Large Chinese Cities Research Articles

Visible body and invisible mind: Bureaucratic performance, self-rehabilitation, and the machinery of Chinese community corrections

Based on a recent ethnographic study of community corrections in two large Chinese cities, this study examines how the rehabilitation work, as the cornerstone of Chinese community corrections, is deployed as a people-processing apparatus that counts offenders’ bodies but almost excludes their agency. In practice, offenders are instrumentalized and disciplined to make up the Chinese community corrections machinery, whose subjectivity is either completely muted or selectively mediated. Given justice actors’ adherence to bureaucratic hierarchy and preoccupation with administrative requirements, offenders are mostly marked as counts and treated more as penal objects utilized to fulfill intricate metrics-related requirements. Justice agents’ formalistic pursuit of, rather than substantive investment in, the well-being of offenders renders their participation in Chinese community corrections symbolic and strenuous. It further breeds offenders’ commitment to self-rehabilitation, a process of relying on self-discipline and personally discovered resources for compliance and reintegration. We contend that the current operation of the Chinese community corrections apparatus, under the rehabilitative guise, exacerbates offenders’ structural disadvantages and reinforces their stigmatized identities. Policy and research implications of this study are discussed.

The effect of incentives and procedure simplification in policy implementation: evidence from a survey experiment on waste sorting

ABSTRACT To encourage residents to sort their waste, governments can use incentives such as cash rewards or social reinforcement. The effect of such incentives remains unclear, and residents often are deterred by the complexity of procedures to obtain their rewards. Based on positive reinforcement theory and using a survey experiment, we study the effect of types and procedures of incentives on waste sorting behavioural intentions in a large Chinese city. We find that cash incentives have a stronger effect on waste sorting behavioural intentions than incentives based on social reinforcement such as a certificate of merit. Cash-based incentives also have a stronger effect on perceived probability to obtain the incentive and on perceptions of procedure difficulty. More simple procedures to obtain the incentive does not seem to have an effect on waste sorting behavioural intentions, neither direct nor in an interaction. However, the simplification of the procedure through which an incentive can be obtained is positively correlated with perceived probability to obtain the incentive.

Refining urban morphology: An explainable machine learning method for estimating footprint-level building height

Fine-grained 3D buildings with diverse morphology are a cornerstone of urban physical structures and have profound implications for sustainable city development. However, accurately estimating building height at the footprint-level is a challenge. This study bridged this gap by using random forest models to integrate the elevation, geometry and shape attributes of individual buildings, further refining those with spatial aggregation. It considered over one million buildings across 10 large Chinese cities and trained two-types models that demonstrated commendable performance in city-specific (the mean absolute error (MAE) ranged from 3.43 m to 5.06 m) and combined (MAE = 4.68 m) models. Results revealed that the current dataset had a finer urban morphology compared with existing datasets and showed outstanding generalisability in method transfer and feature ablation tests. By incorporating Shapley values, we explored the features' global and local impacts. The explainable results demonstrated that building area was the most impactful feature, and the elevation-dimension features were particularly beneficial in estimating high-rise buildings. Using the fine-grained 3D buildings, we explored the connections between explicit morphology differences and implicit contexts in cities. Overall, our work is an endeavour to estimate footprint-level building height as fuel for refining urban morphology and enabling sustainable city studies.

Inferring the Unofficial Incomes of Officials from Home Ownership

We estimate the size of the likely unofficial income of the government official household by assessing the difference between the income necessary to explain their observed home purchase behavior and the official income. Using unique and comprehensive House Provident Fund and home purchases data between 2006 and 2013 in a large Chinese city, we reach three conclusions. First, an average official’s unofficial income is 83% of her official income; this percentage increases sharply with the official’s rank. Second, about 13% of the officials have an unofficial income, and the proportion also increases with rank. Third, government officials are not underpaid, and their unofficial incomes are not compensation for low government salaries. Additionally, evidence suggests that unofficial incomes have declined since the recent anticorruption campaign. An analysis of a separate crosscity data set corroborates the key conclusion. This paper was accepted by David Sraer, finance. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.01725 .

