Urban Innovation Research Articles

Does the National Civilized City policy promote high-quality innovation? Evidence from a quasi-natural experiment in China

ABSTRACT High-quality innovation (HQI) is a crucial contributor to economic development, technological progress, and competitive advantages. This study uses China’s National Civilized City (NCC) policy as a quasi-natural experiment. By applying the difference-in-difference (DID) method to a sample of 284 prefecture-level cities from 2003 to 2022, we test the impact of the NCC policy on urban innovation. Our findings demonstrate that an NCC award significantly enhances the quality of urban innovation in a city, increasing HQI by 19.14% and decreasing low-quality innovation (LQI) by 10.01%. This improvement is robust yet temporary, gradually diminishing over 5 years post-selection. Our mechanism analysis reveals that NCC awards boost HQI by increasing fiscal science expenditure, public cultural services, and human capital accumulation and inhibit LQI by optimizing the human capital structure. The impact of the NCC policy is heterogeneous across economic scales and regions; improvements in HQI are more pronounced in larger cities and eastern regions of China, and the inhibition of LQI is stronger in central and western regions of China. Our study provides empirical evidence of the promoting effects of NCC awards on the quality of innovation. These findings offer valuable insights for policymakers in innovation-driven development and regional coordination.

Understanding the role of urban block morphology in innovation vitality through explainable machine learning

Innovative activities are a key driver of economic and social development, with urban blocks serving as essential hubs for innovation. However, how urban block morphology shapes innovation vitality remains challenging. This study uses spatial analysis and SHAP-based explainable machine learning to analyze how block morphology characteristics affect urban innovation vitality, taking Hangzhou, a typical city of digital innovation, as a sample. The findings show that: 1. Land use diversity, floor area ratio, and street network density are the most influential factors; 2. Block morphology exhibits nonlinear effects. For example, when street network density exceeds 200 m per square kilometer, its impact on innovation vitality is positive, but it diminishes beyond 400 m per square kilometer; 3. Synergistic effects are prevalent, such as when street network density exceeds 200 m per square kilometer and floor area ratio is between 0 and 7, enhancing innovation vitality. The results reveal the nonlinear effects and interaction mechanisms at the block scale. And also discusses potential planning strategies for different regions based on varying influencing factors. The study provides an effective approach to balancing precision and interpretability in spatial analysis and offers empirical support for the application of complexity science in urban studies.

Digitalization and urban carbon emissions: Unraveling the mechanisms of agglomeration economics.

Digitalization and urban carbon emissions: Unraveling the mechanisms of agglomeration economics.

Research on the Performance Evaluation of Urban Innovation Spaces: A Case Study in Harbin

Innovation has become a pivotal factor in driving economic growth for cities and regions. Urban innovation spaces are urban spaces where innovative economic and industrial activities, such as research, teaching, and high-tech manufacturing, are clustered. They have become hot research topics in recent years. Evaluating the performance of urban innovation spaces to promote rational resource allocation and enhance land development potential has become a critical task in urban planning. However, existing studies suffer from insufficient depth of research scales and a lack of quantitative indicators and data analysis. In response to the above gaps, this study constructed a framework for evaluating the performance of urban innovation spaces from 25 indicators of five major types, including core elements of innovation, entrepreneurship support institutions, service facilities, external environments, and diversities, aiming to quantify the performance heterogeneity of innovation spaces at the micro scale. This study took Harbin as an example and employed the entropy, kernel density estimation, and entropy-weighted TOPSIS methods, identifying four high-scoring areas of innovation spaces—the Science and Technology Innovation City area, the High-tech Industrial Development area, the core area of the old city, and the Harbin Veterinary Research Institute area—which were divided into three types: the Entrepreneurial leading area, Environmental Support area, and Balanced Development area. Finally, this study analyzed the interaction between each indicator. It was found that the correlation between the core elements of innovation and the indicators of entrepreneurship support institutions was strong and had a high degree of importance. The correlation of different types of service facility indicators is quite different, and the external environment indicators and diversity indicators are mainly affected by other indicators, especially the core elements of innovation and entrepreneurship support institutions. This paper provides a valuable tool for the performance evaluation of urban innovation spaces for researchers and urban planning decision makers.

