The purpose of this paper is to analyze raw materials, labor, capital, demand, related industries, strategies and policies influencing international competitiveness of Chinese textile and clothing industry.,The analysis is conducted using “Diamond Model”, in which raw materials, labor, capital, demand, related industries, strategies and policies are included as explanatory variables, and the impacts of international competitiveness on market share (MS), trade competitiveness(TC) and revealed comparative advantage(RCA) are examined based on the estimated coefficients of these variables.,These factors have different effects on TC, MS and RCA. While their effects on TC and MS are similar in sign even though their degree of significance differs, their effects on RCA are opposite to TC and MS except for capital. Raw materials and capital have negative effects on TC and MS, while the other factors have positive ones. Raw materials have positive effects on RCA, but all other factors have negative ones.,The results from this study imply that it is necessary to increase investment in fixed assets of Chinese textile and clothing industry, speed up the pace of upgrading equipment, improve the level of industrialization, while strengthening the supply of textile raw materials, and lowering raw material prices, thereby reducing the cost of textile and clothing enterprises.,To the best of the authors’ knowledge, this is the first empirical research made using econometric model about the impact of the main factors of trade competitiveness in Chinese textile and clothing industry based on the “Diamond Model”.

International competitiveness of Chinese textile and clothing industry – a diamond model approach

This study examines the impact of different types and processes of urban renewal on the urban heat island (UHI) effect. The research categorizes renewal projects based on changes in buildings, underlying surfaces, and functions. Using the Spearman correlation coefficient and LOWESS method, the study analyzes the relationships between cooling effects and impact factors. The results reveal that transforming industrial areas into commercial or residential zones and transitioning from compact mid-rise to open high-rise structures have significant cooling effects. However, the renewal implementation of the latter transformation can exacerbate the local UHI, suggesting the need for optimizing the timeline of such projects. Increasing vegetation cover plays a crucial role in mitigating the UHI, while higher floor area ratios and building volumes do not necessarily intensify the UHI. To improve the urban ecosystem, urban renewal planning should prioritize the creation of blue and green spaces, incorporation of natural infrastructure, and reduction of impervious surfaces. These findings have implications for urban renewal policies, selection of preferred renewal types, and insights into the renewal process. 

Impact of urban renewal on urban heat island: study of renewal processes and thermal effects.

As urban redevelopment becomes an essential instrument for further urban development, the spatial outcomes of these redevelopment activities exert an increasingly profound impact on urban development. Unlike past state-dominated urban redevelopment, current market-oriented redevelopment activities are becoming more active, while the government continues to play an important role through various forms of intervention. To optimise the development of urban space, a comprehensive understanding of the effect of government interventions on the spatial variations of market-oriented redevelopment activities is required. Against the background of Shenzhen's market-oriented urban village redevelopment, this study formulated a theoretical framework to identify the core government interventions in terms of urban planning, development intensity control, and decentralisation, and then analysed how they affect the market-oriented redevelopment activities from a spatial perspective. Ordinary least squares regression and geographically weighted regression models were employed to conduct an empirical analysis to measure the specific impact of diverse government interventions. The results show that the planned transport routes, public facilities, and density zones can effectively guide the urban village redevelopment projects towards the future core development areas of a city. The introduction and implementation of Shenzhen's decentralisation of urban redevelopment have promoted urban village redevelopment and have resulted in significant differences in redevelopment activities dominated by market forces across administrative districts. It provides practical implications for implementing proper government interventions for the sustainable spatial development of redevelopment activities. 

Measuring the impact of government intervention on the spatial variation of market-oriented urban redevelopment activities in Shenzhen, China

Urban renewal is a critical avenue and strategic tool for achieving high-quality and sustainable development, and the residential market plays a vital role in promoting urban renewal and urban growth. However, the impact of urban renewal on housing prices remains inconclusive, closely tied to the characteristics of the study area, the sources of research data, and so on. To address this, we employ the difference-in-difference method and a mixed panel dataset of housing transactions from 2010 to 2021 to analyze in detail the effects of different urban renewal types (Industrial Renewal, Residential Renewal, and Commercial Renewal) on surrounding housing prices in Bao'an District at different renewal phases (announcement, start, and completion). We found that Industrial Renewal exerts the most significant impact on housing prices at the beginning and completion of renewal, followed by Residential Renewal and Commercial Renewal. Moreover, Urban renewal generates both positive and negative externalities on housing prices, especially in the case of numerous small-scale renewal projects. The findings suggest that urban renewal should be supported by systematic research on renewal types, the establishment of scale entry threshold, and the monitoring of the entire process. 

