Search Results (162)

This research examines the shifting geography of small firm innovation in the U.S. by tracking the location of small business innovation research (SBIR) and small business technology transfer (STTR) awardees between 2010 and 2024. The SBIR and STTR are “seed fund” awards coordinated by the Small Business Administration (SBA) and funded through 11 U.S. federal agencies. Of particular interest is whether the number of individual SBA awards, awarded firms, and/or funding amounts are (1) becoming increasingly concentrated within regional innovation hubs and (2) exhibiting a shift toward or away from urban centers and other walkable, transit-accessible urban neighborhoods, particularly since 2020 and the COVID-19 pandemic. While the rise of remote work and pandemic-related fears may have reduced the desirability of urban spaces for both living and working, there remain significant benefits to spatial agglomeration that may be especially crucial for startups and other small firms in the knowledge- or information-intensive industries. The results suggest that innovative activity of smaller firms has indeed trended toward more centralized, denser, and walkable urban areas in recent years while also remaining fairly concentrated within major metropolitan innovation hubs. The pandemic appears to have resulted in a measurable, though potentially short-lived, cessation of these trends. Full article

The COVID-19 pandemic has highlighted critical vulnerabilities in urban logistics systems, particularly in last-mile delivery. To enhance logistics resilience and efficiency, the Korean government has initiated an innovative project that repurposes idle spaces in subway vehicle bases within the Seoul Metropolitan Area into logistics centers. This study proposes a comprehensive multi-criteria evaluation framework combining the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess the suitability of ten candidate sites. The evaluation criteria span four dimensions, facility, geographical, environmental, and social factors, derived from the literature and expert consultations. AHP results indicate that geographical factors, especially proximity to urban centers and major logistics facilities, hold the highest weight. Based on the integrated analysis using TOPSIS, the most suitable locations identified are Sinnae, Godeok, and Cheonwang. The findings suggest the strategic importance of aligning infrastructure development with spatial accessibility and stakeholder cooperation. Policy implications include the need for targeted investment, public–private collaboration, and sustainable logistics planning. Future research is encouraged to incorporate dynamic data and consider social equity and environmental impact for long-term urban logistics planning. Full article

The micro-scale interplay between the built environment and innovation has attracted increasing scholarly attention. However, discussions on how such microdynamics operate and vary across high-density cities remain insufficient. This study focuses on nine high-density urban centres along the G60 S&T Innovation Valley and employs a fine-grained grid unit, viz. 1 km × 1 km, combined with the gradient boosting decision tree (GBDT) model to address these issues. Results show that urban construction density-related variables, including the building density, floor area ratio, and transportation network density, generally rank higher than the amenity density and proximity-related variables. The former contributes 50.90% of the total relative importance in predicting invention patent application density (IPAD), while the latter two contribute 13.64% and 35.46%, respectively. Threshold effect analysis identifies optimal levels for enhancing IPAD. Specifically, the optimal building density is approximately 20%, floor area ratio is 5, and transportation network density is 8 km/km². Optimal distances to universities, city centres, and transportation hubs are around 1 km, 17 km, and 9 km, respectively. Furthermore, significant city-level heterogeneity was observed: most density-related variables consistently have an overall positive association with IPAD, with metropolitan cities (e.g., Hangzhou and Suzhou) exhibiting notably higher optimal values compared to medium and small cities (e.g., Xuancheng and Huzhou). In contrast, the threshold effects of proximity-related variables on IPAD are more complex and diverse. These findings offer empirical support for enhancing innovation in high-density urban environments. Full article

This study focuses on the Triangle of Central China and investigates the spatiotemporal evolution, driving factors, and impacts of population aging on regional sustainable development from 2000 to 2020. The study adopts an innovative two-scale analytical framework at the prefecture and district/county level, integrating spatial autocorrelation analysis, the Geodetector model, and geographically weighted regression. The results show a significant acceleration in population aging across the study area, accompanied by pronounced spatial clustering, particularly in western Hubei and the Wuhan metropolitan area. Over time, the spatial distribution has evolved from a relatively dispersed pattern to one of high concentration. Key drivers of the spatial heterogeneity of aging include economic disparities, demographic transitions, and the uneven spatial allocation of public services such as healthcare and education. These aging patterns profoundly affect the region’s potential for sustainable development. Accordingly, the study proposes a multi-scale collaborative governance strategy: At the prefecture level, efforts should focus on promoting the coordinated development of the silver economy and optimizing the spatial redistribution of healthcare resources; At the district and county level, priorities should include strengthening infrastructure, curbing the outflow of young labor, and improving access to basic public services. By integrating spatial analysis techniques with sustainable development policy recommendations, this study provides a basis for scientifically measuring, understanding, and managing demographic transitions. This is essential for achieving long-term socioeconomic sustainability in rapidly aging regions. Full article

