City of Monash
Visitors by reason
In the 5 years up to 2017/18, international visitors to the City of Monash were more likely to be visiting friends and relatives, accounting for 30.0% of all visitors.
Tourism is an important part of the economy. Tourism Research Australia (TRA) run annual visitor surveys to measure the size and composition of the tourism market in each area, and this data is presented here. Tourism may include overseas visitors in the country for a holiday, business or education, Australian visitors staying overnight, or local day trippers visiting the area. These different types of tourists will utilize different services within the economy, so understanding the different tourism markets is important for Local Government and businesses.
NB: In February 2018, concerns were identified with the quality of the main purpose of visit component of the passenger data supplied to TRA by the Department of Home Affairs. This has resulted in the International Visitor Survey results from the March quarter onwards not including any data relating to the purpose of visit. As such, the data is starting to skew towards "other reason". TRA have said they are working to resolve these issues and may re-supply data. Read more from the TRA here.
Tourism Research Australia – Survey data
|International visitors - 5 year total|
|City of Monash - 2013/14 to 2017/18||City of Monash||Victoria|
|Main reason for trip||Visitors||Visitor nights||%||Average length of stay (days)||Visitors||Visitor nights||%||Average length of stay (days)|
|Visiting friends and relatives||127,696||3,561,842||30.0||27.9||3,611,304||64,299,446||22.2||17.8||1001||friends and relatives||608||19,071|
|Other reason||67,524||3,177,963||15.9||47.1||2,361,122||46,886,298||14.5||19.9||1006||for other reasons||330||10,998|
Source: Tourism Research Australia (opens a new window), Unpublished data from the International Visitor Survey 2017/18.
Note: "--" represents unavailable data or data that has been suppressed due to a sample size of 40 or less. A 5 year aggregate is used here to minimize the figures which need to be suppressed, but sample sizes may still be too small for some categories.