A Study on the Factors Influencing Consumer Purchase Decision Under the Live-Streaming Sales Model

In recent years,with the rapid development and popularization of Internet information technology,many new media platforms have risen rapidly,and major e-commerce companies have begun to explore the mode of livestreaming.Especially during the COVID-19 pandemic,due to the lockdown,live-streaming has become an important means of economic development in many places.Owing to its remarkable characteristics of timeliness,entertainment,and interactivity,it has become the latest and trendiest sales mode of e-commerce channels,reflecting huge economic potential and commercial value.This article analyzes two models and their characteristics of live-streaming sales from a practical perspective.Based on this,it outlines consumer purchasing decisions and the factors that affect consumer purchasing decisions under the live-streaming sales model.Finally,it discusses targeted suggestions for using the live-streaming sales model to expand the consumer market,hoping to promote the healthy and steady development of the live-streaming sales industry.

Coupled multiphysical model for investigation of influence factors in the application of microbially induced calcite precipitation

The study presents a comprehensive coupled thermo-bio-chemo-hydraulic(T-BCH)modeling framework for stabilizing soils using microbially induced calcite precipitation(MICP).The numerical model considers relevant multiphysics involved in MICP,such as bacterial ureolytic activities,biochemical reactions,multiphase and multicomponent transport,and alteration of the porosity and permeability.The model incorporates multiphysical coupling effects through well-established constitutive relations that connect parameters and variables from different physical fields.It was implemented in the open-source finite element code OpenGeoSys(OGS),and a semi-staggered solution strategy was designed to solve the couplings,allowing for flexible model settings.Therefore,the developed model can be easily adapted to simulate MICP applications in different scenarios.The numerical model was employed to analyze the effect of various factors,including temperature,injection strategies,and application scales.Besides,a TBCH modeling study was conducted on the laboratory-scale domain to analyze the effects of temperature on urease activity and precipitated calcium carbonate.To understand the scale dependency of MICP treatment,a large-scale heterogeneous domain was subjected to variable biochemical injection strategies.The simulations conducted at the field-scale guided the selection of an injection strategy to achieve the desired type and amount of precipitation.Additionally,the study emphasized the potential of numerical models as reliable tools for optimizing future developments in field-scale MICP treatment.The present study demonstrates the potential of this numerical framework for designing and optimizing the MICP applications in laboratory-,prototype-,and field-scale scenarios.

A Comparative Study on Factors Influencing Food Security in China and India

This paper analyzes and compares the key factors influencing food security in two populous countries(China and India),and cate-gorizes them into three types:agricultural production,economic development and income level,and income distribution.Using the prevalence of undernourishment as an indicator of food security,the paper empirically tests the degree of impact of various factors on food security in both countries using Tobit regression and Newey regression methods.The study finds that improving the level of economic development can significantly enhance food security in both countriesꎻreducing the Gini coefficient has a significant impact on India,but not on Chinaꎻincreasing the agricultural production per capita has a much greater effect on China than on India.Therefore,both countries should take measures that are both similar and different according to their national conditions to improve their food security level.

Analysis of influencing factors and the construction of predictive models for postpartum depression in older pregnant women