Spatio-temporal synergies of digital economy and green finance: Catalyzing green low-carbon transition in the Yangtze River Delta Region.

Spatio-temporal synergies of digital economy and green finance: Catalyzing green low-carbon transition in the Yangtze River Delta Region.

How does new infrastructure affect urban innovation? A spatial spillover perspective

ABSTRACT Moderately ahead of schedule layout and construction of new infrastructure (NI) is an important hand in grasping the opportunities of accelerated maturity of emerging technologies and industries in the current and future periods. This study explores the spatial spillover mechanism of NI on urban innovation (UI) by using the panel data of the Yangtze River Economic Belt from 2008 to 2021. The results are as follows: First, NI has a positive spatial spillover effect on UI. Second, the spillover effect of NI exhibits a geographic decay, with the strongest spillover effect between neighbouring cities and no spillover effect between cities in different provinces. Third, industrial agglomeration is a key factor influencing the spatial causality between NI and UI. Among them, diversified agglomeration and specialised agglomeration of information infrastructure have positive moderating effect on the spatial causality between NI and UI, specialised agglomeration of convergence infrastructure has negative moderating effect, and the moderating effect of specialised agglomeration of innovation infrastructure is not yet obvious. Fourth, the spillover effect of NI is released only at high UI levels or in the lower and upper reaches of the Yangtze River.

Re-examination of urban innovation and its evolution in China: technological complexity and diversity as new perspectives

ABSTRACT This study employs a non-linear iteration methodology to establish a set of indicators, namely technological complexity and innovation complexity, respectively for evaluating patent quality and the cities’ innovation competitiveness. Using Chinese invention patent application data spanning from 2003 to 2020 as a case study, we reassess the innovation competitiveness in Chinese prefecture-level cities and investigate the spatiotemporal evolution of city innovation from the perspectives of technological diversity and technological complexity. Results show: (1) During the study period, overall technological innovation in Chinese cities increased. However, notable heterogeneity was observed among cities in different urban clusters. (2) Technological diversity, indicating innovation breadth, proves less effective than innovation complexity, typically associated with innovation depth, when assessing the cities’ innovation competitiveness, especially for advanced cities. (3) Increased technological innovation in Chinese cities was associated with greater technological diversity and, more importantly, technological complexity enhancement. Nevertheless, noteworthy heterogeneity in technological innovation trajectories existed among cities: Innovation-advanced cities progressively shifted their focus from technological diversity to technological fields characterised by higher complexity, demonstrating a ‘narrow and deep’ tendency. In contrast, innovation-lagging cities tended to focus on technological diversity in fields with lower technological complexity, that is, emphasising innovation breadth rather than depth. List of Abbreviations: TC: Technological Complexity, TD: Technological Diversity, IC: Innovation Complexity, RPA: Relative Patent Advantage

How China’s urban innovation system promotes green finance via FinTech: a connectivity view

ABSTRACT This research focuses on the connectivity perspective of China’s urban innovation system (UIS), and deeply analyzes how UIS can promote the development of green finance (GF) through FinTech. FinTech is examined as a key example of the coevolution of technological and financial innovations, while GF serves as a critical mechanism for achieving inclusive growth. A qualitative study was first conducted to pre-test the assumptions, and then a quantitative study was carried out based on secondary data of 285 Chinese cities. The findings demonstrate that UIS positively influences FinTech development. Furthermore, the results confirm both the mediating role of FinTech and the moderating effect of NIS pilot policy on the relationship between FinTech and GF. Our analysis also highlights regional disparities in the impact of UIS on GF. Theoretically, this research expands the NIS paradigm by identifying UIS as a crucial subsystem within the broader NIS framework, one that drives GF through the synergy of technological and financial innovations. From a practical perspective, our research, with its focus on China, provides valuable policy recommendations for efforts to balance regional connectivity across countries.

