3.2. Analysis of Survey Data on Tourist Experience Quality of Theme Creative Markets
3.2.1. Factor Analysis of Tourist Experience
In this study, we analyzed 25 factors of the tourist experience for four theme creative markets from three perspectives: market environment, activities, and services. Factor analysis was used to determine each factor variable of the 339 samples. First, the validity of the results was tested by using the Kaiser–Meyer–Olkin (KMO) test and the Bartlett test of sphericity. The results indicated that the KMO value of the global variable was 0.963, which is greater than 0.8. In the Bartlett test, the p value was 0.000, less than 0.05, indicating that the scale had good validity and was suitable for further factor analysis.
The average score, the standard deviation of the 25 specific factors of the experience evaluation dimension of the theme creative market, and the reliability of the three evaluation dimensions are shown in
Table 3.
As shown in
Table 3, the mean values of each experience factor of the four theme creative markets were between 3 and 4 points, i.e., the overall satisfaction of the tourists with each experience factor of the thematic commercial market was between ‘general’ and ‘relatively satisfied’, indicating that there was still room for improvement in some factors. Among the three evaluation dimensions, the tourist’s experience evaluation of the market activity was the best, with the highest average score, but the experience evaluation of the market environment was the lowest, indicating that although the tourists recognized the activity content of the theme creative market, they believed that the spatial environment and layout around the theme creative markets needed to be improved.
3.2.2. Factor Analysis of Market Environment
First, the Bartlett test of sphericity and the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy were performed. After testing, the value of the KMO measure of sampling adequacy was 0.911, which indicated that this group of data was suitable for factor analysis (>0.7). Meanwhile, the significance probability of the
statistical value of the Bartlett test of sphericity was 0.000, less than 1%, which indicated that the data correlation matrix was not a unit matrix and had correlation, which showed that the statistical data were suitable for the factor analysis. The factor load matrix after rotation was obtained by factor analysis, as shown in
Table 4:
The characteristic root value and cumulative explained variance were obtained by factor analysis, and the results are shown in
Table 5.
As shown in
Table 5, as the first two principal components explained 72.692% of the total variance in total, replacing the 11 variables with two factors could summarize nearly 70% of the information contained in the original variables. Therefore, it can be preliminarily concluded that these two major factors could explain most variables and summarize most of the information. Moreover, the factor load of each indicator variable was relatively high (>0.5), which indicated that the original indicators of each component had significant correlation.
In the previous analysis, the market environment was divided into ‘space environment’ and ‘social and cultural environment’. In order to understand the experience of tourists more comprehensively and concretely, some elements were subdivided, and a total of eight factors were listed for investigation.
The survey results showed that the humanistic atmosphere, folk culture, stall features, and social security of the market could be combined into one factor, which was named the ‘social environment factor’. The space pedestrian route, spatial distribution, signage system, and landscape features of the market can be combined into one factor, which can be named the ‘spatial environment factor’.
According to the quantitative relationship between each factor and the index, the score of each main factor was calculated by the regression method:
The calculation formula is: .
Among them,
is the score of the
main factor,
is the load of the
indicators on the
main factor, and
is the variable value. The coefficient matrix output results of the market environment factors are shown in
Table 6:
According to the main factor score coefficient matrix, the factor score can be calculated, namely:
Social environment factor (F1) = 0.489 humanistic atmosphere + 0.465 folk culture + 0.282 stall features + 0.214 social security − 0.316 space pedestrian route − 0.200 spatial distribution − 0.128 signage system + 0.085 landscape features.
Spatial environment factor (F2) = − 0.277 humanistic atmosphere − 0.263 folk culture − 0.059 stall features − 0.014 social security + 0.556 space pedestrian route + 0.442 spatial distribution + 0.352 signage system + 0.149 landscape features.
It can be seen from the above formula that, first, the social environment factors basically dominated e1, e2, e3, and e4 (coefficients with large absolute values); that is, the tourists’ evaluation of the social environment experience was mainly affected by four factors: humanistic atmosphere, folk culture, stall features, and social security. In fact, the tourists had a high evaluation of the humanistic atmosphere, folk culture, and social security of the market and a low evaluation of the stall features. This showed that theme creative markets had strong cultural deposits in the past and paid more attention to the protection and inheritance of culture in the transformation. However, there are still some shortcomings in the market stall features, which need to be strengthened in the future to give tourists a better experience.
