Equity Characteristics Research Articles

A New Strategy for Planning Urban Park Green Spaces by Considering Their Spatial Accessibility and Distributional Equity

Urban park green spaces (PGSs) are crucial social public resources that provide various ecological services and enhance human health and well-being. However, with the acceleration of urbanization, the accessibility and equity of urban PGS resources are increasingly threatened. This study aims to propose an integrated framework that considers accessibility and equity simultaneously to optimize the planning and layout of urban PGS within the high-speed ring road of Hefei City. This study first used an improved two-step floating catchment area (2SFCA) method to quantify the level of accessibility of urban PGS within the ring road. Then, with the use of Lorenz curves, Gini coefficients, and bivariate correlation coefficients, the equity characteristics of these PGSs were quantified and evaluated, followed by an analysis of their relationships to the accessibility levels. Based on this comprehensive evaluation, the particle swarm optimization (PSO) algorithm was employed to the areas with low accessibility and equity levels to propose targeted PGS optimization strategies. The results showed that the accessibility of PGS was unevenly distributed, exhibiting a clear spatial difference of “east–west clustering”. The number of subdistricts with good (52.24–94.78) and best (94.79–283.58) accessibility was four, which was less than one-tenth of the total number of subdistricts in the study area. At the subdistrict level, the Gini coefficients for the accessible area of all types of PGSs were substantially higher than the international warning line of 0.4, indicating a substantial inequity in the population’s access to PGS. The implemented PSO algorithm resulted in eight new parks being planned at the specific optimized locations. Based on the actual land use status of the selected sites, recommendations are provided for the planning and layout of PGS. This proposed framework offers valuable data and theoretical insights for urban public green space planning and design in similar regions.

Effect of a Multicomponent Food Pantry Intervention in Client Subgroups.

Nutrition promotion programs may have varying effects and influence health disparities. SuperShelf promotes healthy choices in food pantries through inventory changes and nudge implementation (e.g., choice architecture). This secondary analysis of the SuperShelf cluster-randomized trial assessed whether the effect of SuperShelf on client diet quality differed by equity characteristics. English-, Spanish-, or Somali-speaking adult clients from 11 food pantries in Minnesota were included (N = 193). We measured change in diet quality by the Healthy Eating Index 2015 (HEI-2015; maximum score 100) using up to two 24 h dietary recalls from pre-intervention and post-intervention periods. We used linear mixed-effects models to determine whether the effect of SuperShelf on diet quality varied by self-reported gender, race/ethnicity, education, and employment status. In separate adjusted models, the interactions of SuperShelf and gender, education, or employment status were not significant. The interaction of SuperShelf and race/ethnicity was significant (p-interaction = 0.008), but pairwise comparisons in diet quality were non-significant in all racial/ethnic subgroups. SuperShelf did not have differential effects on diet quality by gender, race/ethnicity, education, or employment status, suggesting it does not worsen dietary disparities among food pantry clients, though more subgroup analyses are needed to explore potential racial/ethnic disparities in this context.

Tax Equity in Low- and Middle-Income Countries

Income inequality is high and persistent in developing countries. In this paper, we ask what role taxation can or might play in reducing inequality in low and middle-income countries. Drawing on the recent literature, three findings emerge. Due to both structural factors and limited enforcement capacity, the effective distributional impacts of taxes often deviate from their ‘statutory’ objectives, in ways that are hard to predict based on evidence from high-income countries. Moreover, administrative reforms which are meant to be distributionally neutral end up having significant equity impacts because of the practical realities of implementation. Finally, the global challenges which tax authorities face to tax the very top of the income distribution appear to be even more pronounced in developing countries. We conclude by offering thoughts on future research and emphasize the need to carefully study equity characteristics of taxes at each stage of a country’s development path.

