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A special‐purpose Committee on DNA Sequences as Types was established at the XIX International Botanical Congress (IBC) in Shenzhen, China, in 2017, with a mandate to report to the XX IBC in Madrid in 2024 with recommendations on a preferred course of action with respect to potential amendments of the International Code of Nomenclature for algae, fungi, and plants to allow DNA sequences as types. This is the first in an expected series of papers from the Special‐purpose Committee on this issue. We set out the background to the establishment of the Committee, explore key issues around typification that are pertinent to the question of DNA sequences as types, enumerate pros and cons of allowing DNA sequences as types, and foreshadow options for future discussion and potential recommendations. [ABSTRACT FROM AUTHOR]

Background: The Longshi Scale is a pictorial assessment tool for evaluating activities of daily living (ADL) in patients with stroke. The paper-based version presents challenges; thus, the WeChat version was created to enhance accessibility. Herein, we aimed to validate the inter-rater and test–retest reliabilities of the WeChat version of the Longshi Scale and explore its potential clinical applications. Methods: We recruited 115 patients with stroke in the study. The ADL results of each patient were assessed using both the WeChat and paper-based version of the Longshi Scale; each evaluation was conducted by 28 health professionals and 115 caregivers separately. To explore the test–retest reliability of the WeChat version, 22 patients were randomly selected and re-evaluated by health professionals using the WeChat version. All evaluation criteria were recorded, and all evaluators were surveyed to indicate their preference between the two versions. Results: Consistency between WeChat and the paper-based Longshi Scale was high for ADL scores by health professionals (ICC2,1 = 0.803–0.988) and caregivers (ICC2,1 = 0.845–0.983), as well as for degrees of disability (κw = 0.870 by professionals; κw = 0.800 by caregivers). Bland–Altman analysis showed no significant discrepancies. The WeChat version exhibited good test–retest reliability (κw = 0.880). The WeChat version showed similar inter-rater reliability in terms of the ADL score evaluated using the paper-based version (ICC2,1 = 0.781–0.941). The time to complete assessments did not differ significantly, although the WeChat version had a shorter information entry time (P < 0.001, 95% confidence interval: –43.463 to –15.488). Health professionals favored the WeChat version (53.6%), whereas caregivers had no significant preference. Conclusions: The WeChat version of the Longshi Scale is reliable and serves as a suitable alternative for health professionals and caregivers to assess ADL levels in patients with stroke. The WeChat version of the Longshi Scale is considered user-friendly by health professionals, although it is not preferred by caregivers. Trial registration: This study was approved by the Ethics Committee of the Second People's Hospital of Shenzhen (approval number: 20210812003-FS01) and registered on the Clinical Trial Register Center website: clinicaltrials.gov on January 31, 2022 (registration no.: NCT05214638). [ABSTRACT FROM AUTHOR]

Momentum-based strategies are widely used by asset managers and have attracted considerable research interest. This paper studies industry momentum from the perspective of correlation consolidation, which consolidates industries according to the correlation coefficient of their historical returns and assesses momentum effects after the consolidation. Studying all Chinese stocks listed on the Shanghai and Shenzhen A-share market with a sample range from June 1, 2007, to December 31, 2020, empirical results show that monthly returns of the industry momentum and Sharpe ratio after the correlation consolidation both increase. The optimal method for consolidating industries is to use the correlation coefficient of 0.75, which increases the Sharpe ratio from 0.71 before the correlation consolidation to 1.16. [ABSTRACT FROM AUTHOR]

This paper takes the establishment of the Green Financial Reform and Innovation Pilot Zone (GFPZ) in 2017 as a natural experiment, adopts the data of a-share industrial listed enterprises in Shanghai and Shenzhen from 2010 to 2020, and utilizes the difference-in-differences (DID) method to carry out empirical tests. The results show that (1) GFPZ policy significantly improves the environmental, social, and governance (ESG) performance of enterprises, and the positive effect is mainly realized by improving the external financing ability and green-technology innovation level of enterprises. (2) There is heterogeneity in the impact of GFPZ policy on the ESG performance of firms with different equity natures and internal control levels. (3) Green finance promotes active corporate social responsibility, and it can further improve environmental governance in the regions where it operates. This paper provides a useful supplement to the comprehensive understanding of green-finance policy effects and ESG impact factors, and it is of great significance in mitigating the negative environmental and social externalities caused by the excessive pursuit of economic benefits by enterprises. [ABSTRACT FROM AUTHOR]

Compared with financial information, whether corporate social responsibility disclosure has impacts on debt financing cost has obviously become a heated topic in the academic. This paper selects A-share listed companies in Shanghai and Shenzhen stock markets of China from 2013 to 2017 as sample to study the impact of corporate social responsibility disclosure on debt financing cost, including bond financing cost and bank loan cost. In addition, this paper divides the sample into voluntary corporate social responsibility disclosure group and mandatory corporate social responsibility disclosure group and studies whether the effects of voluntary corporate social responsibility disclosure and mandatory corporate social responsibility disclosure on bond financing cost and bank loan cost are different. The empirical results are presented as follows: Firstly, enterprise disclosing high-quality corporate social responsibility report is more conducive to reducing the debt financing cost. Specifically, corporate social responsibility disclosure significantly lowers both the bond financing cost and bank loan cost. Moreover, the reduction impact of corporate social responsibility disclosure on bond financing cost is greater than that of bank loan cost. Secondly, enterprises voluntarily disclosing corporate social responsibility reports are more conducive to reducing the debt financing cost than that of enterprises mandatorily disclosing corporate social responsibility reports. Thirdly, non-state-owned enterprises are more conducive to reducing debt financing cost than that of state-owned enterprise. The enterprises with more market competition are more conducive to reducing the debt financing cost than the oligopolistic enterprises. Finally, this paper concludes and gives policy implications. This paper amplifies the literature regarding the economic consequences of corporate social responsibility disclosure and improves the understanding of the impact of corporate social responsibility disclosure on debt financing cost. [ABSTRACT FROM AUTHOR]