The growing global demand for energy has resulted in a demand for innovative strategies for residential energy management. This study explores a novel framework—MELISSA (Modern Energy LLM-IoE Smart Solution for Automation)—that integrates Internet of Things (IoT) sensor networks with Large Language Models (LLMs) to optimize household energy consumption through intelligent automation and personalized interactions. The system combines real-time monitoring, machine learning algorithms for behavioral analysis, and natural language processing to deliver personalized, actionable recommendations through a conversational interface. A 12-month randomized controlled trial was conducted with 100 households, which were stratified across four socioeconomic quintiles in metropolitan areas. The experimental design included the continuous collection of IoT data. Baseline energy consumption was measured and compared with post-intervention usage to assess system impact. Statistical analyses included k-means clustering, multiple linear regression, and paired t-tests. The system achieved its intended goal, with a statistically significant reduction of 5.66% in energy consumption (95% CI: 5.21–6.11%, $p<0.001$) relative to baseline, alongside high user satisfaction (mean = 7.81, SD = 1.24). Clustering analysis ($k=4$, silhouette = 0.68) revealed four distinct energy-consumption profiles. Multiple regression analysis ($R^2=0.68$, $p<0.001$) identified household size, ambient temperature, and frequency of user engagement as the principal determinants of consumption. This research advances the theoretical understanding of human–AI interaction in energy management and provides robust empirical evidence of the effectiveness of LLM-mediated behavioral interventions. The findings underscore the potential of conversational AI applications in smart homes and have practical implications for optimization of residential energy use. Full article

This study systematically reviews the development and application of remote sensing technology in monitoring and evaluating urban heat island (UHI) effects. The urban heat island effect, characterized by significantly higher temperatures in urban areas compared to surrounding rural regions, has become a widespread environmental issue globally, with impacts spanning public health, energy consumption, ecosystems, and social equity. The paper first analyzes the formation mechanisms and impacts of urban heat islands, then traces the evolution of remote sensing technology from early traditional platforms such as Landsat and NOAA-AVHRR to modern next-generation systems, including the Sentinel series and ECOSTRESS, emphasizing improvements in spatial and temporal resolution and their application value. At the methodological level, the study systematically evaluates core algorithms for land surface temperature extraction and heat island intensity calculation, compares innovative developments in multi-source remote sensing data integration and fusion techniques, and establishes a framework for accuracy assessment and validation. Through analyzing the heat island differences between metropolitan areas and small–medium cities, the relationship between urban morphology and thermal environment, and regional specificity and global universal patterns, this study revealed that the proportion of impervious surfaces is the primary driving factor of heat island intensity while simultaneously finding that vegetation cover exhibits significant cooling effects under suitable conditions, with the intensity varying significantly depending on vegetation types, management levels, and climatic conditions. In terms of applications, the paper elaborates on the practical value of remote sensing technology in identifying thermally vulnerable areas, green space planning, urban material optimization, and decision support for UHI mitigation. Finally, in light of current technological limitations, the study anticipates the application prospects of artificial intelligence and emerging analytical methods, as well as trends in urban heat island monitoring against the backdrop of climate change. The research findings not only enrich the theoretical framework of urban climatology but also provide a scientific basis for urban planners, contributing to the development of more effective UHI mitigation strategies and enhanced urban climate resilience. Full article

