CHAPTER 4 RESEARCH RESULTS
4.4 The Results of Objective 3: The Results Examine the Positive Influences of
4.4.4 Results of Hypothesis Testing
According to table 4.19, revealed that with regards to the composite reliability of latent variables (CR), Tourists’ perception (PERC), Tourists’ experience (EXPE), Tourists’ satisfaction (SATI), and Tourists’ loyalty (LOYA) had the composite reliability (CR) ranging from 0.732 to 0.911 which considered quite high as it was greater than 0.70.
Tourists’ perception (PERC), Tourists’ experience (EXPE), Tourists’
satisfaction (SATI), and Tourists’ loyalty (LOYA) had the average variance extracted (AVE) of factors and latent variables ranging from 0.534 to 0.597. It implied that all observed variables can describe quite significantly the variance of factors and latent variables which is greater than 0.70 in each factor.
With reference to the mentioned statement, it can be summarized that the composite reliability (CR) is quite high meaning greater than 0.50 and the observed variables can describe quite significantly the variance of latent variables (AVE) in each factor which is greater than 0.70. Regarding analysis result of the reliability of observed variables (Internal consistency reliability), it can be seen that the observed variables had high level of reliability to measure each factor. It indicates that from the assessment of the measurement model, there is an outstanding evidence showing that defining all factors and latent variables are all correct and reliable.
Table 4.20 Entered Multiple Regression Analysis of Perceived Value has Positive Influences on Experience Economy
(n = 550)
Factors
Un-standardized Coefficients
Standardized
Coefficient t Sig
B SE Beta(β)
(Constant) .943 .083 11.429 .000
PERC (A) .039 .022 .049 1.756 .080
PERC (B) .019 .026 .026 .707 .480
PERC (C) .033 .018 .057 1.832 .067
PERC (D) .128 .025 .181 5.198 .000
PERC (E) .413 .027 .506 15.446 .000
PERC (F) .099 .025 .130 3.994 .000
PERC (G) .053 .029 .071 1.853 .064
Note: ** P < 0.01; R = 0.878, R2 = 0.770, Adjusted R Square = 0.767, F = 259.899**
Table 4.20, considering the variables of tourists’ perceptions and values of local food festivals in Phuket, consisted of perception of emotional value four variables and perception of functional three variables. The seven variables positively influenced creating a good tourist experience economy statistically significant (P <
0.05) were; the value of environment (PERC: D), functional value (PERC: E), and festival program (PERC: F). Which recognizing functional value (PERC: E) had the most decisive positive influence, that is, the number of units of functional value (PERC: E)) increased by one unit, it would result in tourists’ perceptions of the value of local food festivals in Phuket Province increased with 0.506 units (or 50.6%). The second factor that had a positive influence was the value of the environment. An increase of one unit environment (PERC: D) will result in a 0.181-unit (or 18.1%) increase in tourists’ perceptions of the value of local food festivals in Phuket and a festival program (PERC: F). Thus, an increase of 1 unit would result in an increase in
tourists’ perception of the value of a local food festival in Phuket by 0.130 units (or 13.0%), while four variables were not statistically significant (P > 0.05). These include emotional value, festival products, convenience facilities, and information service. Considering the results of the coherence examination of the perceived value variables of local food festivals in Phuket with the creation of a good tourist experience economy according to hypothesis 1, table 4.13 below:
Table 4.21 Indices Used to Consider the Congruence and Goodness of Fit of the Model and Empirical Data
(n = 550) Index of Item Objective
Congruence/Goodness of Fit Index
Criteria Index
Before Adjusting the Model
After Adjusting the Model Analysis
Results
Results Analysis Results
Results
1. Absolute Fit Index 1.1 Relative 2, 2/df) or CMIN/DF
< 2.00 2 = 782.890
df =41 CMIN/DF =
19.095