The influence mechanism of real estate enterprises' status on debt default risk

PurposeThe aim of this study is to analyze the influence mechanism of real estate enterprises' status on debt default risk and explore the heterogeneity effect of the characteristics of enterprises.Design/methodology/approachAgainst the background of the “three red lines” regulation of the financing of real estate enterprises and the COVID-19 pandemic, the authors select 123 real estate enterprises listed on China's Shanghai and Shenzhen A-shares markets from the first quarter of 2021 to the second quarter of 2022 as a research sample. The social network analysis method and Z-score financial risk early warning model are used to measure real estate enterprises' status and debt default risk. The authors construct a panel regression model to analyze how the status of real estate enterprises influences their debt default risk.FindingsThe results show that the status of real estate enterprises negatively and significantly affects their debt default risk. Economic policy uncertainty and financing constraints play negative moderating and mediating roles, respectively. Further research has found that the effect of real estate enterprises' status on debt default risk is characterized by heterogeneity in equity characteristics, i.e. it is significant in the sample of nonstate-owned enterprises but not in the sample of state-owned enterprises.Practical implicationsIt is helpful for real estate enterprises to attach importance to the value of social networks, and the authors provide policy suggestions for real estate enterprises to constantly improve their risk management systems.Originality/valueUsing economic policy uncertainty as the moderating variable and financing constraints as the mediating variable, the authors analyze how the status of real estate enterprises influences debt default risk, which contributes to a better understanding of the formation of the debt default risk of real estate enterprises.

Rooftop solar, electric vehicle, and heat pump adoption in rural areas in the United States

The deployment of residential rooftop solar, electric vehicles (EVs), and heat pumps is critical to meet climate goals. We evaluate historical community- and household-level technology adoption patterns in rural areas, and explore associations with housing, socioeconomic, demographic, political, spatial, and energy equity characteristics. We reveal several emergent patterns and disparities in rural technology adoption. We find that higher educational attainment and democratic voting rates are significant predictors of adoption across all residential technologies. Specifically, EV adoption shows the highest association with democratic voting rates. We also find that rooftop solar adoption is most significantly inversely associated with energy burden, while there is a high degree of spatial dependence in heat pump adoption. Rooftop solar and EV adoption are particularly correlated at household, community, and state levels. Findings suggest that designing policies and programs that promote information diffusion, target low-income renters, and are tailored to the geographic and political context may together increase technology adoption rates and ensure more equitable diffusion. By identifying the factors that influence technology adoption in rural areas, we aim to inform the development of policies and programs that can facilitate the widespread deployment of clean energy technologies and contribute to the achievement of climate goals.

Associations between social media, adolescent mental health, and diet: A systematic review.

Social media use is integral to many adolescents' lives. It brings benefits but can also have detrimental effects on both physical and mental health. We conducted a systematic review examining associations between social media use, adolescent mental health (including body image, self-esteem, stress, interpersonal relationships and loneliness, anxiety, and depressive symptoms), and dietary outcomes. Quantitative studies published between 2019 and 2023 investigating both mental health and diet were searched in 11 databases. The risk of bias was appraised using ROBINS-E. Data were narratively synthesized by type of association, PROGRESS-Plus health equity characteristics, and related to social media influencers. Twenty-one studies were included, of which only one focused on influencers. Sex/gender was the only equity characteristic assessed (n= 8), with mixed results. The findings suggest significant positive correlations between social media use and both depressive and disordered eating symptoms, body dissatisfaction, and anxiety. Four studies identified body image, self-esteem, or anxiety as moderators acting between social media exposure and dietary outcomes. Policy interventions mitigating the impact of social media on adolescents-particularly body image and disordered eating-are needed, alongside follow-up studies on causal pathways, the role of influencers, equity impacts, dietary intake, and the best measurement tools to use.

Prediction of return on equity of the energy industry based on equity characteristics

We take the return on equity of energy enterprises as the research object to predict it. Our research adopts a new framework to solve multivariable time series problems. Compared to a single regression model, this model focuses more on the results of the regression equation rather than the coefficients of each indicator. Compared to the single machine learning regression method, this model can use the two-way encoder representation of the Transformers model to embed text data into the data, and then use the XGBoost model for regression model processing after PCA dimensionality reduction processing, thereby improving the accuracy of model prediction. Comparative experiments have verified that the method we use has advantages in terms of prediction accuracy.

Testing the Survival Model: Does Sukuk Offer a Better Trade-Off Than Bonds?

