The purpose of this study was to explore the psychometric properties of the Chinese version of the autism spectrum rating scale（ASRS）. We recruited 1,625community-based children and 211 autism spectrum disorder（ASD...The purpose of this study was to explore the psychometric properties of the Chinese version of the autism spectrum rating scale（ASRS）. We recruited 1,625community-based children and 211 autism spectrum disorder（ASD） cases from 4 sites, and the parents of all participants completed the Chinese version of the ASRS. A robust weighted least squares means and variance adjusted estimator was used for exploratory factor analysis. The3-factor structure included 59 items suitable for the current sample. The item reliability for the modi？ed Chinese version of the ASRS（MC-ASRS） was excellent. Moreover,with 60 as the cut-off point, receiver operating characteristic analysis showed that the MC-ASRS had excellent discriminate validity, comparable to that of the unmodi？ed Chinese version（UC-ASRS）, with area under the curve values of 0.952（95% CI： 0.936–0.967） and 0.948（95% CI：0.930–0.965）, respectively. Meanwhile, the con？rm factor analysis revealed that MC-ASRS had a better construct validity than UC-ASRS based on the above factor solution in another children sample. In conclusion, the MC-ASRS shows better ef？cacy in epidemiological screening for ASD in Chinese children.展开更多
A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralizatio...A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralization,was selected for interpretation.The median+2 MAD(median absolute deviation)method of exploratory data analysis(EDA)and C-A(concentration-area)fractal modeling were then applied to the Mahalanobis distance,as defined by Zn,Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies.As a result,the median+2 MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model.The soil anomaly identified by the median+2 MAD method on the Mahalanobis distances defined by three principal elements(Zn,Cu and Pb)rather than thirteen elements(Co,Zn,Cu,V,Mo,Ni,Cr,Mn,Pb,Ba,Sr,Zr and Ti)was the more favorable reflection of the ore body.The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation.The results showed that the median+2 MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization,which is therefore useful at the reconnaissance drilling stage.展开更多
The public health workforce is a key component of public health system.To articulate the scope of public health workforce,we reviewed the relevant World Health Organization(wHO)guidance and peer-reviewed journal artic...The public health workforce is a key component of public health system.To articulate the scope of public health workforce,we reviewed the relevant World Health Organization(wHO)guidance and peer-reviewed journal articles on this subject.Specifically,we assessed and compared the relevant publications produced by WHO Headquarters and Regional Offices along with other literature on this issue.Our focus was on the“occupation,workplace setting,and employer of public health workforce”.It is noteworthy that WHO has adopted a conceptual framework with an inclusive scope of the public health workforce,while setting out a 5-year vision to strengthen capacity across all WHO Member States for a multidisciplinary workforce to deliver the essential public health functions,including emergency preparedness and response.The importance of public health workforce in global and national responses to the coronavirus disease 2019(COVID-19)pandemic is recognized.We also observed that there were diverse understandings of the scope of public health workforce worldwide,including macro-,meso-and micro-level perspectives.In the post-COVID-19 era,we suggest that policy-makers and practitioners at the national,regional and global level adopt a coordinated approach to expand and strengthen the national workforce as guided by the WHO towards the health-related targets of United Nations Sustainable Development Goals such as health security and Universal Health Coverage.展开更多
Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building ...Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building refurbishment projects will lead to an increase in organizational interactions in the construction works as building refurbishment works involve interactions among many different organizations and it can cause Inter-Organizational conflict(IOC)among organizations involved in projects.This paper adopted an Exploratory Factor Analysis(EFA)approach to analyses IOC in building refurbishment projects.For this study,a fivepoint Likert Scale was adopted to ensure the instruments of the study are reliable.The researcher ultimately sent questionnaires as a web-link and email invitation to 1050 construction firms and 733 architectural firms.The questionnaire sent to managers and professionals from construction and architectural firms in Malaysia.Finally,one-hundred-seventy-nine(179)refurbishment projects formed a database for this paper.The finding of this paper shows the IOC factors that contribute to the improve the performance of building refurbishment project can be conflict during the construction stage,conflict between the client and the consultant,task expectations,basic responsibilities,final duration,project’s goals,conflict between the client and the contractor,final cost,final quality,standards of behaviors,conflict between the contractor and the consultant,interference and conflict during the design stage.展开更多
