Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for ban...Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects.Additionally,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry.However,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks.To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making approach.First,a credit risk assessment index for Chinese real estate enterprises is established.Then,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods.This approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation information.Finally,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility.This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.展开更多
Since there are some signs of land degradation and desertification showing how soil sustainability is threatened, it is crucial to create a soil quality index(SQI) model in the semi-arid ?orum Basin, situated between ...Since there are some signs of land degradation and desertification showing how soil sustainability is threatened, it is crucial to create a soil quality index(SQI) model in the semi-arid ?orum Basin, situated between the Black Sea and Anatolia Region, Central Turkey. The primary aims of the study are:(1) to determine SQI values of the micro-basin in terms of land degradation and desertification.Moreover, the best-worst method(BWM) was used to determine the weighting score for each parameter;(2) to produce the soils' spatial distribution by utilizing different geostatistical models and GIS(geographic information system) techniques;and(3) to validate the obtained SQI values with biomass reflectance values. Therefore, the relationship of RE-OSAVI(red-edge optimized soil-adjusted vegetation index) and NDVI(normalized difference vegetation index) generated from Sentinel-2A satellite images at different time series with soil quality was examined. Results showed that SQI values were high in the areas that had almost a flat and slight slope. Moreover, the areas with high clay content and thick soil depth did not have salinity problems, and were generally distributed in the middle parts of the basin. However, the areas with a high slope, poor vegetation, high sand content, and low water holding capacity had low SQI values.Furthermore, a statistically high positive correlation of RE-OSAVI and NDVI indices with soil quality was found, and NDVI had the highest correlative value for June(R~2=0.802) compared with RE-OSAVI.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.72171182 and 72031009)the Spanish Ministry of Economy and Competitiveness through the Spanish National Research Project(Grant No.PGC2018-099402-B-I00)the Spanish postdoctoral fellowship program Ramon y Cajal(Grant No.RyC-2017-21978).
文摘Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects.Additionally,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry.However,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks.To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making approach.First,a credit risk assessment index for Chinese real estate enterprises is established.Then,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods.This approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation information.Finally,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility.This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.
文摘Since there are some signs of land degradation and desertification showing how soil sustainability is threatened, it is crucial to create a soil quality index(SQI) model in the semi-arid ?orum Basin, situated between the Black Sea and Anatolia Region, Central Turkey. The primary aims of the study are:(1) to determine SQI values of the micro-basin in terms of land degradation and desertification.Moreover, the best-worst method(BWM) was used to determine the weighting score for each parameter;(2) to produce the soils' spatial distribution by utilizing different geostatistical models and GIS(geographic information system) techniques;and(3) to validate the obtained SQI values with biomass reflectance values. Therefore, the relationship of RE-OSAVI(red-edge optimized soil-adjusted vegetation index) and NDVI(normalized difference vegetation index) generated from Sentinel-2A satellite images at different time series with soil quality was examined. Results showed that SQI values were high in the areas that had almost a flat and slight slope. Moreover, the areas with high clay content and thick soil depth did not have salinity problems, and were generally distributed in the middle parts of the basin. However, the areas with a high slope, poor vegetation, high sand content, and low water holding capacity had low SQI values.Furthermore, a statistically high positive correlation of RE-OSAVI and NDVI indices with soil quality was found, and NDVI had the highest correlative value for June(R~2=0.802) compared with RE-OSAVI.