Digital Economy: The Engine of Public Service Efficiency

Enhancing public service efficiency is crucial for the Chinese government to ensure sustainable economic development. This study compiles data from 288 cities in China from 2011 to 2022 to construct an evaluation framework for the digital economy and public service efficiency. It also develops relevant econometric models to examine their impacts and underlying mechanisms. The results show that the digital economy significantly boosts local public service efficiency, with a more pronounced effect in cities with high or low initial efficiency levels and a less pronounced effect in those with moderate efficiency. The positive moderating roles of the political environment, government autonomy, urban innovation capacity, and social attention are also observed. This study suggests that local governments develop adaptive digital roadmaps to promote the digital economy and enhance public service efficiency. These findings enrich our understanding of how the digital economy influences public service efficiency and offer valuable insights for enhancing public service efficiency.

The impact of urban innovation on migrant settlement: Evidence from China

The impact of urban innovation on migrant settlement: Evidence from China

Emergence of a novel drinking innovation in an urban population of sulphur-crested cockatoos, Cacatua galerita.

The spread of innovation has been proposed as a potentially important source of adaptive behavioural responses to anthropogenic change. Yet, while a diversity of urban innovations have been documented in animals, there are relatively few examples of these spreading to form local traditions. One notable example is the 'bin-opening innovation' in sulphur-crested cockatoos (Cacatua galerita), where individuals open household bin lids to access food waste, with this behaviour spreading across southern Sydney, Australia. Here, we describe a second innovation in this species, the 'drinking-fountain innovation'. Individuals from a population in western Sydney drink from twist-handle public drinking fountains, with this behaviour persisting over at least 2 years. Successful operation requires a coordinated sequence of actions, with only 41% of observed attempts ending in success. Intensive observation at one drinking fountain over 44 days revealed 525 attempts and 46% of marked individuals successfully engaging in the behaviour, with individuals visiting at dawn and dusk in line with expectations for use of a water resource. Public drinking fountains vary in design between local councils but are generally widespread. Yet, to our knowledge, this behaviour has not been observed elsewhere. Altogether, this suggests that this drinking innovation has spread to form a new urban-adapted local tradition.

The role of FinTech in shaping urban innovation: A study of financial markets from the perspective of the patent renewal model

The role of FinTech in shaping urban innovation: A study of financial markets from the perspective of the patent renewal model

Spatial differences and formation mechanisms of innovation ecosystem dynamic operational efficiency along the yellow river

To scientifically evaluate the dynamic operational efficiency, spatial differences, as well as the formation mechanisms of the urban Innovation Ecosystem within the Yellow River Basin is highly important for the high-quality development of China. In the present research, both the economic circulation theory with the Innovation Ecosystem and the Data Envelopment Analysis – Malmquist Productivity Index (DEA-Malmquist) model were adopted to analysis the database from 59 cities along the Yellow River Basin. In parallel, the kernel density estimation, the Gini coefficient, and Panel Vector Autoregression (PVAR) model were applied for further comparison. The results revealed that the dynamic operational efficiency of the Innovation Ecosystem within the Yellow River Basin exhibited an obvious fluctuating downwards trend. The efficiency of spatial distribution in the upstream and midstream basins shows a left-skewed and polarized pattern, whereas the downstream basins exhibited a right-skewed distribution with less pronounced polarization. The results also revealed that the overall Gini coefficients for dynamic operational efficiency (TFP) and technical efficiency (EFF) in the Yellow River Basin tended to convergence, whereas those for technological change (TECH) are of an increasing trend. Moreover, the hypervariable density emerged as the primary factor driving disparities in TFP, TECH, and EFF within the basin. Furthermore, the relationships among TFP, TECH, and EFF were featured with the regional heterogeneity. In the midstream areas, there existed a self-improvement mechanism for the TFP, TECH, as well as the EFF. However, there was a stronger self-improvement mechanism for TECH but a self-weakening mechanism for TFP and EFF in the downstream regions.