China is facing a serious land resource mismatch problem, which will profoundly affect the acceleration of economic growth and technological innovation. Reform of the industrial land allocation system can solve the mismatch of land resources, and that also has an important impact on the promotion of economic and technological development. This paper selects the data of Chinese A-share listed companies in Shanghai and Shenzhen from 2007 to 2020 as the research sample, constructs a double machine learning model, and empirically investigates the impact of a new industrial land use policy on firms' green innovation behavior. The study shows that: (1) the new industrial land use policy significantly promotes firms' substantive and strategic green technological innovation, and the effect on substantive green technological innovation is greater than that on strategic green technological innovation. (2) The enhancement of R&D investment sustainability and the "talent pool" effect are important mechanisms through which the new industrial land use policy influences firms' substantive and strategic green technological innovation. Meanwhile, the new industrial land use policy is conducive to firms' green coinnovation. (3) There is heterogeneity in the effect of the new industrial land use policy, which can significantly promote green technological innovation of firms in the eastern region, while it does not play a significant role in the green innovation behavior of firms in the central and western regions. The above research results enrich the research in the field of industrial land and innovation, help to understand more comprehensively the mechanism of new industrial land affecting firms' green technological innovation, and provide policy insights for strengthening the application of industrial land allocation reform in firms' green innovation. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the impact of digital finance on the breakthrough innovation of enterprises with a sample of A-share listed companies in Shanghai and Shenzhen from 2011 to 2022. It is found that digital finance can promote corporate breakthrough innovation, and presents certain structural heterogeneity characteristics. The mechanism test shows that digital finance has the dual attributes of a financing platform and a social platform, which can promote breakthrough innovation by alleviating corporate financing constraints and expanding corporate social networks. Heterogeneity analysis reveals that the role of digital finance in promoting breakthrough innovation is characterized by regional heterogeneity, with digital finance playing a greater role in promoting breakthrough innovation in provinces with a low level of development of the banking sector, provinces with a high level of development of the capital market sector, and the central region. In addition, the degree of firms' external financing dependence and the degree of product market competition can strengthen the positive effect of digital finance on firms' breakthrough innovation. This paper enriches the related research on the impact of digital finance on enterprise innovation, and provides theoretical basis and policy insights on how digital finance can better assist the innovation-driven development strategy. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of Internet infrastructure construction on enterprise transformation and upgrading and the underlying mechanisms using a progressive double difference model based on a quasi-natural experiment of the Chinese government's "broadband China" policy by matching A-share listed companies and city panel data from 2008–2019 in Shanghai and Shenzhen. The conclusions show that the "broadband China" policy can significantly promote the transformation and upgrading of enterprises in pilot cities. However, its effect shows a diminishing marginal contribution, and the policy is more effective for traditional manufacturing industries during the implementation period. Enhancing human capital and reducing internal transaction costs are two important channels for Internet infrastructure construction to help enterprises transform and upgrade. Combined with the life cycle theory, we find that the "broadband China" policy has the most significant impact on changing and upgrading enterprises in the growth and maturity stages, especially those in the manufacturing industry, but not those in the maturity and decline stages of the service industry. Finally, a series of robustness tests using Monte Carlo simulation, entropy balance method, and instrumental variables method, excluding other factors, show that the findings are still robust. [ABSTRACT FROM AUTHOR]

Purpose: Innovation is the most important quality of enterprise management. It is an important and controversial issue whether the heterosexual leadership structure of the chairman and chief executive officer (CEO) makes the work "easy" or "very tired" in enterprise innovation. This study investigates the specific impact of the heterosexual leadership structure on enterprise innovation investment, and further explores influence mechanism between them from two perspectives. Specifically, from the perspective of enterprise leaders including the chairman and CEO, this paper analyzes the impact of surname sharing, intergenerational differences and top management team (TMT) external social network between the heterosexual leadership structure and enterprise innovation investment. And from the perspective of enterprise itself, this study explores the impact of ownership and organizational slack between the heterosexual leadership structure and enterprise innovation investment. Design/methodology/approach: By using ordinary least squares regression (OLS), this study mainly takes the unbalanced panel data of A-share listed companies from 2008 to 2019 in Shanghai and Shenzhen as the research sample to empirically analyze the relationship and influence mechanism between the heterosexual leadership structure and enterprise innovation investment. Findings: The results show that the heterosexual leadership structure of the chairman and CEO has a negative impact on enterprise innovation investment. Surname sharing and ownership positively moderate the negative impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment. Intergenerational differences and TMT external social network negatively moderate the relationship between the heterosexual leadership structure of the chairman and CEO and enterprise innovation investment. In addition, the moderating effects of intergenerational differences and TMT external social network on the relationship between the heterosexual leadership structure and enterprise innovation investment both depend on organizational slack. When organizational slack is lower and intergenerational differences are higher, the negative impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment will be the strongest. And when organizational slack is lower and TMT external social network is higher, the negative impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment will be the strongest. Originality/value: By exploring the influence and the boundary mechanism of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment, the "heterosexual difference effect" is verified in this paper, that is, when men and women work together, work is very tired. This not only enriches the existing research of enterprise innovation investment, but also provides practical guidance for effectively improving enterprise innovation investment from a new perspective. In addition, it broadens the moderating mechanism of the impact of the heterosexual leadership structure of the chairman and CEO on enterprise innovation investment, which is conducive to reasonable response to improve enterprise innovation investment. [ABSTRACT FROM AUTHOR]

Digital transformation plays a crucial role in improving the quality development of companies in this era of digital economy with ever-changing technologies. This paper empirically investigates the impact of corporate digital transformation on total factor productivity and the mechanism of action, using A-share listed companies in Shanghai and Shenzhen from 2011–2021 as the research sample, and found that the digital transformation of companies significantly improves total factor productivity, with the plausibility of the findings being verified by a series of robustness tests. Based on the heterogeneity study, it is found that such effect is stronger for private companies, non-high-tech companies, and companies with a high degree of industry competition. The mechanism test indicates that digital transformation facilitates total factor productivity through four ways: strengthening company technological innovation, reducing operational costs, increasing resource allocation efficiency, and improving human capital structure. The findings of this paper support a better understanding of the micro effects of digital transformation and provide empirical evidence for policy formulation and adjustment. [ABSTRACT FROM AUTHOR]

Prior literature finds senior executives can influence auditor decision making. However, few studies have discussed the impact of employee's personal characteristics. Our research aims to fill the above research gaps by examining the impact of employee level education on audit costs. Taking A-share listed companies in Shanghai and Shenzhen from 2006 to 2021 as the research object, this paper examines the impact of employee education on audit fees. It is found that highly educated employees can effectively reduce the audit fees borne by the company, but the implementation of the Labor Protection Law weakens this inhibitory effect. In the case of low marketization level and weak Confucian culture intensity, employee education level has a more significant inhibitory effect on audit fees of listed companies. This study provides a basis for empirical research on the impact of employee attributes on auditor decision making, provides a new research perspective on the impact of labor protection law at the corporate micro level, and enriches the theoretical research on corporate governance rooted in traditional Chinese culture. We contribute to the practice that implications for evaluating the effectiveness of adopting labor protection. [ABSTRACT FROM AUTHOR]

Bikeshare, as a convenient transport mode, can address the first- and last-mile travel needs of metro trips while generating many environmental benefits, such as reducing the use of environmentally unfriendly transport modes and lowering the carbon emissions of the urban transportation system. This paper takes bikeshare as a feeder mode of metro stations (BS-FMMS) as the research object and compares the spatial and temporal differences in the carbon emission reduction benefits of BS-FMMS on workdays and non-workdays by using the framework of BS-FMMS carbon reduction benefit analysis and the methods of time-series analysis, spatial aggregation analysis, and box plot analysis. The results show that the carbon emission reduction benefit of bikeshare has obvious morning and evening peaks on workdays, while it tends to be stable without obvious peaks during the day on non-workdays. From the perspective of spatial distribution, the carbon emission reduction benefits of BS-FMMS are more significant in the metro station areas in the south of Baoan district, the west of Nanshan district, the central of Longhua district, and the south of Futian district in Shenzhen city, and the metro stations where the carbon emission reduction benefits of the non-workday are greater than those of the workday are mainly concentrated in Nanshan district, Futian district, and Luohu district. There is a significant positive correlation between BS-FMMS ridership and carbon emission reduction. These findings can provide clear policy implications for the decarbonization development of urban transportation systems. [ABSTRACT FROM AUTHOR]

