Search results

The purpose of this paper is to determine whether the quality and reliability of websites’ content can be assessed through the lens of “wisdom of the crowds”. In particular as a case study the authors examine the information supplied over time on several prominent Israeli real estate websites.

The Israeli real estate market was selected for the study, since there are many large, popular and dynamic real estate websites that feature hundreds of thousands of ads, representing most of the supply of real estate properties in the country. The authors built an automatic, ontology-based system that downloaded advertisements from three selected websites every two weeks for a number of months and checked for changes in these advertisements over time. The authors conjecture that wisdom of the crowds is mostly reflected by the information changes on the websites, since they indicate the anticipated market trends. Hence the authors developed a number of statistical measures to comparatively analyse trends of information changes on these websites, and assess their reliability compared to the actual market data and tendencies.

The primary results suggest similar information change trends amongst all the websites. Surprisingly, although some properties did not sell over time, sellers generally did not lower their asking price and were willing to wait. Sellers even raised their asking price, apparently in anticipation of future price increases. Comparison of recurring trends among the websites with the trends of the real market during the same time period and a few months after reveals that wisdom of the crowds is only partially effective as an indicator and predictor of website content quality: it correctly reflects the fluctuation in demand, but not in the prices.

This study was conducted over a limited time period of five months, and only in several cities in Israel. Additionally, since buyers are not explicitly represented in these sites, their information behaviour was not analysed, although it undoubtedly influences information changes performed by the sellers.

The practical contribution of this study is the ontology of the real estate world. Its assimilation by real estate websites would promote the development of their sites and user services. It would also enable ad sharing amongst the various websites and enable efficient searches by search engines. In addition the tools and measures that the authors developed will allow continued monitoring and analysis of user information change patterns.

To the best of the knowledge this is the first study to examine and compare real estate websites’ quality and evaluate their information reliability as wisdom of the crowds.

The real estate industry is an e‐commerce anomaly. Although the overall growth of ecommerce is driven by the business‐to‐business sector, the majority of real estate e‐commerce is derived from its retail‐oriented residential sector. This study examines the structure of residential and commercial real estate websites, with the goal of determining whether some patterns of content might increase the quality and quantity of information available to buyers and sellers thereby contributing to the disparity between residential and commercial real estate e‐commerce growth. The results of the research show residential real estate websites offer richer informational content than commercial real estate websites. No significant differences are found for the user friendliness and functionality (ie ancillary services) provided by residential and commercial real estate websites.

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.

Brand awareness is a key cognitive metric and a vital component of consumer-based brand equity. Generating and maintaining brand awareness has been an important metric for brands and a significant outcome of advertising and promotional activities. Brand awareness has been studied over the years in the context of market share and mind share and is considered to be the fundamental starting point of a brand relationship. Most branding variables are challenged in their linear definitions by the multi-dimensionality of the connected online world. Consumers may start their brand journey with brand awareness and then proceed to explore higher options in a non-linear fashion. This challenges traditional advertising and brand salience models. In the web context, brand awareness could even happen with little prior cognitive processing. The purpose of this paper is to explore the little researched area of brand awareness in the context of Indian websites.

The study leveraged technology to study the brand discovery behaviour of real estate website users in India. The authors looked at essentially modified processes such as the brand experience journey, specifically, the sources and antecedents of brand awareness for real estate websites. Considering the fact that direct and indirect traffic to a website is indicative of the brand awareness metrics, the authors analyse the metric as a basis of the comparison.

Brand awareness in the digital world can be attributed as firm generated, user generated and, as the authors also discover, experience initiated. The altered dimensions have a profound impact on the brand advertising spends of not just digital brands, but all marketers who will find digital technology increasingly central to their brand communication efforts.

Burgeoning websites and media proliferation have increased the source set for website discovery. Customers do not rely solely on advertising or chance encounter to discover a new brand. Usage of search engines remains the key point of discovery for brand awareness. Some of the respondents recognised websites from prior advertising exposure and selected the brand from the consideration set offered in the search results for their keyword search. In other cases, brand awareness followed brand experience as the users did not process the brand information or, in most cases, were not aware of the brand name prior to website visit. The quality of brand experience created brand awareness and had further implications, including brand visit intent.