BACKGROUND Changes in China's fertility policy have led to a significant increase in older pregnant women.At present,there is a lack of analysis of influencing factors and research on predictive models for postpartum depression(PPD)in older pregnant women.AIM To analysis the influencing factors and the construction of predictive models for PPD in older pregnant women.METHODS By adopting a cross-sectional survey research design,239 older pregnant women(≥35 years old)who underwent obstetric examinations and gave birth at Suzhou Ninth People's Hospital from February 2022 to July 2023 were selected as the research subjects.When postpartum women of advanced maternal age came to the hospital for follow-up 42 d after birth,the Edinburgh PPD Scale(EPDS)was used to assess the presence of PPD symptoms.The women were divided into a PPD group and a no-PPD group.Two sets of data were collected for analysis,and a prediction model was constructed.The performance of the predictive model was evaluated using receiver operating characteristic(ROC)analysis and the Hosmer-Lemeshow goodness-of-fit test.RESULTS On the 42nd day after delivery,51 of 239 older pregnant women were evaluated with the EPDS scale and found to have depressive symptoms.The incidence rate was 21.34%(51/239).There were statistically significant differences between the PPD group and the no-PPD group in terms of education level(P=0.004),family relationships(P=0.001),pregnancy complications(P=0.019),and mother–infant separation after birth(P=0.002).Multivariate logistic regression analysis showed that a high school education and below,poor family relationships,pregnancy complications,and the separation of the mother and baby after birth were influencing factors for PPD in older pregnant women(P<0.05).Based on the influencing factors,the following model equation was developed:Logit(P)=0.729×education level+0.942×family relationship+1.137×pregnancy complications+1.285×separation of the mother and infant after birth-6.671.The area under the ROC curve of this prediction model was 0.873(95%CI:0.821-0.924),the sensitivity was 0.871,and the specificity was 0.815.The deviation between the value predicted by the model and the actual value through the Hosmer-Lemeshow goodness-of-fit test was not statistically significant(χ^(2)=2.749,P=0.638),indicating that the model did not show an overfitting phenomenon.CONCLUSION The risk of PPD among older pregnant women is influenced by educational level,family relationships,pregnancy complications,and the separation of the mother and baby after birth.A prediction model based on these factors can effectively predict the risk of PPD in older pregnant women.

Urban Agglomerations in China: Characteristics and Influencing Factors of Population Agglomeration

Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy has developed rapidly in the recent decades of China,and the UAs have also developed rapidly.However,as a large population country,the population distribution and changes of UAs in China has unique characteristics.Using the fifth,sixth and seventh population census data,spatial auto-correlation and spatial econometric models,we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China’s UAs.Results revealed that:1)from 2000 to 2020,the population gradually converged into UAs,and the characteristics of population agglomeration in different development degree of UAs differ.The higher the development degree of UA,the higher the population agglomeration degree.Besides,UAs are the main area with the most significant population agglomeration degree,and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space.The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities.2)Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs.The main factors of population gather into UAs are similar with the outside UAs,but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020.Meanwhile,the other factors,such as high-quality public services,good urban living environment conditions,high-quality medical and educational resources,are also important factors to promote urban population gather into UAs.This study provides a basis for formulating the development planning of UAs in China,and enriches the relevant theoretical research of population evolution and influencing factors of UAs.

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

Analysis of Factors Influencing Insomnia and Construction of a Prediction Model:A Cross-sectional Survey on Rescuers

Objective To determine the factors influencing insomnia and construct early insomnia warning tools for rescuers to informbest practices for early screening and intervention.Methods Cluster sampling was used to conduct a cross-sectional survey of 1,133 rescuers from one unit in Beijing,China.Logistic regression modeling and R software were used to analyze insomniarelated factors and construct a PRISM model,respectively.Results The positive rate of insomnia among rescuers was 2.74%.Accounting for participants’age,education,systolic pressure,smoking,per capita family monthly income,psychological resilience,and cognitive emotion regulation,logistic regression analysis revealed that,compared with families with an average monthly income less than 3,000 yuan,the odds ratio(OR)values and the[95%confidence interval(CI)]for participants of the following categories were as follows:average monthly family income greater than 5,000 yuan:2.998(1.307–6.879),smoking:4.124(1.954–8.706),and psychological resilience:0.960(0.933–0.988).The ROC curve area of the PRISM model(AUC)=0.7650,specificity=0.7169,and sensitivity=0.7419.Conclusion Insomnia was related to the participants’per capita family monthly income,smoking habits,and psychological resilience on rescue workers.The PRISM model’s good diagnostic value advises its use to screen rescuer early sleep quality.Further,advisable interventions to optimize sleep quality and battle effectiveness include psychological resilience training and smoking cessation.

