Research on the mechanism of information infrastructure affecting industrial structure upgrading.

The construction of information infrastructure as well as the transformation and upgrading of the industrial structure are among the major challenges for the Chinese economy. Therefore, it is of great significance to explore how information infrastructure affects the upgrading of industrial structure. Based on the panel data of 31 provinces in China from 2013 to 2020, mediating effect model and non-parametric percentile bootstrap method are used to carry out empirical research, by creating an information infrastructure construction level and industrial structure upgrading indicators. The results show that, in addition to the direct effect of information infrastructure on industrial structure upgrading, information infrastructure can also work indirectly through three paths: (1) information infrastructure acts on industrial structure upgrading by enhancing urbanization level; (2) information infrastructure affects industrial structure upgrading by boosting technological innovation; (3) information infrastructure first enhances urbanization level, then acts on technological innovation, and finally promotes industrial structure upgrading. In addition, the intermediary effect of technological innovation is stronger than urbanization. In general, this study acknowledges that urbanization and technological innovation are partial mediators in the process of information infrastructure affecting industrial structure upgrading, notwithstanding other potential impact pathways being studied further.

Impact of COVID-19 on domestic air transportation in China.

Assessing the impact of the coronavirus disease 2019 (COVID-19) on air transportation is essential for policymakers and airlines to prevent their widespread shutdown. The panel data observed from January 20, 2020, to April 30, 2020, were used to identify the impact of COVID-19 and the relevant control measures adopted on China's domestic air transportation. Hybrid models within negative binomial models were employed to separate the temporal and spatial effects of COVID-19. Temporal effects show that the number of new confirmed cases and the control measures significantly affect the number of operated flights. Spatial effects show that the network effect of COVID-19 cases in destination cities, lockdown, and adjustment to Level I in the early stages have a negative impact on the operated flights. Adjustment to Level II or Level III both has positive temporal and spatial effects. This indicates that the control measures adopted during the early stage of the pandemic positively impact the restoration of the aviation industry and other industries in the later stage.

Equity in Health-Seeking Behavior of Groups Using Different Transportations.

The equity of health-seeking behaviors of groups using different transportations is an important metric for health outcome disparities among them. Recently, smart card data and taxi trajectory data have been used extensively but separately to quantify the spatiotemporal patterns of health-seeking behavior and healthcare accessibility. However, the differences in health-seeking behavior among groups by different transportations have hitherto received scant attention from scholars. To fill the gap, this paper aimed to investigate the equity in health-seeking behavior of groups using different transportations. With sets of spatial and temporal constraints, we first extracted health-seeking behaviors by bus and taxi from smart card data and taxi trajectory data from Beijing during 13-17 April 2015. Then, health-seeking behaviors of groups by bus and taxi were compared regarding the coverage of hospital service areas, time efficiency to seek healthcare, and transportation access. The results indicated that there are inequities in groups using different travel modes to seek healthcare regarding the coverage of hospital service areas, time efficiency to seek healthcare, and transportation access. They provide some suggestions for mode-specific interventions to narrow health disparity, which might be more efficient than a one-size-fits-all intervention.

Whether Public Hospital Reform Affects the Hospital Choices of Patients in Urban Areas: New Evidence from Smart Card Data.

The effects of public hospital reforms on spatial and temporal patterns of health-seeking behavior have received little attention due to small sample sizes and low spatiotemporal resolution of survey data. Without such information, however, health planners might be unable to adjust interventions in a timely manner, and they devise less-effective interventions. Recently, massive electronic trip records have been widely used to infer people's health-seeking trips. With health-seeking trips inferred from smart card data, this paper mainly answers two questions: (i) how do public hospital reforms affect the hospital choices of patients? (ii) What are the spatial differences of the effects of public hospital reforms? To achieve these goals, tertiary hospital preferences, hospital bypass, and the efficiency of the health-seeking behaviors of patients, before and after Beijing's public hospital reform in 2017, were compared. The results demonstrate that the effects of this reform on the hospital choices of patients were spatially different. In subdistricts with (or near) hospitals, the reform exerted the opposite impact on tertiary hospital preference compared with core and periphery areas. However, the reform had no significant effect on the tertiary hospital preference and hospital bypass in subdistricts without (or far away from) hospitals. Regarding the efficiency of the health-seeking behaviors of patients, the reform positively affected patient travel time, time of stay at hospitals, and arrival time. This study presents a time-efficient method to evaluate the effects of the recent public hospital reform in Beijing on a fine scale.

