Two-stage Analysis Research Articles

Measuring the Efficiency of Turkish Research Universities via Two-Stage Network DEA with Shared Inputs Model

The efficiency of universities, which have a network structure of production process, is an essential component of performance measurement in education. However, most previous studies use traditional Data Envelopment Analysis (DEA), which disregards the network structure of the production process in universities. This study adopts a two-stage Network Data Envelopment Analysis (NDEA) with shared inputs model to assess the overall, teaching and research efficiencies of Turkish research universities. The findings show that only 6 out of 23 research universities are efficient, and some universities with lower world rankings are more efficient than those with higher rankings. On the other hand, no significant difference was found between the efficiency levels of regions with a high level of socio-economic development and regions with a relatively low level of socio-economic development. The study also evaluates the effects of different priority scenarios on efficiency and the optimal allocation of shared inputs between sub-processes. This study provides guidance for universities seeking to improve their performance and for the Council of Higher Education (CHE) in determining incentives for research universities. It also promotes the use of multi-stage NDEA with shared inputs model over traditional DEA for accurate efficiency assessment in the field of education.

Efficiency of Micro and Small Wood-Processing Enterprises in the EU—Evidence from DEA and Fractional Regression Analysis

Micro and small wood-processing enterprises represent the heart of European forest-based industries, being among the key drivers of economic growth in rural, mountainous, and poor regions. Their economic efficiency is of fundamental importance for their existence and the provision of income for the local population in rural areas. Data Envelopment Analysis (DEA) is used in the current research, which is a nonparametric, linear-programming-based approach that is commonly used to analyse the efficiency of organisational units. The main objective of this study was to investigate and evaluate the economic efficiency of micro and small wood-processing enterprises in EU countries and reveal the hidden inputs that facilitate efficiency generation. The economic efficiency evaluation was carried out on the basis of the official statistical data for the micro and small wood-processing companies in EU member states for the period 2015–2020 by performing a two-stage DEA analysis. The data used were standardised by value per employee. In addition to the first stage of DEA, a fractional regression probit and logit models with four contextual variables were used to reveal the influence of the hidden inputs in the model. The results showed that the micro and small wood-processing enterprises can be regarded as more scale-efficient than technically efficient entities. The only contextual variable affecting the economic efficiency was Investments per Person Employed, improving the efficiency by 2% per 1% increase in the investments.

Potentially functional genetic variants in ferroptosis-related CREB3 and GALNT14 genes predict survival of hepatitis B virus-related hepatocellular carcinoma.

Ferroptosis is a known crucial player in the development of cancers. However, the effect of single nucleotide polymorphisms (SNPs) in ferroptosis-related genes on survival in hepatitis B virus (HBV)-related hepatocellular carcinoma (HBV-HCC) patients remains unknown. We used two-stage multivariable Cox proportional hazards regression analyses to estimate the associations between 48,774 SNPs in 480 ferroptosis-related genes and overall survival (OS) of 866 HBV-HCC patients. We identified that two potentially functional SNPs (CREB3 rs10814274 C > T and GALNT14 rs17010547 T > C) were significantly independently associated with the OS of HBV-HCC patients (CT + TT verse CC, hazards ratio (HR) = 0.77, 95% confidence interval (CI) = 0.67-0.89, p < 0.001 for rs10814274 and TC + CC verse TT, HR = 0.66, 95% CI = 0.53-0.82, p < 0.001 for rs17010547, respectively). Additional joint assessment of protective genotypes of these two SNPs showed that patients with 1-2 protective genotypes had a significantly better OS compared with those carrying 0 protective genotypes (HR = 0.56, 95% CI = 0.45-0.70, p < 0.001). Moreover, the expression quantitative trait loci (eQTL) analysis revealed that the survival-associated SNP rs10814274 T allele was significantly correlated with reduced CREB3 transcript levels in both normal liver tissues and whole blood cells, while the GALNT14 rs17010547 C allele had a significant correlation with increased GALNT14 transcript levels in whole blood cells. These results suggest that genetic variants of CREB3 and GALNT14 may affect the survival of HBV-HCC patients, likely via transcriptional regulation of respective genes. However, further studies are required to confirm these findings.