Typological differentiation and time-series effects of urban renewal on housing prices

Increasing residential segregation is emerging as a hindrance to urban sustainability. Urban renewal projects that claim alignment with sustainable development goals still lack comprehensive studies of their impact on social segregation, as evidenced by the ongoing scholarly debate over whether urban renewal has a positive or negative effect on social segregation. This paper explores the dynamics of urban spatial segregation, analyzes the role of urban renewal on segregation, and bridges the gap in existing research by considering dynamic changes, multiple spatial scales, and diverse renewal types. Using multi-source data – house price data, planning permit data and points of interest –stepwise regression models are combined with t-test methods to examine the impact of multiple types of urban renewal on local and regional residential segregation in Shenzhen. Our findings are as follows: 1) Income-based segregation in Shenzhen increased from 0.77 to 0.81 across neighborhoods, from 0.62 to 0.73 across sub-districts, and from 0.58 to 0.67 across districts between 2000 and 2020, therefore increasing at all scales but with more pronounced growth of segregation observed between units at larger scales; 2) Urban renewal can lead to greater income similarity amongst residents of a sub-district, by attracting more high-income people to move in, but this can lead to increased residential segregation of high- and low-income people at the macro-scale. 3) When assessing the impact of urban renewal on segregation, it is recommended to consider the variations in outcomes resulting from temporal changes, spatial scales, the types of renewal, the types of segregation, and the stages of urbanization. Understanding this process can help promote socially sustainable urban renewal projects. 

How does urban renewal affect residential segregation in Shenzhen, China? A multi-scale study

Exploring the drivers of urban renewal through comparative modeling of multiple types in Shenzhen, China

The spatial heterogeneity and dynamics of land redevelopment: Evidence from 287 Chinese cities

Self-similar growth and fractality are important properties found in many real-world networks, which could guide the modeling of network evolution and the anticipation of new links. However, in technology-convergence networks, such characteristics have not yet received much attention. This study provides empirical evidence for self-similar growth and fractality of the technology-convergence network in the field of intelligent transportation systems. This study further investigates the implications of such fractal properties for link prediction via partial information decomposition. It is discovered that two different scales of the network (i.e., the micro-scale structure measured by local similarity indices and the scaled-down structure measured by community-based indices) have significant synergistic effects on link prediction. Finally, we design a synergistic link prediction (SLP) approach which enhances local similarity indices by considering the probability of link existence conditional on the joint distribution of two scales. Experimental results show that SLP outperforms the benchmark local similarity indices in most cases, which could further validate the existence and usefulness of the synergistic effect between two scales on link prediction.

/pdf/self-similar-growth-and-synergistic-link-prediction-in-28tciww0.pdf

Self-Similar Growth and Synergistic Link Prediction in Technology-Convergence Networks: The Case of Intelligent Transportation Systems

This paper analyzes the competitiveness of Beijing’s cultural creative industries, investigates the overall competitiveness of Beijing’s cultural creative industries in the international market share, and reveals the comparative advantage and industrial competitiveness of Beijing’s cultural creative industries in cultural creative products and cultural creative services. This study comprehensively evaluates the competitiveness of Beijing’s cultural creative industries.

/pdf/analysis-on-the-international-competitiveness-of-beijing-s-16tdp5ghga.pdf

Analysis on the International Competitiveness of Beijing’s Cultural Creative Industries

Artificial neural network algorithm has strong nonlinear mapping function. BP neural network algorithm is the representative of artificial neural network algorithm. Due to the relatively small scale of small, medium, and micro enterprises and lack of mortgage assets, the biggest market risk they usually face is credit risk. In order to avoid huge economic losses for banks, the impact of risk analysis on credit decision-making is the key. Therefore, the establishment of a scientific and complete credit risk assessment system has become the primary task. This paper mainly uses BP neural network algorithm to analyze the risk of small and medium-sized enterprises and solve the problem of credit decision-making. First, analyze the various influencing factors that cause credit risk, and layer the factors according to the degree of risk; secondly, use the fuzzy comprehensive evaluation method in mathematical modeling to rank each factor; then, use the fuzzy analytic hierarchy process to calculate the weight of each indicator factor as calculated by establishing the risk value function, using the function expression of the annual interest rate and the total credit formula to calculate the total credit, which solves the problem of the loan line of each enterprise, and use the optimal linear programming to give priority to the selection of the line and the interest rate. Enterprises: finally, for enterprises that do not have a credit rating, reasonable adjustments are made to the quota by establishing lending qualification expression, taking into account the impact of unexpected external factors, establishing an improved annual interest rate function, and achieving an optimized credit strategy through the establishment and solution of the model. The goal of optimizing credit strategy has been achieved.

Study on Risk Analysis and Decision-Making of Small- and Medium-Sized Enterprises on BP Neural Network Algorithm

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