Financial balance is a requisite for the sustained operation of urban regeneration projects in the stock-based planning period. From the perspective of financial balance, this paper analyzes the operation strategy and mechanism of the LM Apartments Project in Shuiwei Village of Shenzhen from four aspects: the financial input in the initial stage, the revenue and expenditure in the operational stage, the financial relationship between multiple stakeholders, and the control of non-financial costs. The findings reveal that under the tripartite cooperation between the government, the state-owned enterprise, and the village collective, the LM Apartments Project in Shuiwei Village is a model of urban village regeneration that effectively supplements Shenzhen's government-subsidized housing system. Of the three parties, the government provides policy support and asset-light investment; Shum Yip Group, a state-owned enterprise, has carried out innovative practices of urban village regeneration while making a small profit; the Shuiwei village collective has achieved sustained economic benefits and a high-quality living environment. The paper further discusses the external effects of this practice and probes into the conditions for the wide application of this mode in the hope of providing a useful reference for promoting the application of the financial balance mechanism in urban village regeneration projects. [ABSTRACT FROM AUTHOR]

The current cases and studies show that the aerosol propagation of COVID-19 is possible in the office buildings. The paper explored the ventilation level and monitoring methods for indoor infection risk in office buildings, improved the Wells-Riley equation and ventilation rate equation, providing the possibility of real-time monitoring of the transmission risk of COVID-19 in office buildings. Then, the main influencing factors of the exposure risk of SARS-CoV-2, including working density, dwell time, and fresh air volume per person, were field measured in three office areas and three conference rooms of an office building in Shenzhen, China. In addition, the field monitored carbon dioxide (CO2) data were used to estimate the possibility of COVID-19 infection in offices and conference rooms. The results show that the number of staff, ventilation rate, and office hours are all important factors affecting the infection risk of workers in the office building environment, but the existing literature rarely considers these three points at the same time. In addition, the paper adopted the method of assessing the infection risk from place to place, time to time, and person to person in the building environment, providing early warning for office buildings and helping to control the spread of airborne diseases. The results can be beneicial to understanding and taking necessary safety considerations against the infection risk in closed public or governmental environments. The paper explored the ventilation level and monitoring methods for indoor infection risk in office buildings and improved the Wells-Riley equation and ventilation rate equation, providing the possibility of real-time monitoring of the transmission risk of COVID-19 in office buildings. The results showed that the number of staff, ventilation rate, and office hours are all important factors affecting the infection risk of workers in the office building environment, but the existing literature has rarely considered these three points at the same time. Meanwhile, research has further demonstrated the connection between the risk of virus infection and indoor monitoring environmental indicators, providing a new path for further accurate prediction of indoor infection risk. The results can be beneficial to understanding and taking necessary safety considerations against the infection risk in closed public or governmental environments. Therefore, evaluating indoor transmission risks through monitoring environmental indicators is feasible and could be used as a reference basis for practical applications. [ABSTRACT FROM AUTHOR]

Enterprise Digital Intelligence Transformation is based on the Digital Conversion of information and process service upgrading, further touching the enterprise's core business, with the goal of building a new business model of Digital Intelligence Transformation at a higher level. Based on dynamic capability theory, this paper conducts an in-depth study on the mechanism of enterprise Digital Intelligence Transformation and firm performance. This paper selects manufacturing companies listed in China's Shanghai and Shenzhen A-shares from 2013 to 2022 as the research sample, and analyzes and tests the sample data using empirical research methods in order to explore the actual impact of Digital Intelligence Transformation on firm performance, including the specific pathways of action and moderating effects. This study helps enterprises to positively face the megatrend of Digital Intelligence Transformation and upgrading and the challenges it brings, and to grasp the new opportunities in the digital era. This study finds that enterprises carry out digital empowerment transformation and development strategies, and implement information Digital Conversion, service upgrading, and Digital Intelligence Transformation to promote firm performance to different degrees. Enterprise innovation resilience has a mechanism effect between information digitalization conversion enterprise performance and process service upgrading enterprise performance. The higher the environmental uncertainty, the greater the positive contribution of information digitalization to firm performance. Digital Conversion is the base and service upgrading is the process. The current sample enterprises have limited years of data collection, and most of them have only carried out the strategic implementation of Digital Conversion or servitization, and have not reached the high-level stage of digital and intellectual transformation. Therefore, it is found that enterprise innovation resilience has not yet shown a significant role mechanism effect between digital–intelligent transformation and enterprise performance at present. And environmental uncertainty has not yet shown a significant moderating effect in the stage of Servitization Upgrading and digital–intelligent transformation. The marginal contributions of this paper are mainly reflected in the following: (1) This study introduces the dynamic capability theory to explore the role of Digital Intelligence Transformation (Digital Conversion + service upgrading) on enterprise performance. (2) This paper investigates the role of Digital Intelligence Transformation in influencing the performance of enterprises from the Digital Conversion and service upgrading phases, and enriches the relevant role and regulatory mechanisms. (3) This study provides new ideas and strategic suggestions on Digital Intelligence Transformation for enterprises with different factor intensities, at different stages of development, and in different regions. [ABSTRACT FROM AUTHOR]

Qianhai—an innovation park in Shenzhen—has the possibility of boosting innovation in Hong Kong, Shenzhen and in the wider region. This paper reviews the existing evidence about which policies have promoted profitable innovation in the Qianhai region (Hong Kong and Shenzhen) in the past. We also point to the importance of profitable innovation—rather than just innovation for its own sake. Profits attract and keep firms in an international financial centre. Yet, until we know exactly how much profitability these innovative firms require and how to promote such profitability, the advice given in the literature to Qianhai's and other policymakers will remain woefully inadequate. [ABSTRACT FROM AUTHOR]

Smart city construction is crucial for regional economic development, and the micro-level impact of such construction on business operations cannot be ignored. Based on the panel data of Shanghai and Shenzhen A-share listed companies from 2008 to 2020, this paper investigates the relationship between smart city construction and firm performance and its mechanism of action. The study findings show that (1) smart city construction significantly improves enterprise performance; (2) the improvements are significant across all industries and regions; and (3) the impact of smart city construction on small and medium-sized enterprises (SMEs) and nonstate enterprises is more significant than that on large enterprises and state-owned enterprises. These findings provide a theoretical framework and fresh perspectives for encouraging coordinated regional development and new urbanization construction. [ABSTRACT FROM AUTHOR]

