English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This study uses a network data envelopment analysis (DEA) approach to measure phased innovation efficiency to explore how fiscal technology innovation policy drives the development of regional innovation. A game model is constructed that includes governments, enterprises, universities, and research institutes to explain the influence mechanism. The innovation process is decomposed into the transformation stage of scientific research results and their commercial application. A Tobit model is used to explain the effect of fiscal policy on innovation efficiency. These methods led to novel conclusions: (1) the growth rate of innovation efficiency in the first stage is greater with smaller regional differences, with larger regional differences in innovation efficiency in the second stage; (2) the intensity of fiscal R&amp;D funding in science and technology has a significant positive effect on overall innovation efficiency and phased innovation efficiency; and (3) the positive effect of fiscal R&amp;D funding is greater on the commercial application of scientific achievements. The targeting effect of fiscal innovation policy on industry–university research (IUR) cooperation needs to be improved through resource sharing, joint participation, sharing of achievements, and risk sharing.

Driving effect of fiscal policy on regional innovation efficiency