Do Spatial Spillovers of Technology Transfer Networks Impact Urban Innovation Capacity? Evidence from Chinese Cities

As the flow of innovation elements breaks through geographical boundaries, patent transfer and the resulting spatial knowledge spillovers have become a crucial pathway for cities to enhance their competitive advantages and foster collaborative innovation. This study crawls technology transfer data through Big Data mining and uses social network analysis to construct an intercity technology transfer network among 286 Chinese cities at the prefecture-level and above between 2000 and 2020. The study explores the influence of technology transfer networks and their spatial spillovers on urban innovation capacity. The results are as follows: (1) Moran’s I results indicate that technology transfer and innovation activities among Chinese cities exhibit significant spatial dependence. (2) The Markov chain analysis reveals that the technology transfer networks among Chinese cities exhibit significant spatial spillovers. (3) Spatial econometric analysis and effect decomposition demonstrate that technology transfer networks exhibit significant spatial dependence and spillover effects. Through the induced spatial knowledge spillovers, technology transfer networks contribute to enhancing the innovation capabilities of neighboring cities.

Smart Cities and the Rural-Urban Divide in Moldova: Balancing Innovation and Tradition

As Moldova advances its smart city initiatives, supported by the EU4Moldova: Focal Regions programme, the country faces both opportunities and challenges in balancing urban innovation with rural traditions. This article explores the impact of digital transformation on Moldova’s urban-rural divide, focusing on the smart city projects in Cahul and Ungheni. These projects, financed by the European Union and implemented by UNDP and UNICEF, include upgrading water supply and waste disposal systems, streamlining public transport, and introducing intelligent public lighting and resource management systems. While these advancements bring significant benefits to urban areas—enhanced governance, improved services, and sustainable infrastructure—rural regions risk being left behind due to limited access to these digital resources. Thus, the digital divide remains a pressing issue as Moldova works to ensure that rural populations also benefit from technological progress. This article critically examines how smart initiatives can bridge the rural-urban divide, integrating rural communities into the digital transformation while preserving cultural traditions. It highlights the importance of public-private partnerships, community involvement, and inclusive policy-making to ensure that Moldova’s digital future benefits all citizens, both urban and rural. This research serves as a foundation for future empirical studies to deepen understanding of these dynamics and guide policymakers in designing effective, inclusive smart city and smart village strategies.

Análisis del enfoque social sostenible de la tecnología emergente Movilidad Aérea Urbana

Urban Air Mobility is an emerging air transport technology whose purpose is to transport passengers and freight at urban, interurban, and regional levels using aerial vehicles capable of vertical takeoff and landing, mostly powered by electric propulsion. This disruptive technology is not only an element of the advancement of aviation technologies but also a pillar of future mobility planning and urban development. To this end, Urban Air Mobility can play a prominent role in shaping urban innovation and sustainable mobility transition strategies. This article, a general thematic review that uses systematic mapping as its methodology, analyzes the sustainable approach to the future development of Urban Air Mobility in cities. However, the concept of sustainability goes far beyond the purely environmental, also considering the social dimension of the concept and considering the entire product/service lifecycle of this emerging technology. At the results level, it is highlighted that the analysis presented here proposes the development of a sustainability framework for Urban Air Mobility that would provide guidelines to support the assessment of environmental, social and economic impacts of this emerging technology, where Life Cycle Assessment would play a key role.

How AI policies influence urban innovation in China: analysis based on feature extraction and fsQCA

PurposeThis study aims to understand the patterns that characterize the impact of artificial intelligence (AI) policies on urban innovation performance, and reveal how these patterns vary across different regions, thereby helping AI policy-making and promoting the urban innovation.Design/methodology/approachThis research focuses on how AI policies influence innovation using the city as unit of analysis. AI policy and patent data were collected from 156 Chinese cities over a decade. Coding and machine learning methods were applied to extract policy features, including three types of policy instruments, policy continuity, policy intensity, and policy count. The fuzzy set Qualitative Comparative Analysis (fsQCA) method is used to identify patterns that explain how AI policies influence urban innovation performance and to further explore regional differences.FindingsComparing four models for extracting policy instruments, ERNIE 3.0 has been proven to be the most accurate and effective model. Three patterns are found using fsQCA: the environment-safeguard, demand-pull, and supply-environment-demand triple-drive patterns. Moreover, these patterns reflect the development distinction of the eastern, middle, and western cities, respectively. Hence, governments should focus on the intricate interplay and synergistic application of multiple policy levers, and enhance creativity in policy formulation based on their specific developmental characteristics.Originality/valueThis research analyzed the patterns that AI policies influence urban innovation from the national and regional perspective. Automated methods were introduced for policy feature extraction, particularly in identifying policy instruments, thereby significantly cutting down on labor and enhancing the efficiency of data analysis. Besides, this research highlights the interplay among various factors, utilizing fsQCA to reveal the collaborative dynamics at work, which compensates for the deficiency of independent assumptions in regression analysis, and analyze the synergistic effects of different factors from a systematic perspective.