To explore the relationship between air pollution and total factor productivity and new pathways, This paper examines the impact of air pollution on total factor productivity of A-share listed companies in Shanghai and Shenzhen between 2015 and 2019. It investigates this relationship by considering two pathways: investor sentiment and government attention. The findings indicate that air pollution suppresses total factor productivity of firms. However, air pollution stimulates investor sentiment, which in turn increases R&D investment and total factor productivity, reducing to some extent the dampening effect of air pollution on total factor productivity. There exists a notable positive correlation between air quality and government attention, acting as a mediating variable. This implies that air pollution has the potential to capture the attention of governmental entities, leading to the implementation of appropriate measures aimed at managing and mitigating the occurrence of air pollution caused by industrial enterprises.And the relevant governments should formulate a series of policies to meet the different needs of different enterprises. These two approaches have varying impacts depending on the type of enterprises, thus governments should develop laws to cater to the various demands of different types of enterprises. [ABSTRACT FROM AUTHOR]

Accurately predicting the price of carbon is an effective way of ensuring the stability of the carbon trading market and reducing carbon emissions. Aiming at the non-smooth and non-linear characteristics of carbon price, this paper proposes a novel hybrid prediction model based on improved feature extraction and non-linear integration, which is built on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), fuzzy entropy (FuzzyEn), improved random forest using particle swarm optimisation (PSORF), extreme learning machine (ELM), long short-term memory (LSTM), non-linear integration based on multiple linear regression (MLR) and random forest (MLRRF), and error correction with the autoregressive integrated moving average model (ARIMA), named CEEMDAN-FuzzyEn-PSORF-ELM-LSTM-MLRRF-ARIMA. Firstly, CEEMDAN is combined with FuzzyEn in the feature selection process to improve extraction efficiency and reliability. Secondly, at the critical prediction stage, PSORF, ELM, and LSTM are selected to predict high, medium, and low complexity sequences, respectively. Thirdly, the reconstructed sequences are assembled by applying MLRRF, which can effectively improve the prediction accuracy and generalisation ability. Finally, error correction is conducted using ARIMA to obtain the final forecasting results, and the Diebold–Mariano test (DM test) is introduced for a comprehensive evaluation of the models. With respect to carbon prices in the pilot regions of Shenzhen and Hubei, the results indicate that the proposed model has higher prediction accuracy and robustness. The main contributions of this paper are the improved feature extraction and the innovative combination of multiple linear regression and random forests into a non-linear integrated framework for carbon price forecasting. However, further optimisation is still a work in progress. [ABSTRACT FROM AUTHOR]

As educational paradigms evolve, the integration of multi-sensory theory into the design of children's educational toys presents a promising avenue for enhancing learning experiences. This paper explores the efficacy of multi-sensory toys in improving children's attraction, interest, and learning efficiency through a systematic review and a pilot empirical study. The study specifically assesses the hypothesis that multi-sensory educational toys significantly increase children's engagement and learning outcomes compared to traditional toys. Conducted with a diverse group of children aged 3-6 in Guangzhou and Shenzhen, China, the research employs both quantitative and qualitative methodologies, including engagement metrics and observational studies. The findings suggest that multisensory toys not only hold the potential to augment learning experiences but also require careful consideration of individual learning styles and preferences. The paper concludes with a discussion on the implications for future research and toy design, emphasizing the need for continued innovation and personalization in the development of educational toys to cater to the multifaceted needs of young learners. [ABSTRACT FROM AUTHOR]

Urban green space is a direct way to improve the carbon sink capacity of urban ecosystems. The carbon storage assessment of megacity green spaces is of great significance to the service function of urban ecosystems and the management of urban carbon zoning in the future. Based on multi-period remote sensing image data, this paper used the CASA model and the InVEST model to analyze the spatio-temporal variation and driving mechanism of carbon storage in Shenzhen green space and discussed the applicability of the two models to the estimation of carbon storage in urban green space. The research results showed that, from 2008 to 2022, in addition to the rapid expansion of construction land, the area of green space and other land types in Shenzhen showed a significant decrease trend. The estimation results of the carbon storage model showed that the carbon storage of green space shows a significant trend of reduction from 2008 to 2022, and the reduction amounts are 0.8 × 106 t (CASA model) and 0.64 × 106 t (InVEST model), respectively. The evaluation results of the model show that, in megacities, the spatial applicability of InVEST model is lower than that of CASA model, and the CASA model is more accurate in estimating the carbon storage of urban green space. The research results can provide a scientific basis for the assessment of the carbon sink capacity of megacity ecosystems with the goal of "dual carbon". [ABSTRACT FROM AUTHOR]

Currently, countries worldwide are embracing digital strategies, enabling enterprises to utilize digital technology, digital supply chains, blockchain, and additional digital measures to increase their competitiveness. This paper analyzed the correlation between the digital transformation of manufacturing export enterprises and their business and export performance, focusing on China's manufacturing export enterprises through empirical analysis. The study investigated the influence of digital transformation on enterprise performance. Using the Resource Based View theory and Trade theory, hypotheses were proposed and regression models were developed to analyze a sample of 1007 enterprises listed on the Shanghai and Shenzhen Stock markets from 2012 to 2019. The study conducted regression analysis, intermediate effect test, robustness test, stage lag, and heterogeneity analysis. The study found that (1) Manufacturing export enterprises listed in the stock market implemented digital transformation, leading to a significant positive impact on their overall performance. (2) Digital transformation led to cost reduction, improved R&D intensity, and enhanced human resources, among other benefits for enterprise performance. (3) According to the fractal analysis, non-state-owned enterprises exhibited more favorable effects on enterprise performance, and the digital transformation of manufacturing export companies in developed regions had a more significant impact on their performance. Finally, the study's empirical results yielded pertinent proposals for digital transformation. [ABSTRACT FROM AUTHOR]

Purpose: To adapt to the rapidly changing market environment, firms must constantly adjust and change their knowledge base to develop new technologies. The purpose of this paper is to analyze the improvement path of firms' breakthrough innovation from the perspective of knowledge recombination in the context of dynamic change in the knowledge base. By analyzing the influencing mechanism of environmental dynamism on the relationship between the two, this paper provides a theoretical foundation for managers to make knowledge recombination decisions under a dynamic external environment while further enriching the firm's innovation achievements. Design/methodology/approach: Using data from 220 manufacturing firms listed on the Shanghai and Shenzhen A-share stock from 2010 to 2018, an extensive panel data set was constructed to investigate the effect of knowledge recombination, which was divided into recombination creation and recombination reuse, on firms' breakthrough innovation. In addition, the authors differentiated environmental dynamism as market dynamism and technological dynamism and then examined its moderating role in the above relationships. Findings: The research results show that various recombination behaviors of knowledge elements have a differentiated effect on firms' breakthrough innovation presented as follows: Knowledge recombination creation is significantly positively correlated with firms' breakthrough innovation, while knowledge recombination reuse is significantly negatively correlated with firms' breakthrough innovation. In addition, environmental dynamism has a considerable moderating effect between knowledge recombination and firms' breakthrough innovation further, emphasizing that the moderating effect on different types of knowledge recombination behaviors is significantly distinct. Research limitations/implications: First, given that this study refers to several Chinese noted databases to collect second-hand data for empirical analysis, future research could use first-hand data by collecting questionnaire survey and interview to provide a more practical and detailed research conclusion. Second, the authors focused on the contextual variable to explore the moderating role of environmental dynamism on the relationship between knowledge recombination and breakthrough innovation. Nevertheless, the indirect effects of other internal factors were not discussed. The authors advocate future studies to involve other moderators from employee social and phycological perspectives, such as trust in colleagues in the proposed theoretical models in this study. Practical implications: This study is conducive for managers to attach great attention to knowledge management practices in the firm and to understand the critical role of knowledge recombination in affecting innovation performance under dynamic environmental changes. Moreover, this study provides practical guidance and serves as a reference for firms to strengthen their knowledge recombination ability as full utilization of existing knowledge elements and exploration of new knowledge values. Originality/value: Primarily, from the perspective of dynamic changes in the knowledge base, this paper explores how the knowledge recombination behaviors affect firms' breakthrough innovation, thereby enriching and extending the relationship theory between knowledge recombination capabilities and breakthrough innovation, while new and valuable ideas are provided in the study of issues related to the firms' breakthrough innovation; Moreover, this study analyzes the moderating effects of diverse types of environmental dynamism on the relationship between knowledge recombination and firms' breakthrough innovation from a multi-dimensional perspective proposing that the moderating effects of environmental dynamism on different knowledge recombination behaviors are distinct. [ABSTRACT FROM AUTHOR]