Second, the spatial environment factor basically dominated e5, e6, e7, and e8; that is, the tourists’ evaluation of the spatial environment experience was mainly affected by four factors: space pedestrian route, spatial distribution, signage system, and landscape features. Then, the tourists did not give a high evaluation to the space pedestrian route, spatial distribution, and signage system. In order to find out the reasons, through field observation and interviews with some tourists who filled in the questionnaire, it was found that theme creative markets were often located in a street or a small area, with a relatively limited area, but the overall flow rate of people was relatively large, resulting in a poor evaluation of the spatial environment by the people. These factors need to be taken into account in the subsequent improvement in order to appropriately expand the market area and further optimize the spatial distribution to provide tourists with a more comfortable spatial environment.
3.2.3. Factor Analysis of Market Activity
First of all, the Bartlett test of sphericity and the KMO measure were performed. After testing, the data were relevant and suitable for factor analysis. The factor load matrix after rotation was obtained by factor analysis, as shown in
Table 7.
The characteristic root value and cumulative explained variance were obtained by factor analysis, and the results are shown in
Table 8.
As shown in
Table 8, the first two principal components explained 76.548% of the total variance (>70%). Moreover, the factor load of each indicator variable was relatively high (>0.5), which indicated that the original indicators of each component had significant correlation.
In the previous analysis, this paper believed that the experience elements of the market activity mainly included the theme of the market activities, the overall atmosphere of the activities, the richness and participation of the activities, and the entertainment of the activities. These elements were subdivided, and a total of 10 factors were listed for investigation.
The results showed that the activity process, consumer demand, richness, innovativeness, and participation can be combined into one factor, which is named the ‘activity content factor’. The stall owner’s words and deeds, the market theme, activity scene layout, decoration layout, and cultural connotation can be combined into one factor, which can be named the ‘activity form factor’.
According to the quantitative relationship between each factor and index, the score of each main factor was calculated by the regression method. The output results of the coefficient matrix of the market activity factor are shown in
Table 9.
According to the main factor score coefficient matrix, the factor score can be calculated, namely:
Activity content (F1) = 0.614 activity process + 0.522 consumer demand + 0.243 richness + 0.097 innovativeness − 0.099 participation − 0.568 stall owner’s words and deeds − 0.024 market theme − 0.196 activity scene layout + 0.000 decoration layout + 0.036 cultural connotation.
Activity form (F2) = − 0.474 activity process − 0.370 consumer demand − 0.084 richness + 0.073 innovativeness + 0.069 participation + 0.750 stall owner’s words and deeds + 0.204 market theme + 0.376 activity scene layout + 0.170 decoration layout + 0.132 cultural connotation.
It can be seen from the above formula that, first, the activity content factor basically dominated e1, e2, e3, e4, and e5 (coefficients with large absolute values); that is, the tourists’ evaluation of the activity content was mainly affected by the activity process, consumer demand, richness, innovativeness, and participation. Among them, the activity process and consumer demand played a decisive role. However, the actual survey results showed that tourists had the lowest evaluation of the innovativeness of the market activity, followed by consumer demand. In the future, these aspects should be strengthened to improve the experience quality of the tourists.
Secondly, the activity form factor basically dominated e6, e7, e8, e9, and e10; that is, the tourists’ evaluation of the activity form was mainly affected by the stall owner’s words and deeds, the market theme, the activity scene layout, the decoration layout, and the cultural connotation. Among them, stall owner’s words and deeds and the market theme played a decisive role. Suitable market themes and the stall owner’s words and deeds played an important role in improving the quality of tourists’ experience. These aspects of the markets still need to be improved.
3.2.4. Factor Analysis of Market Service
After the Bartlett test of sphericity and the KMO measure, the data were relevant and suitable for factor analysis. The factor load matrix after rotation was obtained by factor analysis, as shown in
Table 10.
The characteristic root value and cumulative explained variance were obtained by factor analysis, and the results are shown in
Table 11.
As shown in
Table 11, as the first two principal components explained 76.850% of the total variance (>70%), two factors were used to replace 11 variables. Moreover, the factor load of each indicator variable was relatively high (>0.5), which indicated that the original indicators of each component had significant correlation.
