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<p>With the development of the digital economy, the innovation of the tax preference method is necessary. This paper integrates traditional industries with the digital economy through digital technology, standardizes the tax preference data of digital industries by using a fuzzy comprehensive evaluation algorithm, and builds an innovative mechanism of tax preference by establishing two weighting indicators of tax relief ratio and Q value (tax relief locational entropy) through data feedback. To ensure the accuracy of the feedback indicators, the full-factor algorithm is invoked to detect the intensity of the mechanism’s preferences in the digital industry. To verify the effectiveness of the mechanism, the results of the practical analysis show that after the innovation mechanism constructed in this paper is put into practice, the proportion of tax breaks in two digital industries, manufacturing and industry, increases by 29% and 34%, respectively, and the Q values of the five industries increase by about 4.2% on average, and the yields all increase by about 5.12 percentage points. This illustrates that the tax preference innovation mechanism constructed in this paper can accelerate the economic development of industries and is conducive to giving full play to the positive incentive effect of tax preference on their material benefits.</p>
</abstract>

With the development of the digital economy, the innovation of the tax preference method is necessary. This paper integrates traditional industries with the digital economy through digital technology, standardizes the tax preference data of digital industries by using a fuzzy comprehensive evaluation algorithm, and builds an innovative mechanism of tax preference by establishing two weighting indicators of tax relief ratio and Q value (tax relief locational entropy) through data feedback. To ensure the accuracy of the feedback indicators, the full-factor algorithm is invoked to detect the intensity of the mechanism’s preferences in the digital industry. To verify the effectiveness of the mechanism, the results of the practical analysis show that after the innovation mechanism constructed in this paper is put into practice, the proportion of tax breaks in two digital industries, manufacturing and industry, increases by 29% and 34%, respectively, and the Q values of the five industries increase by about 4.2% on average, and the yields all increase by about 5.12 percentage points. This illustrates that the tax preference innovation mechanism constructed in this paper can accelerate the economic development of industries and is conducive to giving full play to the positive incentive effect of tax preference on their material benefits.

Innovation of tax incentives in the context of integration of traditional industries and digital economy

Applied Mathematics and Nonlinear Sciences

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

With the development of the digital economy, the innovation of the tax preference method is necessary. This paper integrates traditional industries with the...

Innovation of tax incentives in the context of integration of traditional industries and digital economy

Publié en ligne: 07 oct. 2023

Pages: -

Reçu: 11 déc. 2022

Accepté: 17 avr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00517

Mots clés
Tax innovation mechanism, Fuzzy comprehensive evaluation, Full factor algorithm, Q-value

© 2023 Wei Chen et al., published by Sciendo

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

Innovation of tax incentives in the context of integration of traditional industries and digital economy

Publié en ligne: 07 oct. 2023

Pages: -

Reçu: 11 déc. 2022

Accepté: 17 avr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00517

Mots clésTax innovation mechanism, Fuzzy comprehensive evaluation, Full factor algorithm, Q-value

© 2023 Wei Chen et al., published by Sciendo

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

Mots clés
Tax innovation mechanism, Fuzzy comprehensive evaluation, Full factor algorithm, Q-value