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

<p>This paper uses the DEA model and the Malmquist index model to look at how well building a geographical indication brand for an agricultural product works in prefecture-level cities in Jilin Province. It also looks at how the performance of building a geographical indication brand for an agricultural product changes over time in prefecture-level cities in Jilin Province. Then, a brand competitiveness evaluation system was made up of regional elements, brand elements, industrial elements, and support elements. The level of development of agricultural product brand competitiveness in Jilin Province was looked at using fuzzy comprehensive evaluation and hierarchical analysis. The results of the evaluation were used to find the factors that affect the improvement of its brand competitiveness, which helped to map out the next steps for reshaping agricultural product brands in Jilin Province. The comprehensive evaluation of the brand competitiveness of agricultural products in Jilin Province has a specific score of 81.4, and the regional element, brand element, product element, and support element have specific scores of 82.01, 83.2, 81.66, and 80.7, respectively. This study provides references to promote the development of agricultural products’ geographical indications and to enhance the competitiveness of the corresponding brands, and it enriches and improves theoretical research on the competitiveness of the brands of agricultural products’ geographical indications.</p>
</abstract>

This paper uses the DEA model and the Malmquist index model to look at how well building a geographical indication brand for an agricultural product works in prefecture-level cities in Jilin Province. It also looks at how the performance of building a geographical indication brand for an agricultural product changes over time in prefecture-level cities in Jilin Province. Then, a brand competitiveness evaluation system was made up of regional elements, brand elements, industrial elements, and support elements. The level of development of agricultural product brand competitiveness in Jilin Province was looked at using fuzzy comprehensive evaluation and hierarchical analysis. The results of the evaluation were used to find the factors that affect the improvement of its brand competitiveness, which helped to map out the next steps for reshaping agricultural product brands in Jilin Province. The comprehensive evaluation of the brand competitiveness of agricultural products in Jilin Province has a specific score of 81.4, and the regional element, brand element, product element, and support element have specific scores of 82.01, 83.2, 81.66, and 80.7, respectively. This study provides references to promote the development of agricultural products’ geographical indications and to enhance the competitiveness of the corresponding brands, and it enriches and improves theoretical research on the competitiveness of the brands of agricultural products’ geographical indications.

Rebranding and SWOT Analysis of Geographical Indication Agricultural Products in Jilin Province under Digital Transformation

Applied Mathematics and Nonlinear Sciences

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

This paper uses the DEA model and the Malmquist index model to look at how well building a geographical indication brand for an agricultural product works in...

Rebranding and SWOT Analysis of Geographical Indication Agricultural Products in Jilin Province under Digital Transformation

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 23. März 2024

Akzeptiert: 18. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-2186

Schlüsselwörter
Fuzzy hierarchical analysis, DEA model, Malmquist index, SWOT analysis, Agricultural product brands

© 2024 Hui Xu, published by Sciendo

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

Rebranding and SWOT Analysis of Geographical Indication Agricultural Products in Jilin Province under Digital Transformation

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 23. März 2024

Akzeptiert: 18. Juni 2024

DOI: https://doi.org/10.2478/amns-2024-2186

SchlüsselwörterFuzzy hierarchical analysis, DEA model, Malmquist index, SWOT analysis, Agricultural product brands

© 2024 Hui Xu, published by Sciendo

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

Schlüsselwörter
Fuzzy hierarchical analysis, DEA model, Malmquist index, SWOT analysis, Agricultural product brands