Making tourism more sustainable: empirical evidence from EU member countries

AbstractWe analyze the sustainability factors that are pertinent to the tourism industry by exploring the effects of economic, environmental and social determinants on sustainable value added (SVA) in a two-stage analysis on a sample of 27 EU countries for the 2013–2019 period. In the first stage, we determine the relative efficiency based on DEA. In the second stage, we use the obtained variables in a dynamic panel data analysis setup. Contrary to the omnipresent push for complete green and sustainable transformation we find that increased GHG emissions will lead to an initial increase in SVA as the tourism sector needs time and effort to transition from a resource-oriented to an environmental-oriented production process. Contrary to previous findings, we show that environmental policies are not effective and that environmental taxation-related policies and procedures need to be revised. Economic growth implies increased pollution as well as increased SVA, as it requires more inputs and thus consumes more natural resources. Because of this it is of utmost importance to pay more attention to the quality of economic development in order to mitigate negative environmental externalities in the tourism sector.

Associations of meteorological factors and dynamics of scrub typhus incidence in South Korea: A nationwide time-series study

Scrub typhus, also known as Tsutsugamushi disease, is a climate-sensitive vector-borne disease that poses a growing public health threat. However, studies on the association between scrub typhus epidemics and meteorological factors in South Korea need to be complemented. Therefore, we aimed to analyze the association among ambient temperature, precipitation, and the incidence of scrub typhus in South Korea. First, we obtained data on the weekly number of scrub typhus cases and concurrent meteorological variables at the city-county level (Si-Gun) in South Korea between 2001 and 2019. Subsequently, a two-stage meta-regression analysis was conducted. In the first stage, we conducted time-series regression analyses using a distributed lag nonlinear model (DLNM) to investigate the association between temperature, precipitation, and scrub typhus incidence at each location. In the second stage, we employed a multivariate meta-regression model to combine the association estimates from all municipalities, considering regional indicators, such as mite species distribution, Normalized Difference Vegetation Index (NDVI), and urban-rural classification. Weekly mean temperature and weekly total precipitation exhibited a reversed U-shaped nonlinear association with the incidence of scrub typhus. The overall cumulative association with scrub typhus incidence peaked at 18.7 C° (with RRs of 9.73, 95% CI: 5.54–17.10) of ambient temperature (reference 9.7 C°) and 162.0 mm (with RRs of 1.87, 95% CI: 1.02–3.83) of precipitation (reference 2.8 mm), respectively. These findings suggest that meteorological factors contribute to scrub typhus epidemics by interacting with vectors, reservoir hosts, and human behaviors. This information serves as a reference for future public health policies and epidemiological research aimed at controlling scrub typhus infections.

REASONABLE INCOMPLETE REVASCULARIZATION USING MINIMALLY INVASIVE CORONARY ARTERY BYPASS GRAFTING TECHNIQUES

HighlightsIn multivessel coronary artery disease coronary artery bypass grafting under cardiopulmonary bypass using the internal thoracic artery is the accepted standard of revascularization, however, it is characterized by high trauma. Minimally invasive techniques offset this disadvantage but cannot always provide complete revascularization. Determination of feasibility and combined use of incomplete revascularization with minimally invasive techniques of coronary artery bypass may be a worthy alternative to traditional coronary bypass in a certain group of patients. At the same time, literature the data are ambiguous and deficient in the world. Aim. To justify the use of minimally invasive coronary artery bypass technique in incomplete myocardial revascularization in patients with stable ischemic heart disease from the standpoint of efficacy and safety.Methods. The retrospective study focuses on the analysis of minimally invasive coronary artery bypass grafting (minimally invasive direct coronary artery bypass grafting and off-pump coronary artery bypass surgery using sternotomy) and traditional CABG with cardiopulmonary bypass in patients with multivessel coronary artery disease (n = 429) performed in the period from 2013 to 2017. Depending on the CABG technique and the type of revascularization (complete/incomplete), all patients were divided into 3 groups with two comparison subgroups in each. The completeness of revascularization was assessed using the residual SYNTAX score (rSS). The SYNTAX revascularization index (SRI) was calculated using the following formula: SRI = [1 – (rSS/bSS)] × 100. Subsequently, a two-stage (short- and long-term) analysis of the adverse events frequency was carried out.Results. The minimally invasive incomplete revascularization (IR) group and the traditional complete revascularization (CR) group. The rSS in the IR group was 3.0 [2.0; 5.0] compared with the group without traditional CABG, whereas the SRI was 84.31 [75.00; 89.19] % compared with 100.00 [100.00; 100.00] %, respectively (p&lt;0.001). The analysis of in-hospital period did not reveal significant differences in the number of primary and secondary endpoints. Taking into account the additional endpoints, the IR group had a lower level of intraoperative blood loss – 300 [200; 310] mL compared with 500 [400; 500] mL in the CR group (p&lt;0.001). Moreover, the need for blood transfusion was significantly lower – by 4.27 times (95% CI: 0.124–0.441, p&lt;0.001). The length of patients stay with IR in the intensive care unit was 4.12 times shorter (95% CI: 1,954–8,994, p&lt;0.001). The 1-year follow-up visit revealed full comparability between the groups in terms of frequency of both primary and secondary endpoints. There were no differences in freedom from MACCE and mortality.The minimally invasive CR group and the traditional CR group. The in-hospital period and 1-year follow-up visits showed similar outcomes, comparable to the minimally invasive IR and traditional CR groups. The minimally invasive IR group and the minimally invasive CR group. The analysis of in-hospital period and 1-year follow-up visits did not reveal any differences in endpoints. Freedom from MACСE and death was similar as well.Conclusion. The data obtained indicate a similar safety profile and effectiveness of IR. Minimally invasive IR is appropriate with rSS ≤3 and SRI ≥84.3% and can be considered as an alternative approach to myocardial revascularization in patients for whom traditional CABG is undesirable.

