University:
California State University, Northridge
Course:
GEOG 150 | World Geography: People, Places, and Globalization
Academic year:

2024
Views:

407

Pages:

2
Author:

Amel S.

DEFERT’S TOURIST FUNCTION INDEX Pierre defert’s (1966) Tourist Function (TF) index or tourist function index means measuring the intensity or activity of tourists by comparing the number of destination population with the number of tourists. Due to the difficulty in obtaining accurate tourist statistics, Defert (1966) replaced the number of tourists with the total number of beds in a destination using the following formula: TF : 𝑛 𝑥 $%% 𝑝 n : number of beds p : destination population when there are no tourists accommodation/staying (n=0), defert’s index is also equal to 0 (TF=0). Conversely, in cases where there is no population (p=0), for example a national park, defert’s index has a value equal to infinity (TF=∞). According to defert (1966), using the number of beds to measure tourist activity produces inconsistent values. For example, while large cities may have a large number of beds that will accommodate tourists all year round, seasonal destinations (e.g. ski and beach resorts) may have the same capacity for accommodation even though they receive far fewer tourists. Another example is that different types of accommodation may have different types of demand (e.g. campgrounds versus hotels). It is therefore important to consider the use of defert’s index in analyzing the supply of commercial accommodation in a tourism destination because it can introduce distortions as tourists may choose to stay with friends or relatives or even in secondary homes, which would not be considered in an analysis that only deals with commercial accommodation. However, defert’s indexes can be constructed to demonstrate that tourist activity is important in the context of a tourism destination. Boyer (1972; in Pearce, 1995) divides the defert index into 6 parts as follows: • TF> 500 = 'hyper tourist' resorts • 100 < TF ≤ 500: 'large tourist' resorts • 40 < TF ≤ 100: dominant tourism destination • 10 < TF ≤ 40: destinations with important but not prominent or dominant tourism activities. • 4 < TF ≤ 10: little tourism activity or tourism functions are drowned out by other urban activities. • TF ≤ 4: almost no tourism activities The Deferts index is one of the first to be applied in tourism, and can be used as a variable in various studies. According to Smith (2010, p.132), it can also be followed over time or space to examine how the index varies in various situations. Given that the advent of the collaborative economy has given travelers access to other types of accommodation, for example Airbnb (Zervas et al., 2014), the defert model needs to be updated. For example, it could be rephrased as: 1. Include other accommodation supply indicators, for example the number of beds offered by Airbnb, without losing its simplicity. 2. Or perhaps include other tourism supply factors (e.g. air transport, cruise ships, number of rental cars) since considering only the number of beds is not always appropriate.