A Research on the Influential Factors of Listing Sales Based on Online Information in Short Rental Markets

Recent years,sharing economy as a new business model has developed very well in the whole world and the online marketplace for peer-to-peer accommodation rental services such as XiaoZhu change people’s life a lot.With the development of social media and information technology,consumers can not only pubulish text comments but also can share the photos taken by them on the paltform as a supplement.In order to study the impact of online information on the sales volume of houses under the background of sharing-economy, we collect data from XiaoZhu and use the correlation analysis and regression analysis. This research provides a new perspective for the sharing research and foucuses on China’s online short-term rental market. The result shows that the total number of online reviews, the number of picture comments and the price have significant effects on home sales

Two Essays in Real Estate Dynamics

Real estate dynamics encompass a multifaceted interplay of various factors that shape the market. This dissertation presents two distinct essays that delve into critical aspects of real estate dynamics. In the first essay, we investigate the influence of short-term rentals, specifically Airbnb activity, on neighboring house prices in Hampton Roads, Virginia. By employing robust measures such as active listings, reservations, and their cumulative impact over different periods, we uncover a positive association between prior Airbnb rental activity and housing sales prices. Moreover, we observe a spatial decay effect, where the localized impact diminishes with increasing geographic distance, particularly beyond 500 meters. Further analysis employing quantile regression reveals that the effect of Airbnb rentals is more pronounced for higher-priced homes, while middle-range house prices demonstrate a relatively lower sensitivity to Airbnb activity. These findings contribute to the existing literature by shedding light on the nuanced relationship between Airbnb and housing prices. The second essay delves into the relationship between media content sentiments and returns of Real Estate Investment Trusts (REITs). Leveraging proprietary investor sentiment measures from Thomson Reuters, including dimensions such as stress, emotion vs. fact, dividends, and price direction, we employ a multi-step approach to examine their impact on REIT returns. Through time series regression and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, we establish the statistical significance of media content sentiments in explaining REIT returns and market volatility. Employing Lasso analysis, we identify the sentiment related to price direction as the most influential factor impacting excess REIT returns consistently across various REIT types and weighting schemes. Our analysis enhances traditional asset pricing models, improving the adjusted R-squared, and provides insights into the role of media sentiment in shaping REIT returns. By integrating these two essays, this dissertation contributes to a comprehensive understanding of real estate dynamics. The first essay illuminates the impact of Airbnb activity on house prices, emphasizing the spatial decay effect and differential sensitivity across price distributions. The second essay highlights the significance of media content sentiments in explaining REIT returns and the findings are validated through Covariance-based Structural Equation Modeling (SEM) and path analysis. Collectively, these essays broaden our knowledge of the complex dynamics within the real estate market and provide valuable insights for researchers, policymakers, and market participants alike

Determinants of Market Value of Residential Properties in Ibadan Metropolis, Nigeria

Several studies have shown that most of valuations prepared by valuers are unreliable due to valuation inaccuracy in valuation opinion which Nigeria is not excluded. As a result of Ibadan centrally placed position between the hinterland and the coast, its attracted so many traders and investors and serves as an economic centre for so many towns in the country. This study therefore examined major determinants of residential property market values in Ibadan Metropolis with a view to improving valuation accuracy in the study area. The study used random sampling to select 624 residential properties from the portfolio of 52 Estate Surveying and Valuation firms located within Ibadan metropolis, Nigeria. Data were analysed using a hedonic pricing specification. The results showed that while number of toilet (NOT), existence of burglary alarm (EOBA) and condition of the building were major factors influencing rental value of residential property in Ibadan Metropolis, number of toilet (NOT) and type of building (TOB) were the major factors influencing capital value. The study concluded that different major factors influence both rental and capital values and property valuers should recognise this in the process of carrying out residential property valuation in order to make their valuation reliable. Also, residential property investors need to take cognizance of this in decision making. Keywords: Determinants, Inaccuracy, Residential Properties and Valuation

Factors Influencing Real Estate Property Prices A Survey of Real Estates in Meru Municipality, Kenya

