Driving digital innovation through quality incentives: Evidence from Chinese cities in the digital transformation era

The digital era has fundamentally reshaped the innovation landscape. Contextually, quality incentive policies have gained prominence as pivotal instruments for driving technological advancement. This study investigates the causal impact of government quality incentives (GQI) on urban digital innovation (UDI) in China, exploiting the introduction of quality awards as a quasi-natural experiment. Drawing on panel data from 278 cities between 2000 and 2020, the analysis employs difference-in-differences, mediation, and threshold models. Our results show that GQI significantly propels UDI. Heterogeneity analysis reveals that this effect was most robust in the eastern and central regions, in cities with low digital attention, and in those with relatively developed economies. Crucially, the local GQI exerts positive spatial spillovers, fostering digital innovation in geographically and economically proximate areas. The mechanism analysis indicates that GQI promotes UDI by bolstering digital infrastructure and industrial upgrading. Additionally, a double-threshold effect of intellectual property protection (IPP) is identified, indicating a non-linear relationship between IPP and policy effectiveness. These findings provide empirical evidence for leveraging quality incentives for digital transformation in developing economies.

Authors

Institutions

Publication Details

Journal
Journal of Innovation & Knowledge
Published
2026-02-21
DOI
https://doi.org/10.1016/j.jik.2026.100994
Primary Topic
Innovation Policy and R&D
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Driving digital innovation through quality incentives: Evidence from Chinese cities in the digital transformation era

Wenfan Qian, Han Zhang
Journal of Innovation & Knowledge
Innovation Policy and R&D
article

Driving digital innovation through quality incentives: Evidence from Chinese cities in the digital transformation era

Wenfan Qian, Han Zhang
article en

Abstract

The digital era has fundamentally reshaped the innovation landscape. Contextually, quality incentive policies have gained prominence as pivotal instruments for driving technological advancement. This study investigates the causal impact of government quality incentives (GQI) on urban digital innovation (UDI) in China, exploiting the introduction of quality awards as a quasi-natural experiment. Drawing on panel data from 278 cities between 2000 and 2020, the analysis employs difference-in-differences, mediation, and threshold models. Our results show that GQI significantly propels UDI. Heterogeneity analysis reveals that this effect was most robust in the eastern and central regions, in cities with low digital attention, and in those with relatively developed economies. Crucially, the local GQI exerts positive spatial spillovers, fostering digital innovation in geographically and economically proximate areas. The mechanism analysis indicates that GQI promotes UDI by bolstering digital infrastructure and industrial upgrading. Additionally, a double-threshold effect of intellectual property protection (IPP) is identified, indicating a non-linear relationship between IPP and policy effectiveness. These findings provide empirical evidence for leveraging quality incentives for digital transformation in developing economies.

Journal of Innovation & KnowledgeVol. 15
Qingdao University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 50%
Innovation Policy and R&D
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.