Digital Urbanism: AI, IoT, and Blockchain for the Future of Sustainable Smart Cities

Abstract: This research paper explores the transformative convergence of artificial intelligence (AI), the Internet of Things (IoT), and blockchain technology in shaping the next generation of sustainable smart cities. As urban areas face mounting challenges related to population growth, resource management, and environmental sustainability, digital technologies are enabling data-driven governance, efficient infrastructure, and enhanced citizen engagement. The study examines how AI algorithms optimize urban services such as traffic management, energy distribution, and waste control; how IoT devices facilitate real-time monitoring and automation across city systems; and how blockchain ensures data integrity, security, and transparent transactions in urban ecosystems. Through case studies and system-level analysis, the paper highlights successful implementations and identifies best practices and future opportunities for integrating these technologies to create intelligent, resilient, and inclusive urban environments. Keywords: Smart cities, Digital urbanism, Artificial intelligence, Internet of Things, Blockchain, Sustainable development, Urban innovation, Data-driven governance, Intelligent infrastructure, Urban resilience, Real-time monitoring, Smart mobility, Energy efficiency, Urban automation, Secure data systems

How to enhance urban innovation? A coupling study of education- technology- talent focusing on China’s Silicon Valley

Human social activities involving education, technology, and talent are closely related to the innovation of a city, which are also important driving forces for sustainable urban development. Currently, there is a lack of tracking analyses of long-term development potential and drivers of urban innovation capacity. This research takes Hangzhou, China’s Silicon Valley, to study the drivers of urban innovation to achieve sustainability from the perspective of human innovative behavior. By building a comprehensive urban development evaluation framework for the integration development of education, technology and talent, this study uses the coupling coordination degree model to analyze the coupling development mechanism and core factors of urban innovation. It finds: (1) Hangzhou’s comprehensive development level of education, technology and talent has gone through three stages, namely steady growth, rapid growth, and slowing growth, presenting an overall upward trend. (2) The coupling coordination degree gradually improves, promoting a sustained increase in the comprehensive development index. (3) Using emerging digital industries and high-tech enterprises as channels, the deep integration and coordinated development of education, technology, and talent will promote urban innovation. This study focuses on the driving forces of urban innovation, contributing to the sustainability of urban development.

The impact of new quality productivity on carbon emission intensity: evidence from China

The new quality productivity, which integrates the concepts of technological innovation, industrial upgrading, and green development, plays a pivotal role in achieving carbon emission reduction targets. Given that current research on the relationship between new quality productivity and carbon emission intensity remains limited, in order to delve into the impact of new quality productivity on carbon emission intensity, its underlying mechanisms, as well as its heterogeneous performance across different regions and city types, we select panel data from 251 Chinese cities spanning from 2010 to 2021 and conduct an empirical analysis using a panel data two-way fixed-effects model. The research findings reveal that new quality productivity can significantly reduce carbon emission intensity. Further analysis demonstrates that new quality productivity can achieve a reduction in carbon emission intensity by enhancing urban innovation levels and the intensity of government environmental regulations. Moreover, the heterogeneity analysis indicates that, compared with other regions, the inhibitory effect of new quality productivity on carbon emission intensity is more pronounced in the western regions and non-resource-based city samples. This study not only enriches the relevant theories on the relationship between new quality productivity and carbon emissions but also provides a crucial basis for governments to formulate targeted carbon emission reduction policies. Based on this, this paper proposes that investment in areas related to new quality productivity should be increased, technological innovation and industrial upgrading should be promoted, and government environmental regulations should be strengthened. Particular attention should be paid to the development of the western regions and non-resource-based cities to give full play to the role of new quality productivity in carbon emission reduction.