In advanced countries such as the USA and China, some cities are characterized by “knowledge spillover industries”, which play crucial roles in driving innovation, entrepreneurship, and economic growth. However, the excessive expansion of megacities in China has led to the overabsorption of labour from other cities. The unchecked growth of individual megacities causes metropolitan malaise and regional imbalance, further limiting the emergence of new “knowledge spillover” cities, which is detrimental to overall economic development. This study analyses China’s employment population structure to identify the critical population size required for the formation of “knowledge spillover” cities. The results show that 10 million is the unique threshold for which cities with populations above this size see a significant improvement in the prominence of “knowledge spillover” industries. Therefore, a population base of approximately 10 million is essential for these cities to thrive. This result suggests that China should pay more attention to the construction of urban agglomerations as geographic or administrative units to better distribute resources and promote balanced regional development. This approach can help foster the emergence of more “knowledge spillover” cities, thereby enhancing national innovation capacity and economic growth. Full article

Smart city research often emphasises technology while neglecting how governance structures and resources influence outcomes. This study compares Tier 1 (Sydney, Melbourne, Brisbane, Adelaide) and Tier 2 (Geelong, Newcastle, Hobart, Sunshine Coast) Australian cities to evaluate how urban scale, economic capacity, governance complexity, and local priorities influence smart-enabled resilience. We analysed 22 official strategy documents using a two-phase qualitative approach: profiling each city and then synthesising patterns across technological integration, community engagement, resilience objectives and funding models. Tier 1 cities leverage extensive revenues and sophisticated infrastructure to implement ambitious initiatives such as digital twins and AI-driven services, but they encounter multi-agency delays and may overlook neighbourhood needs. Tier 2 cities deploy agile, low-cost solutions—sensor-based lighting and free public Wi-Fi—that deliver swift benefits but struggle to scale without sustained support. Across the eight cases, we identified four governance archetypes and six recurring implementation barriers—data silos, funding discontinuity, skills shortages, privacy concerns, evaluation gaps, and policy changes—which collectively influence smart-enabled resilience. The results indicate that aligning smart technologies with governance tiers, fiscal capacity, and demographic contexts is essential for achieving equitable and sustainable outcomes. We recommend tier-specific funding, mandatory co-design, and intergovernmental knowledge exchange to enable smaller cities to function as innovation labs while directing metropolitan centres towards inclusive, system-wide transformation. Full article

Urban interstices are transitional spaces that emerge between expanding metropolitan regions. Despite increasing scholarly interest, the empirical analysis of these cities’ spatial development and functional integration remains scarce, particularly within the contexts of state-led urbanization, where administrative boundaries significantly shape development outcomes. This study quantitatively investigates urban interstice dynamics through a detailed analysis of Jurong City, which is located between the cities of Nanjing and Zhenjiang in the Chinese Yangtze River Delta. Utilizing mobile phone signaling data and origin–destination (OD) flow analysis, this research study systematically measures the intensity, directionality, and spatial patterns of human mobility flows between Jurong and its neighboring cities. The findings demonstrate that Jurong has a strong functional connection to Nanjing, with nearly 60% of its outbound mobility directed toward the city, despite being governed by Zhenjiang. This misalignment reveals a structural tension between functional integration and administrative hierarchy, fostering distinct subcenters such as Baohua (residential) and Guozhuang (innovation). Overall, the findings highlight the need to move beyond territorially bounded governance toward functionally coordinated regional strategies. Urban interstices can serve as effective connectors across fragmented systems, supporting more balanced and adaptive metropolitan integration. Leveraging real-time mobility data enables planners to identify spatial–functional linkages that transcend administrative boundaries, informing more responsive governance without requiring formal realignment. Full article

Nature-based solutions (NBSs) offer a promising framework for addressing urban environmental challenges while also enhancing social and economic resilience. As cities seek to achieve carbon neutrality, the integration of NBSs with renewable energy sources (RESs) presents both an opportunity and a challenge, requiring an interdisciplinary approach and an innovative planning strategy. This study aims to explore potential ways of achieving synergies between NBSs and RESs to contribute to urban resilience and climate neutrality. Focusing on the railway station district in western Thessaloniki (Greece), this research is situated within the ReGenWest project, part of the EU Cities Mission. This study develops a comprehensive, well-structured framework for integrating NBSs and RESs, drawing on principles of urban planning and energy systems to address the area’s specific spatial and ecological characteristics. Using the diverse typologies of open spaces in the district as a foundation, this research analyzes the potential for combining NBSs with RESs, such as green roofs with photovoltaic panels, solar-powered lighting, and solar parking shaders, while assessing the resulting impacts on ecosystem services. The findings reveal consistent benefits for cultural and regulatory services across all interventions, with provisioning and supporting services varying according to the specific solution applied. In addition, this study identifies larger-scale opportunities for integration, including the incorporation of NBSs and RESs into green and blue corridors and metropolitan mobility infrastructures and the development of virtual power plants to enable smart, decentralized energy management. A critical component of the proposed strategy is the implementation of an environmental monitoring system that combines hardware installation, real-time data collection and visualization, and citizen participation. Aligning NBS–RES integration with Positive Energy Districts is another aspect that is stressed in this paper, as achieving carbon neutrality demands broader systemic transformations. This approach supports iterative, adaptive planning processes that enhance the efficiency and responsiveness of NBS–RES integration in urban regeneration efforts. Full article