Exploring the dynamic impacts of COVID-19 on intercity travel in China.

Many studies have explored the effects of transportation and population movement on the spread of pandemics. However, little attention has been paid to the dynamic impact of pandemics on intercity travel and its recovery during a public health event period. Using intercity mobility and COVID-19 pandemic data, this study adopts the gradient boosting decision tree method to explore the dynamic effects of the COVID-19 on intercity travel in China. The influencing factors were classified into daily time-varying factors and time-invariant factors. The results show that China's intercity travel decreased on average by 51.35% from Jan 26 to Apr 7, 2020. Furtherly, the COVID-19 pandemic reduces intercity travel directly and indirectly by influencing industry development and transport connectivity. With the spread of COVID-19 and changes of control measures, the relationship between intercity travel and COVID-19, socio-economic development, transport is not linear. The relationship between intercity travel and secondary industry is illustrated by an inverted U-shaped curve from pre-pandemic to post-pandemic, whereas that with tertiary industry can be explained by a U-shaped curve. Meanwhile, this study highlights the dynamic effect of the COVID-19 on intercity mobility. These implications shed light on policies regarding the control measures during public health events that should include the dynamic impact of pandemics on intercity travel.

Spread of COVID-19 in China: analysis from a city-based epidemic and mobility model.

Understanding the processes and mechanisms of the spatial spread of epidemics is essential for making reasonable judgments on the development trends of epidemics and for adopting effective containment measures. Using multi-agent network technology and big data on population migration, this paper constructed a city-based epidemic and mobility model (CEMM) to stimulate the spatiotemporal of COVID-19. Compared with traditional models, this model is characterized by an urban network perspective and emphasizes the important role of intercity population mobility and high-speed transportation networks. The results show that the model could simulate the inter-city spread of COVID-19 at the early stage in China with high precision. Through scenario simulation, the paper quantitatively evaluated the effect of control measures "city lockdown" and "decreasing population mobility" on containing the spatial spread of the COVID-19 epidemic. According to the simulation, the total number of infectious cases in China would have climbed to 138,824 on February 2020, or 4.46 times the real number, if neither of the measures had been implemented. Overall, the containment effect of the lockdown of cities in Hubei was greater than that of decreasing intercity population mobility, and the effect of city lockdowns was more sensitive to timing relative to decreasing population mobility.

Inferring transit-based health seeking patterns from smart card data - A case study in Beijing, China.

Massive electronic trip records have recently been utilized to infer people's trips for healthcare. Many inferential methods were developed to derive healthcare trips by taxi using GPS trajectory records, but little attention is paid to public transit, as a common travel mode for healthcare. This paper proposes a method to fill this gap by mining a big data of smart transit cards with spatio-temporal constraints. We demonstrate and validate this method in Beijing, China. The inferred trips achieve a high degree of consistency, in space and time, with empirically observed trips from a survey. The inferred trips are further used to identify spatial disparities in transit-based access to healthcare, which might have been overlooked by health policy makers.

Exploring the roles of high-speed train, air and coach services in the spread of COVID-19 in China.

To understand the roles of different transport modes in the spread of COVID-19 pandemic across Chinese cities, this paper looks at the factors influencing the number of imported cases from Wuhan and the spread speed and pattern of the pandemic. We find that frequencies of air flights and high-speed train (HST) services out of Wuhan are significantly associated with the number of COVID-19 cases in the destination cities. The presence of an airport or HST station at a city is significantly related to the speed of the pandemic spread, but its link with the total number of confirmed cases is weak. The farther the distance from Wuhan, the lower number of cases in a city and the slower the dissemination of the pandemic. The longitude and latitude coordinates do not have a significant relationship with the number of total cases but can increase the speed of the COVID-19 spread. Specifically, cities in the higher longitudinal region tended to record a COVID-19 case earlier than their counterparties in the west. Cities in the north were more likely to report the first case later than those in the south. The pandemic may emerge in large cities earlier than in small cities as GDP is a factor positively associated with the spread speed.

Assessing the role of high-speed rail in shaping the spatial patterns of urban and rural development: A case of the Middle Reaches of the Yangtze River, China.

