Search Results (13)

This study examines the impact of the spatial flow of new quality productive forces (NQPFS) and the optimal combination of new quality productive forces (NQPFC) on the high-quality economic development (HQMED) of China’s coastal regions. Based on panel data from 53 coastal cities (2004–2023), the research constructs comprehensive evaluation systems and employs a two-way fixed effects model for empirical analysis. The main findings are as follows: First, Spatial Evolution: The HQMED level of coastal areas shows a continuous upward trend with marked regional disparities, forming a spatial pattern of “one core, two wings” characterized by “Eastern leadership with Northern and Southern regions following.” The inter-city development gap has widened, with the overall spatial structure evolving from a “core-periphery” model toward a clustered stage of “one core, multiple poles, and networked linkage.” Correspondingly, New Quality Productive Forces have transitioned from initial single-point agglomeration to a multi-polar and ultimately networked distribution. Second, both the spatial flow and optimal combination of New Quality Productive Forces exert stable positive effects on coastal HQMED. The marginal contribution of the factor optimal combination is significantly greater than that of spatial flow. Third, two complete mediation pathways are identified: NQPFS promotes HQMED primarily by enhancing the resilience of the marine industrial chain, while NQPFC drives HQMED mainly through cultivating new-quality marine business forms. Fourth, resource misallocation exerts a significant negative moderating effect on the relationship between NQPFS and HQMED. Conversely, a sound innovation ecosystem positively moderates the impact of NQPFC on HQMED. Fifth, the effects exhibit significant regional and institutional variation. Geographically, the impact follows a pattern of “strong in the East, suppressed in the North, and insignificant in the South.” Administratively, core cities demonstrate stronger factor capture and configuration efficiency compared to ordinary cities. The study confirms that facilitating the cross-regional flow and efficient internal recombination of the New Quality Productive Force is crucial for driving coastal HQMED. Policy should focus on reducing resource misallocation to remove barriers to factor mobility, optimizing regional innovation ecosystems to enhance factor synergy, and implementing differentiated strategies that balance the radiating role of core cities with the distinctive development of ordinary cities, thereby fostering a new, coordinated pattern of high-quality development across coastal regions. Full article

Based on micro-level job seeker data from 41 cities in China’s Yangtze River Delta, this study employs threshold regression to examine how inter-city distance influences talent mobility. The results reveal that distance exerts a negative impact on mobility intention and moderates the relationship between a destination’s economic level and mobility. Notably, significant threshold effects are identified at 164.1 km and 271.5 km, delineating three spatial regimes. Short-distance flows (<164.1 km) show the highest intensity, driven by strong economic incentives and high mobility. In contrast, medium-distance flows (164.1–271.5 km) prove least attractive due to offsetting effects, while long-distance flows (>271.5 km) rebound slightly as talent selectively targets major economic hubs, with distance exhibiting only weak inhibition. Crucially, these nonlinear patterns remain robust after addressing endogeneity concerns via the 2SLS method, substituting spatial distance with temporal distance, and controlling for housing prices and cultural factors. Heterogeneity analysis further indicates that individuals with bachelor’s degrees, those above age 30, and talent in labor-intensive industries exhibit greater sensitivity to distance. Conversely, knowledge-intensive sectors and top-tier economic cities demonstrate broader spatial tolerance and stronger cross-regional attraction capabilities. These findings provide a quantitative basis for developing differentiated regional talent policies. Full article

The global transition toward sustainable mobility and renewable energy integration demands intelligent energy management frameworks capable of coupling electric mobility, distributed generation, and energy storage. This study presents a comprehensive evaluation of the SIMA Project (Sistema Inteligente Multimodal da Amazônia), an innovative mobility pilot implemented at the Federal University of Pará, Brazil. The SIMA consists of the monitoring building, photovoltaic systems, lithium-based energy storage systems, and electric transportation modes (including urban and intercity buses, as well as a solar-powered catamaran), all interconnected within a microgrid. Field monitoring, data processing, and simulation analyses were conducted to assess energy performance, consumption patterns, and the operational feasibility of these electric systems under Amazonian conditions. The results indicate that the PV systems supply most of the SIMA’s demand, with the laboratory building accounting for 70% of total consumption and electric vehicles for 30%. Simulated full operation scenarios reveal the potential for near net-zero energy balance when energy management strategies are applied to generation, storage and charging. The findings demonstrate the technical viability of integrated mobility–energy systems in tropical contexts and provide practical insights for future low-carbon transport infrastructures in isolated or city-scale networks. Full article

