published_or_final_version / abstract / Urban Design / Master / Master of Urban Design

published_or_final_version / Architecture / Doctoral / Doctor of Philosophy

Aim: This study aims to investigate how e-commerce can be used to create perceptions of the residential real estate customers. Method: A qualitative abductive method is used aimed at collecting relevant data. The data was collected in Hanoi, Vietnam from sixteen interviews of residential real estate managers and customers respectively. In regards to the data analysis, content analysis technique was used on the notes gathered in the sixteen interviews. Results & Conclusions: The main results reveal online advertisement was found to be a substantial factor in the creation of residential real estate customers’ perceptions in the e-commerce application. In addition, the results show that social media information could as well create their perceptions. Suggestions for future research: The relationship between the agencies and the customers can be examined by using the residential real estate customers from the chosen agencies rather than using a convenient sampling technique.   The contribution of the thesis: This study has contributed to creating a model of residential real estate customers’ perceptions in the use of e-commerce.

This thesis is concerned with addressing operational issues in two types of dynamic markets where queueing plays an important role: limit order books (financial industry), and dynamic matching markets (residential real estate). We first study the smart order routing decisions of investors in fragmented limit order book markets and the implications on the market dynamics. In modern equity markets, participants have a choice of many exchanges at which to trade. Exchanges typically operate as electronic limit order books operating under a “price-time” priority rule and, in turn, can be modeled as multi-class FIFO queueing systems. A market with multiple exchanges can be thought as a decentralized, parallel queueing system. Heterogeneous traders that submit limit orders select the exchange to place their orders by trading off delays until their order may fill against financial considerations. Simultaneously, traders that submit market orders select the exchange to direct their orders. These market orders trigger instantaneous service completions of queued limit orders. Taking into account the effect of investors’ order routing decisions, we find that the equilibrium of this decentralized market exhibits a state space collapse property. The predicted dimension reduction is the result of high-frequency order routing decisions that essentially couple the dynamics across exchanges. Analyzing a TAQ dataset for a sample of stocks over a one month period, we find empirical support for the predicted state space collapse. In the second part of this thesis, we model an electronic limit order book as a multi-class queueing system under fluid dynamics, and formulate and solve a problem of limit and market order placement to optimally buy a block of shares over a short, predetermined time horizon. Using the structure of the optimal execution policy, we identify microstructure variables that affect trading costs over short time horizons and propose a resulting microstructure-based model of market impact costs. We use a proprietary data set to estimate this cost model, and highlight its insightful structure and increased accuracy over conventional (macroscopic) market impact models that estimate the cost of a trade based on its normalized size but disregarding measurements of limit order book variables. In the third part of this thesis, we study the residential real estate markets as dynamic matching systems with an emphasis on their microstructure. We propose a stylized microstructure model and analyze the market dynamics and its equilibrium under the simplifying approximation where buyers and sellers use linear bidding strategies. We motivate and characterize this near closed-form approximation of the market equilibrium, and show that it is asymptotically accurate. We also provide numerical evidence in support of this approximation. Then with the gained tractability, we characterize steady-state properties such as market depth, price dispersion, and anticipated delays in selling or buying a unit. We characterize congestion and matching patterns for sellers and buyers, taking into account market dynamics, heterogeneity, and supply and demand imbalance manifested in the competition among buyers and sellers. Furthermore, we show the effects of market primitives with comparative statics results.

In the competitive and fast-paced industry of residential real estate, digital marketing strategies must effectively meet the information needs and demands of the industry’s three key stakeholders: buyers, sellers, and agents. Digital house hunting is the predominant search strategy for prospective homebuyers who scour the Internet looking for homes to purchase. Property sellers and real estate professionals, whose shared end-goal is to transact a successful sale, must discern which digital marketing choices are optimal for marketing for-sale properties online in the digital channels where buyers are searching. A 2008 settlement agreement between the Department of Justice and the National Association of Realtors over concerns of anticompetitive policies relating to virtual office websites (VOWs) led to a shift in responsibility from the agent to the seller regarding which online marketing options will be associated with the online property listings. Real estate agents allocate time and resources to market properties on behalf of sellers, and need strategies that cater to buyers’ search preferences and sellers’ online marketing prerogatives while remaining effective and cost-efficient. Previous empirical studies using MLS data have considered the effects of seller marketing choices of real estate platforms and types of agents (i.e. full-service, flat-fee, etc.) as well as the impacts of a variety of agent marketing efforts on the market outcomes of sales price, time on the market, and the probability of sale. This research extends prior work by providing a quantitative analysis of the effects digital marketing choices of sellers (allowing “blogging” or third-party commentary) and digital marketing efforts of the agents (using a virtual tour) have on market outcomes. This analysis also includes a novel inquiry into what, if any, measurable effects the various platforms chosen for the virtual tours have on market outcomes.

While it is generally accepted that residential submarkets exist, this is not the case for either their definition or delineation. This study has developed and assessed a methodology for deriving the geospatial dimensions of residential real estate submarkets based on the behaviour of the marketplace with respect to the underlying dimensions of the residential real estate living structure (RLS). Importantly, the methodology makes no prior assumptions about where the spatial boundaries might be. They were empirically derived from the data alone. It is achieved by building on previous work in the field and seeking to identify the fundamental issues in residential real estate market behaviour. The first basic premise of the thesis is that when a dwelling is sold, the commodity traded is a piece of real estate geography comprising a complex bundle of both spatial and structural attributes. The second basic premise is the recognition in the methodology of the importance of ‘location’. The price of the real estate geography varies across geographical space in a continuous fashion and it is this price variability that is defined, in this study, to be the geospatial submarket identifier. The study adopts a two-stage methodology reflecting these two basic premises. Firstly, a complex bundle of attributes is collected for every property in the study area and distilled into its underlying dimensions using principal component analysis. The resulting factors are used in the second stage as independent variables in a hedonic geographically weighted regression model to determine the price variability across geographical space of the underlying residential real estate structure. User-defined breaks in the continuous price surface delineate the geospatial submarket boundaries. The study represents a new approach to the delineation of geospatial submarket boundaries and is yet to be fully assessed by the two major identified users (the planning profession and the valuation profession). However, initial feedback indicates that the ability of the methodology to describe the geospatial submarket boundaries in terms of ‘how’ and ‘where’ location affects the market price of the underlying real estate geography, gives the land professional a better understanding of the submarket structure in which they are working. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1330874 / Thesis (Ph.D.) -- University of Adelaide, School of Social Sciences, 2008

The recent economic recession has had a significant impact on residential real estate both nationally and regionally. Our research is focused specifically on Cobb County, Georgia and the impact that the declining economy has had on home buying and property values in this area. Specifically, this research aims to identify changes in the residential market in terms of significant characteristics of housing and their corresponding effect on home values.

published_or_final_version / Housing Management / Master / Master of Housing Management

published_or_final_version / Housing Management / Master / Master of Housing Management

published_or_final_version / Housing Management / Master / Master of Housing Management