Water resources are a fundamental natural and strategic economic resource and are closely related to high-quality economic and societal development. This paper uses the pilot implementation of the water resource tax reform to explore the impact of that reform on the green innovation and total factor productivity of enterprises. The study sample includes data for high water-consuming A-share listed enterprises in Shenzhen and Shanghai, China, from 2007 to 2021; the double-difference method was used for the analysis. Study findings indicate that replacing water resource fees with taxes significantly improves the green innovation level and total factor productivity of enterprises. Green innovation has a significant partial mediating effect between the water resource tax reform and total factor productivity. The water resource tax reform promotes green innovation in enterprises, enhancing total factor productivity. When considering different types of enterprise property rights, the economic effect of the water resource tax reform is more pronounced in non-state-owned enterprises, compared to state-owned enterprises. This paper provides empirical evidence for expanding the pilot scope of the water resource tax reform. [ABSTRACT FROM AUTHOR]

This paper explores an expanding area of policy interest: the networks and collaboration mechanisms between universities and creative industries actors in cities. While much is known about such relationships in Science, Technology, Engineering, and Mathematics (STEM), they remain taken for granted and under researched in the creative industries. We argue that they are pivotal for different domains of research and policy, notably, cultural policy, higher education, innovation systems, and regional development. To that end, this paper aims to open up consideration of these relationships which we argue 1) stimulate innovation and 2) make broader contributions to local communities and economic regeneration via a creative economy approach. Using the Triple Helix framework, we explore university-industry-governemnt relationships and knowledge exchange mechanisms via a comparative analysis of two creative industries case cities: Shenzhen, China and Brisbane, Australia. Despite differences in certain important respects the two cities have both adopted creative industries policy frameworks. We found important differences between the cases in the roles and relative strength of the three sectoral actors. This study also shows a need for strategic incentives to foster collective capacity and governance interventions as a push to broker relationships that were not there before. Focussing on boundary spanning we also argue that cultural policy should have formal mechanisms and informal interactions to build a sustainable innovation ecosystem based on knowledge exchange. [ABSTRACT FROM AUTHOR]

At present, the determination of tunnel parameters mainly rely on engineering experience and human judgment, which leads to the subjective decision of parameters and an increased construction risk. Machine learning algorithms could provide an objective theoretical basis for tunnel parameter decision making. However, due to the limitations of a machine learning model's performance and parameter selection methods, the prediction model had poor prediction results and low reliability for parameter research. To solve the above problems, based on a large number of construction parameters of a composite section subway in Shenzhen, this paper combined dimensionality reduction data with service analysis to optimize the selection process of shield tunneling parameters, and determined the total propulsion force, cutter head torque, cutter head speed, and advance rate as key tunneling parameters. Based on an LGBM algorithm and Bayesian optimization, the prediction model of key tunneling parameters of an earth pressure balance shield was established. The results showed that the average error of the LGBM model on the test set was 8.18%, the average error of the cutter head torque was 13.93%, the average error of the cutter head speed was 3.16%, and the average error of advance rate was 13.35%. Compared with the RF model, the prediction effect and the generalization on the test set were better. Therefore, an LGBM algorithm could be used as an effective prediction method for tunneling parameters in tunnel construction and provide guidance for the setting of tunneling parameters. [ABSTRACT FROM AUTHOR]

Based on the sample of major asset restructuring transactions of Shanghai and Shenzhen A-share listed companies from 2009 to 2018, this paper uses Logit model to examine the impact of auditors ' cooperation experience with independent financial advisors on the reliability of performance commitments, and to examine the moderating effect of management overconfidence on the relationship between the two. The results show that the cooperation experience between auditors and independent financial advisors is significantly positively correlated with the reliability of performance commitment, and the closer the cooperation experience is, the easier the performance commitment will be realized, this has played a financial intermediary team effect. Further analysis shows that in the context of management overconfidence, the positive relationship between financial intermediaries ' cooperation experience and the reliability of performance commitment is stronger. The research results enrich the research on the influencing factors of M & A performance commitment and the economic consequences of financial intermediaries ' cooperation, and help the transaction subjects to rationally view performance commitment and regulators to improve policies and regulations. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to empirically analyze the impact of chief executive officer (CEO) turnover on strategic change and explore the mediating role of organizational slack between them, as well as the moderating role and joint moderating role of top management team (TMT) external social network, ownership nature and industry type. Design/methodology/approach: Based on the upper echelons theory, resource allocation theory and structuration theory, this paper takes the unbalanced panel data of A-share listed companies in Shanghai and Shenzhen Stock Exchanges of China from 2001 to 2018 as the research sample, uses ordinary least squares (OLS) regression method and fixed effect model to study the relationship between CEO turnover and strategic change, and focuses on the mediating mechanism and moderating mechanism between them. Findings: The authors find that CEO turnover is positively related to strategic change. When a CEO turns over, a new CEO will initiate strategic change. Precipitation organizational slack plays a mediating role between CEO turnover and strategic change. Non-precipitation organizational slack has no mediating effect between CEO turnover and strategic change, which is embodied as "suppressing effects." When the non-precipitation organizational slack variable is controlled, the impact of CEO turnover on strategic change will be enhanced. TMT external social network, ownership nature and industry type all negatively moderate the relationship between CEO turnover and strategic change. TMT external social network and ownership nature have a joint moderating effect between CEO turnover and strategic change. When TMT external social network is small, CEO turnover has a positive effect on strategic change in both state-owned enterprises and non-state-owned enterprises, but the promotion effect is stronger in non-state-owned enterprises. When TMT external social network is large, the positive effect of CEO turnover on strategic change in state-owned enterprises is from strong to weak, but in the non-state-owned enterprises is from weak to strong. TMT external social network and industry type have a joint moderating effect between CEO turnover and strategic change. When TMT external social network is small, CEO turnover has a positive impact on strategic change in high-tech enterprises and non-high-tech enterprises, but the promotion effect is stronger in non-high-tech enterprises. When TMT external social network is large, the positive impact of CEO turnover on strategic change in high-tech enterprises is from strong to weak, but in the non-high-tech enterprises is from weak to strong. Originality/value: On the basis of previous studies, this paper further expands the research scope of the mechanism of CEO turnover on strategic change, echoing the research arguments of relevant scholars. At the same time, the research results reveal the mechanism of organizational slack, TMT external social network, ownership nature and industry type in the relationship between CEO turnover and strategic change, and further deepen the application of upper echelons theory, resources allocation theory and structuration theory in China. In addition, the research conclusions of this paper also provide reference value for Chinese enterprises in carrying out strategic change, promoting enterprise transformation and improving the level of corporate governance, and help to enhance the understanding and attention of Chinese enterprises to CEO turnover, organizational slack, TMT external social network, strategic change and corporate governance under the background of high-quality economic development. [ABSTRACT FROM AUTHOR]