If at first, you don’t succeed: Strategies used by environmental activist volunteer leaders to overcome failure

ABSTRACT Environmental activist leaders play a critical role in organizing grassroots activism. They often do so in a voluntary capacity while enduring long periods of failure in their quest to achieve environmental goals. Through 21 interviews we investigate how environmental activist volunteer leaders experience failure and the strategies they use to overcome it. Using a two-stage reflexive thematic analysis approach, four dimensions of failure were identified: movement, campaign, organization, and individual. Participants used three overarching strategies to manage these experiences of failure: Re-evaluating outcomes, emphasizing individual benefits, and changing tactics. Our findings suggest that environmental activist volunteer leaders regularly experienced failure across all four dimensions. The strategies they used to manage failure enabled them to maintain belief that success is achievable. We conclude with a discussion of how these findings can be used to develop tools and resources to enhance activist leaders’ capacity to prevail in the face of failure.

Assessment of the regional potential of technological sovereignty of the Russian Federation

Aim. To identify the regions with a high potential for ensuring technological sovereignty of the Russian Federation (RF).Objectives. To perform a structural analysis of non-resource exports and imports of the RF regions; to propose a methodological approach to the development of typology of regions according to the criterion “the level of import dependence of production”; to identify the regional nuclei of technological sovereignty of the Russian Federation.Methods. Two-stage structural analysis of statistical data on regional exports and imports with the allocation of the share of goods with low and high level of processing, as well as with the definition of the purpose of products: production or for consumption by the population. The choice of the research period is conditioned by the absence in 2019 of the influence of the factor of the decline in global production during the COVID-19 pandemic in the following years, as well as the absence of the pressure exerted by sanctions restrictions.Results. 12 types of Russian regions were defined according to the criterion “high, medium and low levels of technological import dependence of the industrial complex”. The second level of the regional typologization depth is determined by the ratio of such indicators as the share of industrial technological export of the region in the country’s export, the share of industrial technological export of the region in the country’s technological export, the share of industrial technological import of the region in the country’s import, the share of industrial technological import of the region in the country’s technological import. Structural analysis allowed us to identify the regions - the nuclei of technological sovereignty of the country.Conclusions. First of all, it is necessary to study the experience of economic activity of seven regions that have exports of technological products at a high level with a low level of technological import dependence of industry. Among these regions are the Irkutsk, Arkhangelsk, Penza oblasts, the Republic of Bashkortostan, Altai Krai, the Republic of Mari El, and the Komi Republic. Two leading regions of the listed subjects of the Russian Federation deserve special attention: the Irkutsk Oblast and the Republic of Bashkortostan. It is important to highlight the most successful cases of their sectoral development to be used in other territories in order to ensure national technological sovereignty.