The trade-off theory assumes that there are benefits to leverage up until the optimal capital structure is reached. However, the fact yet remains puzzled whether sukuk companies possess the same trade-off effect because sukuk holds both debt and equity characteristics. The topic is prominent because of the increasing interest of sukuk issuance in the capital market, and series of financial distress occurrence especially among the debt issuers. The aims of the study are twofold, first is to identify whether sukuk issuance companies survive longer than bonds issuance companies, and second is to identify factors that contribute to the survival time. Samples of the study were consisting of all financially distressed sukuk and bonds issuance companies in Malaysia. The Cox regression model was conducted to develop the model. The result reveals a similar length of survival time for both sukuk and bonds companies. However, the results show that the liquidity ratio, measured by operating cash flow to current liability (OCFCL), is the most significant predictor in the case of sukuk. Contrary to expectations, none of the predictors tested are significant for bond companies. These results suggest a new theoretical understanding that even though the survival time between sukuk and bonds companies is similar, there is a unique factor in determining the survival time for sukuk companies. Future research may explore further on the importance of liquidity on asset-backed securities versus asset-based securities.

The health equity characteristics of research exploring the unmet community mobility needs of older adults: a scoping review

BackgroundUnmet community mobility needs of older adults, published since the announcement of the UN sustainable development goals was synthesised to describe the health equity characteristics of research identifying unmet community mobility needs of older adults.MethodsSearches were conducted in March and April 2020, 2275 articles were screened and 100 identified for data extraction.ResultsFindings showed underrepresentation of articles considering rural settings [9%] and originating in the global South [14%]. Gender, disability, education, and transport / driving were identified as key health equity characteristics and only 10 articles provided detail on all four of these. External factors inhibiting community mobility included built environments, service availability, and societal attitudes. Internal factors included finances, fear and apprehension, and functional limitations.ConclusionsThe need for standardised reporting of participant characteristics in the community mobility of older adults was highlighted. These characteristics are required by research consumers to judge equity dimensions, and the extent to which findings represent minority or marginalised groups. Fifteen years after the UN pledge to reduce inequalities, peer reviewed primary research does not reflect a global drive to end discrimination, exclusion and reduce the inequalities and vulnerabilities that leave people behind.

The influence of digital finance based on the intermediary effect of investor confidence on organizations' financing constraints.

This study examines the impact of digital financing on the degree of financing constraints and discusses the mediating effect of investor confidence. The data are based on companies listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2010 to 2019. To investigate the impact of digital financing on the financing constraints of companies in different situations, the heterogeneity of internal control and equity characteristics of different organizations is analyzed. The results using fixed-effects models show that (i) the change in digital finance has a significant negative impact on the level of corporate financing constraints; (ii) investor confidence plays a mediating role between digital finance and financing constraints; and (iii) the level of internal control impacts the relationship between the digital finance and the corporate financing constraints. Specifically, for the organizations with better internal control, there is a significant negative relationship between digital finance and corporate financing constraints while for organizations with poor internal control, digital finance has no significant influence on the extent of financing constraints; and (iv) digital finance of private organizations is significantly negatively correlated with the extent of financing constraints, while for government organizations, a negative relationship is not evident.

Financial Crisis Warning for Listed Manufacturing Companies in China

In this paper, we have first selected 28 indicators based on the selection principle of financial indicators adopted in relevant studies both at home and abroad from seven aspects, which include profitability, long-term and short-term solvency, company development capacity, operating capacity, cash flow generation capability, equity characteristics, and board characteristics. Subsequently, we have conducted the comparative analysis and comprehensive study on the logistic early warning model and BP neural network to provide reference for managers and stakeholders to select the optimal model. In addition, through our study on the dynamic early warning of BP neural network, we intend to convey the concept of constantly updating the model to both managers and stakeholders. Therefore, this paper provides ideas for the research on the model of financial crisis early warning for China's manufacturing industry. The study is of significance for guiding the research of related issues in the manufacturing sector and can also provide reference for the early warning of other industries.

Sex/gender and additional equity characteristics of providers and patients in perioperative anesthesia trials: a cross-sectional analysis of the literature.

Sex/gender and additional equity characteristics of providers and patients in perioperative anesthesia trials: a cross-sectional analysis of the literature.

Development of an extension of the OMERACT Summary of Measurement Properties table to capture equity considerations: SOMP-Equity

ObjectiveTo develop an equity extension of the OMERACT Summary of Measurement Properties (SOMP) Table, SOMP Equity to describe whether a patient reported outcome measure (PROM) works well among patients of diverse languages and cultures, education levels, and other population characteristics. MethodsWe used the PROGRESS-Plus framework to categorize equity characteristics assessed in trials of PROM. PROGRESS refers to Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social Capital, while the ‘plus’ captures additional characteristics, such as age. We pilot tested our SOMP Equity Extension using the Health Assessment Questionnaire (HAQ) as a prototypical PROM. ResultsThe SOMP Equity Extension retains the same columns as the original OMERACT SOMP (domain match, feasibility, construct validity, test-retest reliability, longitudinal construct validity, clinical trial discrimination, thresholds of meaning) but uses the PROGRESS-Plus characteristics as rows. We found several examples of studies of the HAQ which had assessed one or more PROGRESS-Plus characteristics. ConclusionsThe most commonly reported equity considerations were related to language. OMERACT Equity virtual meeting participants were polled and they indicated that the SOMP Equity Extension is useful for highlighting and tracking equity considerations for OMERACT Core Outcome Measurement Instruments.