Influencing Factors of Total Factor Energy Efficiency in Bohai Rim Region Based on DEA-Tobit Model

Bohai Rim region is an important economic development area and a large carbon emission area in China.It is of great significance to explore the total factor energy efficiency and its influencing factors for the low carbon transformation and high-quality development of the Bohai Rim region.Based on the total factor energy efficiency framework,the DDF-DEA model was used to calculate the total factor energy efficiency,and the internal and external differences of the total factor energy efficiency were further analyzed.The internal and external influencing factors were determined by ML index method and classical endogenous growth theory,and then the Tobit panel model was used to empirically analyze the action mechanism of all influencing factors of total factor energy efficiency in the Bohai Rim region.The results show that the pure technical efficiency,scale efficiency and technological progress among the internal influencing factors contribute to the improvement of energy efficiency in the Bohai Rim region.Industrial structure,industrial internal structure and ownership structure inhibit the improvement of energy efficiency.Energy consumption structure and energy endowment also have a negative impact on energy efficiency.Therefore,measures such as promoting technological progress,adjusting economic structure and optimizing energy structure will effectively improve total factor energy efficiency in the Bohai Rim region.

Influencing factors of fatigue in young and middle-aged patients with coronary heart disease:a cross-sectional study

Objective:To examine the present state of fatigue in young and middle-aged patients with coronary heart disease(CHD)and to identify the elements that may be affecting it.Methods:From December 2020 to June 2021,240 young and middle-aged patients with CHD who were being treated in the cardiology department of a tertiary care hospital in Suzhou were chosen using a convenience sampling method in order to gather data on the patients’sociodemographic status,fatigue,social support,and stress.Results:Of the 240 disseminated questionnaires,220 valid responses were returned,resulting in an effective recovery rate of 91.67%.The frequency of exhaustion was 51.8%,and the fatigue score was(5.27±2.77).The stress score was(11.15±3.36),while the overall social support score was(39.13±4.72).Binary logistic regression analysis indicated that age,exercise,staying up late,stress,social support,high-sensitivity troponin T,high-density lipoprotein,and ejection fraction were independent risk factors for fatigue in young and middle-aged patients with CHD(P<0.05).Conclusions:Fatigue is more prevalent in young and middle-aged patients with CHD.Clinical nurses can create a unique management plan for patients based on their lifestyle and behavioral patterns,stress levels,social support,and clinical signs to reduce fatigue.

Factors affecting land dissection density in geomorphological regions of China

Land dissection density(LDD)provides morphological evidence regarding prior intense soil erosion and quantifies the distribution of land dissections.A comprehensive understanding of the potential factors influencing the spatial pattern and value of the LDD is vital in geological disasters,soil erosion,and other related domains.Land dissection phenomena in China affects large areas with different morphological,pedological,and climatic characteristics.Prior studies have focused on the potential factors influencing the LDD at a watershed scale.However,these results are insufficient to reflect the status quo of dissection development and its primary influencing factors on a national scale.LDD’s spatial patterns and the dominant factors at a regional scale in millions of square kilometers remain to be ascertained.This study used the geomorphon-based method and the geographical detector model to quantify the spatial pattern of LDD over China and identify the dominant factors affecting this pattern in China’s six first-order geomorphological regions(GR1~GR6).The results yield the following findings:(1)LDD in China ranges from 0~4.55 km/km^(2),which is larger in central and eastern regions than in other regions of China;(2)dominant factors and their dominant risk subcategories vary with each geomorphological region’s primary internal and external forces;(3)the influence of natural factors is more significant on the large regional scale in millions of square kilometers compared to anthropogenic factors;relief degree of land surface(RDLS)is dominant in GR1,GR2,and GR5;the slope is dominant in GR6,soil type is dominant in GR3 and GR4,and lithology plays a critical role in the dominant interactions of GR3,GR4,and GR6;(4)the interactions between factors on LDD’s spatial pattern have a more significant effect than individual factors.

Influencing factors on the accuracy of local geoid model

Different modification methods and software programs were developed to obtain accurate local geoid models in the past two decades.The quantitative effect of the main factors on the accuracy of local geoid modeling is still ambiguous and has not been clearly diagnosed yet.This study presents efforts to find the most influential factors on the accuracy of the local geoid model,as well as the amount of each factor’s effect quantitatively.The methodology covers extracting the quantitative characteristics of 16 articles regarding local geoid models of different countries.The Statistical Package of Social Sciences(SPSS)software formulated a strong multiple regression model of correlation coefficient r = 0.999 with a high significance coefficient of determination R^2 = 0.997 and adjusted R^2 = 0,98 for the required effective factors.Then,factor analysis is utilized to extract the dominant factors which include:accuracy of gravity data(40%),the density of gravity data(25%)(total gravity factors is 65%),the Digital Elevation Model(DEM)resolution(16%),the accuracy of GPS/leveling points(10%)and the area of the terrain of the country/state under the study(9%).These results of this study will assist in developing more accurate local geoid models.