Population mobility links cities, propelling the spatiotemporal spread of urban pandemics and adding complexity to disease dynamics. It also closely shapes, and is shaped by, the selection and intensity of intervention measures. Revealing the multistage spatial-temporal dynamics of cross-regional epidemic continuity under this interaction is often overlooked but critically important. This study innovatively applies a self-organizing map (SOM) neural network to classify cities into six distinct types based on population mobility characteristics: high-inflow core (HIC), low-inflow core (LIC), low-inflow sub-core (LISC), high-outflow semi-peripheral (HOSP), equilibrious semi-peripheral (ESP), and low-outflow peripheral (LOP). Building on this, we propose a novel SEIR-AHQ theoretical framework and construct an epidemiological model using network-coupled ordinary differential equations (ODEs). This model captures the dynamic interplay between inter-city population mobility and intervention measures, and quantifies how heterogeneous city types shape the evolution of epidemic transmission across the coupled mobility network. The results show that: (1) Cities with stronger population mobility face significantly higher infection risks and longer epidemic durations, characterized by “higher peaks and longer tails” in infection curves. HIC cities experience the greatest challenges, and LOP cities experience the least. (2) Both higher transmission rates and delayed intervention timings lead to exponential growth in infections, with nonlinear effects amplifying small changes disproportionately. (3) Intervention efficacy follows a “diminishing marginal returns” pattern, where the incremental benefits of increasing intervention intensity gradually decrease. This study offers a novel perspective on managing interregional epidemics, providing actionable insights for crafting tailored and effective epidemic response strategies. Full article

Travel policies during crises strongly reshape mobility patterns, raising the challenge of protecting public health while minimizing socio-economic disruption—an essential concern for sustainable development. Most evaluations quantify changes in travel volume, which hampers cross-city comparison and policy monitoring. This study proposes a distance-based sustainability metric—distance equivalence (DE)—that translates policy-induced mobility frictions into interpretable “added distance” within a gravity framework, enabling consistent measurement and monitoring of policy impacts. Using inter-city flows for 358 Chinese cities during the Stay-in-Place for Lunar New Year (SIP) guidance, we map DE, test spatial dependence (Moran’s I; LISA), and apply fuzzy-set Qualitative Comparative Analysis (fsQCA) to identify city-level configurations associated with high DE. DE exhibits significant spatial clustering, concentrating east of the Hu line, where dense urban networks amplify advisory checks. Three recurrent configurations—combining case counts, health-care capacity (hospital beds), and average inter-city distance—are linked to high DE. As a sustainability assessment tool, DE supports adaptive management, region-differentiated strategies, and ex-ante risk assessment for governments, public-health authorities, and transport agencies. The framework generalizes to short-term mobility interventions under crisis conditions, advancing the quantification of policy impacts on sustainable mobility and urban resilience. Full article

This study investigates the relationship between intercity transportation accessibility and network centrality across South Korea by integrating Global Positioning System (GPS)-based mobility data with graph-theoretic centrality measures, including degree, PageRank, local clustering coefficient, harmonic, Katz, and information centrality. Employing both statistical modeling and machine learning techniques, this analysis uncovers key structural patterns and interaction effects within the national mobility network. The findings yield several important insights. First, the Seoul Metropolitan Area emerges as the dominant mobility hub, with Busan, Daegu, and Daejeon functioning as secondary centers, reflecting a polycentric urban configuration. Second, intermediary transfer hubs—despite having lower direct connectivity—substantially enhance overall network efficiency and interregional mobility. Third, transportation accessibility, particularly in relation to regional transit and highway infrastructure, exhibits a significant association with centrality measures and strong feature importance, identifying these modes as primary determinants of spatial connectivity. Fourth, the impact of accessibility on centrality is characterized by nonlinear relationships and threshold effects. By elucidating the complex interplay between mobility infrastructure and spatial network dynamics, this study contributes to a more comprehensive understanding of regional connectivity and network centrality and offers policy-relevant insights for future transportation planning. Full article