Financial Bias and Manufacturing Innovation Differentiation: On the View of Credit Allocation

The coordinated development of the financial sector and the entity sector has become one of the core tasks of the strategy for an innovative and powerful country under the new normal. To this end, exploring how financial bias affects the innovation and the formation of innovation differentiation has positive practical significance for guiding the economy to “returning to the reality”, and motivating financial capital to enter the real investment field in an orderly manner to promote the innovation of micro-market entities. This paper explores the existence, mechanism and differentiated impact of bank credit bias on the formation of enterprise innovation, and conducts an empirical test based on the data of manufacturing enterprises from 2007 to 2018. The research results show that the bank credit allocation shows a significant bias, and is more inclined to the formulation of fixed assets, investment returning and the degree of financialization. On the whole, the expansion of bank credit supply significantly promotes the innovation input and output of manufacturing enterprises by alleviating the financing constraints and internal cash flow constraints, but bank credit bias leads to the problem of innovation differentiation. The RD the innovation ability of state-owned enterprises has more “quantitative” advantages. Bank credit bias can promote more manufacturing innovation in the eastern and southern coastal regions, the middle reaches of the Yangtze River and the Yellow River, and the non-high-tech enterprise. The marginal contribution of this paper is mainly reflected as follows: Firstly, it analyzes the “bank credit bias and differentiation of enterprise innovation” from the perspective of financial bias. This provides a micro-theoretical foundation for building a two-wheel-driven policy system of “financial support and technological innovation”. Secondly, it conducts a more in-depth systematic investigation of the relationship between financial bias and enterprise innovation differentiation through the three dimensions of equity characteristics, industry heterogeneity, and regional differences. Thirdly, it uses the Heckman’s two-stage selection model to apply bank credit bias to the research on the relevance of manufacturing enterprise innovation, and provides a new analysis tool for exploring the actual relationship between bank credit preference and enterprise innovation. This study provides a certain policy basis for the financial market under the guidance of bank credit to return to the function of serving the real economy and accelerate the collaborative reconstruction of industrial innovation chain and financial capital chain.

Barriers to Use of Remote Monitoring Technologies Used to Support Patients With COVID-19: Rapid Review.

BackgroundThe COVID-19 pandemic has acted as a catalyst for the development and adoption of a broad range of remote monitoring technologies (RMTs) in health care delivery. It is important to demonstrate how these technologies were implemented during the early stages of this pandemic to identify their application and barriers to adoption, particularly among vulnerable populations.ObjectiveThe purpose of this knowledge synthesis was to present the range of RMTs used in delivering care to patients with COVID-19 and to identify perceived benefits of and barriers to their use. The review placed a special emphasis on health equity considerations.MethodsA rapid review of published research was conducted using Embase, MEDLINE, and QxMD for records published from the inception of COVID-19 (December 2019) to July 6, 2020. Synthesis involved content analysis of reported benefits of and barriers to the use of RMTs when delivering health care to patients with COVID-19, in addition to health equity considerations.ResultsOf 491 records identified, 48 publications that described 35 distinct RMTs were included in this review. RMTs included use of existing technologies (eg, videoconferencing) and development of new ones that have COVID-19–specific applications. Content analysis of perceived benefits generated 34 distinct codes describing advantages of RMTs, mapped to 10 themes overall. Further, 52 distinct codes describing barriers to use of RMTs were mapped to 18 themes. Prominent themes associated with perceived benefits included a lower burden of care (eg, for hospitals, health care practitioners; 28 records), reduced infection risk (n=33), and support for vulnerable populations (n=14). Prominent themes reflecting barriers to use of RMTs included equity-related barriers (eg, affordability of technology for users, poor internet connectivity, poor health literacy; n=16), the need for quality “best practice” guidelines for use of RMTs in clinical care (n=12), and the need for additional resources to develop and support new technologies (n=11). Overall, 23 of 48 records commented on equity characteristics that stratify health opportunities and outcomes, including general characteristics that vary over time (eg, age, comorbidities; n=17), place of residence (n=11), and socioeconomic status (n=7).ConclusionsResults of this rapid review highlight the breadth of RMTs being used to monitor and inform treatment of COVID-19, the potential benefits of using these technologies, and existing barriers to their use. Results can be used to prioritize further efforts in the implementation of RMTs (eg, developing “best practice” guidelines for use of RMTs and generating strategies to improve equitable access for marginalized populations).