Clustering is used to gain an intuition of the struc tures in the data.Most of the current clustering algorithms pro duce a clustering structure even on data that do not possess such structure.In these cases,the algor...Clustering is used to gain an intuition of the struc tures in the data.Most of the current clustering algorithms pro duce a clustering structure even on data that do not possess such structure.In these cases,the algorithms force a structure in the data instead of discovering one.To avoid false structures in the relations of data,a novel clusterability assessment method called density-based clusterability measure is proposed in this paper.I measures the prominence of clustering structure in the data to evaluate whether a cluster analysis could produce a meaningfu insight to the relationships in the data.This is especially useful in time-series data since visualizing the structure in time-series data is hard.The performance of the clusterability measure is evalu ated against several synthetic data sets and time-series data sets which illustrate that the density-based clusterability measure can successfully indicate clustering structure of time-series data.展开更多
The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis w...The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis was applied in a sample consisting of workers of the S?o Paulo Metropolitan Area, based on the origin-destination home interview survey, carried out in 1997, in order to: 1) examine the interdependence between travel patterns and a set of socioeconomic and urban environment variables;2) determine if the original database can be synthetized on components. The results enabled to observe relations between the individual’s socio-economic class and car usage, characteristics of urban environment and destination choices, as well as age and non-motorized travel mode choice. It is then concluded that the database can be adequately summarized in three components for subsequent analysis: 1) urban environment;2) socio-economic class;and 3) family structure.展开更多
This paper discusses the utilization of latent variable modeling related to occupational health and safety in the mining industry.Latent variable modeling,which is a statistical model that relates observable and laten...This paper discusses the utilization of latent variable modeling related to occupational health and safety in the mining industry.Latent variable modeling,which is a statistical model that relates observable and latent variables,could be used to facilitate researchers’understandings of the underlying constructs or hypothetical factors and their magnitude of effect that constitute a complex system.This enhanced understanding,in turn,can help emphasize the important factors to improve mine safety.The most commonly used techniques include the exploratory factor analysis(EFA),the confirmatory factor analysis(CFA)and the structural equation model with latent variables(SEM).A critical comparison of the three techniques regarding mine safety is provided.Possible applications of latent variable modeling in mining engineering are explored.In this scope,relevant research papers were reviewed.They suggest that the application of such methods could prove useful in mine accident and safety research.Application of latent variables analysis in cognitive work analysis was proposed to improve the understanding of human-work relationships in mining operations.展开更多
Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 pref...Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 prefecturelevel cities in the Yangtze River Economic Belt(YREB)as study areas.We calculated the YREB’s level of urban resilience based on the aspects of“economy-society-population-ecology-infrastructure”,which ensured that the comprehensive evaluation of urban resilience is complete and sufficient.The spatio-temporal evolution of urban resilience was analyzed using exploratory spatial data.Geodetectors were used to investigate the impact of several indicators,focusing on economic,social,population,ecological,and infrastructure factors,on urban resilience.The results showed that the urban resilience of the YREB has maintained a slow upward trend from 2005 to 2018,and the average urban resilience of the YREB has risen from 0.2442 to 0.2560.The resilience gap between cities in the study region increased initially and then decreased.The dominant factor in the spatial differentiation of urban resilience was the economic factors,followed by the population factors.Urban resilience has been clarified and an evaluation index system is constructed,which can provide an effective reference for the evaluation of urban resilience among countries around the world.Based on this,factors that optimize urban resilience are configured,and the regional and national sustainable development can be promoted.展开更多
Factor analysis (FA) is a time-honored multivariate analysis procedure for exploring the factors underlying observed variables. In this paper, we propose a new algorithm for the generalized least squares (GLS) estimat...Factor analysis (FA) is a time-honored multivariate analysis procedure for exploring the factors underlying observed variables. In this paper, we propose a new algorithm for the generalized least squares (GLS) estimation in FA. In the algorithm, a majorization step and diagonal steps are alternately iterated until convergence is reached, where Kiers and ten Berge’s (1992) majorization technique is used for the former step, and the latter ones are formulated as minimizing simple quadratic functions of diagonal matrices. This procedure is named a majorizing-diagonal (MD) algorithm. In contrast to the existing gradient approaches, differential calculus is not used and only elmentary matrix computations are required in the MD algorithm. A simuation study shows that the proposed MD algorithm recovers parameters better than the existing algorithms.展开更多
Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to o...Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to offer a unique opportunity to monitor air quality and help fill air pollution data gaps that hinder efforts to study air pollution and protect public health. This geographical study explores if there is an association between PM2.5 and lung cancer mortality rate in the conterminous USA. Lung cancer (ICD-10 codes C34- C34) death count and population at risk by county were extracted for the period from 2001 to 2010 from the U.S. CDC WONDER online database. The 2001-2010 Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset was used to calculate a 10 year average PM2.5 pollution. Exploratory spatial data analyses, spatial regression (a spatial lag and a spatial error model), and spatially extended Bayesian Monte Carlo Markov Chain simulation found that there is a significant positive association between lung cancer mortality rate and PM2.5. The association would justify the need of further toxicological investigation of the biological mechanism of the adverse effect of the PM2.5 pollution on lung cancer. The Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset provides a continuous surface of concentrations of PM2.5 and is a useful data source for environmental health research.展开更多
That SOEs are inefficient is still a consensus in most economic literature. However, in recent studies, more and more arguments are made in favor of the efficiency of SOEs, yet existing empirical studies are mostly ba...That SOEs are inefficient is still a consensus in most economic literature. However, in recent studies, more and more arguments are made in favor of the efficiency of SOEs, yet existing empirical studies are mostly based on production industry data as samples. On the basis of adopting distribution samples and conducting a cross-sector comparison between the production industry and the distribution sector, this paper offers a multi-perspective empirical assessment on the efficiency of SOEs. Through the analysis of major JTnancial indicators and adopting the Data Envelopment Analysis-Malmquist index for total factor productivity comparison, we find that SOEs generally do not have any disadvantage in efficiency and their superior efficiency is particularly pronounced in the distribution sector as compared with production industry. Moreover, the high share and high efficiency of state capital in the wholesale sector needs particular attention. This paper employs case studies to reveal the positive correlation between the assets-heavy operation of state-owned wholesale firms and their profitability. The implications are as follows： policymakers must deliberate prudently before deciding to withdraw or increase state capital in various sectors; in the wholesale sector where state capital is more efficient, the functions of state capital can be bolstered by increasing its presence in the sector,＂ the notion that state capital must be withdrawn from competitive sectors cannot be adopted likely, nor should the benefits of asset-light operation be exaggerated.展开更多
Burnout is an escalating global occupational health challenge,requiring valid and reliable assessment tools.This study validates the Copenhagen Burnout Inventory(CBI)for assessing burnout among Sudanese workers in the...Burnout is an escalating global occupational health challenge,requiring valid and reliable assessment tools.This study validates the Copenhagen Burnout Inventory(CBI)for assessing burnout among Sudanese workers in the education,healthcare,and banking sectors,where burnout prevalence is high.Utilizing the 19-item CBI,translated into Arabic,the study measured burnout across three dimensions:Personal Burnout(PB),Work-related Burnout(WB),and Client-related Burnout(CB).A total of 1068 participants were surveyed,including 438 teachers(41%),326 healthcare workers(30.5%),and 304 bank employees(28.5%).Exploratory and Confirmatory Factor Analyses confirmed the construct validity of the CBI,while concurrent validity was supported through moderate to high correlations with the Maslach Burnout Inventory(MBI)domains,except for a weak correlation between Depersonalization and PB/WB.Reliability was established through Cronbach’s Alpha(α),McDonald’s Omega(ω),Composite Reliability(CR),Average Variance Extracted(AVE),and discriminant validity,all of which were satisfactory across the three groups.The study resulted in two final versions of the CBI:a 17-item version for healthcare workers and a 19-item version for teachers and bank employees.Both versions are available in Arabic,and stakeholders are recommended to use the CBI tailored to each sector’s specific psychometric properties.This tailored approach ensures accurate measurement of burnout,aiding psychologists,therapists,and policymakers in addressing and mitigating burnout effectively within each professional group.展开更多
