Case Study Of Shanghai Research Articles

Resolving the unintended consequences of collective co-production through group co-production: a case study in Shanghai

Co-production is an important approach to enhance service resilience in disaster response. However, most existing studies did not differentiate various types of co-production (i.e., collective vs. group co-production) and consider the potential tension between them. Based on evidence from self-organized groups for people with disabilities in Shanghai, this study found that as a type of collective co-production, compulsory epidemic prevention measures during the Covid-19 pandemic produced unintended consequences for people with disabilities: both government-organized and independent NGOs were forced to close offices, causing formal social services to be discontinued. However, as a type of group co-production, self-organized groups played an indispensable role in helping restore service resilience by providing material and consultation services to people with disabilities through online and offline approaches. This study not only contributes to the co-production literature through unveiling the tension and discussing the relation between collective and group co-production, but also provides valuable guidance for the government on how to promote self-organized groups to improve emergency management capacity.

Measuring Rurality and Analyzing the Drivers of Rurality in Megacities—A Case Study of Shanghai, China

The Rurality Index is an important reference for the formulation of rural development strategies and policies, but the evaluation of the rurality of megacities based on the township scale is relatively limited. Based on the perspective of spatial governance, this study constructed the evaluation index system of Shanghai’s rurality and carried out the evaluation of Shanghai’s rurality at the township scale from 2005 to 2020. The article adopts the MGWR model to analyze the driving effects of five key driving factors (the proportion of foreign population, per capita industrial output value, public finance revenue, social fixed asset investment, and rail transit coverage), and adopts the Geo-Detector model to analyze the interactive driving effects of two factors. The results indicate that the rurality index of megacities and townships as a whole shows a weakening trend, and the above factors have a predominantly negative impact on rurality, with differences in the intensity of the impact in different periods. There is an obvious interactive additive effect between the factors. When formulating policies for township development, government departments need to take into account the functional positioning of the region and comprehensively adopt targeted policies on population, industry, transportation, finance and investment to regulate and guide the transformation or sustainable development of the countryside.

Soundscapes in Urban Green Spaces of a Megacity Across an Urban–Rural Gradient: A Case Study of Shanghai

Urban soundscapes are valuable indicators of urban biodiversity and ecosystem health. This study investigated the spatial and temporal characteristics of soundscapes in megacity green spaces and their relationship with the urban environment. An acoustic index was formulated and calculated using long-term data from Shanghai’s urban green spaces. The results show a significant increase in the acoustic index during spring and summer, peaking during these periods, while a decrease was observed from December to February, dominated by abiotic sounds. Diurnal variations indicate a rapid increase in the acoustic index at sunrise, reflecting heightened avian activity during the dawn chorus. Human interference in the urban center limited acoustic activity, whereas the outer suburbs, with their more natural environments, supported greater acoustic richness.

Integrated Design Methods for Sustainable Public Seating in Urban Communities—A Shanghai Case Study

In the context of sustainable regeneration of urban communities, the sustainable construction of community urban furniture has gradually been emphasized. This study focuses on the existing problems of experience, culture, environmental protection, function, and other aspects of community urban furniture; starts from the user’s perspective to screen the user’s sustainable design needs for community public seating; and combines the scientific method to quantify and transform them into design factors to form a reasonable community sustainable public seating design program. Taking the public seating in Gumei Community Park in Shanghai as an example, the study adopts the qualitative research method to obtain demand indicators of users. It utilizes the integrated design framework of “AHP-QFD-FBS” to quantify the user needs and maps them into the product structure to identify the ten factors affecting the sustainability of public seating. A community co-creation workshop was conducted to complete a sustainability assessment with the help of life cycle assessment and scales. From the perspective of residents’ needs, it emphasizes the scientific process of demand transformation and ultimately produces sustainable design factors and serialized products for public seating. This approach introduces new ideas for the sustainable renewal of urban furniture and enhances the quality of urban residents’ leisure time.