Analysis of road traffic accidents and casualties associated with electric bikes and bicycles in Guangzhou, China: A retrospective descriptive analysis

IntroductionElectric bicycles (e-bikes) and bicycles in large Chinese cities have recently witnessed substantial growth in ridership. According to related accident trends, this study analyzed characteristics and spatial distribution in the period when e-bike-related accidents rapidly increased to propose priority measures to reduce accident casualties. MethodsFor e-bike- and bicycle-related accident data from the Guangzhou Public Security Traffic Management Integrated System, linear regression was used to examine the trends in the number of accidents and age-adjusted road traffic casualties from 2011 to 2021. Then, for the period when e-bike-related accidents rapidly increased, descriptive statistics were computed regarding rider characteristics, illegal behaviors, road types, collision objects and their accident liability. One-way analysis of variance (ANOVA) followed by Bonferroni's multiple comparison test. P < 0.05 was considered statistically significant. Finally, the density distribution of accidents was presented, and Moran's I (MI) was used for assessing spatial autocorrelation. Hotspots were identified based on an optimized hotspot analysis tool. ResultsBetween 2011 and 2021, the number of accidents and casualty rate (per 100,000 population) increased for e-bikes but decreased for bicycles. After 2018, e-bike-related accidents increased rapidly, and bicycle-related accidents plateaued. Accident hotspots were concentrated in central city areas and suburban areas close to the former. Three-quarters of accidents occurred in motorized vehicle lanes. Most occurred on roads without physically segregated nonmotorized vehicle lanes. More than three-fifths of the accidents involved motor vehicles with at least four wheels. The prevalence (per 100 people) of casualties among e-bike rider victims and cyclist victims accounted for 92.0 % and 96.5 %, respectively. A total of 71.6 % of e-bike-related accidents involved migrant workers. Riding in motorized vehicle lanes was the most common illegal behavior. ConclusionsAlthough e-bike-related and bicycle-related accidents presented similar characteristics, the sharp increase in e-bike-related accidents requires attention. To improve e-bike safety, governments should develop appropriate countermeasures to prevent riders from riding on motorways, such as improving road infrastructure, adjusting the driver's license system and addressing priority control areas.

A clustering-based analysis method for simulating seismic damage of buildings in large cities

Earthquakes are major threats to cities. Refined simulations of urban earthquake damage are significant for disaster prevention planning, including post-earthquake emergency rescue operations. However, this approach is time-consuming and computationally demanding. This study presents a novel machine learning method for simulating seismic damage of large urban building groups, thus minimizing the computational time and resources associated with the simulation process. First, the proposed method clusters building structures based on their seismic damage index (DI) under specific ground motions. Subsequently, one structure is selected from each cluster for seismic analysis. This approach significantly reduces the number of analyzed structures. The efficiency and accuracy of this method are studied based on a parametric study that involved an improved K-means clustering algorithm and a grid-based clustering algorithm. A batch-clustering algorithm is also developed to further improve the speed of clustering and efficiency of regional seismic simulations. A large Chinese city is considered as research application example. The results indicated the following: (1) the method based on the improved K-means clustering algorithm was superior; (2) the batch-clustering algorithm significantly speeded up clustering analysis and enhanced efficiency of the seismic simulation; (3) the clustering-based simulation method demonstrated high efficiency and accuracy, with a significant decrease of 90.5% in the calculation time compared with direct nonlinear time history analysis. In addition, the average relative error of the DI was only 11.0%. Moreover, over 85.0% of the structures were estimated to be in the correct damage state.

Electronic health record and primary care physician self-reported quality of care: a multilevel study in China

ABSTRACT Background Health information technology is one of the building blocks of a high-performing health system. However, the evidence regarding the influence of an electronic health record (EHR) on the quality of care remains mixed, especially in low- and middle-income countries. Objective This study examines the association between greater EHR functionality and primary care physician self-reported quality of care. Methods A total of 224 primary care physicians from 38 community health centres (CHCs) in four large Chinese cities participated in a cross-sectional survey to assess CHC care quality. Each CHC director scored their CHC’s EHR functionality on the availability of ten typical features covering health information, data, results management, patient access, and clinical decision support. Data analysis utilised hierarchical linear modelling. Results The availability of five EHR features was positively associated with physician self-reported clinical quality: share records online with providers outside the practice (β = 0.276, p = 0.04), access records online by the patient (β = 0.325, p = 0.04), alert provider of potential prescription problems (β = 0.353, p = 0.04), send the patient reminders for care (β = 0.419, p = 0.003), and list patients by diagnosis or health risk (β = 0.282, p = 0.04). However, no association was found between specific features availability or total features score and physician self-reported preventive quality. Conclusions This study provides evidence that the availability of EHR systems, and specific features of these systems, was positively associated with physician self-reported quality of care in these 38 CHCs. Future longitudinal studies focused on standardised quality metrics, and designed to control known confounding variables, will further inform quality improvement efforts in primary care.