基金supported by the National Health and Family Planning Commission of the People’s Republic of China(201302002Clinical Trials.gov number NCT 02200679)+1 种基金the Shanghai International Cooperation Ministry of Science Projects(14430712200)the Development Project of Shanghai Peak Discipline-Integrated Chinese and Western Medicine
文摘The purpose of this study was to explore the psychometric properties of the Chinese version of the autism spectrum rating scale（ASRS）. We recruited 1,625community-based children and 211 autism spectrum disorder（ASD） cases from 4 sites, and the parents of all participants completed the Chinese version of the ASRS. A robust weighted least squares means and variance adjusted estimator was used for exploratory factor analysis. The3-factor structure included 59 items suitable for the current sample. The item reliability for the modi？ed Chinese version of the ASRS（MC-ASRS） was excellent. Moreover,with 60 as the cut-off point, receiver operating characteristic analysis showed that the MC-ASRS had excellent discriminate validity, comparable to that of the unmodi？ed Chinese version（UC-ASRS）, with area under the curve values of 0.952（95% CI： 0.936–0.967） and 0.948（95% CI：0.930–0.965）, respectively. Meanwhile, the con？rm factor analysis revealed that MC-ASRS had a better construct validity than UC-ASRS based on the above factor solution in another children sample. In conclusion, the MC-ASRS shows better ef？cacy in epidemiological screening for ASD in Chinese children.
文摘A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralization,was selected for interpretation.The median+2 MAD(median absolute deviation)method of exploratory data analysis(EDA)and C-A(concentration-area)fractal modeling were then applied to the Mahalanobis distance,as defined by Zn,Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies.As a result,the median+2 MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model.The soil anomaly identified by the median+2 MAD method on the Mahalanobis distances defined by three principal elements(Zn,Cu and Pb)rather than thirteen elements(Co,Zn,Cu,V,Mo,Ni,Cr,Mn,Pb,Ba,Sr,Zr and Ti)was the more favorable reflection of the ore body.The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation.The results showed that the median+2 MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization,which is therefore useful at the reconnaissance drilling stage.
文摘The public health workforce is a key component of public health system.To articulate the scope of public health workforce,we reviewed the relevant World Health Organization(wHO)guidance and peer-reviewed journal articles on this subject.Specifically,we assessed and compared the relevant publications produced by WHO Headquarters and Regional Offices along with other literature on this issue.Our focus was on the“occupation,workplace setting,and employer of public health workforce”.It is noteworthy that WHO has adopted a conceptual framework with an inclusive scope of the public health workforce,while setting out a 5-year vision to strengthen capacity across all WHO Member States for a multidisciplinary workforce to deliver the essential public health functions,including emergency preparedness and response.The importance of public health workforce in global and national responses to the coronavirus disease 2019(COVID-19)pandemic is recognized.We also observed that there were diverse understandings of the scope of public health workforce worldwide,including macro-,meso-and micro-level perspectives.In the post-COVID-19 era,we suggest that policy-makers and practitioners at the national,regional and global level adopt a coordinated approach to expand and strengthen the national workforce as guided by the WHO towards the health-related targets of United Nations Sustainable Development Goals such as health security and Universal Health Coverage.
基金the Exploratory Research Grant Scheme(ERGS)of Universiti Teknologi MARA(UiTM)Malaysia(No.ERGS/1/2013/SSl11/UITM/01/01)High-Level Talents Introduction Funding of Haixi Research Institute,the Chinese Academy of Sciences(No.19Q3671boa).
文摘Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building refurbishment projects will lead to an increase in organizational interactions in the construction works as building refurbishment works involve interactions among many different organizations and it can cause Inter-Organizational conflict(IOC)among organizations involved in projects.This paper adopted an Exploratory Factor Analysis(EFA)approach to analyses IOC in building refurbishment projects.For this study,a fivepoint Likert Scale was adopted to ensure the instruments of the study are reliable.The researcher ultimately sent questionnaires as a web-link and email invitation to 1050 construction firms and 733 architectural firms.The questionnaire sent to managers and professionals from construction and architectural firms in Malaysia.Finally,one-hundred-seventy-nine(179)refurbishment projects formed a database for this paper.The finding of this paper shows the IOC factors that contribute to the improve the performance of building refurbishment project can be conflict during the construction stage,conflict between the client and the consultant,task expectations,basic responsibilities,final duration,project’s goals,conflict between the client and the contractor,final cost,final quality,standards of behaviors,conflict between the contractor and the consultant,interference and conflict during the design stage.