Exploring the coherence and divergence between the objective and subjective measurement of streetscape perceptions at the neighborhood level: A case study in Shanghai

Understanding micro-level perceptions of street scenes is highly concerned with residents’ behaviors and socioeconomic outcomes. While many studies rely on objective measures, such as physical features extracted from Street View Imagery (SVI) to proxy perceptions using derived formulas, others employ subjective measures from visual surveys to capture more subtle human perceptions. We argue that the two measurements can diverge significantly over the same perception concept, which might lead to opposite spatial implications in policy if not properly understood. Moreover, as perceptions are often examined individually, few studies have investigated their joint distribution patterns to reflect perceptions’ multi-dimensional nature. To fill the gaps, we collected five pairwise perceptions from SVIs (i.e., complexity, enclosure, greenness, imageability, and walkability) at the neighborhood level in Shanghai. Each perception consists of pairwise values subjectively measured using a GeoAI-based approach and objectively quantified using formulas. We statistically and spatially compared the coherence and divergence of the two measures, further examining the perceptual differences. Advanced techniques including cluster analysis and factor analysis were employed to jointly evaluate their spatial distribution discrepancy. Our results revealed more differences than similarities between the two measures statistically and spatially, confirming any spatial implications concluded from one approach can vary significantly from the other. The joint spatial pattern further corroborated our conclusions. Our study enriches the literature on micro-level street perception measures, uncovers their critical differences to guide future comparative studies, and offers new approaches for urban perception mapping.

Influencing factors on NLP technology integration in teaching: A case study in Shanghai

Influencing factors on NLP technology integration in teaching: A case study in Shanghai

Temporal insights into mega-events and waterfront industrial heritage transformation: a case study of Shanghai’s Huangpu River industrial zone

This research examines the evolution and renewal of Shanghai’s Huangpu River industrial zone after the 2010 Shanghai Expo, with a temporal focus on the profound changes and development philosophies driven by this mega-event. By investigating emblematic case studies along the Huangpu River, such as the transformative 80,000-ton silo, the Shanghai Museum of Contemporary Art, and the Long Museum, this research articulates how mega-events serve as pivotal moments for reimagining and repurposing industrial heritage. In the wake of the 2010 Shanghai Expo, these industrial relics emerged as focal points of urban regeneration, embodying the tensions and synergies between historical preservation and contemporary urban development. This study explores the temporal layers—from the event’s catalytic role to enduring legacies—and reveals how time influences the trajectory of urban spaces and the community’s connection to them. Through this temporal lens, the paper analyses the redevelopment process, assessing how these initiatives have reconfigured the industrial waterfront into a dynamic cultural landscape. The findings offer a dynamic perspective on the temporal dimensions that underpin the redevelopment of industrial heritage sites, providing insights into how such spaces can be continuously activated and symbiotically integrated into the fabric of the city. This paper aims to contribute to a broader understanding of the complexities involved in harnessing industrial heritage for mega-events, with implications for future urban planning and heritage conservation strategies.

The Nexus Between Real Estate Industry and Economy Growth: Case study of Shanghai

In the 1970s, the theory circle of China put forward the idea of housing commercialization for the first time. After the 1990s, the housing monetization policy began to be implemented. After China opened the door of reform and opening up and the door of urbanization process, the real estate industry also continuously seized the opportunity brought by the reform and opening up to make its own growth. In addition, the real estate industry not only promotes the growth of national economy, but also plays an significant role in improving residents' living quality and seeking benefits for residents. So far, the real estate industry has become the bellwether and main force of China's economic development. The outbreak of the global financial crisis in 2008, followed by 2013, China began to advocate the "new normal" trend of economic development, explore new ways of economic growth and improve the structure of economic growth, which hindered the development of the real estate industry to varying degrees. However, under the macro-background of a series of policies and controls, the real estate industry still plays an immeasurable role in China's economic growth. Therefore, this chapter attempts to carry on a further elaboration in the current macroeconomic background, to clarify the purpose and significance of the research。 In this context, this paper will analyze the relevant data of Shanghai real estate from 1991 to 2021 as the basis. Through the process of data analysis to explain the real estate industry to Shanghai's economic contribution. It also determines whether the relationship between Shanghai real estate industry and economic growth is negative or positive and fills the literature gap between Shanghai real estate industry and economic growth. Provide strong support for future research or policy decision.

Factors influencing housing prices: A case study of Shanghai

Housing is a major consumer good for residents, and housing prices affect people's quality of life and happiness. This paper analyzes the factors influencing housing prices based on the housing price dataset for Shanghai in 2023-2024. Comparison is made via multiple linear regression model to discover the difference between with and without considering interaction terms, assessing the importance and accuracy of the two models' results, and optimizing the model. According to the analysis, living area, decoration type, and building usage are the factors most positively correlated with housing prices. The number of bathrooms, living rooms, and bedrooms also shows a significant positive correlation with housing prices. Additionally, building type and the construction age of the house are negatively correlated with housing prices, and this correlation is very significant. Finally, the housing area weakens the positive impact of the number of bathrooms and bedrooms on housing prices.

