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.

Spatial distribution characteristics and influence factor analysis of landslides——case study of the Hanwang area in Qinba Mountains

The geological hazards of landslides in Hanwang Town, Ziyang County, Ankang City, Shaanxi Province, have emerged. Yet, the current understanding of the spatial distribution characteristics and influencing factors of landslides in this area remains unclear. Combining the results of remote sensing interpretation and field investigation, seven influencing factors, namely, elevation, slope direction, slope gradient, distance from rivers, distance from faults, engineering geologic lithology, and distance from roads, are selected for the study. The distribution characteristics of landslides in each influencing factor and the influence of the resolution of the Digital Elevation Model(DEM) on the results are statistically and analytically analyzed. Furthermore, two highrisk landslides within the study area were subjected to comprehensive analysis, integrating the findings from drilling and other field investigations in order to examine their deformation mechanisms. Based on this analysis,the following conclusions were derived:(1) 34 landslides in the study area, mainly small earth landslides, with a distribution density of 0.42/km~2, threatening 414 people and property of about 55.87 million Yuan.(2)The landslides in the study area easily occur in the <400 m elevation range;the landslides are developed in all slope directions, the gradient is mainly concentrated in the range of 10°–40°, the distribution density of the landslides is higher in the closer distance from the river and the faults(0–200 m), the landslide-prone strata are mainly the softer and weaker metamorphic rocks, and the landslides are mainly around roads.(3) The resolution of the DEM should be selected based on the specific conditions of the study area, the requirements of the investigation, and the scale of the landslide. Opting for an appropriate DEM resolution is advantageous for understanding the patterns of landslides and conducting risk assessments in the region.(4) The Zhengjiabian landslide is a traction Landslide. The landslide body is a binary structure of gravel soil and slate weathering layer, and the damage process can be divided into three stages:(1)damage to the leading edge and stress release,(2)continuous creep and cracking,(3)rainfall infiltration and damage. The predominant slope material in the Brickyard landslide comprises clay, and the landslide is triggered by a combination of the traction effect resulting from the excavation at the slope's base and the nudging effect caused by the stacking load of the brick factory. Additionally, the Brickyard landslide exhibits persistent creep deformation. The study results provide a scientific basis for disaster prevention and mitigation in the Hanwang Township area.

Machine Learning-Based Decision-Making Mechanism for Risk Assessment of Cardiovascular Disease

Cardiovascular disease(CVD)has gradually become one of the main causes of harm to the life and health of residents.Exploring the influencing factors and risk assessment methods of CVD has become a general trend.In this paper,a machine learning-based decision-making mechanism for risk assessment of CVD is designed.In this mechanism,the logistics regression analysismethod and factor analysismodel are used to select age,obesity degree,blood pressure,blood fat,blood sugar,smoking status,drinking status,and exercise status as the main pathogenic factors of CVD,and an index systemof risk assessment for CVD is established.Then,a two-stage model combining K-means cluster analysis and random forest(RF)is proposed to evaluate and predict the risk of CVD,and the predicted results are compared with the methods of Bayesian discrimination,K-means cluster analysis and RF.The results show that thepredictioneffect of theproposedtwo-stagemodel is better than that of the comparedmethods.Moreover,several suggestions for the government,the medical industry and the public are provided based on the research results.

Research on the Continuous Participation of Virtual Brand Community in Decision-Making Based on Social Influence Theory

Based on the social influence theory,the influence of virtual brand community members’perceived value on social influencing factors is discussed,and the influence of social influencing factors on virtual brand community members’continuous participation in decision-making is analyzed.Through an empirical analysis of the survey data of Xiaomi users in the Xiaomi Community,the results showed that the perceived value of virtual brand community members significantly and positively affects social influencing factors,which also significantly and positively affect the members’continuous participation in virtual brand communities.Therefore,only by sharing valuable information resources and improving the efficiency of information flow,thereby enhancing the perceived value of the community and increasing the stickiness of members to the virtual community,will we have an opportunity to enhance the interaction among members and effectively promote continuous participation in community activities through the strong bonds formed among members.