The survey results showed that the stall owner service, tour guide service, traffic service, and commodity price accepted by tourists in the market can be combined into one factor, which was named ‘basic service factor’. The souvenir service, personalized service, and public facilities service can be combined into one factor, which can be named the ‘professional service factor’.
According to the quantitative relationship between each factor and index, the score of each main factor was calculated by the regression method. The output results of the coefficient matrix of the market service factor are shown in
Table 12.
According to the main factor score coefficient matrix, the factor score can be calculated, namely:
Basic service (F1) = 0.563 stall owner service + 0.428 tour guide service + 0.433 traffic service + 0.317 commodity price − 0.383 souvenir service − 0.236 personalized service − 0.256 public facilities service.
Professional service (F2) = − 0.353 stall owner service − 0.202 tour guide service − 0.219 traffic service − 0.094 commodity price + 0.664 souvenir service + 0.508 personalized service + 0.520 public facilities service.
It can be seen from the above formula that, first, the basic service factor basically dominated e1, e2, e3, and e4; that is, the tourists’ evaluation of the basic service of the market is mainly affected by the stall owner service, tour guide service, traffic service, and commodity price. Among them, the stall owner service and tour guide service had a greater impact. The survey found that the tourists’ evaluation of the basic services of the market was generally average, especially the stall owner service and the tour guide service, which require strengthening with regard to personnel management and training.
Secondly, the professional service factor basically dominated e5, e6, and e7; that is, the tourists’ evaluation of the professional service was mainly affected by three factors: the souvenir service, personalized service, and public facilities service. Among them, the souvenir service and personalized service played a decisive role. The development of tourism had led to higher local prices. Both tourists and local residents complained about this. However, the solution of this problem requires more macroeconomic regulation by the government. For the tourism industry, the key to solving this problem is to improve the service quality of the market.
3.3. Overall Evaluation of Tourist Experience and Linear Regression Analysis of Experience Factors
To sum up, the tourist market experience system included six main factors: the social environment, spatial environment, activity content, activity form, basic service, and professional service. The linear regression analysis method can be used to explore the relationships between these factors and the overall experience evaluation so as to try to build a linear regression equation between the overall evaluation of the market experience and its experience factors. Before linear regression analysis, we analyzed the correlation between each experience factor and the overall experience evaluation. See
Table 13 for details.
The
Table 13 correlation measures show that each experience factor was significantly related to the overall experience evaluation at the confidence level, which also shows that each experience factor was significantly related to the overall experience evaluation of the tourists. Next, the overall evaluation of the tourist experience was taken as the dependent variable and the six experience factors as the independent variable to carry out linear regression analysis. The results are shown in
Table 14.
According to the above table, the significance probability of the constant term was 0.000 (<0.05), indicating that there was a significant difference between the constant term and 0. The constant term should appear in the equation as an explanatory variable, with a coefficient of 3.759. The significance probability of the t-value of ‘social environment factor’ was 0.020, which indicated that the coefficient of the social environment factor was significantly different from 0. The social environment factor should appear in the equation as an explanatory variable, and its standard regression coefficient was 0.148. The factors that should appear in the equation as explanatory variables included ‘spatial environment’ and ‘professional service’, and their standard regression coefficients were 0.144 and 0.188, respectively. The significance probabilities of the t-values of ‘activity content’, ‘activity form’, and ‘basic service’ were 0.159, 0.179, and 0.101 (>0.05), indicating that there was no significant difference in the coefficients of these three factors and that they should not appear in the equation as explanatory variables. Therefore, the standard linear regression equation between the market tourist experience factor and the overall experience evaluation is as follows.
The overall experience evaluation = 0.148 ‘social environment’ + 0.144 ‘spatial environment’ + 0.188 ‘professional service’ + 3.759 ‘constant’.
From the above regression equation, it can be seen that the contributions of the social environment, spatial environment, and professional service to the overall experience evaluation of the tourists were not much different; of these, the professional service had the most significant impact on the evaluation of the tourists’ experience quality, with a correlation coefficient of 0.444. Both the social environment and the spatial environment belong to the elements of the market environment. In other words, the market environment is the decisive factor for the quality of the tourists’ experience.