The Promises and Pitfalls of Machine Learning for Predicting Stock Returns

Recent research suggests that machine learning models dominate traditional linear models in predicting cross-sectional stock returns. The authors confirm this finding when predicting one-month-forward-looking returns based on a set of common stock characteristics, including predictors such as short-term reversal. Despite the statistical advantage of machine learning model predictions, the authors demonstrate that the economic gains tend to be more limited and critically dependent on the ability to take risk and implement trades efficiently. Unlike traditional models, machine learning models have been somewhat more effective over the past decade at discerning valuable predictions from cross-sectional equity characteristics. <b>TOPICS:</b>Security analysis and valuation, big data/machine learning <b>Key Findings</b> ▪ The authors compare a nonlinear machine learning model called gradient boosting machine (GBM) with traditional linear models in predicting cross-sectional stock returns based on well-known equity characteristics. ▪ They demonstrate how to rationalize the mechanics and outcome of GBM to alleviate its black-box characteristics. ▪ The extent to which the statistical advantage of GBM’s performance over that of linear models can be translated into economic gains depends critically on one’s ability to take risk and implement trades efficiently.

Equity considerations in outcome measures of the HIV pre-exposure prophylaxis care continuum in high-income countries: a systematic review protocol

IntroductionHIV pre-exposure prophylaxis (PrEP) is an effective intervention to reduce acquisition of HIV. PrEP provision has increased in recent years, however, it is not known whether PrEP implementation has been...

Research on Influencing Factors of Carbon Accounting Information Disclosure

As of April 2018, 476 A-shares traded in the Shanghai Stock Exchange and the Shenzhen Stock Exchange of six energy-intensive industries are selected as research samples. According to their carbon accounting information disclosure of the situation analysis from 2015 to 2017, it can be seen that the five influencing factors, such as the size, development ability, equity characteristics, market approval, whether the company is in a pilot city of carbon emissions, are correlated with the level of carbon accounting information disclosure, while the effect of profitability on the level of carbon accounting information disclosure is not correlated.

Environmental effect, price subsidy and financial performance: Evidence from Chinese new energy enterprises

Owing to the advantages of resources conservation and environmental improvement, the new energy industry has become a strategic emerging industry all over the world, and the majority of countries have formulated different kinds of subsidies policies to new energy enterprises. Therefore, environmental effects and price subsidies become important influencing factors on financial performance. Based on 185 samples from 37 new energy listed companies in China from 2011 to 2015, combining with the sequential regression test program, the current study systematically discusses the relationship between environmental effect and financial performance, as well as the mediating effect of price subsidy. The result shows that, the environmental effects have a significant positive impact on the financial performance in the current and the lag period. Meanwhile, price subsidy implemented by government improved the financial performance in the current and the lagging period, while it only positively impacts the lagging period environmental effect. Besides, both current and the lagging period of price subsidy plays a significant positive mediating effect role in the relationship between environmental effect and financial performance. Moreover, the marketing degree and enterprises' age stimulate the mediating effect of price subsidy, while the enterprises' size and owners’ equity characteristics inhibit the mediating effect.

Private Equity Characteristics, Corporate Governance and Firm Value: Empirical Evidence from Small and Medium‐sized Enterprises*

To extend existing research, this study examines whether private equity (PE) and corporate governance affect firm value using empirical data on the small and medium‐sized boards of listed initial public offering companies in China. The empirical results show that PE investment can raise firm value as well as affect management behavior at the macro level. At the micro level, the greater PE firms' shareholding, the higher is firm value, which is positively influenced by the time the PE stake has been held. PE reputation and foreign PE are also positively related to firm value. Finally, corporate governance plays a partial mediating role in the relationship between PE investment and firm value.