Development and validation of a predictive model for acute-onchronic liver failure after transjugular intrahepatic portosystemic shunt

BACKGROUND Transjugular intrahepatic portosystemic shunt(TIPS)is a cause of acute-onchronic liver failure(ACLF).AIM To investigate the risk factors of ACLF within 1 year after TIPS in patients with cirrhosis and construct a prediction model.METHODS In total,379 patients with decompensated cirrhosis treated with TIPS at Nanjing Drum Tower Hospital from 2017 to 2020 were selected as the training cohort,and 123 patients from Nanfang Hospital were included in the external validation cohort.Univariate and multivariate logistic regression analyses were performed to identify independent predictors.The prediction model was established based on the Akaike information criterion.Internal and external validation were conducted to assess the performance of the model.RESULTS Age and total bilirubin(TBil)were independent risk factors for the incidence of ACLF within 1 year after TIPS.We developed a prediction model comprising age,TBil,and serum sodium,which demonstrated good discrimination and calibration in both the training cohort and the external validation cohort.CONCLUSION Age and TBil are independent risk factors for the incidence of ACLF within 1 year after TIPS in patients with decompensated cirrhosis.Our model showed satisfying predictive value.

Factors influencing the quality of rural human settlements in a peripheral metropolitan area based on a structural equation model:A case study from Beijing

Rural human settlement is a significant indicator of the living standards of rural residents,and its improvement can contribute to promoting the positive interaction between inhabited environment and the social,economic,and resource environment in the countryside.Based on 557 valid questionnaires of satisfaction evaluation of human settlement in the peripheral metropolitan area of Beijing,this paper analyzed the elemental characteristics and factors influencing human settlement quality using multivariate statistical analysis and a structural equation model.The result shows that,first,the rural residents in a peripheral metropolitan area of Beijing are generally satisfied with the quality of human settlement(satisfaction rate is 66.2%).Specifically,the natural and social environment of the countryside is excellent and harmonious and corresponding standard of countryside infrastructure is advanced,but the quality of public services and follow-up management of facilities are in urgent need of improvement and the imbalance between revenue and expenditure of rural households has led to a continuous increase in the pressures of life.Second,factors such as social atmosphere,appearance of the village,entertainment,living costs,fundamental public services,and production costs have significant effects on human settlement quality in this peripheral metropolitan area,with social atmosphere as the main one.Living costs and supporting services are the main constraints to improvement in the quality of human settlement.

Analysing the Influencing Factors of a Postgenetic Subsidence Doline’s Development Using Model Experiments

The subsidence dolines are the most common surface forms of the concealed karsts.One type of these dolines is the suffosion doline.In this model experiment the influential role of these kind of dolines’development factors were analyzed.The aim of the study was to determine the significance of the parameters(cover thickness,secondary porosity of the bedrock,chimney diameter,grain size)that influence the development of a suffosion doline.To study the influencing factors numerous(162)experiments were made with different parameters,in a manner that during the experiments we changed only one parameter,so the effects of it would be detectable from the final solution.These measurements were made with the use of a special tool,designed and built for this purpose.According to the data we gained from the model experiments,the development of a suffosion doline is influenced by many parameters.If these parameters are in an optimal connection to each other,a suffosion doline may appear on the surface.Knowing these parameters of the covered karstic depressions lets us estimate other parameters that may influence the development of the subsidence dolines.