Short-term inbound rail transit passenger flow prediction based on BILSTM model and influence factor analysis

Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model is not good for datasets with large changes in passenger flow characteristics and the deep learning model with added influencing factors has better prediction accuracy.In order to provide persuasive passenger flow forecast data for ITS,a deep learning model considering the influencing factors is proposed in this paper.In view of the lack of objective analysis on the selection of influencing factors by predecessors,this paper uses analytic hierarchy processes(AHP)and one-way ANOVA analysis to scientifically select the factor of time characteristics,which classifies and gives weight to the hourly passenger flow through Duncan test.Then,combining the time weight,BILSTM based model considering the hourly travel characteristics factors is proposed.The model performance is verified through the inbound passenger flow of Ningbo rail transit.The proposed model is compared with many current mainstream deep learning algorithms,the effectiveness of the BILSTM model considering influencing factors is validated.Through comparison and analysis with various evaluation indicators and other deep learning models,the results show that the R2 score of the BILSTM model considering influencing factors reaches 0.968,and the MAE value of the BILSTM model without adding influencing factors decreases by 45.61%.

Grain Crop Fertilization Status and Factors Influencing Farmers' Decision Making on Fertilizer Use: China Case Study

[Objective] China is the world＇s largest fertilizer consumer. Fertilizer plays an important role in maintaining China＇s food security. Along with population and economic growth, overuse of fertilizers has caused serious environmental problems, such as soil acidification, decline in soil organic carbon, and agricultural non-point source pollution. This study aimed to analyze the factors influencing farmers＂ decision making on fertilizer use, and provide policy recommendations on ways to affect fertilization. [Method] An econometric model reflecting fertilization of rural households was estimated from a survey distributed to 1 043 households randomly selected from 19 provinces in China. [Result] Results of the study showed that education years of fertilizer decision maker, fertilizer quality, organic fertilizer application, fertilizer price, and agricultural product price had significant effects on the fertilizer application rate at 1% level. Soil nutrient affected the fertilizer application rate at 10% level. [Conclusion] Policies aimed at improving the reasonable use of fertilizer should focus on the regulation of chemical fertilizer price, foundation of the organic-inorganic fertilizer system, soil testing, formulated fertilization, and agricultural extension service.

Research on development of urban taxi supply based on influence factors classification

In order to determine the regulations of the development of taxi supply under entry regulations in Chinese cities, an improved neural network model is applied to find the particular years when the government artificially puts new taxis into the market, and then extract the political influence from the taxi supply. The model is also utilized to study the relationships between the adjusted taxi supply and non-policy factors. A case study of Nanjing city is conducted. The results show that 2001 and 2007 are the particular years that the Nanjing government artificially put new taxis into its taxi market, which is in accordance with the five-year plan of China and the local development plans. The results also show that the improved neural network model has a good performance in expositing the evolution of adjusted taxi supply related to non-policy factors.

Sequential maneuvering decisions based on multi-stage influence diagram in air combat

A multi-stage influence diagram is used to model the pilot＇s sequential decision making in one on one air combat. The model based on the multi-stage influence diagram graphically describes the elements of decision process, and contains a point-mass model for the dynamics of an aircraft and takes into account the decision maker＇s preferences under uncertain conditions. Considering an active opponent, the opponent＇s maneuvers can be modeled stochastically. The solution of multistage influence diagram can be obtained by converting the multistage influence diagram into a two-level optimization problem. The simulation results show the model is effective.

Advances on Internal Influence Factors of Adventitious Rooting of Forest Trees

This paper reviews the internal influence factors of adventitious root, in- ducing oxidase activity, endogenous hormones, rooting inhibiting substances, and fu- ture research ideas are also proposed.

Research of Influence Factors on Apple NIR Spectroscopy Acquisition

[Objective] The aim was to optimize experimental conditions of Gala apple NIR（Near Infrared）spectroscopy acquisition through study on the accuracy of NIR spectroscopy information under different influence factors.[Method]Gala apple was taken as the experimental material,and FieldSpec3 spectrometer（Analytical Spectral Device Company,America）was employed to acquire the NIR spectroscopy at room temperature.Then,the effects of different conditions including the environmental stray light,instrument stability,different distance,different chromatic aberration,different sites and different shelf-life on spectroscopy acquisition were investigated.[Result]The stray light had a significant effect on the visible light region of NIR spectroscopy;FieldSpec3 spectrometer had higher stability in 9 h;the measure distance of 2.5-12.5 mm could obtain good repeatability of absorbance;the effects of different chromatic aberration of the same apple on spectra was acceptable;the spectral stability of equatorial plane of the apple was better than those of the bottom and stalk;at room temperature;different shelf-life could make significant influence to NIR spectroscopy of the apple simple.[Conclusion]This study will provide reference for the researchers and analysis workers of apple NIR spectroscopy.