Real estate is often used to refer to things that are not movable such as land and improvements permanently attached to the land. Different types of real estate can have very different cyclic properties. Real estates go through bubbles followed by slumps in Meru municipality and some real estate properties take shorter time while others take longer to sell despite that the prevailing conditions seem similar. Several studies done especially on changes in prices of real estates revealed that real estate prices go through bubbles and slumps. The study therefore, investigated factors at play in determining real estate property prices in Meru Munincipality in Kenya. The study investigated factors such as incomes of real estate investors, the influence of location on the price, demand and realtors influence on the price. The study adopted descriptive research design to obtain information on the current status of the phenomenon. Structured questionnaires were used in data collection to obtain the required information needed for the study. The population consisted of all 15,844 registered real estate owners in the 5 (five) selected areas of Meru municipality from which a sample of 390 real estate owners were selected by stratifying the population and then selecting the respondents by use of simple random sampling. The data obtained was analyzed by use of available statistical packages for social sciences to obtain descriptive statistics and a regression model. Findings indicated that incomes alone contributed almost 70% of the variations in prices. Demand alone contributed 20% of the changes in prices of real estate. Location and Realtors were found insignificant in determining real estate prices. A summary regresion showed that the variables consindered could explain up to about 70% of variations in prices. The study  recommends that  further investigation be done on reasons why location and realtors were not significat in determining real estate property prices in Meru municipality

The impact of Airbnb on the economic performance of independent hotels: an empirical investigation of the moderating effects

The evidence on the effect that sharing economy accommodation platforms have on the performance of hotels is not univocal, and a general picture about the circumstances under which hotels may suffer the least from this disruption is still missing. This paper contributes to bridge this gap by examining the role that contingent factors can play in reducing the negative impact of Airbnb on the profitability growth of independent hotels. We examine whether the attractiveness of the city zone where hotels are located and their online reputation moderate the effect that the usage of Airbnb listings has on the profitability growth of independent hotels. Using a panel dataset of a sample of 725 independent hotels located in six Italian cities with high tourism attractiveness, and by triangulating ISTAT, AIDA, AirDNA, TripAdvisor and Trustyou datasets, we found that the negative effect of Airbnb on the profitability growth of hotels is reduced when the hotels are located in attractive city zones. However, the online reputation of hotels does not have any significant moderating effect on the relationship investigated. We discuss how these results contribute to understand competitive dynamics in the hotel industry through a lens based on the disruptive innovation theory

Individuals' capabilities in pricing their offering in commercial sharing systems

This study seeks to shed light on the capability and preparedness of individual sharing economy users to price their offering and adjust the pricing based on changes in demand. Central to the topic are the concepts of revenue management, yield pricing and price determinants identified in hotel industry and Airbnb price determination. The chosen research approach is to use statistical data analysis based on open source data from Insideairbnb.com and Trivago hotel price indices. This allows for drawing conclusions based on host pricing behavior during 2015-2017 in five Europeans cities, five North American cities and two Australian cities. All twelve are major cities with thousands of Airbnb listings available each month. Previous research has not sought to examine pricing in sharing economies in this way. Previous research has identified that user characteristics influence participation in sharing economy and findings in the empirical section of this study would suggest that a majority of users do not actively pursue higher profits through revenue management that is comparable with the hotel industry in magnitude. Additionally, this study showed that due to the different nature of rented space on Airbnb to hotels, prices may be cheaper closer to the actual stay rather than several months beforehand. This study does not suggest that Airbnb hosts should pursue higher profits and do business with their apartments. Hosts should be aware of the limitations that regulation sets on their rentals and applicable taxation practices. Should future business models be dependent on individuals pricing their own offering, based on the findings in this study, considerations should be made not only from the view of the viability of the business for the individual and platform provider, but also the regulatory point of view to avoid unleveled playing fields and predatory pricing

What Airbnb Reviews can Tell us? An Advanced Latent Aspect Rating Analysis Approach