China has experienced rapid residential land expansion in both urban and rural areas over the past three decades, causing complex ecological and environmental challenges. Much research attention has been paid on urbanisation, yet little is known about rural development. In this study, we analysed and compared the changes in a selected number of landscape indices describing the spatial patterns of both urban and rural area in the Middle Reaches of the Yangtze River in central China from 2005 to 2015 and explored how these changes could be associated with the development of high-speed rail (HSR) using spatial error models. We found a partial synchronised spatial development pattern between urban and rural areas in central China, with an increasingly fragmented pattern for both urban and rural areas, albeit rural areas were expanded in a less contiguous but more complex and dispersed fashion. The impacts of the provision of HSR services on the region's spatial development were found to be multi-level. It was associated with greater urban expansion and dispersion at the county/district level and amplified rural patch size and complexity at the patch level. The departure frequency of HSR trains and proximity to HSR station were found to have affected the magnitude of the impact of HSR service provision on regional spatial development. Our results shed lights on the spatio-temporal evolution of an ecologically important region, add new evidence into the expanding fields of urban and rural morphological studies in China, and provide valuable decision support information for integrated spatial planning of transportation and land use.

Tracking job and housing dynamics with smartcard data.

Residential locations, the jobs-housing relationship, and commuting patterns are key elements to understand urban spatial structure and how city dwellers live. Their successive interaction is important for various fields including urban planning, transport, intraurban migration studies, and social science. However, understanding of the long-term trajectories of workplace and home location, and the resulting commuting patterns, is still limited due to lack of year-to-year data tracking individual behavior. With a 7-y transit smartcard dataset, this paper traces individual trajectories of residences and workplaces. Based on in-metro travel times before and after job and/or home moves, we find that 45 min is an inflection point where the behavioral preference changes. Commuters whose travel time exceeds the point prefer to shorten commutes via moves, while others with shorter commutes tend to increase travel time for better jobs and/or residences. Moreover, we capture four mobility groups: home mover, job hopper, job-and-residence switcher, and stayer. This paper studies how these groups trade off travel time and housing expenditure with their job and housing patterns. Stayers with high job and housing stability tend to be home (apartment unit) owners subject to middle- to high-income groups. Home movers work at places similar to stayers, while they may upgrade from tenancy to ownership. Switchers increase commute time as well as housing expenditure via job and home moves, as they pay for better residences and work farther from home. Job hoppers mainly reside in the suburbs, suffer from long commutes, change jobs frequently, and are likely to be low-income migrants.

The implications of high-speed railways on air passenger flows in China.

The High-speed Railway (HSR) network in China is the largest in the world, competing intensively with airlines for inter-city travel. Panel data from 2007 to 2013 for 138 routes with HSR-air competition were used to identify the ex-post impacts of the entry of HSR services, the duration of operating HSR services since entry, and the specific impacts of HSR transportation variables such as travel time, frequency, and ticket fares on air passenger flows in China. The findings show that the entry of new HSR services in general leads to a 27% reduction in air travel demand. After two years of operating HSR services, however, the negative impact of HSR services on air passenger flows tends to further increase. The variations of the frequency in the temporal dimension and the travel time in the spatial dimension significantly affect air passenger flows. Neither in the temporal nor spatial dimensions are HSR fares strongly related to air passenger flows in China, due to the government regulation of HSR ticket prices during the period of analysis. The impacts of different transportation variables found in this paper are valuable to consider by operational HSR companies in terms of scheduling and planning of new routes to increase their competitiveness relative to airlines.

Spatial access to residential care resources in Beijing, China.

BACKGROUND: As the population is ageing rapidly in Beijing, the residential care sector is in a fast expansion process with the support of the municipal government. Understanding spatial accessibility to residential care resources by older people supports the need for rational allocation of care resources in future planning. METHODS: Based on population data and data on residential care resources, this study uses two Geographic Information System (GIS) based methods--shortest path analysis and a two-step floating catchment area (2SFCA) method to analyse spatial accessibility to residential care resources. RESULTS: Spatial accessibility varies as the methods and considered factors change. When only time distance is considered, residential care resources are more accessible in the central city than in suburban and exurban areas. If care resources are considered in addition to time distance, spatial accessibility is relatively poor in the central city compared to the northeast to southeast side of the suburban and exurban areas. The resources in the northwest to southwest side of the city are the least accessible, even though several hotspots of residential care resources are located in these areas. CONCLUSIONS: For policy making, it may require combining various methods for a comprehensive analysis. The methods used in this study provide tools for identifying underserved areas in order to improve equity in access to and efficiency in allocation of residential care resources in future planning.