Characterizing Temporal Patterns of Intra-Urban Human Mobility in Bike-Sharing through Trip Analysis: A Case Study of Shanghai, China

Human mobility, encompassing the movement of individuals and/or groups across space and time, significantly impacts various aspects of society, with intra-urban mobility being a major research focus of scholars in diverse disciplines. Bike-sharing systems have become an alternatives in cities for achieving more sustainable transportation. Hence, bike-sharing-related data are considered an important data source to study intra-urban human mobility. To better understand human mobility in cities, it is essential to characterize the typical patterns involved in intra-urban human mobility. This paper mainly focuses on characterizing the temporal patterns of intra-urban human mobility on bike-sharing based on the trip information of the acquired bike-sharing data. To achieve this, on the one hand, we adopted an exploratory data analysis (EDA) method to describe the temporal patterns by performing exploratory analyses of bike-sharing trips. On the other hand, we used the continuous triangular model (CTM) to conduct multi-temporal-scale analysis of bike-sharing trips for further explorations of the temporal patterns where necessary. The data of bike-sharing trips in Shanghai, China, were adopted as the dataset for the case study. Generally, the study was conducted at two different levels: the trip level and the bike level. Specifically, at each level, the explorations were conducted from varying perspectives. According to the analyses, numerous meaningful temporal patterns were discovered, and several distinctive findings were acquired. The results of this study show the effectiveness of the EDA and CTM methods in characterizing temporal patterns of intra-urban human mobility, based on which potentially insightful information and suggestions can be provided to assist related actions.

A Two-Stage Evaluation of China’s New Energy Industrial Policy Package

Energy structural transformation plays a strategically important role in achieving the dual-carbon reduction goals. Among the various approaches to carbon reduction, the Chinese government regards the growth of the new energy industry as an essential means. Considering that the government policy support determines the long-term growth of the new energy industry, how to improve and optimize the policy support system has always been the core issue. Based on the fact that policy evaluation is a prerequisite, and the new energy industrial development requires the government to promote solutions in the form of a policy package rather than just individual policies, we investigate whether the implementation of the new energy industry policy package (NEIPP) is effective through an empirical case study of Shanghai. A two-stage evaluation method, which integrates the content analysis method (CAM) and synthetic control method (SCM), was used to empirically evaluate the actual effect of the NEIPP. At Stage One, four policy goals were summarized. SCM was used to identify the pure multi-effect of the NEIPP. The results showed that the NEIPP had a significant positive effect on green economic growth and industrial structure, while having a negative effect on carbon emissions. The NEIPP had no impact on the promotion of technological innovation. Several policy implications were drawn from this study.

Life cycle carbon emission calculation model of energy system in public buildings: A case study in Shanghai

Energy consumption and carbon emissions (CE) in the building sector have grown in importance in relation to global climate change for China's sustainable development. Relatively few research have addressed the embodied CE, despite the fact that many have examined the operational CE from energy system operational use. In order to determine the CE of the energy production, transportation, construction, operation, and recycling stages, we therefore put up an integrated model. An inventory analysis of the energy system's life cycle CE, a scenario forecast of various combinations of building energy system equipment, and a case study of the building energy system of a typical office building in Shanghai's service industry. According to the results, the embodied CE emits 38.01 % of its energy, and the operational CE emits 61.99 %. However, we should not underestimate the significance of the impact of the embodied CE. Among all projection scenarios, the suggested CE share is highest (18.40 %) when the system combination of air-source heat pump units, LED lights, and ground-source heat pump units is implemented. In the end, based on the structural analysis of the embodied CE, low-carbon growth strategies and policy recommendations for Shanghai's service sector will be made.