There is no doubt that the rapid growth of Airbnb has changed the lodging industry and tourists’ behaviors dramatically since the advent of the sharing economy. Airbnb welcomes customers and engages them by creating and providing unique travel experiences to “live like a local” through the delivery of lodging services. With the special experiences that Airbnb customers pursue, more investigation is needed to systematically examine the Airbnb customer lodging experience. Online reviews offer a representative look at individual customers’ personal and unique lodging experiences. Moreover, the overall ratings given by customers are reflections of their experiences with a product or service. Since customers take overall ratings into account in their purchase decisions, a study that bridges the customer lodging experience and the overall rating is needed. In contrast to traditional research methods, mining customer reviews has become a useful method to study customers’ opinions about products and services. User-generated reviews are a form of evaluation generated by peers that users post on business or other (e.g., third-party) websites (Mudambi & Schuff, 2010). The main purpose of this study is to identify the weights of latent lodging experience aspects that customers consider in order to form their overall ratings based on the eight basic emotions. This study applied both aspect-based sentiment analysis and the latent aspect rating analysis (LARA) model to predict the aspect ratings and determine the latent aspect weights. Specifically, this study extracted the innovative lodging experience aspects that Airbnb customers care about most by mining a total of 248,693 customer reviews from 6,946 Airbnb accommodations. Then, the NRC Emotion Lexicon with eight emotions was employed to assess the sentiments associated with each lodging aspect. By applying latent rating regression, the predicted aspect ratings were generated. With the aspect ratings, , the aspect weights, and the predicted overall ratings were calculated. It was suggested that the overall rating be assessed based on the sentiment words of five lodging aspects: communication, experience, location, product/service, and value. It was found that, compared with the aspects of location, product/service, and value, customers expressed less joy and more surprise than they did over the aspects of communication and experience. The LRR results demonstrate that Airbnb customers care most about a listing location, followed by experience, value, communication, and product/service. The results also revealed that even listings with the same overall rating may have different predicted aspect ratings based on the different aspect weights. Finally, the LARA model demonstrated the different preferences between customers seeking expensive versus cheap accommodations. Understanding customer experience and its role in forming customer rating behavior is important. This study empirically confirms and expands the usefulness of LARA as the prediction model in deconstructing overall ratings into aspect ratings, and then further predicting aspect level weights. This study makes meaningful academic contributions to the evolving customer behavior and customer experience research. It also benefits the shared-lodging industry through its development of pragmatic methods to establish effective marketing strategies for improving customer perceptions and create personalized review filter systems

Sarkar, Butler & Steinfield (1995) “Intermediaries and Cybermediaries” Revisited: A Review and Identification of Future Research Directions for Intermediaries in Electronic Markets

Intermediation in markets is a phenomenon that has been studied by many researchers from a variety of different theoretical angles. With the introduction and diffusion of the Internet in everyday life, broad predictions were made that called for disintermediation enabled by direct Internet linkages between suppliers and buyers and lower transaction costs. The often-cited paper by Sarkar, Butler and Steinfield (1995) challenges this prediction. By comparing Internet effects on transaction costs with the cost situation ex ante, the paper explains that both direct sales or cybermediated sales are possible outcomes. In this paper we confront key assumptions of the Sarkar et al. paper with recent developments in the tourism market. We find that in the tourism market a multitude of direct and indirect distribution channels exist next to each other. Multi-level distribution channels often including several cybermediaries have been built, resulting in a complex market topology. We also see a large variety of intermediary roles, resulting from highly specialized and highly integrated cybermediary business models. Furthermore the model of Sarkar et al. fails to deliver an explanation for the on-going dynamics in the tourism market in terms of shifts towards more or less intermediaries and the emergence of new intermediary-like business models. By taking these trends into account we are able to identify relevant future research directions in order to extend our understanding of the phenomenon of electronic intermediaries in markets

An Analysis of the Changing Competitive Landscape in the Hotel Industry Regarding Airbnb

This thesis analyzes the competition between hotels and Airbnb in San Francisco. Airbnb is an internet platform that allows hosts to rent shared space, private rooms or homes to tourists. This study identifies the affect Airbnb has on hotels, workers, renters, neighborhoods, and tax revenue. Interviews and research was engaged with travel industry professionals. Hoteliers were found to be apathetic about the competition between hotels and Airbnb. Airbnb can be a meaningful experience between hosts and tourists. Budget travelers might not travel if not for low Airbnb rates. Airbnb rooms supplement hotel inventory during extraordinary events. This utopian view of Airbnb seems to overcome the dark sides; evidenced by rising apartment rental rates and declining inventory. Pressures are placed on working class neighborhoods driving out the local workforce for high rate tourists. To date, Airbnb has defeated efforts to be effectively regulated. Unregulated conversions of residential to hotel use is a safety concern. San Francisco Ordinance 218-14 was passed to legalize and regulate Airbnb; however 218-14 is unenforceable. California Senator McGuire authored SB 593: The Thriving Communities and Sharing Economy Act to empower regulation of Airbnb. SB 593 has not been passed yet by the California Senate. Until tax payments, legal, regulatory, safety codes, and compliance issues are addressed the majority of Airbnb will be operating illegally with an unfair competitive advantage over hotels

The Economics of Internet Markets

The internet has facilitated the creation of new markets characterized by large scale, increased customization, rapid innovation and the collection and use of detailed consumer and market data. I describe these changes and some of the economic theory that has been useful for thinking about online advertising markets, retail and business-to-business e-commerce, internet job matching and financial exchanges, and other internet platforms. I also discuss the empirical evidence on competition and consumer behavior in internet markets and some directions for future research.internet, market, innovation, advertising, retail, e-commerce, financial exchanges