Understanding the effectiveness of different quarantine strategies is crucial for controlling the spread of COVID-19, particularly in regions with limited data. This study presents a SCIRD-inspired model to simulate the transmission dynamics of COVID-19 in medium-sized cities and their surrounding satellite towns. Unlike previous works that focus primarily on large urban centers or homogeneous populations, our approach incorporates intercity mobility and evaluates the impact of spatially differentiated interventions. By analyzing lockdown strategies implemented during the first year of the pandemic, we demonstrate that short, localized lockdowns are highly effective in reducing virus propagation, while intermittent restrictions balance public health concerns with socioeconomic demands. A key contribution of this study is the validation of the epidemic model using real-world data from the 2021 lockdown that occurred in a medium-sized city, confirming its predictive accuracy and adaptability to different contexts. Additionally, we provide a detailed analysis of how mobility patterns between municipalities influence infection spread, offering a more comprehensive mathematical framework for decision-making. These findings advance the understanding of epidemic control in regions with sparse data and provide evidence-based insights to inform public health policies in similar contexts. Full article

The phenomenon of patient mobility is becoming increasingly frequent, altering the actual service ranges of hospitals across various cities. However, its impact on the spatial equity of healthcare services at the national scale has yet to be fully explored. This paper aims to reveal the impact of intercity patient mobility on healthcare equity in China. Using one million patient mobility records from online healthcare platforms, we construct the 2023 Cross-City Patient Mobility Network in China and identify the patterns of cross-city patient mobility. Furthermore, we employ the Dagum Gini coefficient to measure the spatial disparities in per capita healthcare services before and after patient mobility. The results show that: (1) cross-city patient mobility exhibits administrative boundary effects and reflects the administrative hierarchy system, yet megacities extend their healthcare service ranges beyond provincial and urban agglomeration boundaries; (2) patient mobility enhances the equity of per capita healthcare services at both intra-provincial and inter-provincial levels, with inter-provincial disparities contributing significantly more than intra-provincial disparities—a trend further reinforced by patient mobility. This study not only provides a methodological framework for understanding the impact of patient mobility on the healthcare system but also offers empirical support for public health policymaking. Full article

Studies on urban shrinkage in eastern China lack relevant contributions. This study investigates population dynamics in Jiangsu Province, focusing on county-level cities to understand the factors influencing urban population size. It developed a multidimensional indicator system per 2014, 2017, 2020, and 2023 statistical data, incorporating road network accessibility, socio-economic levels, resident income, public services, and the built environment. Employing static fixed effects models and dynamic panel regression models, it analyses trends and evolutionary patterns of permanent population changes. The findings indicate an overall increase in the permanent population over the past decade, although the growth rate has slowed in the last five years. Notably, there is a significant spatial clustering of population growth and contraction, often aligned with high-speed transportation corridors. Unlike existing research findings, the urban shrinkage pattern in Jiangsu Province is unique. Some cities in northern Jiangsu exhibit a ‘relative contraction’ pattern, where population decline coexists with high economic growth and spatial expansion. Key short-term factors influencing population size include the city’s economic level and residents’ disposable income, while long-term factors encompass city level, industrial structure, and transportation networks. Small towns exhibit ‘close-range mobility’, with primary short-term influences stemming from residents’ income, public service quality, and intercity transportation accessibility. Indeed, long-term factors primarily reflect economic development quality and urban employment rates. Full article