While mass media television advertising and ubiquitous online advertising can build brand awareness, the impact of search engine advertising and search engine optimisation is equally significant, if not more important. Brand managers can additionally focus on branding on the search channel in the light of increasing search intensity. Beyond traditional keyword planning, this can be an enhanced branding platform for reaching out to specific behavioural or character traits of the target audience. Brand experience can mature from task completion to brand awareness and higher level values if the website includes key brand messages and goals.

This paper offers insight into the little known field of online brand management. Information intermediary websites are unique in their value proposition, and brand building is challenging. Real estate websites have grown in popularity, but have not merited researcher attention. This paper offers a unique perspective on branding websites, specifically in the context of emerging markets like India.

The purpose of this study is to compare quality perceptions of virtual servicescapes and physical service encounters among buyers and renters of real estate.

Qualitative data from a sample of 27 professionals engaged in higher education in the USA are gathered by recorded interview before being transcribed and imported into MAXQDA 2007 software for analytical coding.

Particular differences are found to exist between renters and buyers with regard to specific service attributes – for example, description of properties and type of visuals during the pre‐purchase stage, knowledge/experience and honest behavior of realtors during the service encounter stage and a continuous relationship with the realtor in the post‐encounter stage.

Generalization of the results is limited because the study utilizes data from only one industry (real estate) and from only one demographic segment (professionals in higher education).

Real‐estate firms need to pay attention to both the training of agents and the design and content of their websites.

This paper contributes to knowledge regarding virtual servicescapes in professional services.

The paper aims to provide a comprehensive analysis of artificial intelligence’s (AI) transformative impact on the real estate industry. By examining various AI applications, from property recommendations to compliance automation, this study highlights potential benefits such as increased accuracy and efficiency. At the same time, this study critically discusses potential drawbacks, like privacy concerns and job displacement. The paper's goal is to offer valuable insights to industry professionals and policy makers, aiding strategic decision-making as AI continues to reshape the landscape of the real estate sector.

This paper employs an extensive literature review, combined with a qualitative analysis of case studies. Various AI applications in the real estate industry are examined, including machine learning for property recommendations and valuation, VR/AR property tours, AI automation for contract and regulatory compliance, and chatbots for customer service. The study also delves into the optimisation potential of AI in building management, lead generation, and risk assessment, whilst critically discussing potential challenges such as data privacy, algorithmic bias, and job displacement. The outcomes aim to inform strategic decisions for industry professionals and policy makers.

The study finds that AI has significant potential to revolutionise the real estate industry through enhanced accuracy in property valuation, efficient automation and immersive AR/VR experiences. AI-driven chatbots and optimisation in building management also hold promise. However, this study also uncovers potential challenges, including data privacy issues, algorithmic biases, and possible job displacement due to increased automation. The insights gleaned from this study underscore the importance of strategic decision-making in harnessing the benefits of AI while mitigating potential drawbacks in the real estate sector.

The paper's practical implications extend to industry professionals, policy makers, and technology developers. Professionals gain insights into how AI can enhance efficiency and accuracy in the real estate sector, guiding strategic decision-making. For policy makers, understanding potential challenges like data privacy and job displacement informs regulatory measures. Technology developers can also benefit from understanding the sector-specific applications and concerns raised. Additionally, highlighting the need for addressing algorithmic bias and privacy concerns in AI systems may foster better design practices. Therefore, the paper's findings could significantly shape the future trajectory of AI integration in real estate.

The paper provides original value by offering a comprehensive analysis of the transformative impact of AI in the real estate industry. Its multi-faceted examination of AI applications, coupled with a critical discussion on potential challenges, provides a balanced perspective. The paper's focus on informing strategic decisions for professionals and policy makers makes it a valuable resource. Moreover, by considering both benefits and drawbacks, this study contributes to the discourse on AI's broader societal implications. In the context of rapid technological change, such comprehensive studies are rare, adding to the paper's originality.

This paper aims to discuss the essential features, merits and drawbacks of the recently enacted Indian Real Estate Act, 2016, an economic reform measure pertaining to the real estate sector (RES). This paper analyses the impact of the Act and Union Budget 2016 on the inflow of foreign d irect investment (FDI) in India, and examines its ramifications on the world economy.