Fail 2 = 21.268 df =19 CMIN/D F = 1.119
Pass
1.2 P value of 2 or P of CMIN P > 0.05 0.000 Fail .322 Pass 1.3 GFI (Goodness of Fit
Index)
≥ 0.90 .787 Fail .993 Pass
1.4 AGFI (Adjusted Goodness of Fit Index)
≥ 0.90 .657 Fail .976 Pass
1.5 RMR (Root Mean Square Residual)
≤ 0.05 .023 Pass .005 Pass
1.6 RMSEA (Root Mean Square Error of
Approximation)
≤ 0.05 .182 Fail .015 Pass
2. Relative Fit Index
2.1 NFI (Normed Fit Index) ˃ 0.80 .823 Pass .995 Pass
Index of Item Objective Congruence/Goodness of Fit
Index
Criteria Index
Before Adjusting the Model
After Adjusting the Model Analysis
Results
Results Analysis Results
Results
2.2 RFI (Relative Fit Index) ˃ 0.80 .763 Fail .986 Pass 2.3 IFI (Incremental Fit Index) ˃ 0.80 .831 Pass .999 Pass 2.4 TLI (Tucker-Lewis Index) ˃ 0.80 .772 Fail .998 Pass 2.5 CFI (Comparative Fit
Index)
˃ 0.80 .830 Pass .999 Pass
3. Parsimony Fit Index 3.1 PRATIO (Parsimonious Ratio)
˃ 0.50 .745 Pass .545 Pass
3.2 PNFI (Parsimony Normed Fit Index)
˃ 0.50 .614 Pass .544 Pass
3.3 PCFI (Parsimony Comparative Fit Index)
˃ 0.50 .619 Pass .545 Pass
4. Sample size determination index
4.1 Hoelter >200 46 Fail 935 Pass
According to table 4.21, showed the Chi-square statistic (2) of the related structural equation model before adjusting the model = 782.890, degrees of freedom (df) = 41 with a statistical significance level l 0.000. It indicated that the causal relationship model was not congruent with the empirical data. However, since the chi- square value was sensitive to the sample size, the bigger the sample size was, the more the chi-square value became statistically significant. Consequently, the ratio between the chi-square value and the number of degrees of freedom (2/df) should altogether consider. The analysis revealsed that the ratio between the chi-square value and the number of degrees of freedom = 19.095, which was higher than the determined criteria equal to 2. Furthermore, considered the goodness of fit index of other aspects, it could be noticed that those indices did not meet the determined criteria according to the following details: GFI = 0.787 could meet the determined criteria (≥ 0.90), and AGFI = 0.657, which could not meet the determined criteria (≥
0.90). RMSEA = 0.182 could not meet the determined criteria (< 0.05) and RMR = 0.023 could not meet the determined criteria (< 0.05). Considered a comparison of the goodness of fit test, it found that NFI = 0.823, Tucker-Lewis Index (TLI) = 0.763, CFI = 0.830, which meet the determined criteria (>0.90). PCFI = 0.619, which meet the determined criteria (>0.50), PNFI = 0.614, which meet the determined criteria (>
0.50), and Hoelter value = 46, which could not meet the determined criteria (> 200).
After adjusting the model by redrawing the model’s relationship lines after the final adjustment according to a suggestion, the model was more congruent with the empirical data, and the statistics followed the determined criteria. The analysis showed that the structural equation model (Modified Model) was congruent with the empirical data after the adjustment. It implied that it could accept the main hypothesis that the theoretical model was congruent with the empirical data. Considered the chi- square statistic (2) = 21.268, degrees of freedom (df) = 19, P-value = 0.322 which could meet the criteria as it was greater than 0.05. The ratio between the chi-square statistic and the number of degrees of freedom or the relative chi-square (2/df) = 1.119 could meet the criteria as it was less than 2 and lower than the determined criteria that were equal to 2. Therefore, the model was congruent with the empirical data. The congruence from the goodness of fit index (GFI) = 0.993, AGFI = 0.976 which could meet the criteria as it was higher or equal to 0.90, NFI = 0.995, RFI = 0.986, TLI = 0.998, and CFI = 0.999, which could meet the criteria as they were greater than 0.90, PNFI = 0.545 which could meet the criteria as it was greater than 0.50 and RMSEA = 0.015 and RMR = 0.005 which could meet the criteria as they were lower than 0.05 and Hoelter value = 935 which could meet the criteria as it was higher than 200. The analysis results are shown in figures 4.5