Introduction: The purpose of this paper is to empirically test the impact of CEO's financial background on industrial AI transformation of manufacturing enterprises based on upper echelons theory and imprinting theory. Methods: The paper preliminarily takes listed manufacturing companies in Shanghai and Shenzhen stock markets that are affiliated to enterprise groups from 2014 to 2020 as samples, and manually collects and collates datas of CEO's financial background and industrial AI transformation. The research hypotheses are tested by stata 15.0 software*. Results: It is found that CEO's financial background significantly inhibits the industrial AI transformation of manufacturing enterprises, and when the CEO works part-time in the parent company, it will strengthen the negative impact of CEO's financial background on industrial AI transformation. Further research shows that enterprise financialization plays a partial intermediary role between CEO's financial background and industrial AI transformation; Compared with private enterprise groups, the inhibiting effect of CEO financial background on industrial AI transformation is stronger in state-owned enterprise groups; CEOs with non-banking financial background have a stronger inhibitory effect on industrial AI transformation. Discussion: Firstly, based on the process of making business decisions, it verifies and clarifies the action mechanism of CEO's financial background on industrial AI transformation through internal driving mechanism, which expands the research horizon of industrial AI transformation, and further applies the Imprinting Theory in biology to the research of business decision-making, which forms a beneficial complement to the relevant research on economic consequences of CEO's financial background. Secondly, different from the research of single independent company, this paper focuses on the special situation of parent-subsidiary corporate governance, and explores the mechanism of action, deepening the research on the synergy of enterprise groups. Finally, this paper further explores the influence of CEO's financial background on industrial AI transformation, which is conducive to a deeper understanding of the heterogeneity of managers except manpower and capital factors in the industrial AI transformation practice of manufacturing enterprises, and provides a new idea and a more comprehensive analysis perspective for industrial AI transformation. [ABSTRACT FROM AUTHOR]

Science and technology and skills have increasingly become the driving force to lead the development of knowledge economy. With the changes in the demand for knowledge workers and the location of enterprises, a new type of innovation space—innovation districts—has emerged. Countries have begun to identify and nurture innovation districts. Therefore, how to accurately identify innovation districts in cities has become an important research topic. The existing research on identifying innovation districts is mainly based on a qualitative description method at the element level. However, whether there are other potential innovation districts in urban space can be identified by quantitative identification. Therefore, the purpose of this paper is to establish an innovation district identification framework and a case study of the framework. The identification framework includes spatial identification and factor identification. In spatial identification, the identification index system is constructed based on the spatial location, range limit, and the surrounding area of innovative assets. In factor identification, the identification index system is constructed based on innovative assets, physical assets, and network assets, and Kendall Square and Boston innovation districts are used as the reference basis to determine whether the identified districts meet the standards of the constructed innovation districts. In empirical case research, spatial identification identified the Gaoxin South District (GXSD) spatial range. In factor identification, it was found that GXSD does not fully meet the standard of innovation district identification. This paper argues that the framework is essential for urban managers, planners, and urban designers to identify and evaluate high-quality innovation districts. [ABSTRACT FROM AUTHOR]

Real‐time individuals' destination prediction is of great significance for real‐time user tracking, service recommendation and other related applications. Traditional technology mainly used statistical methods based on the travel patterns mined from personal history travel data. However, it is not clear how to predict the destinations of individuals with only limited personal historical data. In this paper, taking the public transportation metro systems as example, we design a practical method called practical model with strong interpretability and predictability to predict each passenger's destination. Our main novelties are two aspects: (1) We propose to predict individuals' destination by combining personal and crowd behavior under certain context. (2) An explanatory model combining discrete choice model and neural network model is proposed to predict individuals' stochastic trip's destination, which can be applied to other transportation analysis scenarios about individuals' choice behavior such as travel mode choice or route choice. We validate our method based on extensive experiments, using smart card data collected by automatic fare collection system and weather data in Shenzhen, China. The experimental results demonstrate that our approach can achieve better performance than other baselines in terms of prediction accuracy. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this paper is to explore the specific relationship between managerial power and enterprise innovation performance. Combined with managerial power theory and stewardship theory, financing constraints and strategic orientation, including, strategic market orientation and strategic technology orientation are included in the analysis framework to test how managerial power influences enterprise innovation performance in detail from the perspective of enterprise internal influence mechanisms. Design/methodology/approach: Based on the A-share listed companies in Shanghai and Shenzhen covering the period from 2001 to 2017, this paper uses the ordinary least square method (OLS) to explore how managerial power affects enterprise innovation performance. Findings: The results show that managerial power has a positive impact on enterprise innovation performance. Furthermore, the authors find that financing constraints, strategic market orientation and strategic technology orientation all have partial mediating effects in the relationship between managerial power and enterprise innovation performance. Originality/value: This paper verifies the application of managerial power theory and stewardship theory in the relationship between managerial power and enterprise innovation performance in Chinese A-share listed companies, contributing to the literature on enterprise innovation. Moreover, by introducing the mediating mechanisms of financing constraints, strategic market orientation and strategic technology orientation, this paper builds an effective path for in-depth study to analyze how managerial power influences enterprise innovation performance and finds ways to improve enterprise innovation performance from the inside view of the enterprise. [ABSTRACT FROM AUTHOR]

In this paper, we first proposed a statistical test for the detrended multiple moving average cross-correlation coefficient DMMC (s). The DMMC (s) mainly was used to analyze the correlation between the dependent variable y and other n independent variables x i . We proved that DMMC (s) approximately obeys the chi-square distribution. We studied the statistical properties of the DMMC (s) between normally distributed random sequences and power-law ARFIMA long memory random sequences. Furthermore, we discussed the influence of the cross-correlation among the target variable and independent variables on DMMC (s). Finally, we further study the application of DMMC (s) to China's stock markets and China carbon emission trading markets to investigate multiple cross-correlation. The empirical results show that there is a strong multiple correlation between China's Shanghai, Shenzhen and Hong Kong stock markets, while the correlation between China's carbon markets is not significant. This paper provides new ideas and theoretical support for exploring the correlation between multiple variables, which has implications for investors and policymakers. [ABSTRACT FROM AUTHOR]

