Estate Companies In China Research Articles

A Study of Debt Problems in the Chinese Real Estate Industry

This paper will focus on real estate industry in China, uses Evergrande group as a case to compare with another Chinese real estate company Vanke and a real estate company of United State which is AvalonBay Communities, Inc. This paper will introduce the background of real estate industry in China, and base on the case which is bankruptcy of Evergrande Group to throughout the causes find out the issues of real estate in China, in causes is discuss of three factors: Industry characteristics, financing channels, loan evaluation, analysing what make Evergrande can owe a massive $2.4 trillion in debt, and analysing the United States real estate industry not usually having such high leverage. Essay will tell the strategy of real estate companies in China usually do. The strategy led to Evergrande group bankruptcy and compare with Vanke uses what strategy avoid debt crisis. Finally, conclude the chaos of real estate industry in China reflected by Evergrande group, recognise the issues of Evergrande group and prevent the significant consequence occur again.

Research on Digital Finance and Financial Risk in the Context of High-quality Development: Evidence from Listed Real Estate Companies in China

The paper practically investigates relationships among digital finance, financial risks, and high-quality development of real estate companies using data from listed real estate companies and digital finance from 2011 to 2020. The research findings are as follows: (1) Digital finance significantly foster the high-quality development of real estate companies; (2) Mechanism analysis indicates that digital finance can advocate the high-quality development of real estate companies by alleviating financial risks. Therefore, this paper suggests policy recommendations such as the government issuing policies to drive the development of digital finance, companies establishing sound internal control and risk management mechanisms, and companies undergoing digital transformation to promote the high-quality development of real estate companies.

Social Responsibility, Media Attention and Financial Risk of Listed Real Estate Companies in China

In the past two years, real estate companies have been actively exploring new development models at the policy level. For the future sustainable development of real estate companies, ESG performance can reflect the overall credit quality of companies in non-financial aspects, while the fulfillment of social responsibility is an important factor in measuring the ESG performance of companies, and therefore gradually becomes a focus of attention. In order to analyse the relationship between social responsibility fulfillment and financial risk of real estate companies, this paper proposes hypotheses based on theories such as stakeholder theory, introduces media attention into the analysis framework, and selects data of Chinese A-share real estate listed companies from 2010 to 2019 for empirical testing. It is found that the fulfillment of social responsibility by real estate companies is negatively related to financial risk, while media attention plays a negative moderating role in this regard. The findings provide empirical support for the mechanism of the impact of social responsibility fulfillment on real estate companies' financial risk and offer policy options for real estate companies to reduce their own financial risk.

Unemployment Rate and Gender Discrimination in the Chinese Real Estate Market During the Covid Pandemic

In the past several decades, the Chinese real estate market played an important role in economic activities, which drove nearly one-third of the financial activities in China. In addition, based on the data from Statista, real estate companies in China recruited nearly 3 million employees in 2021. Although Chinese real estate companies offer many job opportunities yearly, the unemployment rate increased during the pandemic in Chinese real estate markets. One factor that may cause the unemployment rate to increase is gender discrimination. The overall goal of this work was to study the relationship between the unemployment rate and gender preferences in the Chinese real estate market during the covid pandemic and does the pandemic reduce gender discrimination in the real estate markets. The paper uses a primary source, interviewing, to find the data for recruitment and layoffs in Chinese real estate companies during the covid pandemic. The paper finds that the unemployment rate in the Chinese real estate market is based on gender preferences in different departments, and Covid-19 did not reduce gender bias and stereotypes in Chinese real estate companies.

Comparison of Different Financing Methods of Real Estate Enterprises

Since China reform and opening, the real estate industry has gradually developed into a pillar industry of China's economy. In recent years, the Chinese government introduced a tightening policy to limit the expansion of the real estate bubble, but also put pressure on the real estate sector, financing problems are imminent. This article investigates the theme of China's real estate enterprises different financing methods. This study selects two Chinese listed real estate companies as the case, analyzes the relevant data in the financial reports published by the two companies contemporarily. It compares the advantages and disadvantages of different financing methods. According to the analysis, companies that pay attention to internal financing, develop diversified financing channels, have strong corporate strength, and have financing methods that respond to government policies are more capable of financing. These results shed light on helping the choice of financing methods of real estate companies in China and further exploration of financing modes.