Spatiotemporal Dynamics of Green Total-factor Water-use Efficiency and Its Influencing Factors in China

In this study,we developed an evaluation index system for green total-factor water-use efficiency(GTFWUE)which reflected both economic and green efficiencies of water resource utilization.Then we measured the GTFWUE of 30 provinces/municipalities/autonomous regions(hereafter provinces)in China(not including Tibet,Hong Kong,Macao,Taiwan as no data)from 2000 to 2018 using a minimum distance to the strong frontier model that contained an undesirable output.We further analyzed the regional differences and spatial correlations of GTFWUE using these values based on Global and Local Moran’s I statistics,and empirically determined the factors affecting GTFWUE using a spatial econometric model.The evaluation results revealed that the GTFWUE differed substantially between the regions.The provinces with high and low GTFWUE values were located in the coastal and inland areas of China,respectively.The eastern region had a significantly higher GTFWUE than the central and western regions.The GTFWUEs for all three regions(eastern,central,and western regions)decreased slowly from 2000 to 2011(except 2005),remained stable from 2012 to 2016,and rapidly increased in 2017 before decreasing again in 2018.We found significant spatial correlations between the provincial GTFWUEs.The GTFWUE for most provinces belonged to the high-high or low-low cluster region,revealing a significant spatial clustering effect of provincial GTFWUEs.We also found that China’s GTFWUE was highly promoted by economic growth,population size,opening-up level,and urbanization level,and was evidently hindered by water endowment,technological progress,and government influence.However,the water-use structure had little impact on GTFWUE.This study fully demonstrated that the water use mode would be improved,and water resources needed to be used more efficiently and green in China.Moreover,based on the findings of this study,several policy recommendations were proposed from the aspects of cross-regional cooperation,economy,society,and institution.

Analysis on the Influencing Factors of Low-carbon Economy and Its Mitigation Countermeasures in Sichuan Province

[Objective]The study aimed to analyze the influencing factors of low-carbon economy and its mitigation countermeasures in Sichuan Province.[Method]Taking Sichuan Province as an example,an extended STIRPAT model was established firstly,then the impacts of population,economy and technology on carbon emissions from 2000 to 2009 were analyzed econometrically by using the principal component analysis method.Finally,some corresponding countermeasures to reduce carbon dioxide emissions were put forward.[Result]At present,population scale had the greatest influence on carbon emissions in Sichuan Province,then energy consumption per industrial added value and the proportion of industrial added value to GDP.In addition,the influence of population scale on carbon emissions was still greater than that of population structure,and technical factor also has certain explanatory power on carbon emissions.Some countermeasures,like controlling population growth,advocating low-carbon life style and consumption model,paying more attention to the strategic adjustment of industrial structure to gradually reduce the proportion of high-carbon industries,encouraging energy consumption and emissions reduction plus scientific and technological innovation in a new energy technology filed,could be adopted to reduce carbon dioxide emissions,so as to adjust to the development of low-carbon economy in Sichuan Province.[Conclusion]The research could provide references for the establishment of policies for reducing carbon emissions.

Factors influencing oil recovery by surfactant-polymer flooding in conglomerate reservoirs and its quantitative calculation method

This study aims to clarify the factors influencing oil recovery of surfactant-polymer(SP)flooding and to establish a quantitative calculation model of oil recovery during different displacement stages from water flooding to SP flooding.The conglomerate reservoir of the Badaowan Formation in the seventh block of the Karamay Oilfield is selected as the research object to reveal the start-up mechanism of residual oil and determine the controlling factors of oil recovery through SP flooding experiments of natural cores and microetching models.The experimental results are used to identify four types of residual oil after water flooding in this conglomerate reservoir with a complex pore structure:oil droplets retained in pore throats by capillary forces,oil cluster trapped at the junction of pores and throats,oil film on the rock surface,isolated oil in dead-ends of flow channel.For the four types of residual oil identified,the SP solution can enhance oil recovery by enlarging the sweep volume and improving the oil displacement efficiency.First,the viscosity-increasing effect of the polymer can effectively reduce the permeability of the displacement liquid phase,change the oil-water mobility ratio,and increase the water absorption.Furthermore,the stronger the shear drag force of the SP solution,the more the crude oil in a porous medium is displaced.Second,the surfactant can change the rock wettability and reduce the absorption capacity of residual oil by lowering interfacial tension.At the same time,the emulsification further increases the viscosity of the SP solution,and the residual oil is recovered effectively under the combined effect of the above two factors.For the four start-up mechanisms of residual oil identified after water flooding,enlarging the sweep volume and improving the oil displacement efficiency are interdependent,but their contribution to enhanced oil recovery are different.The SP flooding system primarily enlarges the sweep volume by increasing viscosity of solution to start two kinds of residual oil such as oil droplet retained in pore throats and isolated oil in dead-ends of flow channel,and primarily improves the oil displacement efficiency by lowing interfacial tension of oil phase to start two kinds of residual oil such as oil cluster trapped at the junction of pores and oil film on the rock surface.On this basis,the experimental results of the oil displacement from seven natural cores show that the pore structure of the reservoir is the main factor influencing water flooding recovery,while the physical properties and original oil saturation have relatively little influence.The main factor influencing SP flooding recovery is the physical and chemical properties of the solution itself,which primarily control the interfacial tension and solution viscosity in the reservoir.The residual oil saturation after water flooding is the material basis of SP flooding,and it is the second-most dominant factor controlling oil recovery.Combined with the analysis results of the influencing factors and reservoir parameters,the water flooding recovery index and SP flooding recovery index are defined to further establish quantitative calculation models of oil recovery under different displacement modes.The average relative errors of the two models are 4.4%and 2.5%,respectively;thus,they can accurately predict the oil recovery of different displacement stages and the ultimate reservoir oil recovery.