This paper takes the Chemical Industry and Computers and other Electronic Equipment Manufacturing Industry enterprises, listed in Shanghai and Shenzhen stock markets as samples, selects the 2017-2021 annual report data of each enterprise, and it uses multiple regression analysis method to test empirically the impact of high and low polluted enterprises to share social responsibility on corporate financial performance. The results of the research show that: the impact of disclosing environmental accounting information of high-polluted enterprises has a positive effect on financial performance. The impact of disclosing environmental accounting information of low-pollution enterprises on financial indicators could be relatively inconsistent. [ABSTRACT FROM AUTHOR]

Under the background of the rapid development of digital economy, this paper empirically analyzes the impact of digital transformation on enterprise innovation and selects the panel data of China's Shanghai and Shenzhen A-share listed companies from 2013 to 2021 as the research objective is to study the impact of digital transformation on enterprise innovation from theoretical and empirical perspectives. First, we find that digital transformation accelerates enterprise innovation, a conclusion that has been validated through robustness testing. Second, digital transformation impacts enterprise innovation by enhancing productivity and information transparency. Third, financing constraints and financial redundancy play distinct regulatory roles in the process. Fourth, heterogeneity analysis finds that the role of digital transformation in promoting enterprise innovation has different effects in state-owned and non-state-owned enterprises, high-tech and non-high-tech enterprises, and enterprises with different life cycles. Finally, the functional analysis suggests that further investigation is needed to determine whether digital transformation can significantly promote the sustainable development of enterprises through innovation while also recognizing that this function may have a lag effect. Overall, this study contributes to a deeper understanding of digital transformation and innovation-driven practices and encourages more significant integration of the real and digital economies. [ABSTRACT FROM AUTHOR]

Lung segmentation is an essential step in a computer‐aided diagnosis system for chest radiographs. The lung parenchyma is first segmented in pulmonary computer‐aided diagnosis systems to remove the interference of non‐lung regions while increasing the effectiveness of the subsequent work. Nevertheless, most medical image segmentation methods nowadays use U‐Net and its variants. These variant networks perform poorly in segmentation to detect smaller structures and cannot accurately segment boundary regions. A multi‐interaction feature fusion network model based on Kiu‐Net is presented in this paper to address this problem. Specifically, U‐Net and Ki‐Net are first utilized to extract high‐level and detailed features of chest images, respectively. Then, cross‐residual fusion modules are employed in the network encoding stage to obtain complementary features from these two networks. Second, the global information module is introduced to guarantee the segmented region's integrity. Finally, in the network decoding stage, the multi‐interaction module is presented, which allows to interact with multiple kinds of information, such as global contextual information, branching features, and fused features, to obtain more practical information. The performance of the proposed model was assessed on both the Montgomery County (MC) and Shenzhen datasets, demonstrating its superiority over existing methods according to the experimental results. [ABSTRACT FROM AUTHOR]

By using dynamic game analysis, a theoretical framework is constructed to investigate the impact of environmental regulations on corporate financial performance. A sample of 3021 A-share listed companies, listed on the Shanghai and Shenzhen stock exchanges from 2010 to 2018, is used for empirical testing with GMM model. Through the matching of regional data and enterprise data, this paper expands the measurement of environmental regulation from meso to micro and then, systematically estimates the impact and mediating effect of environmental regulation on corporate financial performance. The results show that environmental regulation policies and instruments are important factors influencing corporate financial performance and that the main way to improve the efficiency of environmental regulation is to encourage firms to carry out pollution control through technological innovation. The empirical results not only show that environmental regulations can facilitate the upgrading of corporate financial performance, but also that technological innovation, especially green technology innovation, also partially mediates the effect of environmental regulations in promoting corporate financial performance. At the same time, the impact of environmental regulations on corporate financial performance is both constrained and influenced by corporate ownership, industry classification and city level. Environmental regulations are more likely to improve the corporate financial performance of non-state-owned companies than that of state-owned companies. Environmental regulation significantly boosts corporate financial performance in clean industries, but significantly depresses corporate financial performance in polluting industries. Compared with higher-level cities, environmental regulations only facilitate improvements to corporate financial performance in ordinary prefecture-level cities. [ABSTRACT FROM AUTHOR]

The recent revival of the private rented sector in many regions highlights the importance of understanding the well-being of private renters. While there is a consensus that private renters are less satisfied with their life than homeowners, little attention has been given to examining the life satisfaction of private renters from different sub-sectors, nor has the underlying mechanism linking residential environment and life satisfaction been thoroughly investigated. The present paper aims to address these gaps by examining the life satisfaction of private renters from different sub-sectors in Shenzhen, China. We propose a model, based on Amérigo and Aragones' (1997) theoretical framework, that links residential environment, social exclusion, and life satisfaction. The model fits well with the data collected from 619 renters. The results showed that only 38% of the respondent private renters were satisfied with their life. Furthermore, we found urban village renters were significantly less satisfied with their life compared with renters living in commercial housing and Long-term Rented Apartments. Path analysis results suggest that some objective aspects of the residential environment, renters' perceived social exclusion, and their residential satisfaction could explain a substantial proportion of the variances in life satisfaction while the influence of demographic variables was found to be insignificant. Perceived equal citizenship rights, perceived discrimination, and perceived reasonable rent were shown to have significant effects on life satisfaction. The paper concludes with a discussion on policy implications aimed at enhancing the life satisfaction of private renters. [ABSTRACT FROM AUTHOR]

As an essential part of geocoding, address matching has gained increasing research attention. Due to the long-distance dependency and unstructured property, existing address-matching methods hardly capture the contextual and implicit semantic information of unstructured text addresses. This paper presents a Contrastive Learning model based on Global and Local representation Interaction for Address Matching (referred to as CLGLIAM), which introduces a novel global and local interaction network to enhance the discrimination ability of the model on the hard negative address by associating the relationship between the global and local address representation explicitly. Simultaneously, to improve the generalization and transferability of the model, we utilize contrastive learning to enrich the data sample and extricate the model from task-specific knowledge. Furthermore, extensive experiments are conducted on Shenzhen and national address datasets to verify the effectiveness of our approach. Our model achieves state-of-the-art F1 scores of 99.26 and 98.50 on the two datasets, respectively. And the extended hard negative experiments further demonstrate the better performance of CLGLIAM in terms of semantic discrimination. [ABSTRACT FROM AUTHOR]

The key to solving the problem of redundant financial indicators in addressing financial warning issues is to reduce the dimensionality of the original financial indicators. This paper proposes a model based on the whale optimization algorithm with mixed strategy (IWOA) combined with support vector machine (SVM), namely, the IWOA-SVM early warning model, which simultaneously performs index optimization and dimensionality reduction, and financial risk early warning identification. This paper takes a total of 302 enterprises specially treated in Shanghai and Shenzhen stock exchanges and normal enterprises of the same specification as the research samples to design the model. The results show that the improved whale optimization algorithm has better optimization speed and accuracy and improves the search ability of the original algorithm for the optimal solution. Compared with other dimensionality reduction methods, the IWOA-SVM model has the lowest index dimension after dimensionality reduction and has more excellent recognition effect. The dimensionality reduction results have certain universality for different classifiers, which provides a new idea for the selection of indicators for financial early warning. [ABSTRACT FROM AUTHOR]