A business-continuity plan is crucial in providing an organization with the ability to maintain operations against possible risks. Therefore, companies should consider holistic risk management to sustain their activities and enhance their capabilities. Also, sustainability is able to eliminate the number of adverse environmental effects and increase the financial and social performance of a company. The purpose of this paper is to evaluate the sustainability and risk performance pillars for logistics networks, including a business-continuity plan. For this particular aim, this study considers the ten main criteria and sixty-six sub-criteria to evaluate sustainability and risk performances in logistics operations when dealing with a business-continuity plan under uncertainty. A novel and innovative four-phased integrated procedure involving a fuzzy-based AHP method with novel linguistic scales and operators is proposed. The TOPSIS technique, part of the integrated technique, is also presented to rank the alternative cities for an urban logistics network analysis. Moreover, the criteria of transportation and information infrastructures are analyzed for logistics operations. A case study of the thirty metropolitan cities in Türkiye is conducted to determine the best logistics center for a logistics firm. Several scenario analyses are performed, and a comparison study is also carried out from the literature. This study comprehensively analyzes the problem, including sustainability, risks, renewable energy and social aspects. Based on the results from the fuzzy-based AHP method, economic, safety and hazard risk are the top three main criteria. Moreover, Istanbul, Konya and Ankara are the top three alternatives for logistic networks from the results of the TOPSIS technique. Finally, managerial and policy implications are presented for policy-makers who should pay attention to the main criteria and sub-criteria in this paper for successful logistics operations dealing with the business-continuity plan when achieving Sustainable Development Goals. Full article

Green technological innovation is pivotal in advancing the ‘dual carbon’ target and promoting sustainable and low-carbon development. This research examines 17 prefecture-level cities in Hubei Province, employing the Super-SBM model for assessing emissions of carbon efficiency from 2010 to 2020. The kernel density estimation and the Dagum coefficient of Gini are also used to examine the spatio-temporal differentiation and the evolution of these efficiencies. A data panel regression model is utilized to evaluate how green technological innovation impacts carbon emission efficiency in Hubei Province. The research revealed that (1) Hubei Province’s carbon emission efficiency first fluctuated and then increased rapidly, and (2) the overall regional difference in carbon emission efficiency in Hubei Province shows a trend of first decreasing and then gradually increasing. The Wuhan metropolitan area and the Xiang-yang-Shiyan-Suizhou-Shennongjia urban area are quite different; the differentiation within the Yichang-Jingzhou-Jing-Enshi urban agglomeration shows a narrowing trend. (3) The innovation elements of green technology are positively correlated with the effectiveness of carbon emissions; the relationship between economic expansion and population density among the control variables also shows a positive correlation, while the industrial structure and government environmental regulations are negatively correlated. (4) In Hubei Province, there is a temporal lag between green technological innovation and its impact on carbon emission efficiency. Capital investment and technical achievement currently enhance carbon emission efficiency, while human capital positively affects carbon emission efficiency during a second lag period. This article proposes countermeasures and recommendations for R&D capital spending, innovative talent cultivation, and regional differentiation, providing specific references to advance the coordinated growth of the whole Hubei Province and green sustainable development. Full article