Factors influencing the degree of participation in surgical decision-making among Chinese patients with prostate cancer:A qualitative research

Objective:There was increasingly demand of participation in surgical decision-making among Chinese patients with prostate cancer.However,due to the complex healthcare system and advanced care settings,it is quite challenging for the patients to gain sufficient support from the institute and the government.This research aimed to investigate the factors that impact the degree of participation in surgical decision-making among Chinese prostate cancer patients.Methods:A phenomenological approach of qualitative research based on the results of semi-structured interviews was adopted,to explore the influencing factors which hinder the participation in surgical decision-making.Consolidated Criteria for Reporting Qualitative Research were utilized.Up to 160 post-operative patients who had undergone radical prostatectomy along with 68 medical and nursing staffs,were purposively recruited in this research.This retrospective study was carried out from September 2018 to August 2019.After recording and transcribing the interviews,the interview materials were evaluated via the Colaizzi's seven step approach and the NVivo Version 10 software to analyze the interview content.Results:According to the analysis and summary of the interviews,there were three factors affecting the degree of participation in surgical decision-making.Firstly,insufficient information was provided by medical and nursing staffs because of their lack of time,proper communication skills,and career experience,as well as difficulties in the development of patient decision aid and inconsistent resource availability.Secondly,the cognitive level of decision-making among patients was relatively low due to poor psychological endurance,insufficient amount of education,senility,and less knowledge and information demand.Ultimately,decisions were constantly made by family members with/without patients.Conclusions:The degree of participation of Chinese prostate cancer patients in the surgical decision-making had much space for improvement.

Study on the Key Influence Factors of Environmental Mass Incidents by Delphi-PCA-Frequency Analysis Composite Method

In order to prevent and control environmental mass incidents,by comprehensively using literature research,case analysis and logical reasoning method,27 factors influencing environmental mass incidents were selected. Among them,15 key influencing factors were screened by Delphi-PCA-frequency analysis composite method. The key influencing factors were analyzed,and corresponding countermeasures were put forward.

Intervention decision-making in MAV/UAV cooperative engagement based on human factors engineering

Aiming at the intervention decision-making problem in manned/unmanned aerial vehicle（MAV/UAV） cooperative engagement, this paper carries out a research on allocation strategy of emergency discretion based on human factors engineering（HFE）.Firstly, based on the brief review of research status of HFE, it gives structural description to emergency in the process of cooperative engagement and analyzes intervention of commanders. After that,constraint conditions of intervention decision-making of commanders based on HFE（IDMCBHFE） are given, and the mathematical model, which takes the overall efficiency value of handling emergencies as the objective function, is established. Then, through combining K-best and variable neighborhood search（VNS） algorithm, a K-best optimization variable neighborhood search mixed algorithm（KBOVNSMA） is designed to solve the model. Finally,through three groups of simulation experiments, effectiveness and superiority of the proposed algorithm are verified.

The Marketing Factors Affecting Customer Decision-Making of Xiaomi Smart Wearable Devices in Guangxi,China

From an empirical point of view,this paper proposes research hypotheses and models based on the market situation of Xiaomi smart wearable devices in Guangxi,as well as the research status of consumers’purchasing decisions,combined with the empirical research of some researchers.This paper designs questionnaires and scales.The sampling survey method is used to investigate and analyze the influencing factors of Guangxi consumers’decision to purchase Xiaomi smart wearable devices.Questionnaires were distributed through Questionnaire Star,and 385 valid questionnaires were collected for descriptive statistics and correlation analysis.Conclusions are as follow:(1)Consumers in Guangxi who purchase Xiaomi smart wearable devices are between 19 and 32 years old,and most of them have a bachelor’s degree.Among the five factors of demographic characteristics,only income and marketing mix satisfaction have a positive correlation,indicating that customers are sensitive to Xiaomi smart wearable products.And among the customers of Xiaomi smart wearable products,the monthly income of less than 5,000 yuan accounted for 30.91%of the total number of surveys;the monthly income was 5,000-7,000 yuan,accounting for 34.29%.(2)The satisfaction of the marketing mix is positively correlated with the satisfaction of customer decision-making.The satisfaction of the marketing mix varies with the age,gender,education,income,and working years of each population,and only the income is positively correlated with the satisfaction of the marketing mix.Relationships,age,gender,education,and years of employment were not associated with marketing mix satisfaction.According to the above conclusions,relevant and reasonable product development and marketing suggestions are put forward for the enterprise,which provides a reference for the enterprise’s brand building and market development.Therefore,on the basis of comparing with other scholars at home and abroad,through the 7P marketing theory and purchasing decision theory and the research on the current situation of influencing factors for customers to purchase Xiaomi smart wearable devices in Guangxi,this paper compiled a questionnaire for 385 private colleges and universities in Guangxi.A questionnaire survey was carried out with customers,and the current situation of customers’purchasing decision-making behavior was obtained and analyzed and the following suggestions were put forward:continuously innovating products,targeting target customers,reasonably setting product prices,improving marketing mix.