As the subject of pollutant emissions, enterprises play an important role in environmental governance and should consciously fulfil their environmental responsibility. So, can the enterprise perform environmental responsibility to increase their investment in research and development (R&D)? Based on the data from China's Shanghai and Shenzhen A-share listed enterprises in 2011–2019, this paper explores the relationship between corporate environmental responsibility and R&D investment and examines the dual moderating effects of public attention and intellectual property protection. It is found that the implementation of corporate environmental responsibility can promote R&D investment. Public attention moderates the positive relationship between corporate environmental responsibility and R&D investment; it seeks that the positive relationship becomes higher with public attention. With higher regional intellectual property protection levels, the moderating effect of public attention on corporate environmental responsibility and R&D investment will be more obviously higher. This research provides theoretical support for enterprises to fulfil their environmental responsibilities and a new perspective for revealing the factors of enterprises' R&D investment, which can offer a foundation for future research and practices. [ABSTRACT FROM AUTHOR]

Understanding mobility patterns of taxi ridership is important for transport planning. However, there is still room for a thorough understanding of the role of the built environment for taxi ridership across different spatial–temporal patterns. This paper proposes an analytical framework that combines non-negative CANDECOMP/PARAFAC (NCP) decomposition for pattern extraction and the light gradient boosting machine (LightGBM) for modeling the relationship between the built environment and taxi ridership. The case study was conducted in Shenzhen, China. We identified four spatial–temporal patterns by evaluating the root mean square error of the decomposition result and the representativeness of patterns. Based on the LightGBM method, we examined the nonlinear associations between taxi ridership for different patterns and the built environment. The results show that demographic characteristics are important across space. Housing-price is mainly associated with taxi ridership in western Shenzhen. Among all types of POIs, finance and entertainment are the most prominent, affecting taxi ridership in southern Shenzhen. The effects of influencing factors exhibit a high degree of localization, and mixed effects may result from localization. All variables show significant nonlinear and threshold effects on taxi ridership, and these effects could guide transport planning in different areas of the city. [ABSTRACT FROM AUTHOR]

This study explores the peer and economic effects of corporate poverty alleviation behavior. Using the data of A-share non-financial listed corporates in Shanghai and Shenzhen of China from 2016 to 2020, the empirical analysis of this study finds that: corporate poverty alleviation behavior has significant peer effects; the guidance of local poverty alleviation policies weakens the peer effects of corporate poverty alleviation behavior; compared to private enterprises, the poverty alleviation behavior of the peer firms has a more significant impact on state-owned enterprises; and corporate poverty alleviation behavior can result in the backflow of economic benefits and achieve the organic unity of economic and social benefits. The purpose of this paper is to explore the peer effects of corporate poverty alleviation behaviors through empirical analysis using available public data. The results of the study not only increase the motivation of corporate to participate in poverty alleviation from a peer effects perspective, but also reveal key factors for sustaining corporate poverty alleviation behaviors. [ABSTRACT FROM AUTHOR]

Industry applications that support massive mobile nodes are an important part of 5G Narrow Band Internet of Things (NB-IoT). The mobile node is abstracted as a terminal scene with many shapes and complex behaviors in the cellular internet of things, which makes the network need a better radio resource management strategy to meet more mobility, larger connection requests and higher access rate services. Therefore, the feature extraction of the node trajectories will greatly facilitate the development of optimal algorithms for radio resource management in the large mobile scene of 5G NB-IoT networks. This paper presents a feature mining of the real trajectories from the urban operating vehicles in the city of Shenzhen, China. Meanwhile, the generated trajectories by four common mobility models are also handled as a comparison. The self-similarity, hot-spots, long-tails and travel time are evaluated due to the widely recognized four features of human traces. Mining results show that the vehicles to serve the daily trip of human in the city always take a short travel and activate in several hot-spots with randomly roaming, while the vehicles to serve the goods are showing the opposite characteristics. Moreover, the trajectory generated by the models does not have the characteristics of short travel and roaming in multiple hot spots, nor does it have different movement trends in various time periods. [ABSTRACT FROM AUTHOR]

This paper explores the ideological valence of atmosphere, grounding the notion of interpellation in investigating the widely welcomed light shows at Civic Centre in Shenzhen, China. Combining theoretical development and empirical research, this paper examines how these light shows generated particular atmospheres that impinged upon the formation of spectators' subjectivity. In a time when atmospheric staging is widely adopted to engineer urban space and events, ideological interpellation has become increasingly atmospherically diffused. Meanwhile, material contingencies and lived varieties of atmosphere also condition and potentially disturb the communication of ideological messages. Atmosphere thus needs to be considered in terms of its conceived, perceived and lived dimensions. This paper draws from Henri Lefebvre's space triad and rhythmanalysis to outline a framework for tracing the production of atmosphere, and applies it to empirical data to illustrate how light shows at Civic Centre generated ideological appeals through the atmospheric constellation of content, environmental materiality and subjects. It is through atmosphere that we grasp and imagine what the world is. In critical response to atmospheric interpellation, new modes of the reproduction of life derive not from an atmospheric outside but precisely through a reorientation from within. [ABSTRACT FROM AUTHOR]

COVID-19 has seriously impacted China's real economy and directly threatened the survival and healthy development of enterprises. Based on the data of Chinese A-share listed enterprises in Shanghai and Shenzhen from 2017 to 2021, this paper empirically examines the impact and mechanism of COVID-19 on enterprises financial distress. The findings are as follows: (1) The impact of COVID-19 significantly increases the risk of enterprises financial distress. (2) There are differences in the effect of COVID-19 on the financial situation of enterprises with different characteristics, with significant negative impacts on enterprises in industries such as mining and manufacturing, as well as smaller enterprises and those located in the central and western regions. (3) Digital transformation and government subsidies can alleviate the negative effects of COVID-19 on enterprises financial distress. The paper provides a basis for enterprises to recover from financial difficulties as soon as possible, enhance competitiveness, and realize sustainable development. [ABSTRACT FROM AUTHOR]

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The potential of the low carbon city pilot (LCCP) to foster enterprise green technology innovation (EGTI) is contingent upon enhancing the quality of urban development, improving the ecological environment, and ultimately achieving the objective of "double carbon" reduction. Due to this, this article uses data from Chinese A‐share listed businesses in Shanghai and Shenzhen from 2009 to 2021 to investigate the effect of LCCP on EGTI. It is found that LCCP significantly contributes to EGTI, and a number of robustness tests later, this finding remains valid. The mechanism analysis confirms that LCCP promotes EGTI by weakening economic policy uncertainty and increasing firms' R&D investment. Through the heterogeneity analysis, this paper explores that optimizing corporate staff structure, increasing media attention, and increasing government subsidies are effective paths to promote EGTI development with LCCP. The moderating effect confirms that executives' environmental cognition plays a positive moderating role between LCCP and EGTI. This paper enriches the related research on the evaluation of the effect of low‐carbon pilots and provides important policy insights for promoting the development of corporate green transformation. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Planning Education & Research is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)