Chi-Square = 21.268; df = 19; Relative Chi-Square = 1.119; p-value = .322 GFI = .993; NFI = .995; TLI = .998; CFI = .999; RMSEA = .015; RMR = .005 Figure 4.5 The Analysis Results of the Structural Equation Model Research
Hypothesis 1 (After Adjusting the Model)
Hypothesis 2: Experience economy has positively influence on behavior intention
Figure 4.6 The Structural Equation Model of Research Hypothesis 2
Table 4.22 Entered Multiple Regression Analysis of Experience Economy has Positivel Influence on Behavior Intention
(n = 550)
Factors
Un-standardized Coefficients
Standardized
Coefficient t Sig
B SE Beta(β)
(Constant) .591 .171 3.463 .001
EXPE (H) .071 .040 .074 1.760 .079
EXPE (I) .093 .034 .116 2.740 .006
EXPE (J) .009 .032 .010 0.292 .771
EXPE (K) .681 .034 .633 19.757 .000
Note: ** P < 0.01; R = 0.712, R2 = 0.507, Adjusted R Square = 0.503, F = 139.857**
Table 4.22, considering the variables for creating a good experience economy and behavioral intention of tourists participating in local food festivals in Phuket, those are 4 variables of creating a good experience economy has positively on behavioral intentions of tourists statistically significant (P < 0.05) were educational experience (EXPE: I) and esthetic experience (EXPE: K) had the highest positive influence, that is, the number of units of the esthetic experience (EXPE: K) increased with one unit, it resulted in tourists have a positive experience with the behavioral intention they entered participation in local food festivals in Phuket increased with 0.633 units (or 63.3%) and educational experience (EXPE: I) increased with 1 unit resulting in tourists better behavioral experiences intention attendance at a local food festival in Phuket increased with 0.116 units (or 11.6%), while the 2 variables that were not statistically significant (P > 0.05) were entertainment experience (EXPE: H), and escapist phase ( EXPE: J).
Considering the results of the coherence examination of the behavioral intention economy variables of tourists participating in local food festivals in Phuket according to hypothesis 2, Table 4.23
Table 4.23 Indices Used to Consider the Congruence and Goodness of Fit of the Model and Empirical Data of Research Hypothesis 2
(n = 550) Index of Item Objective
Congruence/Goodness of Fit Index
Criteria Index
Before Adjusting the Model
After Adjusting the Model Analysis
Results Results Analysis
Results Results 1. Absolute Fit Index
1.1 Relative 2, 2/df) or CMIN/DF
< 2.00 2 = 418.073
df =13 CMIN/DF =
32.159
Fail 2 = 11.008 df =10 CMIN/D F = 1.101
Pass
1.2 P value of 2 or P of CMIN P > 0.05 0.000 Fail .357 Pass 1.3 GFI (Goodness of Fit
Index)
≥ 0.90 .869 Fail .994 Pass
1.4 AGFI (Adjusted Goodness of Fit Index)
≥ 0.90 .717 Fail .985 Pass
1.5 RMR (Root Mean Square Residual)
≤ 0.05 .050 Fail .011 Pass
1.6 RMSEA (Root Mean Square Error of
Approximation)
≤ 0.05 .238 Fail .014 Pass
2. Relative Fit Index
2.1 NFI (Normed Fit Index) ˃ 0.80 .724 Pass .993 Pass
2.2 RFI (Relative Fit Index) ˃ 0.80 .555 Fail .985 Pass 2.3 IFI (Incremental Fit Index) ˃ 0.80 .731 Fail .999 Pass 2.4 TLI (Tucker-Lewis Index) ˃ 0.80 .563 Fail .999 Pass 2.5 CFI (Comparative Fit
Index)
˃ 0.80 .729 Fail .999 Pass
Index of Item Objective Congruence/Goodness of Fit
Index
Criteria Index
Before Adjusting the Model
After Adjusting the Model Analysis
Results Results Analysis
Results Results 3. Parsimony Fit Index
3.1 PRATIO (Parsimonious Ratio)
˃ 0.50 .476 Pass .619 Pass
3.2 PNFI (Parsimony Normed Fit Index)
˃ 0.50 .448 Fail .573 Pass
3.3 PCFI (Parsimony Comparative Fit Index)
˃ 0.50 .451 Fail .576 Pass
4. Sample size determination index
4.1 Hoelter >200 37 Fail 1158 Pass