Perceived Facilitators and Barriers in Implementing Hospice Care: A Qualitative Study Among Health Care Providers in Binzhou, China

Although many large Chinese cities have begun to implement hospice services, hospice care is still a relatively new concept in many parts of the country, especially in smaller cities. The purpose of this study was to gain a better understanding of health care providers’ (physicians and nurses) perceptions of the facilitators and barriers to hospice care implementation in a fourth-tier city. Using a qualitative descriptive approach, semi-structured, open-ended interviews were conducted with 15 health care providers. Two major categories for developing hospice care were identified: (a) prospective facilitators and (b) perceived barriers. In addition, there is currently much ambiguity regarding what agency should oversee hospice services if implemented, who should be responsible for payment, the importance of developing interdisciplinary care teams and concerns about worker shortages. Future research is encouraged to investigate attitudes towards hospice care across various local healthcare systems and to promote the development of local hospice care support.

Highly Heterogeneous Heat‐Related Health Impacts in China and Implications for Sustainable Urban Heat Governance

AbstractUnderstanding heat‐related impacts is crucial to improving public awareness of addressing urban heat challenges and enabling decision makers to mainstream heat action plans. This study explores heat‐related physiological and psychological impacts, symptoms, and demographic determinants based on 4210 questionnaires across nine large Chinese cities, including Chengdu, Chongqing, Guangzhou, Hangzhou, Nanchang, Nanjing, Shanghai, Shenyang, and Xi'an in August 2020. The results indicate that heat‐related psychological impacts are equally severe as physiological impacts. Chongqing is under the most severe heat‐related health impact on both the physiological and psychological aspects. Skin heat damage (SKI), digestive system illnesses (DIG), respiratory illnesses (RES), and cardiovascular illnesses (CAR) are prominent physiological illnesses in all cities, while emotional irritability (EMO), easy to lose control temper (EAS), low mood (LOW), and insomnia (INS) are prominent psychological symptoms. Chongqing and Guangzhou are the most vulnerable cities in terms of physiological and psychological symptoms. Chengdu, Hangzhou, Nanjing, and Shanghai are more resilient in terms of physiological symptoms, whereas Chengdu, Hangzhou, and Shanghai are more resistant to psychological symptoms. Heat‐related health impacts, symptoms, and demographic determinants are spatially heterogeneous. The elderly and patients are more vulnerable, while such a conclusion is not always true. The spatial heterogeneity of heat‐related physiological and psychological impacts, symptoms, and drivers highlights the significance of developing city‐specific heat health action plans.

Intensified discrimination against tenants and its health effects during the COVID-19 pandemic in large Chinese cities

The COVID-19 pandemic in many senses reconstructs social norms and reshapes social behaviour, which typically assumes a close correlation between mobility with a higher risk of COVID-19 infection. This may intensify the pre-existing discrimination against tenants and widen tenure-based health inequalities. Drawing on an online questionnaire survey conducted in five major cities in China in 2020, we employ multi-level regression models to examine the intensified discrimination against tenants during COVID-19 and its impacts on residents’ physical and mental health inequalities. Results show that the pre-existing inequalities have been intensified during COVID-19 and the perceived discrimination has rendered worsened self-rated health and mental health and enlarged health inequalities. The discrimination particularly affected tenants with better economic profiles or worse health conditions; by contrast, despite being exposed to more tenant-related discriminatory experiences, rural hukou holders suffered from less severe health inequalities. A clear linkage is found between renting in poorly-managed and larger health gaps generated by discrimination. The negative health impact of intensified discrimination is found to be more significant in communities with lower infection risk, which points to the necessity of understanding the long-term health impact of discrimination against tenants in a more holistic way. In terms of community environment, we discover a positive effect of community social capital, i.e., higher level social capital helps mitigate the health threat of discrimination against tenants during COVID-19. Besides, public housing tenants reported better health outcomes and were less exposed to intensified discrimination during COVID-19 than private housing tenants. These findings provide a nuanced understanding of variations determined by individual and territorial factors, thus present timely policy implications for promoting healthy and inclusive urban development in the post-pandemic era.