Influencing Factors of Personal Retirement Decision： Perspective of Research Summary

Because the policy of delay retirement is facing demand differences widely, research workers retirement needs and the basic law from the micro perspective will become increasingly important. Based on the demographic characteristics, family relationships, social and economic factors and professional environment, such as in four dimensions, the article has reviewed the individual retirement decisions affecting factors and its mechanism of action, and summed up the consensus theory and some controversy. In future research, we need to strengthen the cross disciplines and integration, to explore more available research variables, provide a new starting point for further theoretical research and policy making.

Marketing Factors Affecting Middle Class Consumer’s Buying Decision in Housing Market in Nanning City

It is important to study the relationship between marketing factors and purchase decisions of middle-class consumers in Nanning housing market.This study will investigate the factors influencing people decision to purchase houses in Nanning City.The extrinsic housing attributes at this study consist of environmental attributes and location attributes.I have a limited understanding of the purchase behavior of Nanning home buyers in Nanning City.This study adopts the data collection methods of e-mail and field survey.Based on 509 questionnaires,the data were analyzed using descriptive statistics analysis and logistic regression.The results show that location attributes,such as school districts,positively influence housing purchase decisions in Nanning City.This study contributes to an improved understanding of home buyers’decision making in Nanning City.The beneficiaries of this study include home buyers and marketers and academic institutions.To better meet home buyers’needs and achieve a competitive advantage,marketers can use the research outcomes to focus more on those housing purchase factors that significantly influence house buyers’purchase decision making.

Analysis of Influencing Factors Tourists1 Purchase Decision-making Behavior in Kunming

Based on the theory of consumer behavior,this paper analyzes the current situation of tourism shopping market in Kunming,and analyzes the decision-making behavior of tourists shopping in Kunming with the questionnaire survey,and clarifies the influencing factors of the decision-making behavior of visitors to Kunming.In the future,the influencing factors of Kunming tourists'shopping decision-making behavior are combined with the current situation of Kunming's tourism shopping market.The problems of cheating-induced shopping,the high price of shopping products,the low level of tourism shopping experience and the imperfect after-sales service are analyzed.Finally,the corresponding countermeasures and suggestions are proposed from four aspects:rectifying the tourism shopping market,establishing a sound price supervision mechanism,strengthening the tourism shopping experience,and improving after-sales service.

Review on the decomposition and influence factors of coarse woody debris in forest ecosystem

Coarse woody debris （CWD） is an important and particular component of forest ecosystems and is extremely important to forest health. This review describes the decomposition process, decomposition model and influence factors. CWD decomposition is a complex and continuous process and characterizes many biological and physical processes, including biological respiration, leaching, and fragmentation. All these processes have closed relationships between each other and work synergistically. During decomposition, there are many controlling factors mainly including site conditions （temperature, humidity, and OJCO2concentration）, woody substrate quality （diameter, species and compound） and organism in CWD. The decomposition rate is generally expresses through a constant k which indicate the percent mass, volume or density loss over time, and can be determined by long-term monitoring, chronosequence approach and the radio between input and the total mass. Now using mathematical models to simulate decomposition patterns and estimate the decomposition rate is widely applied, especially the exponential model. We brought forward that managing and utilizing for the CWD in forest was a primary objective on all forest lands. And it is should be intensified to integrate many related research subjects and to carry a comprehensive, long-term and multi-scale research which mainly focus on seven sections.

Coupling effects of influence factors on probability of corrosion initiation time of reinforced concrete

The coupling model of major influence factors such state affecting the chloride diffusion process in concrete is as environmental relative humidity, load-induced crack and stress discussed. The probability distributions of the critical chloride concentration Cc, the chloride diffusion coefficient D, and the surface chloride concentration Cs were determined based on the collected natural exposure data. And the estimation of probability of corrosion initiation considering the coupling effects of influence factors is presented. It is found that the relative humidity and curing time are the most effective factors affecting the probability of corrosion initiation before and after 10 years of exposure time. At the same exposure time, the influence of load-induced crack and stress state on the probability of corrosion initiation is obvious, in which the effect of crack is the most one