文摘Clustering is used to gain an intuition of the struc tures in the data.Most of the current clustering algorithms pro duce a clustering structure even on data that do not possess such structure.In these cases,the algorithms force a structure in the data instead of discovering one.To avoid false structures in the relations of data,a novel clusterability assessment method called density-based clusterability measure is proposed in this paper.I measures the prominence of clustering structure in the data to evaluate whether a cluster analysis could produce a meaningfu insight to the relationships in the data.This is especially useful in time-series data since visualizing the structure in time-series data is hard.The performance of the clusterability measure is evalu ated against several synthetic data sets and time-series data sets which illustrate that the density-based clusterability measure can successfully indicate clustering structure of time-series data.
文摘The main objective of this study is to analyze work travel-related behavior through a set of variables relative to socio-economic class, urban environment and travel characteristics. The Principal Component Analysis was applied in a sample consisting of workers of the S?o Paulo Metropolitan Area, based on the origin-destination home interview survey, carried out in 1997, in order to: 1) examine the interdependence between travel patterns and a set of socioeconomic and urban environment variables;2) determine if the original database can be synthetized on components. The results enabled to observe relations between the individual’s socio-economic class and car usage, characteristics of urban environment and destination choices, as well as age and non-motorized travel mode choice. It is then concluded that the database can be adequately summarized in three components for subsequent analysis: 1) urban environment;2) socio-economic class;and 3) family structure.
基金Natural Sciences and Engineering Research Council of Canada(NSERC)(ID:236482)for supporting this research
文摘This paper discusses the utilization of latent variable modeling related to occupational health and safety in the mining industry.Latent variable modeling,which is a statistical model that relates observable and latent variables,could be used to facilitate researchers’understandings of the underlying constructs or hypothetical factors and their magnitude of effect that constitute a complex system.This enhanced understanding,in turn,can help emphasize the important factors to improve mine safety.The most commonly used techniques include the exploratory factor analysis(EFA),the confirmatory factor analysis(CFA)and the structural equation model with latent variables(SEM).A critical comparison of the three techniques regarding mine safety is provided.Possible applications of latent variable modeling in mining engineering are explored.In this scope,relevant research papers were reviewed.They suggest that the application of such methods could prove useful in mine accident and safety research.Application of latent variables analysis in cognitive work analysis was proposed to improve the understanding of human-work relationships in mining operations.
基金I would like to thank the National Natural Science Foundation of China(Grant No.42061041)for the funding.
文摘Urban resilience assesses a city’s ability to withstand unknown risks.Scholars are not comprehensive in assessing urban resilience,and they lack consideration of population resilience.This study investigated 110 prefecturelevel cities in the Yangtze River Economic Belt(YREB)as study areas.We calculated the YREB’s level of urban resilience based on the aspects of“economy-society-population-ecology-infrastructure”,which ensured that the comprehensive evaluation of urban resilience is complete and sufficient.The spatio-temporal evolution of urban resilience was analyzed using exploratory spatial data.Geodetectors were used to investigate the impact of several indicators,focusing on economic,social,population,ecological,and infrastructure factors,on urban resilience.The results showed that the urban resilience of the YREB has maintained a slow upward trend from 2005 to 2018,and the average urban resilience of the YREB has risen from 0.2442 to 0.2560.The resilience gap between cities in the study region increased initially and then decreased.The dominant factor in the spatial differentiation of urban resilience was the economic factors,followed by the population factors.Urban resilience has been clarified and an evaluation index system is constructed,which can provide an effective reference for the evaluation of urban resilience among countries around the world.Based on this,factors that optimize urban resilience are configured,and the regional and national sustainable development can be promoted.