Measurement of the Public Activity Richness of Urban Park Based on Large Language Models and Social Media Data: A Case Study of Shanghai

Measurement of the Public Activity Richness of Urban Park Based on Large Language Models and Social Media Data: A Case Study of Shanghai

Optimization of reverse logistics network for end-of-life vehicles: A Shanghai case study

With the surge in car ownership, the end-of-life vehicles recycling market has shown enormous development potential. As the reverse logistics network for recycling end-of-life vehicles suffers from high operating costs and low recycling rates, there is an urgent need to upgrade the actual recycling measures for end-of-life vehicles to an operable level. This article first uses the OGM (1, N) model to predict the number of end-of-life vehicles in the coming years. At the same time, a reverse logistics network model with the second-hand car market as the recycling centre was constructed with the goal of minimizing the total cost of the end-of-life vehicles reverse logistics network. The network model was simulated using mixed integer programming (MILP), and the optimal solution was solved through LINGO 12 programming. Through an example analysis of Shanghai, it is found that the market of end-of-life vehicles will embrace growth, and it is verified that the optimized reverse logistics network can effectively reduce the operation cost and logistics cost of recycling centres, and can effectively improve the actual recycling rate of end-of-life vehicles. Finally, the optimized site selection results are obtained, and a specific traffic distribution scheme is proposed, which is crucial for promoting cars that meet scrap standards to be recycled through formal channels and reducing logistics costs for recycling enterprises.

Combining statistical and hydrodynamic models to assess compound flood hazards from rainfall and storm surge: a case study of Shanghai

Abstract. Coastal regions have experienced significant environmental changes and increased vulnerability to floods caused by the combined effect of multiple flood drivers such as storm surge, heavy rainfall and river discharge, i.e., compound floods. Hence, for a sustainable development of coastal cities, it is necessary to understand the spatiotemporal dynamics and future trends of compound flood hazard. While the statistical dependence between flood drivers, i.e., rainfall and storm surges, has been extensively studied, the sensitivity of the inundated areas to the relative timing of a driver's individual peaks is less understood and location dependent. To fill this gap, here we propose a framework combining a statistical dependence model for compound event definition and a hydrodynamic model to assess inundation maps of compound flooding from storm surge and rainfall during typhoon season in Shanghai. First, we determine the severity of the joint design event, i.e., peak surge and precipitation, based on the copula model. Second, we use the same frequency amplification (SFA) method to transform the design event values in hourly time series so that they represent boundary conditions to force hydrodynamic models. Third, we assess the sensitivity of inundation maps to the time lag between storm surge peak and rainfall. Finally, we define flood zones based on the primary flood driver, and we delineate flood zones under the worst compound flood scenario. The study highlights that the temporal delay between storm surge and rainfall plays a pivotal role in shaping the dynamics of flooding events. More specifically, that the peak rainfall occurs 2 h before the peak storm surge would cause the deepest average cumulative inundation depth. At the same time, the results show that in Shanghai surge is the primary flood driver. High storm surge at the eastern part of the city (Wusongkou tidal gauge) propagates upstream in the Huangpu River, resulting in fluvial flooding in Shanghai city center and several surrounding districts. This calls for a better fluvial flooding control system hinging on the backwater effect during high surge in the upper and middle Huangpu River and in the newly added urbanized areas to ensure flood resilience. The proposed framework is useful to evaluate and predict flood hazard in coastal cities, and the results can provide guidance for urban disaster prevention and mitigation.

Disaster loss index development and comprehensive assessment: A case study of Shanghai

Accurate measurement of socio-economic loss and the impact of disasters is crucial for effective risk assessment and management. This study introduces a Disaster Severity Index (DSI) and a Disaster Impact Index (DII), along with a composite severity matrix, to evaluate comprehensive disaster losses. By utilizing seven loss indicators across six types of natural disasters and socioeconomic indicators, we thoroughly assessed Shanghai’s historical disaster losses from 1978 to 2020. Our analysis reveals that Shanghai’s most severe annual disaster losses occurred in 1991 and 2005; however, the overall impact on the local socio-economy has been declining. According to the DSI, Chongming (0.88), Songjiang (0.64), and Qingpu (0.51) Districts exhibit the highest severity. In terms of the DII, Songjiang (0.87), Chongming (0.71), and Qingpu (0.64) Districts are most affected. The comprehensive disaster severity grading indicates that Chongming and Songjiang Districts experience the most severe impacts, while Huangpu and Xuhui Districts are less affected. The spatial distribution of disaster losses is concentrated in suburban areas, with less impact in the central city. Our methodology provides a framework for analyzing and comparing historical disaster losses in terms of time (inter-annual), space (administrative divisions), and types of disasters. It can also be used for statistical analysis and regular monitoring of disaster losses. This study not only elucidates the spatiotemporal distribution of historical disaster losses in Shanghai but also validates the efficacy of our comprehensive index models.