Implications for TB control among migrants in large cities in China: A prospective population-based genomic epidemiology study in Shenzhen

Internal migrants are a challenge for TB control in large Chinese cities and understanding this epidemiology is crucial for designing effective control and prevention strategies. We conducted a prospective genomic epidemiological study of culture-positive TB patients diagnosed between June 1, 2018 and May 31, 2021 in the Longhua District of Shenzhen. Treatment status was obtained from local and national TB registries and all isolates were sequenced. Genomic clusters were defined as strains differing by ≤12 SNPs. Risk factors for clustering were identified with multivariable analysis and then Bayesian models and TransPhylo were used to infer the timing of transmission within clusters. Of the 2277 culture-positive patients, 70.1% (1596/2277) were migrants: 72.1% (1043/1446) of the migrants patients developed TB within two years of arriving in Longhua; 38.8% within 6 months of arriving; and 12.3% (104/843) had TB symptoms when they arrived. Only 15.4% of Longhua strains were in genomic clusters. More than one third (33.6%) of patients were not treated in Shenzhen but were involved in nearly one third of the recent transmission events. Clustering was associated with migrants not treated in Shenzhen, males, and teachers/trainers. TB in Longhua is prinicipally due to reactivation of infections in migrants, but a proportion may have had clinical or incipient TB upon arrival in the district. Patients diagnosed but not treated in Longhua were involved in recent local TB transmission. Controlling TB in Shenzhen will require strategies to comprehensively diagnose and treat active TB in the internal migrant population.

A more accurate estimation with kernel machine for nonparametric spatial lag models

Ignoring potential spatial autocorrelation in georeferenced data may cause biased estimators. Furthermore, existing studies assume insufficiently flexible structure of spatial lag model for some practical applications, which makes it difficult to portray the complex relationship between responses and covariates. Thus, we propose a novel garrotized kernel machine estimation method for the nonparametric spatial lag model and develop an eigenvector spatial filtering algorithm with sparse regression to filter spatial autocorrelation out of the residuals. The “one-group-at-a-time” cyclical coordinate descent algorithm is introduced for a solution path of tuning parameters. Our method can better describe the potential nonlinear relationship between responses and covariates, making it possible to model high-order interaction effects among covariates. Numerical results and the analysis of commodity residential house prices in large and medium-sized Chinese cities indicate that the proposed method achieves better prediction performance compared with competing ones. The result of real data analysis can provide guidance for the government to take targeted suppression measures of house prices for different areas.

“Quick Response” Economic Stimulus: The Effect of Small-Value Digital Coupons on Spending

We study a new consumption stimulus program implemented by a large Chinese city that leverages mobile payment platforms to dispense massive amounts of small-value digital coupons. Exploiting a “rush” design of the dispensing process in which over 1 million program participants compete for coupons on a first-come, first-served basis through a digital portal, we estimate that winning coupons increases weekly out-of-pocket spending by US$3 for every US$1 in government subsidy. Coupon-winning consumers practice inter-temporal substitution by moving up purchases that would have been made four months in the future. Customer flow analysis suggests that coupons distort consumption toward pricier options. (JEL D15, E21, E42, H71, O18, P25, P36)

Extracting the pickpocketing information implied in the built environment by treating it as the anomalies

The practice of crime risk mapping, enabled by the utilization of geospatial big data such as street view images, has received significant research attention. However, in situations where available data is scarce, mapping models may suffer from underfitting and generate inaccurate spatial pattern estimations of crime risk. The covert nature of pickpocketing crimes results in limited observed areas relevant to such criminal events, leading to insufficient coverage of geospatial data. Moreover, the location of crime is also influenced by socio-economic characteristics that may introduce biases into crime risk estimates. These factors render it challenging for the model to capture a valid crime risk pattern, potentially yielding misleading conclusions. Therefore, effectively extracting crime risk with limited data remains a challenge, especially when relying on easily accessible, widespread, and unbiased geospatial data. To address this challenge, we propose a novel crime risk assessment framework based on deep anomaly detection techniques, assuming that urban landscape anomalies carry deep crime risk information. We take Shenzhen as the study area and map the distribution of pickpocketing risk using street view images, accurately revealing the spatial aggregation of pickpocketing crime risk. Our findings indicate that pickpocketing crime in China is caused by regional economic conditions, built environment factors, and human routine activities. This study provides valuable insights for policing and prevention strategies aimed at addressing pickpocketing crimes in large Chinese cities. By leveraging our proposed crime risk assessment framework, decision-makers can allocate resources more efficiently and develop targeted interventions to mitigate crime risks.

Factors influencing engagement in online dual practice by public hospital doctors in three large cities: A mixed-methods study in China.

