers’ willingness to purchase. The mediation effects of trust on the relationship of consumers’ willingness to purchase with health benefits and rural development were not found with this approach.

Table II. Results of mediation analysis

Relationship Standardized regression weights without mediator Standardized regression weights with mediator Standardized indirect effects
CT –> T* –> CWP 0.- -0.- 0.012**
HB –> T –> CWP 0.222** 0.-** -0.-
PQS –> T –> CWP 0.-*** 0.028 0.-***
RD –> T –> CWP 0.110 0.- -0.067

*The variable in the middle of relationship is the mediator variable

**p < 0.1

***p < 0.01

 

All path estimates based on relationships between culture and traditions, health benefits, perceived quality and safety, rural development, trust, and consumers’ willingness to purchase are shown in Figure 1.

 

 

 

Figure 1. A path model with standardized path coefficients

 

*p < 0.1, ***p < 0.001

[1]Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.

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