Research on the Development Characteristics of Urban Commercial Districts in the Consumer Society: A Case Study of Shanghai

With the advent of the consumer era, the spatial structure of urban areas in China has undergone significant changes, exhibiting new development characteristics. This study aims to investigate the consumer space structure, functional structure, and consumer demand from three dimensions. By examining the development history, architectural space, and community form, as well as studying the basic attributes and behavioral characteristics of consumers, it summarizes that Shanghai’s commercial communities demonstrate a mutual penetration of consumption and non-consumption. The need for a community-oriented, experiential integration of commercial formats is evident in these areas.

Regional Seismic Damage Prediction of Buildings Based on Bayesian Network and Community Information Database: A Case Study in Shanghai

ABSTRACT The development of the Community Information Database (CID) provides an opportunity to enhance the accuracy of predicting regional seismic damage. The CID includes fundamental attributes of buildings and daily operation information such as maintenance record, loading variation, and structural defect inspection. However, existing models cannot leverage the daily operational information of the CID to calibrate the real-time seismic performance of regional buildings. In this study, a novel Bayesian network (BN) model is proposed to assess the regional seismic damage of buildings based on information provided by the CID. Buildings in an area in Shanghai, China, are selected to investigate the applicability and accuracy of the proposed model. The investigation indicated that the proposed model can synthesize seismic fragility curves and matrices for various building types and calibrate the prediction based on daily operational information such as structural defect, structural alteration, and property management. If the CID has missing building attributes, the proposed model can also utilize an embedded subnetwork to supply the database. Therefore, the proposed model integrates more comprehensive information than the traditional methods to enhance the accuracy of predicting the regional seismic damage.

Research on the impact of colleges’ English education on regional economic development: A case study of Shanghai and Jiangsu province

In the era of globalization of the knowledge economy and significant global population mobility, language serves not only as a tool for acquiring and exchanging information but also as a bridge and conduit for the dissemination and promotion of technology, culture, and knowledge on a global scale. Language can serve as both a tool to acquire other knowledge and skills, forming human capital, and can also be directly used to serve society, bringing about relative economic benefits to both the nation and individuals. The world language, English, with its unique advantages of spanning regions and borders, widely disseminates various technological, cultural, and economic information. With the increasing integration of the global economy and the development of regional economies in China, there is a growing and strong interactive relationship and interdependence between college English education and regional economic development. This paper selects relevant data from Shanghai and Jiangsu Province over the past decade and, through correlation analysis and regression analysis, establishes a significant correlation between colleges English teaching and regional economic development. It proves that college English teaching has become an important factor in promoting sustainable regional economic development. Based on this conclusion, it proposes the concept that colleges of English teaching and regional economic development should support and promote each other, achieving harmonious development and mutual progress.

Impact of sudden public crises on spatial distribution patterns and driving factors of the urban catering industry: a case study of Shanghai’s catering POI data before and after COVID-19

ABSTRACT This study uses Shanghai to explore the effects of the COVID-19 pandemic on the spatial distribution patterns and driving factors of the urban catering industry. Through quantitative analysis of restaurant point-of-interest data and influencing factors in Shanghai’s main urban area from 2016 to 2022 using geographic information technology, machine learning, and spatial econometric models, this study predicts spatial changes in the catering industry. The number of restaurants in Shanghai’s main urban area continuously decreased from 2016 to 2022, with a significant pre-pandemic decline. The catering industry in this area has a significant spatial correlation in the spatial distribution, showing a pattern of “one core dominance with multiple cores coexisting,” with Jing’an and Huangpu Districts having the highest densities, which is expected to continue. Target markets remain a decisive factor in restaurant location selection post-COVID. Restaurant aggregation is most favorable when the population density is between 0 –50,000 people/km2, GDP is between 0–20 billion yuan/km2, housing prices are between 20,000 –130,000 yuan/m2, school density is between 0–20/km2, hospital density is between 0–10/km2, and attraction density is between 0–40/km2. Transportation conditions have no apparent threshold; the more developed the transportation, the more favorable the conditions for the catering industry. Post-COVID-19, areas with high housing prices and around tourist attractions are less likely to attract many restaurants. Areas around hospitals maintain restaurant aggregation, although this will decrease. Areas around schools will become popular for restaurants in the future.