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In recent years, housing prices and rents have recorded impressive growth in Iran. Several observers believe that real estate agents have had a significant effect on this phenomenon. However, some do not agree with this viewpoint and argue that the role of real estate agents is not that much and housing prices and rents are affected by macroeconomic factors. The purpose of this paper is to investigate whether real estate agents can influence housing prices and rents across provinces of Iran.

Applying panel data technique, this paper uses observations from 28 provinces of Iran covering 2000 and 2003 to examine the role of real estate agents on housing prices and rents.

The empirical results indicate that the increased number of real estate agents and their activities positively significantly stimulate housing prices and rents.

To the author's knowledge, most studies in this area cover the US and European real estate markets. Since findings for developed countries might not be directly transferable to emerging market economies such as Iran, more work is necessary to obtain a clearer picture of the role of real estate agents on housing prices and rents in emerging economies.

Although there has been a series of cross‐sectional studies published in this area, few empirical works have examined the effects of real estate agents on housing prices and rents by applying panel data set. The paper begins to fill this gap by analyzing a data sample of 28 provinces of Iran covering 2000 and 2003.

Because of competition, residential property developers use a variety of promotional tools to gain recognition and increase their market share and the demand for housing, and to manage their customer relations. This study aims to examine what real estate developers did to detect the need for types of housing, and pricing and promoting housing. It also sought clues about how they manage customer relations in residential sales.

In this study, semi-structured interviews were conducted with real estate developers. This study has heuristic characteristics based on qualitative data. Document reviews, descriptive analysis and discourse analysis were carried out on the interview data and other sources. As purposeful sampling is generally used in qualitative studies; intensity sampling, homogeneous sampling, criterion sampling and snowball sampling were used together in this study.

The study found that real estate developers were inadequate at advertising and promoting, allocated little budget for promotion and did not use technology sufficiently. The real estate developers gave discounts at rates that did not actually desire, had to create payment plans, and as a result, they lost customers because they could not manage customer relations well.

Interviews were conducted with 15 real estate developers who have been selling residential properties for more than 10 years in Süleymanpasa and Çorlu districts of Tekirdag. Data obtained are mostly qualitative.

This study aimed to determine real estate developers’ ability to implement a variety of promotional strategies and manage customer relations. Results and conclusions can offer significant clues about real estate developers with similar characteristics. Its conclusions of this study can be compared to similar studies of real estate developers in many regions of Turkey.

The purpose of this paper is to find out the causes of increasing population in the real estate area. The demographic in information of the respondents and the level of satisfaction was also carried out for this study.

The authors use both primary and secondary data. Total 329 respondents were surveyed at the real estate area after completing sample size determination. Secondary data was collected from journals, real estate offices and papers. After that, using regression and correlation analysis, the data was analyzed and finalized.

This study identified migration as the most critical variable. The study determined ten hypotheses and only accepted two. By that, this study finds out the causes of the increasing demand of plots and flats in real estate.

This study will work as a baseline study for the real estate sector in Bangladesh. Most of the research on Bangladesh’s real estate is done mainly on real estate market assessment and consumer satisfaction. Nevertheless, this study will find out the causes of the increasing population in real estate.

The purpose of the study is to determine website quality, materialism, psychological factors, hedonic value and social media as factors that influence the young adults’ impulsive housing and real estate buying behavior in India. In addition, this study also measures the mediating effects of social media influence between psychological factors and hedonic value and young adults’ impulsive housing and real estate buying behavior.

Related literature, quantifiable variables with a five-point Likert Scale, hypothesis testing and mediators are used to study the model. A systematic questionnaire that was divided into six sections was used. A total of 385 valid responses were collected and analyzed through a structural equation model.

The results suggest that materialism, psychological factors and social media have a considerable impact on young adults’ impulsive housing and real estate buying behavior. The findings also ascertained that website quality and hedonic value do not have a considerable impact on young adults’ impulsive housing and real estate buying behavior.

This study is limited to the responses of young consumers from a limited number of brokers and regions in India. Future studies could be more widespread across the globe.

As per the review of existing literature, this research is the first, to the best of the authors’ knowledge, to determine the factors affecting the impulse buying decision mainly in the housing and real estate sector with the target consumers being young.

This study aims to recognize the role of information system (IS) model on young adults’ experience of housing and real estate chatbots. This model of IS takes into account the quality of information, the quality of system and the quality of service.

This study uses a sample frame for analysis which comprises young adult population in India, i.e. between the ages of 18 and 35. A questionnaire consisting of five components was used to collect information in a structured manner. The 386 responses thus collected were analysed using the structural equation model.