According to table 4.23, showed the Chi-square statistic (2) of the related structural equation model before adjusting the model = 418.073, degrees of freedom (df) = 13 with a statistical significance level 0.000. It indicated that the causal relationship model was not congruent with the empirical data. However, since the chi- square value was sensitive to the sample size, the bigger the sample size was, the more the chi-square value became statistically significant. Consequently, the ratio between the chi-square value and the number of degrees of freedom (2/df) should altogether consider. The analysis revealsed that the ratio between the chi-square value and the number of degrees of freedom = 32.159, which was higher than the determined criteria equal to 2. Furthermore, considered the goodness of fit index of other aspects, it could be noticed that those indices did not meet the determined criteria according to the following details: GFI = 0.869 could meet the determined criteria (≥ 0.90), and AGFI = 0.717, which could not meet the determined criteria (≥
0.90). RMSEA = 0.238 could not meet the determined criteria (< 0.05) and RMR = 0.050 could not meet the determined criteria (< 0.05). Considered a comparison of the goodness of fit test, it found that NFI = 0.724, Tucker-Lewis Index (TLI) = 0.555, CFI = 0.731, which meet the determined criteria (>0.90). PCFI = 0.451, which meet
the determined criteria (>0.50), PNFI = 0.448, which meet the determined criteria (> 0.50), and Hoelter value = 37, which could not meet the determined criteria (> 200).
After adjusting the model by redrawing the model’s relationship lines after the final adjustment according to a suggestion, the model was more congruent with the empirical data, and the statistics followed the determined criteria. The analysis showed that the structural equation model (Modified Model) was congruent with the empirical data after the adjustment. It implied that it could accept the main hypothesis that the theoretical model was congruent with the empirical data. Considered the chi- square statistic (2) = 11.008, degrees of freedom (df) = 10, P-value = 0.357 which could meet the criteria as it was greater than 0.05. The ratio between the chi-square statistic and the number of degrees of freedom or the relative chi-square (2/df) = 1.101 could meet the criteria as it was less than 2 and lower than the determined criteria that were equal to 2. Therefore, the model was congruent with the empirical data. The congruence from the goodness of fit index (GFI) = 0.994, AGFI = 0.985 which could meet the criteria as it was higher or equal to 0.90, NFI = 0.993, RFI = 0.985, TLI = 0.999, and CFI = 0.999, which could meet the criteria as they were greater than 0.90, PNFI = 0.573 which could meet the criteria as it was greater than 0.50 and RMSEA = 0.014 and RMR = 0.011 which could meet the criteria as they were lower than 0.05 and Hoelter value = 1158 which could meet the criteria as it was higher than 200. The analysis results are shown in figures 4.7
Chi-Square = 11.008; df = 10; Relative Chi-Square = 1.101; p-value = .357 GFI = .994; NFI = .993; TLI = .999; CFI = .999; RMSEA = .014; RMR = .011 Figure 4.7 The Analysis Results of the Structural Equation Model Research
Hypothesis 2 (After Adjusting the Model)
Hypothesis 3: Experience economy has positively influence on Tourist’s loyalty
Figure 4.8 The Structural Equation Model of Research Hypothesis 3
Table 4.24 Entered Multiple Regression Analysis of Experience Economy has Positively Influence on Tourist’s Loyalty of Research Hypothesis 3
(n = 550)
Factors
Un-standardized Coefficients
Standardized
Coefficient t Sig
B SE Beta(β)
(Constant) 1.716 .228 7.535 .000
EXPE (H) .040 .054 .041 0.754 .451
EXPE (I) .188 .046 .223 4.128 .000
EXPE (J) .081 .043 .086 1.901 .058
EXPE (K) .259 .046 .231 5.542 .000
Note: ** P < 0.01; R = 0.438, R2 = 0.192, Adjusted R Square = 0.186, F = 32.427**
Table 4.24, considering the variables of creating a good experience economy and tourist loyalty to local food festivals in Phuket, consisting of four variables of creating a good experience economy, the four variables have a positive influence on tourist loyalty statistically significant (P < 0.05) were educational experience (EXPE:
I) and aesthetic experience (EXPE: K) had the most decisive positive influence, that is,