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Catching the long tail: competitive advantage through distribution strategy

Catching the long tail: competitive advantage through distribution strategy Purpose – The purpose of this paper is to examine the demand curve for information on tourism destinations and accommodation. The current study compares the demand curves for this information to trends described by Chris Anderson as the “long tail”. Design/methodology/approach – The current study examines the demand for information about accommodation establishments and destinations in Australia through the Australian Tourism Data Warehouse (ATDW). The study examines the demand for information received through the ATDW in 2009 for 5,600 Australian destinations and over 33,200 accommodation listings. Demand for information was measured by page impressions (PIs). Over 10 million PIs were received for destinations and more than 17 million PIs were received for accommodation listings, all of which were examined. Findings – The current research shows that both accommodation and destination demand curves display the extended demand curve typical of the long tail phenomenon. The analysis also shows that demand curves within the aggregate demand curve also follow “long tail” demand curves. The study contributes to understanding of the demand curve for tourism information for Australian product using the ATDW. Originality/value – The paper provides analysis of tourism information demand in the context of the “long tail” phenomenon. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Hospitality and Tourism Technology Emerald Publishing

Catching the long tail: competitive advantage through distribution strategy

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Publisher
Emerald Publishing
Copyright
Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
ISSN
1757-9880
DOI
10.1108/17579881111173758
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to examine the demand curve for information on tourism destinations and accommodation. The current study compares the demand curves for this information to trends described by Chris Anderson as the “long tail”. Design/methodology/approach – The current study examines the demand for information about accommodation establishments and destinations in Australia through the Australian Tourism Data Warehouse (ATDW). The study examines the demand for information received through the ATDW in 2009 for 5,600 Australian destinations and over 33,200 accommodation listings. Demand for information was measured by page impressions (PIs). Over 10 million PIs were received for destinations and more than 17 million PIs were received for accommodation listings, all of which were examined. Findings – The current research shows that both accommodation and destination demand curves display the extended demand curve typical of the long tail phenomenon. The analysis also shows that demand curves within the aggregate demand curve also follow “long tail” demand curves. The study contributes to understanding of the demand curve for tourism information for Australian product using the ATDW. Originality/value – The paper provides analysis of tourism information demand in the context of the “long tail” phenomenon.

Journal

Journal of Hospitality and Tourism TechnologyEmerald Publishing

Published: Oct 4, 2011

Keywords: Australia; Tourism; Internet; Information searches; Consumer behaviour; Databases; Long tail; Distribution

References