Assessing environmental and operational efficiencies: a multi-objective optimization problem in a two-stage network data envelopment analysis

Abstract Accepted by: Ali Emrouznejad The environmental efficiency of industries plays an important role in economic development of countries. Accordingly, dividing the internal network structure of industries into two sub-processes, including green and operational stages, enables decision-makers to assess both of the efficiencies simultaneously. Such assessment can be implemented using a non-parametric methodology termed data envelopment analysis (DEA). Standard DEA models consider the whole system of decision-making units (DMUs) as a single process (i.e. black-box). The black-box approach ignores modelling of the internal network structure of the assessed DMUs. This issue tackled by network DEA models since it considers the internal network structure of DMUs. In the network DEA, the efficiency evaluation of system stages is essential to identify its overall efficiency, resulting to a multi-objective optimization problem. Therefore, the network DEA is a widely welcomed methodology proposed for solving multi-objective problems. This paper assesses the operational and environmental efficiencies of a network structure system by converting the multi-objective optimization problem into a linear single objective function. In this investigation, a technique of tri-objective function problem is proposed. The proposed technique transforms into a single objective function by keeping one objective function and shifting the other two objective functions into the model’s constraints. The applicability and usefulness of the proposed technique have been tested using a data set of 20 industries. The developed approach provides valuable evaluations to decision-makers to rank DMUs by considering their green and operational efficiency simultaneously.

Inverse two-stage data envelopment analysis with interval measures for resource planning

PurposeAssessing inputs and outputs is a significant aspect of taking decisions while there are complex and multistage processes in many examinations. Due to the presence of interval performance measures in various real-world studies, the purpose of this study is to address the changes of interval inputs of two-stage processes for the perturbations of interval outputs of two-stage systems, given that the overall efficiency scores are maintained.Design/methodology/approachActually, an interval inverse two-stage data envelopment analysis (DEA) model is proposed to plan resources. To illustrate, an interval two-stage network DEA model with external interval inputs and outputs and also its inverse problem are suggested to estimate the upper and lower bounds of the entire efficiency and the stages efficiency along with the variations of interval inputs.FindingsAn example from the literature and a real case study of the banking industry are applied to demonstrate the introduced approach. The results show the proposed approach is suitable to estimate the resources of two-stage systems when interval measures are presented.Originality/valueTo the best of the authors’ knowledge, there is no study to estimate the fluctuation of imprecise inputs related to network structures for the changes of imprecise outputs while the interval efficiency of network processes is maintained. Accordingly, this paper considers the resource planning problem when there are imprecise and interval measures in two-stage networks.

The problem of anesthesia of regional society (on the example of the Republic of Mordovia)

Target: the aim is to identify the factors contributing to the involvement of the population of the Republic of Mordovia in drug use.Materials and methods. The study was conducted among residents of the Republic of Mordovia aged 14 to 60 years. Here we used a multi-stage sampling with quota selection of respondents at the last stage. A two-stage cluster analysis was applied to determine the factors of population involvement in drug use.Results. The study showed that the population is aware of the seriousness of the problem of drug addiction in the country. However, other questions require priority resolution at the respondent’s place of residence.The article compares the indicators of the spread of non-medical drug use according to official medical statistics and the results of sociological research. There is a discrepancy between the values of the prevalence of non-medical drug use according to the data of the Ministry of Health of the Republic of Mordovia and the data of sociological studies. According to the study, the proportion of the population of Mordovia who consume drugs is 0,7%. The main factors of involvement in drug use were the social environment, the influence of the Internet, and the availability of narcotic drugs.Conclusion. According to the analysis, two clusters are identified. The first one forms the majority (90%) of the inhabitants of Mordovia. It includes those who have not received offers to try drugs, do not use the Internet to get information about drugs and who do not have drug users in their social environment. The second cluster (10%) included respondents who received an offer to try drugs, who were familiar with drug users and resorted to the Internet for drug information. The socio-demographic characteristics of the second cluster differ from the general sample, men prevail here, and the population in the age ranges from 21 to 25 years, 26–30 years and 31–35 years.

Exploring Cultural Meaning Construction in Social Media: An Analysis of Liziqi's YouTube Channel

Hall's encoding/decoding model has been widely used in mass media, but its potential in social media studies has not been explored thoroughly. To this end, this paper aims to broaden the fundamental principles and assumptions of the model and apply them to audience engagement and interaction in constructing cultural meaning through social media. By analysing the YouTube channel of Liziqi (Vlogger), this study adopts a two-stage content analysis to investigate the possibility of textual coding frameworks and audience engagement processes in the construction of cultural narratives. The study reveals that Liziqi represents Chinese culture through various symbols and constructs a micro-narrative coding framework that influences audience perceptions. The audience interprets the content in proactive and diverse ways, resulting in four types of decoding: pleasuring, reflective, empathic, and questioning. This research expands Hall's encoding/decoding model by exploring the production and reception processes in a multicultural context, revealing a shared cultural framework between sender and receiver. This paper provides a tool for scholars to use new conceptual tools for encoding/decoding to explore the meaning dimensions of social media interaction.