The study is based on secondary data sources, including consumer forum reports, investigative reports from national agencies, court decisions, government websites, real estate companies and industry associations. A sample survey on the implications of the Act has been conducted using Facebook and and through personal interaction with various stakeholders.

The Indian RES was unregulated prior to the passage of the Act, which has several provisions aimed at protecting the interest of consumers by tightening fraudulent practices of promoters/developers. Stakeholders are hopeful, but there is some apprehension. The government’s budgetary and fiscal support for infrastructure development has had an impact on the FDI inflow.

The Act is new, so there is not enough data to judge its real impact on the economy. However, it has started showing evidence of impact through a recent judgment by the Supreme Court of India punishing a promoter.

Regulating the Indian RES is a challenging task, but the new regulations are likely to provide confidence to foreign investors who may see India as a safety net for investment. This paper is timely and may help move things in this direction.

Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.

This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.

Four domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.

This paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

The purpose of this paper is to review the literature on the Disruptive Innovation Theory and on the disruptive potential of real estate crowdfunding (RECF) in the real estate finance industry, assessing whether RECF constitutes a potentially disruptive innovation to the real estate finance industry. Based on a review and synthesis of the literature, the paper advances an initial conceptual framework of core characteristics of disruptive innovations. This framework is used to examine the disruptive potential of RECF in the real estate finance industry.

This paper is a systematic literature review that synthesizes and analyzes relevant extant research articles retrieved from online databases.

Findings suggest that according to the theory of disruptive innovations, and the core characteristics of disruptive innovations, RECF is a potentially disruptive innovation to the real estate finance industry. RECF seems to generally align with the classic characteristics of disruptive innovations. A more comprehensive and systematic analysis, supported by empirical data, is necessary to evaluate whether and to what extent RECF constitutes a disruptive innovation to the real estate finance industry.

This study has only captured and reviewed articles published and available in database searches. RECF is a nascent field that has recently begun receiving academic attention.

Real estate plays an integral part in the economy, and the way it is financed has become an increasingly important issue following the Global Financial Crisis. This paper provides useful insights for assessing whether and to what extent RECF may be disruptive to the real estate finance industry.

RECF may potentially improve accessibility and affordability of real estate finance, thereby helping to address the problem of shortage of real estate project finance.

While RECF is portrayed in the academic and gray literature as a disruptive innovation, its disruptive potential is yet to be determined. This paper advances an initial conceptual framework of defining characteristics of disruptive innovations. This framework is used to evaluate RECF as a potentially disruptive innovation in the real estate project finance industry. This study forms a basis for future empirical examination of the disruptive potential of RECF in the real estate finance industry.

This study aims to empirically examine the relationship between real estate and stock market of Pakistan.

The data of two real estate indices (house price index and plot price index) are taken for the Pakistan and its four big cities, i.e. Lahore, Karachi, Rawalpindi and Islamabad. It estimates the integration between series by applying the Johansen cointegration test. Moreover, the vector error correction model is applied to examine the short and long-run causal relationships between series.

The findings show that the real estate markets are cointegrated with the stock market. They imply that the real estate and stock markets are good substitutes in investment allocation, but investors cannot get the benefit of diversification by making a portfolio of real estate and stock markets in Pakistan. Moreover, the long-run causality is observed from majority house markets to the stock market, whereas short-run causality is evident from majority plot markets to the stock market. Hence, the real estate market leads the stock market in the short run and long run, suggesting the credit-price effect in the majority of real estate markets in Pakistan. These causality results are helpful for investors in the forecasting of real estate and stock markets in Pakistan.

The limitation of the study is the lower number of observations (107), because house and land prices are only available in monthly frequency from January 2011 in Pakistan.

To the best of the authors’ knowledge, no researcher has investigated the real estate and stock market nexus in Pakistan. Therefore, this study focuses on examining the relationship between the real estate and stock market of Pakistan. The link between real estate and stock markets will provide useful insights to the portfolio managers, real estate companies, property agents, stockbrokers and investors.