Research on Stock Price Prediction of BP Neural Network Based on Factor Analysis

In this thesis, the real estate industry is focused on, the financial data of 27 listed real estate companies in China is chosen, and the method of factor analysis is used to carry out the dimensionality reduction processing for the collected 20 variables. Finally, six main factors are extracted. Besides, the stock prices before and after the factor analysis are predicted and studied respectively based on the BP neural network prediction model. In line with the results, the better prediction accuracy for the BP neural network model established with the main factor determined by factor analysis as the independent variable and the stock price as the dependent variable is embodied. In contrast with the research carried out by other scholars, the BP neural network is established from more dimensions, so the prediction accuracy is greatly enhanced.

The Impact of Economic Uncertainty on the Cash Flow of Listed Real Estate Companies in China

After the policies of "no speculation in housing" and "three red lines" have been introduced one after another, more real estate enterprises have heard the news of "thunder explosion" one after another. Based on this, it is particularly important to explore how real estate companies can develop under the influence of increasing economic policy uncertainty. Among them, cash flow is very important for real estate enterprises. Based on this, this paper uses TVP-VAR model to simulate the impact of economic policy uncertainty on the cash flow of listed real estate companies in the important regulatory period and time point of national policies. It is found that the cash flow of operating activities is most affected by economic policy uncertainty, while the cash flow of financing activities is relatively less affected by economic policy uncertainty. Cash flow from short-term operating activities is more sensitive to impact performance, and cash flow from investment activities is more intense in the long run; At the same time, it explains the conclusion that the government is making efforts to end the "barbaric era" of capital power. Based on the conclusion, this paper puts forward some enlightenment, such as strengthening cost management and strategic adjustment, and for high-risk real estate enterprises, we can consider looking for positioning transformation.

Unveiling the nexus between corporate social responsibility, industrial integration, economic growth and financial constraints under the node of firms sustainable performance

This research investigates the impact of corporate social responsibility (CSR), industrial integration, and economic growth in realising financial constraints using firm’s level attributes of sustainable performance. In doing so, this study utilised annual data of 555 Chinese real estate firms from 2015 to 2019 and applied a spatial effect model (SEM) to integrate spatial effects. This study also used two-step Generalized Method of Moments (GMM) and two-stage least square (2SLS) methods to deal with possible endogeneity. Manifestly, we have constructed a mathematical derivation framework based on linear algebra and offer easy computing Moran's index. The preliminary results revealed that CSR, industrial integration, and economic growth reduce financial constraints of listed real estate companies in China. However, these effects are not persistent at different stages of development. The findings of Moran index describe that the early and growth stages of CSR instigate financial constraints while the mature stage of CSR produces inhibitory effects that reduce financial constraints. Notably, these effects also varied across different regions. This outcome offers valuable policy recommendations.

Emotional Intelligence of Local and Overseas Graduates in Real Estate Industry in China

There is still limited research that investigates emotional intelligence in the context of the real estate sector in China, despite the rapid growth of the industry. Furthermore, there has been an exponential increase in the number of Chinese students studying overseas. Underpinned by these tendencies, this research investigates the levels of emotional intelligence of overseas and local graduates in the real estate sector in China. Data were collected using a survey of 140 employees and semi-structured interviews of four human resource managers in six Grade One state-owned real estate companies in China. The findings suggest that emotional intelligence influences the levels of interpersonal skills, represented by communication skills and teamwork behaviour. However, there is no difference in the levels of emotional intelligence between overseas and local graduates, suggesting that there are other factors that influence emotional intelligence development. Overseas graduates also seem to have greater difficulties than local graduates from elite universities to find jobs in the real estate sector. This suggests that international study experience is no longer adequate; instead, various contextualised interpersonal skills are needed to meet work demands in China. Developing emotional intelligence has been found to promote success across cultures and is a way to meet the demands of today's work environments in the real estate industry in China.