The Yangtze River Delta region is facing the demand for high-quality economic development, and the study of urban network as a manifestation of the interaction between cities is becoming increasingly important. This study focused on the node structure of the urban network in the Yangtze River Delta urban agglomeration from 2010 to 2021, used the modified gravity model to construct a polycentric city network from the perspective of economic flow, used the spatial Durbin model for spatial econometric analysis, and identified the conduction path through the two-step method of causal stepwise regression mediating effect test. The results show that Shanghai, as the core node city, has significantly promoted the economic development of Hangzhou, Nanjing, Hefei, and other cities and formed a metropolitan network structure characterized by “one core and five circles”. Under different spatial weight matrices, the polycentric city network has a significant positive impact on economic growth, and its impact is not only related to the economic level of the city itself but also closely related to the economic status of its neighboring cities. The polycentric city network significantly enhances economic growth by accelerating the flow of regional factors, promoting regional industrial division of labor and cooperation, and enhancing regional innovation capabilities. Full article

This paper presents a case study of Fog Computing, Edge Computing (EC) and Intelligent EC applied to Smart Buildings, focusing on the deployment of innovative services and smart IoT devices, discussing new architecture as Software-Defined Network (SDN). Specifically, a comprehensive solution of a Smart Building case is proposed to validate main statements and conclusions are drawn, providing a general guideline to address the problems of choosing between Edge or Fog Computing and the specific category of IoT devices. The methodology employed in this study is based on field research conducted in buildings within the metropolitan region of São Paulo, Brazil, that aim to enable their transformation into Smart Buildings (SBs). Moreover, principles of Electronic Systems Engineering and Cloud Computing such as reliability, scalability and security are applied. In that way, this study integrates advanced multimedia technical services to enhancing security and communication within the SBs through centralized control. The method focuses on identifying and analyzing the most common problems observed in field research within SBs in early stages of development, prior to the intensive implementation of IoT devices and Fog or Edge Computing technologies on the state of the art. The research adopts a comparative approach, investigating the best solutions for each application category. The results are consolidated in a main table within the article, correlating solutions to the four main problems identified in the field research, such as impairments in voice over IP and video communication using IoT devices; latency and delays in communication between SBs and the Cloud center; access security issues; and the Quality of Experience of video over IP communication, both in live transmissions and recordings between SBs. Regarding applications, this study considers the use of specific IoT devices and Cloud Computing architectures, such as Fog or IEC. Furthermore, it explores the implementation of new open network and communication models, such as SDN and NFV, to optimize communication between the various SBs and the SB’s connection to the control center of a Smart City. Full article

This extensive study examines the solar rooftop photovoltaic potential (RTP) over polluted cities in major geographic and economic zones of India. The study examines the climatology of solar radiation attenuation due to aerosol, clouds, architectural effects, etc. The study exploits earth observations from ground, satellite, and radiative transfer modeling (RTM) in conjunction with geographic information systems tools. The study exploits long-term observations of cloud properties from the Meteosat Second Generation (MSG) satellites operated by EUMETSAT and aerosol properties data gathered from ground-based measurements provided by AERONET. The innovation in the study is defined in two steps. Firstly, we estimated the RTP using the current state of the art in the field, which involved using suitability factors and energy output based on the PVGIS simulations and extrapolating these for effective rooftop areas of the cities. Secondly, we advanced beyond the current state of the art by incorporating roof morphological characteristics and various area share factors to assess the RTP in more realistic terms. These two steps were applied under two different scenarios. The study determined that the optimum tilt angle is equal to the cities’ latitude for installing solar PV systems. In addition, the research emphasizes the advantages for the environment while offering energy and economic losses. According to our findings, the RTP in the rural city examined in this study is 31% greater than the urban city of India under both scenarios. The research has found that the metropolitan city, which boasts a maximum rooftop area of approximately 167 km², could host a significant RTP of around 13,005 ± 1210.71 (6970 ± 751.38) MWh per year under scenario 1 (scenario 2). Overall, solar radiation losses due to aerosol effects dominate radiation losses due to cloud effects on the city scale. Amongst all polluted cities, estimated financial losses due to aerosols, clouds, and shadows are 11,241.70 million, 4439 million, and 1167.65 million rupees, respectively. Our findings emphasize the necessity of accounting for air pollution for accurate solar potential assessments in thoughtful city planning. The creative approach that utilizes publicly available data establishes a strong foundation for penetrating solar photovoltaic (PV) technology into society. This integration could significantly contribute to climate change mitigation and adaptation efforts, promoting environmentally sustainable urban development and prevention strategies. Full article