China’s Cross-Border E-Commerce: Evolution Pattern and Influencing Factors

In recent years,while the traditional trade sectors have been shrinking,China’s cross-border e-commerce has undergone rapid development and has become a new driver of its international trade.Based on analysis of the evolution pattern of China’s cross-border e-commerce,this paper uses a revised gravity model to test empirically the driving factors and the resistance factors in the development of the country’s cross-border e-commerce.The results show that the total GDP,per capita disposable income of urban residents,total imports and exports,and the scale of the online shopping market have a positive relationship with cross-border e-commerce transactions,which are conducive to the development of cross-border e-commerce,while logistics costs inhibit the development of cross-border e-commerce.Accordingly,the paper puts forward several policy recommendations.

Research on China's Aquaculture Efficiency Evaluation and Influencing Factors with Undesirable Outputs

Taking the aquaculture area, the number of farming boats and that of aquaculturist as input variables, the aquaculture production as desirable output variable and polluted economic loss as undesirable output variable, this paper conducts SBM model to evaluate the aquaculture efficiency based on the data of 16 aquaculture-developed provinces in China from 2004 to 2011. The results show the efficiency in China has not changed much in recent years with the efficiency values mainly between 0.39 and 0.53, and the efficiency of marine-aquaculture-dominated provinces is generally higher than that of freshwater-aquaculture-dominated ones. To analyze the difference under the efficiency, the panel Tobit model is used with education level factor, training factor, technology extension factor, technical level factor, scale factor and species factor as the efficiency influencing factors. The results show that technology extension factor and technical level factor have significant positive influence.

Modelling the response of larch growth to age,density,and elevation and the implications for multifunctional management in northwest China

Plantations of Rupprecht's larch(Larix principis-rupprechtii)have been widely established in the drylands of northwest and north China under traditional fastgrowing plantation management strategies.These strategies and the long-term logging ban have led to over-populated stands with lower structural and functional stability,less economic benefit and higher water consumption.To guide the sustainable management of larch plantations,field surveys and historical data compilation were undertaken in the Liupan Mountains of northwest China.The main influencing factors(stand structure and site condition)and their effects on mean tree height,mean DBH and timber volumes were determined based on up-boundary line analysis.Tree growth models coupling the effects of tree age,stand density,and elevation were established.Both height and DBH markedly increased initially and then slowly with tree age,decreased with stand density,and showed unimodal change with elevation.The coupled growth models accounted for72-78%of the variations in tree height,DBH and timber growth.Recommendations for future plantation management are:(1)prolong the rotation to at least 60 years to produce large-diameter,high-quality timber and maintain greater carbon stocks;(2)zone the target functions of stands by elevation;and,(3)reduce stand density for balanced supply of multiple ecosystem services.The growth models developed can predict growth response of larch plantations to density alteration under given ages and elevations,and assist the transformation from traditional management for maximum timber production to site-specific and multifunctional management with longer rotations and moderate tree density.