In the digital age, a rising number of public sector doctors are providing private telemedicine and telehealth services on online health care platforms. This novel practice pattern - termed online dual practice - may profoundly impact health system performance in both developed and developing countries. This study aims to understand the factors influencing doctors' engagement in online dual practice. Using a mixed-methods design, this study concurrently collects quantitative demographic and practice data (n = 71 944) and semi-structured interview data (n = 32) on secondary and tertiary public hospital doctors in three large Chinese cities: Beijing, Shanghai and Guangzhou. We use the quantitative data to examine the prevalence of the online dual practice and its associated factors via the binary logit regression model. The qualitative data are used to further explore associated factors of online dual practice via thematic analysis. The findings about associated factors from the two parts were merged using the categories of personal, professional, and organisational characteristics. Our quantitative analysis shows that at least 47.1% of public hospital doctors are involved in online dual practice. The shares in Beijing, Shanghai, and Guangzhou are 43.7%, 53.1%, and 44.8%, respectively. This practice is more prevalent among doctors who are male, senior, and non-managerial. Different specialties, hospital ownership, hospital levels, and locations are also significantly associated with this practice. The qualitative analysis further suggests that financial returns, perceived effectiveness of telemedicine, and hospital directors' attitude towards telemedicine may affect doctors' engagement with online dual practice. Online dual practice is prevalent among doctors at tertiary and secondary public hospitals in Beijing, Shanghai, and Guangzhou. Personal, professional, and organisational characteristics are all associated with doctors' choice to engage in online dual practice. The findings in this study provide implications for promoting telemedicine adoption and developing relevant regulatory policies in China and other countries.

Smallpox Prevention and Public Healthcare in China in the 1920s and 1930s: Focusing on the Cases of Shanghai and Beijing.

Beijing and Shanghai, representative modern cities in China, witnessed the development of various urban infrastructures and quarantine systems in the 1920s and 1930s. Both cities established Health Demonstration Stations in the 1930s, as part of their implementation of modern health administration. This foundation played a pivotal role for making health administration more practical. Huang Zi-fang (1899-1940) and Hu Hung-ji (1894-1932), the inaugural directors of the health bureau in the respective cities, were both graduates of the Johns Hopkins University School of Public Health in the United States. They shared a similar view of public health. Active exchanges occurred between the heads of the health administration in the two cities who were the leading forces in the health reform, encompassing various health experiments including the Health Demonstration Station. During the 1930s in China, state medicine gained prominence as the most ideal medical model for constructing a modern state. As such, the quarantine activities they promoted were also considered the most ideal model. The public health care centered on Health Demonstration Stations in the 1920s and 1930s that developed in large Chinese cities such as Beijing and Shanghai pursued similar goals by strengthening quarantine administration through free medical treatment and modern spatial control. Nonetheless, each city exhibited differences in terms of the subjects and targets of quarantine, as well as the primary bases of quarantine, which were either Health Demonstration Stations or hospitals. Both municipal governments and the civilian sector led the sanitary infrastructure development. While Shanghai showed stronger development in terms of the number of vaccinations, Shanghai's dualized quarantine system did not necessarily create a better health environment than Beijing in terms of spatial control. In the 1940s, the Japanese occupation government implemented measures to inherit and further develop existing health administrations in Beijing and Shanghai. Existing international settlements were incorporated into the Japanese occupation government, and the occupation government pursued homogenization of urban space and tried to maintain the existing urban policy as much as possible to preserve the status quo. However, the intensification of the Anti-Japanese War and the Chinese Civil War brought an end to the health experiment centered around the Health Demonstration Station in China in the first half of the twentieth century.

The social equity and the spatial accessibility of general hospitals in big Chinese cities: an exploration based on different income groups and transportation modes in Shenzhen

Abstract Objectives: The rational planning and allocation of hospitals significantly improve residents’ health and quality of life. However, the unequal allocation of medical resources remains a significant issue in large Chinese cities. This study investigated the disparities in access to health care among different social groups in Shenzhen and explored the discrepancy in equity and its influencing mechanisms. Methods: The population was divided into 5 social groups based on housing prices: high-income, middle-high income, middle-income, middle-low income, and low-income. The actual travel times of residential neighborhoods and general hospitals under both driving and public transportation were accessed through the application programming interface Amap, a mapping technology application. The accessibility of general hospitals was calculated by the Gaussian-based 2-step floating catchment area method. The Gini coefficient was used to further investigate the equity in medical facility services. Results: Accessibility to first and second-level hospitals was adequate for the high-income group. However, a significant spatial mismatch in the allocation of hospitals was identified for the middle-low income and low-income groups, especially those reliant on public transportation. Conclusions: This study reveals an inequitable allocation of hospitals, with driving accessibility generally superior to public transport accessibility in Shenzhen, and a significant spatial mismatch for middle-low income and low-income groups. This study suggests optimizing public transportation around hospitals and middle-low income or low-income neighborhoods through urban planning to improve the accessibility of public service facilities for middle-low income and low-income households, thereby promoting more health equity.