It was found that there is a significant influence of the quality of information, quality of system and quality of service on young adults’ experience of housing and real estate chatbots. The findings also showed that there is moderation role of effort expectancy between the quality parameters and young adults’ user experience of housing and real estate chatbots.

This study focusses exclusively on the young adults from various parts of India. Future research can consider larger population categories across age groups and across sectors employing chatbots.

This study will enable in-depth understanding of IS model – quality dimensions’ relation with the user experience. In particular, housing and real estate organisations will profit from the expanded usage of artificial intelligence through chatbots for user correspondence and communication.

To the best of the authors’ knowledge, this study is first of its kind, as it investigates how IS model – quality dimensions affect the young adults’ experience of housing and real estate chatbots in India. This study also ventures into identifying the moderation role of effort expectancy between the quality dimensions as per IS model and young adults’ experience of housing and real estate chatbots. This study will be useful for the stakeholders of housing and real estate industry.

The study aims to identify the reality of the role of the banking sector in financing the Palestinian real estate and construction sector. The study demonstrated the importance of this issue by highlighting the role that Palestinian banks play in treating the problem of the increasing demand for housing because of the natural increase in population numbers and their various needs, and through knowledge of historical development for banks and the facilities they provided, especially to the real estate and construction sector.

This study carried out data from (2000–2019). The descriptive analytical method and regression method was used for analyzing the measurement model. Holt’s method was used to estimate the size of housing units needed in the Palestinian territories over the next seven years.

The study concluded that there is a need to build about (200,000) residential units in the next seven years, and the study recommended the necessity of increasing the pooled contribution of banks and directing part of it to the real estate and construction sector, amending legislative laws for the real estate market and construction, reducing taxes on building supplies and encouraging the private sector with stimulus policies or share.

The study provided results and data regarding the state of the housing sector and how its financed by Palestinian banks; it clarified the limitations and difficulties that face this sector and provides a clear path for what needs to be done to develop this sector and overcome its barriers.

This current study contributes to focusing on the reality of the banking sector and its role in financing the real estate and construction sector, in addition to the appropriate period of time for the study, which ranges between 2000 and 2019, which is a period sufficient to identify the reality of Palestinian real estate and construction and banks and the relationship between them.

The researcher believes that the study differed from its predecessors through an in-depth analysis of the existing relationship between cash assets and real assets, given that the priority of real assets over cash assets, as cash assets are considered as real over cash assets, but they do not constitute a substitute for them in economic development, the study contains a vision that recommends linking the activities of the banking sector with economic and social problems and the national issue, i.e. independence and self-determination.

This study aims to analyze the variables that affect residential real estate demand by millennials based on hedonic demand functions.

The method of analysis in this study is robust regression ordinary least square using cross-sectional data from Indonesian Family Survey Wave 5 (IFLS-5) with a sample of 1.672 households of male married millennials.

The aspect of millennial generation characteristics is significant on the variables of income, number of dependents, education level and presence of millennial generation in urban and rural areas. While the variable of age of the millennial generation does not significantly influence expenditure for residential real estate. All aspects of the millennial generation’s spending behavior consisting of spending on food consumption, education, health, telephone and internet, transportation, recreation and the variable of the presence of urban and rural millennial generations significantly affect the spending of the millennial generation for residential real estate with the assumption of ceteris paribus.

The implication of this study brings together the characteristics of the millennial generation with the aspect of behavior to expenditure for residential real estate assets relevant to the needs of the housing microfinance market.

In this study, it was found that the character and behavior of the millennial generation towards spending on residential real estate can be factors in determining policies by both the government and financial institutions that will serve the millennial generation through housing microfinance.

This implication study, it was found that the needs and behavior of the millennial generation towards the demand for housing microfinance principles according to their character and behavior.

The difference between the results of this study and previous studies is possible because previous studies did not differentiate the unit of analysis for the millennial generation.

This paper aims to examine real estate price volatility in Hong Kong. Monthly data on housing, offices, retail and factories in Hong Kong were analyzed from February 1993 to February 2019 to test whether volatility clusters are present in the real estate market. Real estate price determinants were also investigated.

Autoregressive conditional heteroscedasticity–Lagrange multiplier test is used to examine the volatility clustering effects in these four kinds of real estate. An autoregressive and moving average model–generalized auto regressive conditional heteroskedasticity (GARCH) model was used to identify real estate price volatility determinants in Hong Kong.