Two-Stage Data Envelopment Analysis Models with Negative System Outputs for the Efficiency Evaluation of Government Financial Policies

The main purpose of this study is to provide a comparative analysis of several possible approaches to applying data envelopment analysis (DEA) in the case where some decision making units (DMUs) in the original sample have negative system outputs. In comparison to the traditional model of Charnes, Cooper, and Rhodes (CCR) and the CCR model with a scale shift to measure second-stage outputs, the range directional measure (RDM) model produces the most appropriate results. In this paper, an approach is proposed for estimating returns to scale. The study applies a two-stage DEA model with negative second-stage outputs to assess the public support for research, development, and demonstration projects in the energy sector in 23 countries over the period from 2010 to 2018. The assessment of government performance depends on its contribution to the growth of energy efficiency in the national economy and the reduction of its carbon intensity. Intermediate outputs (patents in the energy sector) are included in the analysis as both outputs of the first stage and inputs of the second stage. Taking the similarity between the calculations obtained without stage separation and the system efficiency calculations from the two-stage model as a measure of model adequacy, the RDM model shows the highest similarity scores.

Exploring the association between primary care efficiency and health system characteristics across European countries: a two-stage data envelopment analysis

BackgroundPrimary care is widely seen as a core component of resilient and sustainable health systems, yet its efficiency is not well understood and there is a lack of evidence about how primary care efficiency is associated with health system characteristics. We examine this issue through the lens of diabetes care, which has a well-established evidence base for effective treatment and has previously been used as a tracer condition to measure health system performance.MethodsWe developed a conceptual framework to guide the analysis of primary care efficiency. Using data on 18 European countries during 2010–2016 from several international databases, we applied a two-stage data envelopment analysis to estimate (i) technical efficiency of primary care and (ii) the association between efficiency and health system characteristics.ResultsCountries varied widely in terms of primary care efficiency, with efficiency scores depending on the range of population characteristics adjusted for. Higher efficiency was associated with bonus payments for the prevention and management of chronic conditions, nurse-led follow-up, and a financial incentive or requirement for patients to obtain a referral to specialist care. Conversely, lower efficiency was associated with higher rates of curative care beds and financial incentives for patients to register with a primary care provider.ConclusionsOur results underline the importance of considering differences in population characteristics when comparing country performance on primary care efficiency. We highlight several policies that could enhance the efficiency of primary care. Improvements in data collection would enable more comprehensive assessments of primary care efficiency across countries, which in turn could more effectively inform policymaking.

Source credibility plays the central route: an elaboration likelihood model exploration in social media environment with demographic profile analysis

PurposeThis study aims at building a framework for the electronic word-of-mouth (eWOM) response under the social media environment. The elaboration likelihood model was adopted to explain how message source credibility and message appeal jointly influence the eWOM response process, while source credibility provides a central route and message appeal plays a peripheral route for information processing.Design/methodology/approachThis study used a scenario design to test the decision behavior in the Facebook environment through message content manipulation. A convenience sampling method was adopted in this study. We collected 203 valid questionnaires and tested this research model with LISREL 8.8. This study used a two-stage structural equation modeling data analysis method with LISREL 8.8, by which the measurement model was assessed through confirmatory factor analysis for the reliability and validity of the research model, and the causal relationship among factors was assessed through exploratory factor analysis .FindingsThe results showed that 53% variance of eWOM responses could be explained by message source credibility and emotional message appeal from the elaboration likelihood model perspective. Message source credibility plays a central role in the social media environment. The model was further tested with a demographic profile analysis for both gender and age. It is found that a female user is influenced by both source credibility and emotional appeal, but a male user is only influenced by message source credibility. The mature age group is more responsive to eWOM messages.Research limitations/implicationsThe sample might not represent all social networking sites (SNS) users. The participants represent a small segment of the Facebook population around the globe. Secondly, this research design could be improved by using more recreational messages to test the effects of message appeal and message source credibility. Thirdly, the mobile phone is a type of physical product rather than an experiential product. Future studies could try to identify the same eWOM determinants with different SNS functions, for example, the inbox message function. Similarly, Facebook users are allowed to use both text and pictures to disseminate promotional messages.Practical implicationsThis study provides an insight for SNS administrators regarding the determinants of driving more customer responses toward a message. Message source credibility and message appeal are identified as the antecedents for eWOM responses in SNS. Companies could make use of this finding to improve their marketing communication strategy in SNS. The finding can inform administrators of the importance of focusing on both customers’ psychological state and message attributes during the dissemination of promotional messages to improve the efficiency of the promotional effort. Companies aimed at receiving different types of eWOM responses in SNS may need to consider other factors for creating their promotional messages.Originality/valuePrevious studies have mainly identified factors influencing eWOM responses from the people-centered variables such as personal traits and social relationships. This study proposes that the eWOM response is a dual information processing process that can be explained by the ELM. When a user processes information in SNS, he follows both the central route and the peripheral route (i.e. source credibility and message appeal) which can influence the eWOM response. It is the first time that the source credibility is investigated as the central route in ELM model.

