<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study explores the dynamics of inheritance and innovation within opera, focusing specifically on Wuhua Caicha Opera, a key cultural asset in Lotus County. Utilizing a mixed-method approach that includes questionnaire surveys and field interviews, this paper systematically examines the current status of Wuhua Caicha Opera's transmission. We collected and analyzed data using a robust statistical model in SPSS, which integrates principal component analysis and stepwise regression techniques. The findings reveal that the self-factors and governmental influences on the preservation and development of the Wuhua tea-picking opera troupe in Lotus County have statistically significant impacts, with Sig. Values of 0.012 and 0.001, respectively. This indicates a notable effect of both intrinsic and extrinsic factors on the opera's transmission. However, less than half of the participants affirmed the current methods of heritage transmission, protection of cultural bearers, and innovation in the repertoire. The average scores for governmental influence on recognition were all above 3.6, suggesting a strong governmental role. The insights from this study provide empirical evidence that can guide policy formulations and support efforts to foster the sustainable evolution and transmission of Wuhua Caicha Opera.</p>
</abstract>

This study explores the dynamics of inheritance and innovation within opera, focusing specifically on Wuhua Caicha Opera, a key cultural asset in Lotus County. Utilizing a mixed-method approach that includes questionnaire surveys and field interviews, this paper systematically examines the current status of Wuhua Caicha Opera's transmission. We collected and analyzed data using a robust statistical model in SPSS, which integrates principal component analysis and stepwise regression techniques. The findings reveal that the self-factors and governmental influences on the preservation and development of the Wuhua tea-picking opera troupe in Lotus County have statistically significant impacts, with Sig. Values of 0.012 and 0.001, respectively. This indicates a notable effect of both intrinsic and extrinsic factors on the opera's transmission. However, less than half of the participants affirmed the current methods of heritage transmission, protection of cultural bearers, and innovation in the repertoire. The average scores for governmental influence on recognition were all above 3.6, suggesting a strong governmental role. The insights from this study provide empirical evidence that can guide policy formulations and support efforts to foster the sustainable evolution and transmission of Wuhua Caicha Opera.

The Inheritance and Innovation Path of Wuhua Tea Casting Opera Music under the Perspective of Chinese Modernization

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This study explores the dynamics of inheritance and innovation within opera, focusing specifically on Wuhua Caicha Opera, a key cultural asset in Lotus County....

The Inheritance and Innovation Path of Wuhua Tea Casting Opera Music under the Perspective of Chinese Modernization

Published Online: Jul 09, 2024

Page range: -

Received: Mar 13, 2024

Accepted: Jun 02, 2024

DOI: https://doi.org/10.2478/amns-2024-1747

Keywords
Principal component analysis, Stepwise regression analysis, Wuhua tea-picking opera, Influencing factors

© 2024 Jing Yang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The Inheritance and Innovation Path of Wuhua Tea Casting Opera Music under the Perspective of Chinese Modernization

Published Online: Jul 09, 2024

Page range: -

Received: Mar 13, 2024

Accepted: Jun 02, 2024

DOI: https://doi.org/10.2478/amns-2024-1747

KeywordsPrincipal component analysis, Stepwise regression analysis, Wuhua tea-picking opera, Influencing factors

© 2024 Jing Yang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Principal component analysis, Stepwise regression analysis, Wuhua tea-picking opera, Influencing factors