Peer abusive supervision and third-party employee creativity from a social exchange theory perspective

We used social exchange theory to construct a theoretical framework of peer abusive supervision, third-party perception of organizational support, third-party employee creativity, and third-party perception of supervisory organizational embodiment. We then empirically tested the theoretical model with 367 supervisor–employee paired dyads from five large real estate companies in China. The results show that peer abusive supervision had a negative impact on third-party employee creativity, and third-party perception of organizational support played a mediating role in this relationship. Further, third-party perception of supervisory organizational embodiment positively moderated the impact of peer abusive supervision on third-party perception of organizational support. Our results, which show the spillover effect and boundary conditions of abusive supervision on third-party employee creativity, are significant for the enhancement of employee creativity in corporate management practice.

Do Political Connections Affect Corporate Performance? Evidence from Listed Real Estate Companies in China

Do Political Connections Affect Corporate Performance? Evidence from Listed Real Estate Companies in China

Study of the Relationship between Political Connections and Corporate Re-Entrepreneurial Performance

Based on both resource-based theory and institution-based theory, this study places political connections, acquisition of entrepreneurial resources, institutional environment, and corporate re-entrepreneurial performance into the same research framework. Using data from 223 real estate companies in China as a sample and with the help of the statistical tools SPSS 22.0 and Mplus 7.0, the study examines the internal influence mechanism of political connections on corporate re-entrepreneurial performance as well as the mediating effect of acquisition of entrepreneurial resources and the moderating effect of institutional environment. The empirical results show that both explicit political connections and implicit ones have positive impacts on corporate re-entrepreneurial performance through the mediating effect of acquisition of entrepreneurial knowledge resources and entrepreneurial asset resources. Meanwhile, institutional environment positively regulates the relationship between political connections and corporate re-entrepreneurial performance. The results of the study suggest that political connections have positive impacts on corporate re-entrepreneurial performance under the circumstances of China’s transitional economy, but the impacts are restricted by institutional environment to a large extent.

Research on the Financing Strategy of Real Estate Listed Companies in China

The real estate industry has developed rapidly in recent years. This is certainly related to the strong demand for rapid urbanization in China, but excessive investment has caused the existence of a speculative bubble. A single investment and financing model no longer adapts to changes in the current real estate investment market and capital markets. Therefore, it is urgent to solve the real estate company's financial problems. This paper uses charts, data and other methods to analyze the financing methods of listed real estate companies in China. The first part of this article describes the research background; the second part analyzes the financing strategy of listed real estate companies in China; the third part describes a case; finally, it puts forward policy recommendations on the financing methods of Chinese currently listed real estate companies.

Financial Risk Diagnosis of Listed Real Estate Companies in China Based on Revised Z-score Model

Under the background of China’s economic slow-down and property boom, financial risk analysis of listed real estate companies has gained great importance in recent years. The aim of this study is to investigate the financial risk of China’s real estate companies between the years 2011 and 2015 by using Z-China score model. Based on panel data of a sample of 45 listed real estate companies, this study finds that financial risk of China’s real estate industry has been increasing over the past five years, and a growing number of listed real estate companies are classified as unhealthy companies. In specific, 35 listed companies are grouped into gray area in 2015, and 4 companies are identified as financially distressed companies who are very likely to suffer financial crisis in the following two years. Further analysis identifies that profitability decline is the key factor raising the risk of a financial distress.

Empirical Analysis on Efficiency of Listed Real Estate Companies in China by DEA

The real estate industry plays an important role in the economic development in China. The purposes of this paper are to measure the operating efficiency of the real estate industry and also compare the different influencing factors on the efficiency. 30 companies listed in Shenzhen and Shanghai markets are selected as the sample companies of operating efficiency study. The data is collected from 2009 until 2015. C2R and B2C models of the data envelopment analysis (DEA) are used to derive findings. The present study applied Tobit regression model to study different factors’ influence on the efficiency. We concluded that efficiency was not high among most companies and the efficiency gap was quite wide. The results of the Tobit regression model showed that the efficiency was positively correlated with the net interest rate and education level, not so correlated with proportion of the first major shareholders and negatively with asset-liability ratio. Based on the conclusions, the paper put forward some specific suggestions.