Machine Learning Model with Computed Tomography Radiomics and Clinicobiochemical Characteristics Predict the Subtypes of Patients with Primary Aldosteronism

Adrenal venous sampling (AVS) is the primary method for differentiating between primary aldosterone (PA) subtypes. The aim of study is to develop prediction models for subtyping of patients with PA using computed tomography (CT) radiomics and clinicobiochemical characteristics associated with PA. This study retrospectively enrolled 158 patients with PA who underwent AVS between January 2014 and March 2021. Neural network machine learning models were developed using a two-stage analysis of triple-phase abdominal CT and clinicobiochemical characteristics. In the first stage, the models were constructed to classify unilateral or bilateral PA; in the second stage, they were designed to determine the predominant side in patients with unilateral PA. The final proposed model combined the best-performing models from both stages. The model's performance was evaluated using repeated stratified five-fold cross-validation. We employed paired t-tests to compare its performance with the conventional imaging evaluations made by radiologists, which categorize patients as either having bilateral PA or unilateral PA on one side. In the first stage, the integrated model that combines CT radiomic and clinicobiochemical characteristics exhibited the highest performance, surpassing both the radiomic-alone and clinicobiochemical-alone models. It achieved an accuracy and F1 score of 80.6%±3.0% and 74.8%±5.2% (area under the receiver operating curve [AUC] = 0.778±0.050). In the second stage, the accuracy and F1 score of the radiomic-based model were 88%±4.9% and 81.9%±6.2% (AUC=0.831±0.087). The proposed model achieved an accuracy and F1 score of 77.5%±3.9% and 70.5%±7.1% (AUC=0.771±0.046) in subtype diagnosis and lateralization, surpassing the accuracy and F1 score achieved by radiologists' evaluation (p<.05). The proposed machine learning model can predict the subtypes and lateralization of PA. It yields superior results compared toconventional imaging evaluation and has potential to supplement the diagnostic process in PA.

Prevalence of congenital anomalies according to maternal race and ethnicity, Texas, 1999-2018.

Few studies of congenital anomalies provide prevalence estimates stratified by maternal race/ethnicity. We sought to determine whether the prevalence of a broad spectrum of anomalies varies among offspring of women from different race/ethnic groups. We obtained information on cases with anomalies from the population-based Texas Birth Defects Registry, and denominator data on livebirths among Texas residents during 1999-2018 from the Texas Center for Health Statistics. We estimated the prevalence ratio (PR) and 95% confidence interval (CI) of N = 145 anomalies among offspring of Hispanic and non-Hispanic Black relative to non-Hispanic White women using Poisson regression, adjusting for maternal age, education, body mass index, and previous livebirths. We performed a two-stage analysis with a Bonferroni-adjusted p < 1.7 × 10-4 in the initial screening phase to identify anomalies with statistically significant variation. There were 7,698,768 livebirths and 1,187,385 anomalies diagnosed in 368,393 cases. The prevalence of any monitored congenital anomaly was similar among offspring of non-Hispanic White (referent), non-Hispanic Black (PR 0.98, CI 0.96-1.00), and Hispanic (PR 0.95, CI 0.93-0.96) women. We observed statistically significant racial/ethnic variation for 42 anomalies. Marked differences were observed when comparing offspring of non-Hispanic Black to non-Hispanic White women with respect to polydactyly (PR 4.38, CI 4.07-4.72), pyloric stenosis (PR 0.34, CI 0.29-0.40), and aortic valve atresia/stenosis (PR 0.51, CI 0.36-0.72). Birth prevalence of many major congenital anomalies varies by maternal race and ethnicity. While the reasons for these differences are likely multifactorial, a thorough understanding of racial and ethnic disparities is useful to stimulate etiologic research.