文摘Factor analysis (FA) is a time-honored multivariate analysis procedure for exploring the factors underlying observed variables. In this paper, we propose a new algorithm for the generalized least squares (GLS) estimation in FA. In the algorithm, a majorization step and diagonal steps are alternately iterated until convergence is reached, where Kiers and ten Berge’s (1992) majorization technique is used for the former step, and the latter ones are formulated as minimizing simple quadratic functions of diagonal matrices. This procedure is named a majorizing-diagonal (MD) algorithm. In contrast to the existing gradient approaches, differential calculus is not used and only elmentary matrix computations are required in the MD algorithm. A simuation study shows that the proposed MD algorithm recovers parameters better than the existing algorithms.
文摘Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to offer a unique opportunity to monitor air quality and help fill air pollution data gaps that hinder efforts to study air pollution and protect public health. This geographical study explores if there is an association between PM2.5 and lung cancer mortality rate in the conterminous USA. Lung cancer (ICD-10 codes C34- C34) death count and population at risk by county were extracted for the period from 2001 to 2010 from the U.S. CDC WONDER online database. The 2001-2010 Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset was used to calculate a 10 year average PM2.5 pollution. Exploratory spatial data analyses, spatial regression (a spatial lag and a spatial error model), and spatially extended Bayesian Monte Carlo Markov Chain simulation found that there is a significant positive association between lung cancer mortality rate and PM2.5. The association would justify the need of further toxicological investigation of the biological mechanism of the adverse effect of the PM2.5 pollution on lung cancer. The Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset provides a continuous surface of concentrations of PM2.5 and is a useful data source for environmental health research.
文摘That SOEs are inefficient is still a consensus in most economic literature. However, in recent studies, more and more arguments are made in favor of the efficiency of SOEs, yet existing empirical studies are mostly based on production industry data as samples. On the basis of adopting distribution samples and conducting a cross-sector comparison between the production industry and the distribution sector, this paper offers a multi-perspective empirical assessment on the efficiency of SOEs. Through the analysis of major JTnancial indicators and adopting the Data Envelopment Analysis-Malmquist index for total factor productivity comparison, we find that SOEs generally do not have any disadvantage in efficiency and their superior efficiency is particularly pronounced in the distribution sector as compared with production industry. Moreover, the high share and high efficiency of state capital in the wholesale sector needs particular attention. This paper employs case studies to reveal the positive correlation between the assets-heavy operation of state-owned wholesale firms and their profitability. The implications are as follows： policymakers must deliberate prudently before deciding to withdraw or increase state capital in various sectors; in the wholesale sector where state capital is more efficient, the functions of state capital can be bolstered by increasing its presence in the sector,＂ the notion that state capital must be withdrawn from competitive sectors cannot be adopted likely, nor should the benefits of asset-light operation be exaggerated.
基金funded by King Saud University,Riyadh,Saudi Arabia,grant number(ORFFT-2025-136-1).
文摘Burnout is an escalating global occupational health challenge,requiring valid and reliable assessment tools.This study validates the Copenhagen Burnout Inventory(CBI)for assessing burnout among Sudanese workers in the education,healthcare,and banking sectors,where burnout prevalence is high.Utilizing the 19-item CBI,translated into Arabic,the study measured burnout across three dimensions:Personal Burnout(PB),Work-related Burnout(WB),and Client-related Burnout(CB).A total of 1068 participants were surveyed,including 438 teachers(41%),326 healthcare workers(30.5%),and 304 bank employees(28.5%).Exploratory and Confirmatory Factor Analyses confirmed the construct validity of the CBI,while concurrent validity was supported through moderate to high correlations with the Maslach Burnout Inventory(MBI)domains,except for a weak correlation between Depersonalization and PB/WB.Reliability was established through Cronbach’s Alpha(α),McDonald’s Omega(ω),Composite Reliability(CR),Average Variance Extracted(AVE),and discriminant validity,all of which were satisfactory across the three groups.The study resulted in two final versions of the CBI:a 17-item version for healthcare workers and a 19-item version for teachers and bank employees.Both versions are available in Arabic,and stakeholders are recommended to use the CBI tailored to each sector’s specific psychometric properties.This tailored approach ensures accurate measurement of burnout,aiding psychologists,therapists,and policymakers in addressing and mitigating burnout effectively within each professional group.
