Search
  Advanced Search
 
Journal search
Journal cover: International Journal of Housing Markets and Analysis

International Journal of Housing Markets and Analysis

ISSN: 1753-8270

Online from: 2008

Subject Area: Built Environment

Content: Latest Issue | icon: RSS Latest Issue RSS | Previous Issues

Options: To add Favourites and Table of Contents Alerts please take a Emerald profile

Icon: .Table of Contents.Icon: .

Direct versus search engine traffic: An innovative approach to demand analysis in the property market


Document Information:
Title:Direct versus search engine traffic: An innovative approach to demand analysis in the property market
Author(s):Manuel Kaesbauer, (IREBS International Real Estate Business School, University of Regensburg, Regensburg, Germany), Ralf Hohenstatt, (IREBS International Real Estate Business School, University of Regensburg, Regensburg, Germany), Richard Reed, (Deakin University, Melbourne, Australia)
Citation:Manuel Kaesbauer, Ralf Hohenstatt, Richard Reed, (2012) "Direct versus search engine traffic: An innovative approach to demand analysis in the property market", International Journal of Housing Markets and Analysis, Vol. 5 Iss: 4, pp.392 - 413
Keywords:Google Insights for Search, Home buying search process, House price, Housing, Prices, Property marketing, Search engines, Search query data, Sentiment, Transaction volume
Article type:Research paper
DOI:10.1108/17538271211268538 (Permanent URL)
Publisher:Emerald Group Publishing Limited
Abstract:

Purpose – The application of “Google” econometrics (Geco) has evolved rapidly in recent years and can be applied in various fields of research. Based on accepted theories in existing economic literature, this paper seeks to contribute to the innovative use of research on Google search query data to provide a new innovative to property research.

Design/methodology/approach – In this study, existing data from Google Insights for Search (GI4S) is extended into a new potential source of consumer sentiment data based on visits to a commonly-used UK online real-estate agent platform (Rightmove.co.uk). In order to contribute to knowledge about the use of Geco's black box, namely the unknown sampling population and the specific search queries influencing the variables, the GI4S series are compared to direct web navigation.

Findings – The main finding from this study is that GI4S data produce immediate real-time results with a high level of reliability in explaining the future volume of transactions and house prices in comparison to the direct website data. Furthermore, the results reveal that the number of visits to Rightmove.co.uk is driven by GI4S data and vice versa, and indeed without a contemporaneous relationship.

Originality/value – This study contributes to the new emerging and innovative field of research involving search engine data. It also contributes to the knowledge base about the increasing use of online consumer data in economic research in property markets.



Fulltext Options:

Login

Login

Existing customers: login
to access this document

Login


- Forgot password?
- Athens/Institutional login

Purchase

Purchase

Downloadable; Printable; Owned
HTML, PDF (266kb)Purchase

To purchase this item please login or register.

Login


- Forgot password?

Recommend to your librarian

Complete and print this form to request this document from your librarian


Marked list


Bookmark & share

Reprints & permissions