Real earnings management and ESG disclosure in emerging markets: The moderating effect of managerial ownership from a social norm perspective

Drawing on social norm theory, this study delves into the nexus between real earnings manipulation (REM) and Environmental, Social, and Governance (ESG) disclosure within Egypt's emerging capital market. By analyzing data from the S&P/EGX ESG index (2013–2018) through a two-stage regression analysis, we unearth a noteworthy pattern: heightened REM practices correspond with reduced tendencies for ESG sustainability disclosure. Notably, this association is moderated by managerial ownership, which diminishes the negative linkage between REM and ESG transparency. A unique cultural insight emerges, revealing that religiously-aligned firms leverage REM as a risk-mitigation mechanism, leading to curtailed ESG disclosures. Our findings cast a spotlight on a possible managerial tilt towards short-term gains, often overshadowing long-term sustainability imperatives, especially in religiously influenced contexts. As we advance understanding of REM-ESG dynamics in religious emerging markets, our study highlights the pressing need for enhanced sustainability consciousness and accountability in these regions.

How to Comprehensively Evaluate Firm Performance from Operational, Financial, and Sustainability Perspectives? A Two-Stage Data Envelopment Analysis Approach

ABSTRACT This study proposes a two-stage modeling framework to evaluate the efficiency of firm performance based on sustainability (environmental, social, and governance (ESG)), operational and financial measures. Diverging from previous studies, this study conceptualizes firm performance as two serially linked stages, with operational performance as the first stage and market performance as the second stage. Acknowledging that ESG activities may reflect firm value and that these activities depend on a firm’s operational performance, ESG scores are modeled simultaneously as an output of the operational performance stage and as an input for the market stage. Under this performance appraisal framework, two-stage data envelopment analysis models capturing overall and stage-level efficiency are constructed. The application of the proposed modeling framework is demonstrated using a sample of large Saudi listed firms as a case study of an emerging market. The main conclusion is that ESG legislation, regulations, and disclosure guidelines should be well defined in emerging markets to increase the overall efficiency of listed firms’ performance.

Economy or ecology? The relationship between biodiversity and human health in regions with different economic development

Climate change and the rapid loss of biodiversity pose threats to human survival and development. However, there remains a limited understanding of the relationship between biodiversity and human health, especially in the context of developing countries. This study pursues two objectives: (1) to explore the relationship between biodiversity and human health; and (2) to investigate how this relationship varies across different economic regions. Using a cross-sectional design, we analyzed data from 31 provinces, autonomous regions and municipalities across China. The dataset encompassed information on biodiversity (animals, plants, and fungi), subjective health, and mental health. We employed a two-stage least squares analysis, designating the proportion of part-time rangers and the completion of investments in wild fauna and flora per unit area as instrumental variables. Subsequently, we examined the moderating effect of the average Per Capita Disposable Income on the relationship between biodiversity and mental health. Additionally, we conducted grouped regression analyses for three regions with varying levels of economic development. The regression model incorporated macroecological, macroeconomic, and sociodemographic data as control variables. The results indicated a correlation between bird, plant species richness, biological richness (the total number of plants, animals, and fungi), and mental health. However, these biodiversity measures were significantly associated with poor subjective health. Additionally, the contribution of biological richness to mental health declines as the average Per Capita Disposable Income rises. The relationship between biodiversity and mental health was significantly negative in regions with low economic development, significantly positive in medium economic development regions, and not significant in high economic development regions. The analysis indicates that as the economy grows, there may exist a lower and upper threshold at which biodiversity exerts a positive impact on mental health. These thresholds merit further investigation. This observed gap might be attributed to the diminishing natural experiences in regions undergoing rapid economic development. The findings of this study offer insights that could guide policy decisions in developing countries, balancing biodiversity preservation, economic growth, and public health.