There was volatility clustering in all four kinds of real estate. Determinants of price volatility vary among different types of real estate. In general, housing volatility in Hong Kong is influenced primarily by the foreign exchange rate (both RMB and USD), whereas commercial real estate is largely influenced by unemployment. The results of the exponential GARCH model show that there were no asymmetric effects in the Hong Kong real estate market.

This volatility pattern has important implications for investors and policymakers. Residential and commercial real estate have different volatility determinants; investors may benefit from this when building a portfolio. The analysis and results are limited by the lack of data on real estate price determinants.

To the best of the authors’ knowledge, this paper is the first study that evaluates volatility in the Hong Kong real estate market using the GARCH class model. Also, this paper is the first to investigate commercial real estate price determinants.

Over a long period, even low inflation has an impact on portfolio value and households’ purchasing power. In such a context, inflation hedging should remain an important issue for investors. In particular, long-term investors, who are concerned with the protection of their wealth, seek to hold effective hedging assets. This study aims to demonstrate that residential assets in “Grand Paris” are a hedge against inflation and particularly against its unexpected component.

In this study, the physical residential markets in 127 communes in Paris and the Parisian first-ring suburbs are considered as potential asset classes. We simplified the analysis by clustering the 127 communes into five homogenous groups using ascending hierarchical classification (AHC). Then, we test the hedging ability of these groups within a mixed asset portfolios using both correlation and regression analysis.

This paper presents an analysis of the “Grand Paris” housing market and its inflation hedging ability with comparison to other financial asset classes. Results show that the five housing groups act as a highly positive hedge against unexpected inflation. Furthermore, cash and bonds seem to provide, respectively, a partial and an over hedge against unexpected inflation. Stocks act as a perverse hedge against unexpected inflation and provide no significant hedge against expected inflation. Also, indirect listed real estate demonstrates little correlation with inflation, which makes us reject its hedging ability contrary to physical residential real estate.

The inflation topic: although several researches exist that question the hedging property of real estate, very few concentrate on physical residential assets and to the best of the authors’ knowledge, this study is the only one that targets the “Grand Paris” area. Residential assets of the “Grand Paris” communes are confirmed to be a hedge against inflation and particularly against its unexpected component thanks to its capital appreciation rather than income one. Also, we show that the listed real estate in France (Sociétés d’Investissement Immobilier Cotée) does not provide the same hedging properties contrary to the US real estate investment trusts (REITs) who demonstrate this ability. Listed real estate could thus not be used interchangeably with housing to protect from inflation in the French market.

Protection of investors against inflation and in particular in the face of its return to France in 2022. Reassuring promoters and investors of the interest of residential investment projects in “Greater Paris” and of the potential that this holds.

Inflation takes a chunk out of the purchasing power of money and thereby erodes the real value of people’s finance. Investors and households who seek protection from inflation erosion should invest in direct housing, and in particular within areas that are experiencing an effective metropolization process.

The originality of the study is precisely relative to the geographical area studied. The latter has experienced favorable economic conditions for several years and offers interesting fundamentals to explore and exploit in investment strategies that prove capable of protecting against imminent inflation. The database is specific to this project and has been built through the compilation of several sources and with the support of BNP Paribas Real Estate.

China's real estate market is rampantly expanding. The purpose of this paper is to examine the factors underpinning China's real estate price escalation from 1998 to 2009.

Cointegration approach, vector error correction model and Granger causality test are adopted to analyze whether stable and long‐run equilibrium interactions exist between housing prices and key macroeconomic variables, such as CPI, land sale and GDP.

Cointegration analysis shows long‐term equilibrium between real estate price (HP) and CPI or GDP, but not land sale. A bilateral Granger causality is observed between CPI and HP. However, GDP does not Granger cause HP, indicating personal gain (disposable income) does not catch up with national gain (GDP) in China, or “Guojinmintui” (national gain outpaces personal gain). Neither is there a feedback effect from HP to GDP, indicating housing price appreciation does not result in immediate capital gain or speculations in housing purchase. Besides, lack of cointegration relationships between HP and land sale is probably caused by restrictive polices on land supply.

This paper represents the first attempt to adopt cointegration approach and Granger causality tests to examine the real estate price escalation in China using national monthly data. Econometric analysis and subsequent policy discussion suggest that real estate price is driven by both economic and institutional factors. In particular, “Guojinmintui” is a fiscal issue while capital gain is a monetary issue. Together with land market policies, these institutional factors significantly contribute to the price escalation.