Understanding intercity mobility patterns is important for future urban planning, in which the intensity of intercity mobility indicates the degree of urban integration development. This study investigates the intercity mobility patterns of the Greater Bay Area (GBA) in China. The proposed workflow starts by analyzing intercity mobility characteristics, proceeds to model the spatial-temporal heterogeneity of intercity mobility structures, and then identifies the intercity mobility patterns. We first conduct a complex network analysis, based on weighted degrees and the PageRank algorithm, to measure intercity mobility characteristics. Next, we calculate the Normalized Levenshtein Distance for Population Mobility Structure (NLPMS) to quantify the differences in intercity mobility structures, and we use the Non-negative Matrix Factorization (NMF) to identify intercity mobility patterns. Our results showed an evident ‘Core-Periphery’ differentiation characterized by intercity mobility, with Guangzhou and Shenzhen as the two core cities. An obvious daily intercity commuting pattern was found between Guangzhou and Foshan, and between Shenzhen and Dongguan cities at working time. This pattern, however, changes during the holidays. This is because people move from the core cities to peripheral cities at the beginning of holidays and return at the end of holidays. This study concludes that Guangzhou and Foshan have formed a relatively stable intercity mobility pattern, and the Shenzhen–Dongguan–Huizhou metropolitan area has been gradually formed. Full article

Recent research has attempted to document large-scale emotional contagion on online social networks. Despite emotional contagion being primarily driven by in-person mechanisms, less research has attempted to measure large-scale emotional contagion in in-person contexts. In this paper, I operationalize the temporal emotions associated with a particular city at particular points in time using sentiment analysis on Twitter data. Subsequently, I study how emotions converge between seven proximal cities in the state of Virginia, using two-way fixed effect models. I find that positive emotions tend to be synchronous between cities, but that effect is conditional on the level of contact between city residents at that period of time, as indicated by cell phone mobility data. I do not find any synchrony based on other types of emotions or general sentiment. I discourage drawing causal conclusions based on the presumed existence of several unmeasured sources of bias. Full article

Estimation of economic development in advance is benefit to test the validity of economic policy or to take timely remedial measures for economic recession. Due to the inevitable connections between human mobility and economic status, estimation of economic trend in advance from easily observable big data in human mobility has the superiority of authenticity, timeliness, and convenience. However, high-precision quantitative relations between human mobility and economic growth remain an outstanding question. To this issue, we firstly analyzed and compared the general patterns of human mobility and economic development; then, a novel, simple, and effective hybrid human mobility indicator ( $HHM{I}_i$ ) of weighted human mobility networks was proposed to quantitatively estimate economic growth. $HHM{I}_i$ contained two parts, that is, the interaction volumes of a given city with all participation cities and only top hub cities, respectively. This implied that the economic growth of a city is affected by not only its own strength, but also the cooperation with hub cities. Several empirical experiments demonstrated that the proposed $HHM{I}_i$ had an exceedingly high estimation ability of economic growth, especially for the tertiary industry. Compared with other complex network indicators, $HHM{I}_i$ had a distinct advantage and its best accuracy reached 0.9543. These results can provide policy-making supports for inter-city sustainable coordinated development. Full article

Spatial patterns of tourist mobility are important for tourism management and planning. A large number of traveler-generated content accumulated on the internet provide a unique opportunity for revealing comprehensive spatial patterns of tourist movements. Instead of concentrating on a single city or attraction in previous research, this work investigates the intercity travel flows extracted from the online travel blogs in China from 2012 to 2016. The descriptive statistics of travel flows are first analyzed. The distribution of travel volume is found to satisfy the power-law distribution. Based on the intercity travel flows, a network structure is then constructed to investigate tourism interactions between cities. After four communities and 14 sub-communities being detected from the network, a tourism spatial layout with regional agglomeration effects are recognized. This research concludes that distance is essential in determining tourist movements based on a spatial interaction model. Intercity travel flows decline with distance under a power-law function. These results reveal the spatial patterns of tourist movements at an intercity scale. It will be helpful for arranging tourism resources, predicting tourist flows, and maintaining sustainable tourism. Full article