Investigating the effect of people on the street and streetscape physical environment on the location choice of street theft crime offenders using street view images and a discrete spatial choice model

As street crime occurs in the street, it is reasonable to assume that the location choice of street crime offenders is affected by streetscape conditions and people on street. However, this issue has not been investigated by previous research, possibly because fine-grained streetscape data are hard to obtain. Traditional data-gathering methods like questionnaires, field surveys, and manual audits are inefficient and only applied to small areas. Social media and mobile phone data have recently been used to measure the ambient population. However, they are unable to distinguish between indoor and on-street people. To overcome these limitations, the present research applied an integrative deep learning algorithm combining an object detection network and a semantic segmentation network to extract on-street people and physical environment elements from fine-grained street view images (SVIs) in a large Chinese city. The extracted elements include fences, walls, windows, grass, sidewalk, and plants. Controlling the influence of residence-crime proximity, crime attractors, generators, detractors, and socioeconomic features, we constructed a discrete spatial choice model to investigate the influence of people on the street and the streetscape's physical environments on the location choice of street theft crime offenders. Results reveal an improvement in model performance after the streetscape variables are considered. Therefore, the streetscape context is essential for understanding offenders' preferences for crime locations. Specifically, the number of people on the street presents a significantly positive relationship with the offenders' preferences. Fences and plants have significant and positive effects on attracting criminals. Grasses and sidewalks negatively affect offenders' location choices. Walls and windows do not significantly affect criminals' crime location choices. Additionally, the associations between most control variables and offenders' preferences for crime locations conform to previous research findings. As the first attempt in combining SVIs, deep learning algorithms, and discrete spatial choice model, this study makes a contribution to the extant crime location choice literature.

Impact of new talent settlement policy on housing prices: Evidence from 70 large and medium-sized Chinese cities.

Since 2017, Chinese cities have set off a wave of talent migration, with major cities joining the talent war and issuing new talent settlement policies that might stimulate the real estate market through the inflow and outflow of human capital. However, the effects of new talent settlement policies on housing prices have not been extensively studied. This study used a difference-in-differences model to examine the causal effects of new talent settlement policies on housing prices in China based on data from 70 large and medium-sized cities. The results showed that new talent settlement policies had positive effects on housing prices, and the effects revealed pronounced regional heterogeneity: they were more significant in the eastern region, first-tier, and new first-tier cities, and varied across major migration zones. Further, the varying policy tools in the new talent settlement policies had disparate effects on housing prices. Thus, we recommend that new talent settlement policies must be coordinated with the goals of real estate regulation and reasonable regional standards, and that the policy tools should be tailored according to the actual conditions of cities.

Effects of rising and extreme temperatures on production factor efficiency: Evidence from China's cities

Cities are the main drivers of climate change; they are also more vulnerable to it than rural areas. Improving the utilization efficiency of various production factors is an important way for cities to fight climate change. Using observations from across 36 large and medium-sized Chinese cities, this study finds that most cities experienced temperature rises in the past half century, with average increases of 0.5 °C. Based on the city-level production possibility set, this study constructs a factor-specific efficiency model of the directional distance function version. Using data from Chinese prefectures and above-level cities with a population of more than 1 million, we calculated three factor efficiencies: labor, energy, and environment. The econometric analysis revealed that the rising temperatures had a positive effect on all three efficiencies. This finding may be related to China's geographical location within a temperate zone; consequently, the increase in temperature moved its temperatures to an optimal level. However, extreme temperatures had a negative impact on the efficiency of three factors. Further analysis found that rising temperatures brought more benefits to cities dominated by tertiary industries, while extreme temperatures brought more harm to cities dominated by secondary industries. As part of China's urbanization process, large central cities often support tertiary industries with various resources, thereby moving secondary industries to the surrounding small cities. Our results suggest that as global warming intensifies, new economic inequalities may arise between cities with different industrial structures.