112 E. Szymańskatroduced TFI which is derived by comparing the number of bed available to tourists withresident population of the researched area. In this case tourist density is measured.The Tourism Function Index is calculated:TFI = (N · 100)/Pwhere: N = number of bed spaces and P is the population.However, Boniface and Cooper [2009] pay attention to the fact that Defert’s tourismfunction index works good as a measure for holiday resorts but it underestimates theimpact of tourism in cities with a large resident population, or in historic towns that attractlarge numbers of day visitors [Cooper 2009]. Also, it is important to underline thatwhile TFI used to compare variations in accommodation density between regions withinthe same country is very meaningful, at the international level, though, can be misleadingbecause of the differences in definitions and registration requirements among thecountries.Tourism function can be also measured by searching tourism intensity expressed bythe quotient of the number of tourists to the local population (Scheider’s index) or, proposedby Defert, to an area in km 2 (Defert’s index). Another approach described in theliterature is Charvat’s index which examines the amount of beds according to an area.Coccossinis and Parparis [2000] describes some indexes which are less used namely:tourist comfort index based on a formula which distinguishes the quality between differenttypes of accommodation using certain criteria, the concentration index which is anattempt to determine the degree of concentration of tourist activity as well as the attractivenessindex, derived by comparing the number of bed nights between international anddomestic tourists. Attractiveness index can be used in order to evaluate a region’s profilein attracting specific types of tourism overall or by category.For the purpose of evaluating spatial diversification of tourism function in Mazoviaregion the complex approach has been used. The tourism function has been researched inthree aspects: tourism features, tourism movement and tourism values.Two variables have been specified in order to evaluate tourist movement in the researchedregion, namely number of guests staying overnight per 100 inhabitants (Schneider’sindex) and number of guests per km 2 (Defert’s index).Variables examining tourism features have been divided in two groups: beds and tourismservices. The amount of beds is referred to an area in km 2 (Charvat’s index) and to100 inhabitants (TFI) Tourist services are phrased in the amount of enterprises in sectionI and in the share of this objects in the total number of enterprises in the county.While examining tourism features of some area, it is important to take into accountenvironmental factors, which give physical and mental relaxation of tourists and anthropogenicones, such as monuments of history, cultural heritage, collections of art but alsosports centers, events, etc. However, while in case of towns cultural heritage, collectionsof art, sports centers, events are the most important, in peripheral areas environmentalfactors attracts tourists the most. Because of limited statistical data the natural values inthis paper have been specified by percentage of an area protected by law and percentageof forests in the county. Anthropogenic values have been described by number of sitesregistered as historic monuments per area unit. The Table 1 shows the schema of variablesused for the purpose of research.Acta Sci. Pol.
Tourism function of Mazovia Voivodship 113Table 1. Variables for tourism function evaluationTabela 1. Zmienne tworzące wskaźnik poziomu rozwoju funkcji turystycznejTouristmovementTourismfeaturesTourismvaluesSpecificationGuestsBedsTouristservicesin the countyNatural valuesAnthropogenicvaluesVariableNumber of guests staying overnight/100 inhabitantsNumber of guests staying overnight/km 2Number of beds/km 2Number of beds/all inhabitants · 100Number of companies registered in section INumber of companiesregistered in section I/number of all companiesPercentage of area in the county protected by lawPercentage of forestsSource: Own elaboration based on Derek [2008].Źródło: Opracowanie własne na podstawie Derek [2008].Number of sites registered as historic monuments per area unitDatasourceGUSGUSGUSKOBiDZRESULTSThe analyses of tourist movement and tourism features in the counties of Mazoviaregion delivered the following findings. Three counties shows Schneider’s index higherthan average for Poland namely Warsaw, Legionowski and Warsaw West poviat. Relativehigh index has also Pruszkowski poviat, whereas the lowest values show: Ostrołęcki(0), Zwoleński (0) and Lipski poviat. Looking at the number of tourists according tokm 2 (Defert’s index), the highest values, much above the national average, appear inthe poviats: Warsaw, Siedlce, Radom, Ostrołęka, Pruszkowski, Płock, and Legionowski.These are mainly towns with big population or poviats situated near Warsaw. The lowestDefert’s index appears again in the counties: Ostrołęcki (0), Zwoleński (0), Lipski andŻuromiński.Analysing he number of beds per km 2 it can be observed that Warsaw, Siedlce, Radom,Ostrołęka, Płock, Legionowski and Pruszkowski have higher values then average,where Warsaw is definitely a leader. Generally, Defert’s index is connected with relativehigh number of beds. However, sometimes poviats show insufficient use of existing accommodationunits (e.g. Węgrowski). Meanwhile the highest rate of beds according to100 inhabitants (TFI) has Łosicki and Legionowski poviat. The lowest values in thistwo, referring accommodation, groups can be observed in Ostrołęcki (0), Żuromiński (0),Przasnyski, Żyrardowski.Examining the amount of tourism enterprises per 1000 inhabitants it can be observedthat poviats: Warsaw, Legionowski, Warsaw West and Piaseczyński are in front ranks.However, taking into account the average for Poland, the share of these companies in theall enterprises in the poviat is not meaningful. It indicates the fact, that Mazovia showslow scale of tourism companies in compression to other polish regions. The lowest num-Oeconomia 10 (1) 2011
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