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The present study aims to investigate resident attendees' perceptions and attitudes towards a traditional cultural festival. It further clusters the attendees and identifies the profiles of each cluster based on its demographic, attitudinal and behavioral variables.

The Drunken Dragon Festival, a traditional cultural festival in Macao SAR, which has been embedded in the local community for about a century, is used as a case. Data collected from 378 residents on the day of the festival were factor analyzed and then grouped by using cluster analysis.

A two-cluster solution revealed that the two groups, overall, had distinct demographic characteristics and had somewhat different perceptions and attitudes towards the festival.

The results not only show the overall perceptions of the Drunken Dragon Festival among the resident attendees, but they also imply that the government and the organizers need to communicate with and involve the two resident attendee clusters differently.

This study is one of the first attempts to investigate the residents' attitudes towards the transformational development of a traditional cultural festival as an effort to ensure the viability of intangible cultural heritage and to utilize it as a tourism resource.

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”.

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.

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.

The paper provides analysis of tourism information demand in the context of the “long tail” phenomenon.