Guanxi influence and talent management in Chinese organisations; evidence from the real estate sector

ABSTRACTThe Chinese context has been characterised as one where guanxi influence is significant, shaping the choices, considerations, challenges, and consequences of talent management (TM). There is though little empirical research which shows that this is what is experienced, and that guanxi influence does feature prominently. The purpose of our research is to explore experiences of TM in China, and the extent to which the guanxi influence affects TM.Case study research to identify and explore guanxi influence on TM was undertaken in three real estate companies in China. Interviews with managers and employees on how talent is defined, attracted, developed, and retained were analysed for guanxi influence. These show that guanxi influence is clearly present in the experience of TM, though this is not the sole or always dominant influence on choices, considerations, challenges, and consequences. This paper contributes to the TM literature by showing that guanxi influences play important roles in defining, attracting, developing, and retaining talent in the Chinese context and also highlighting both advantages and potential disadvantages of guanxi influence in TM activities.Evidence suggests that guanxi influence is a relevant focus for understanding TM and for framing further research on TM in China. Guanxi influence in this TM context will continue, and by extension in contexts where Chinese organisations develop their presence globally, and adapt to the wider international context of organisation development and change in which best practice TM is a stronger influence.

Performance Evaluation of the Listed Real Estate Companies in China Based on Fuzzy Neural Networks: The Perspective of Stakeholders

In this paper, we utilize a fuzzy neural network to evaluate the performance of listed real estate companies in China. We analyze the special interests of the stakeholders and construct a performance evaluation indicator system for these companies. We evaluate a sample of listed real estate companies using the fuzzy neural network method to determine their performance. The results show that the scores of the sample companies range within a certain scale (50, 90), and the performance of the different companies varies greatly. The results also show that the trained neural network model can well identify the performance of the listed real estate companies.

Default Prediction for Real Estate Companies with Imbalanced Dataset

When analyzing default predictions in real estate companies, the number of non-defaulted cases always greatly exceeds the defaulted ones, which creates the two- class imbalance problem. This lowers the ability of prediction models to distinguish the default sample. In order to avoid this sample selection bias and to improve the prediction model, this paper applies a minority sample generation approach to create new minority samples. The logistic regression, support vector machine (SVM) classification, and neural network (NN) classification use an imbalanced dataset. They were used as benchmarks with a single prediction model that used a balanced dataset corrected by the minority samples generation approach. Instead of using prediction- oriented tests and the overall accuracy, the true positive rate (TPR), the true negative rate (TNR), G-mean, and F-score are used to measure the performance of default prediction models for imbalanced dataset. In this paper, we describe an empirical experiment that used a sampling of 14 default and 315 non-default listed real estate companies in China and report that most results using single prediction models with a balanced dataset generated better results than an imbalanced dataset. Keywords—Default prediction, Imbalanced dataset, Real estate listed companies, Minority- sample generation approach

Relationship between Free Cash Flow and Corporate Performance Evidence from the Listed Real Estate Companies in China

There is no consensus on the impact of free cash flow upon corporate performance. Based on the data from 2006-2012 of all listed real estate companies in China, authors studied the relationship between the free cash flow and performance of these firms. Using principal component analysis and regression analysis, key financial performance indicators were calculated out of 18 financial performance indicators, and these key indicators of sample companies were correlated to their free cash flow. The results showed that the free cash flow of a company is negatively linear-correlated to its performance, i.e., too much free cash flow will lead the corporate performance to decline. Therefore, the investors and the managers should avoid business inefficient because of too much free cash flow, which triggers the investment risk and loss.

Examining the Relationship between Capital Structure and Executive Compensation for Listed Real Estate Companies in China

This paper focuses on the relationship between capital structure and executive compensation, based on capital structure theories and the principal-agent theory, and using data from fifty real estate companies listed in the Chinese Stock during the period of 2010–2012. Our results show a significantly positive relationship between executive compensation and capital structure. The control variables of company size, profitability, and growth opportunities were also found to have a positive relationship with executive compensation.