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1. Each collection of tourism related statistics has specific objectives and covers a range of data unique to that collection. Many collections, however, include some data which do, or potentially could, overlap with those of other collections. Consistency of definitions and classifications for the data items used in the various collections increases their value through enabling the results to be linked and compared. This Framework provides the standards for those commonly required attributes, referred to here as the Typical Measures, relating to each of the three elements of the event.
3. The recommended classification systems in some cases provide categories down to a level of detail which is more than that required for some tourism collections. These detailed categories, however, allow the collector the flexibility to compile customised groupings which comprise selected relevant detailed categories. These groupings can then be identified in terms of the detailed categories in the standard classification.
4. The Typical Measures comprise variables which will be of varying degrees of interest depending on the objectives of each collection. In any particular collection, some will be of crucial importance, while others will not be required at all. The size of a sample survey may also affect decisions on the inclusion or exclusion of any particular measure. A small sample size may not permit estimates with acceptable standard errors for some characteristics and thus their inclusion would only contribute to cost and respondent load without providing useable data. The size of a sample may also affect the level of category detail chosen in any particular classification. A small sample size may prohibit the use of the required level of detail in a classification, and necessitate the use of a higher, broader level of classification.
5. The Figure in Chapter 1 listed the Typical Measures identified for each of the three elements of the Framework, the CONSUMER, the PRODUCT and the SUPPLIER. This chapter provides definitions, and classifications where relevant, for each of these measures.