culture, nature and sustainable tourism development: a space-time analysis on european regions

Culture, Nature and Sustainable Tourism Development: a space-‐(me analysis on European regions

João Romão University of Algarve Towards opera9onalising UNESCO Recommenda9ons on Historic Urban Landscape Naples, March 2–3, 2015

New Tools for Planning Sustainable, Safe, Resilient and Sustainable Ci9es Naples March 2015

João Romão Culture, Nature and Sustainable Tourism Development: a space-‐9me analysis on European regions

Despite the close rela9on between tourism and the territory, the applica9on of spa9al analysis methods in tourism is not abundant in the literature. The recent developments in the analysis of space-‐?me models, the existence of geo-‐referenced informa9on and the availability of suitable soQware tools create new opportuni9es for studying the role of space in tourism ac9vi9es. An exploratory spa9al data analysis is developed and a space-‐9me panel model is computed in this work in order to analyse the rela9ons between tourism demand and the existence of infrastructures, cultural assets and natural resources in European regions, Spa?al effects have been clearly iden?fied.

Abstract

Tourism is a place oriented ac?vity, where territories interact with each others. Natural resources and cultural heritage are essen9al for the sustainable development of tourism. The crea9on of a differen?ated experience in each tourism des9na9on depends on the ability to integrate these local and specific assets into the tourism supply: unique experiences can only be created if they are based on the local characteris9cs of the territory, once they are not possible to imitate in other places. This exploita9on of local resources raises the ques9on of the poten9al nega9ve impacts on the territories and establishes a link between the concepts of compe??veness -‐ the ability to compete in global markets for the aUrac9on of tourists -‐ and sustainability -‐ the ability to preserve local resources in the long run. “Environmental paradox”: the produc9on of tourism experiences depends on the exploita9on of local natural resources and, in the long run, it also depends on its preserva9on. The same can be applied to cultural heritage. In the last years, most of the interna9onal tourism related organiza9ons (including UNESCO) have proposed orienta9ons for a sustainable process tourism development.

1. Introduc?on



Analysis of the importance of cultural and natural resources for regional tourism demand. Test and evalua9on of spa?al effects among the regions. Presenta9on of overall data (252 NUTS 2 European regions; 2003-‐2012). Exploratory spa?al data analysis (237 NUTS2 European regions). Space-‐?me panel model. All the NUTS 2 regions from Austria, Belgium, Bulgaria, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Italy, Latvia, Lithuania, Luxemburg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain and United Kingdom.

Introduc?on



Tourism demand -‐ Nights spent at tourist accommoda9on establishments in 2012 (millions)

Tourism demand, culture and nature: data and variables

Importance of South European regions (West Mediterranean)



Tourism demand -‐ Nights spent at tourist accommoda9on establishments (growth between 2003 and 2012)


Importance of Eastern European regions (West Mediterranean)



Tourism demand -‐ Nights spent at tourist accommoda9on establishments (growth between 2003 and 2012)


Importance of urban areas (Paris, Barcelona, London, Berlin)



Regional cultural assets -‐ number of sites classified as World Heritage by UNESCO


Importance of South European regions (West Mediterranean)



Regional natural resources -‐ percentage of the territory in Natura 2000


Importance of South European regions



Regional natural resources and cultural assets


Importance of South European areas



logNIT it = ß0 + ß1 logBEDS it + ß2 HERIT it + ß3 NAT it + uit

Parameters Estimate Std. Error t-value Pr(>|t|) Significance

Intercept 10.1960

0.2089

48.8098 < 2.2e-16 0.001

LogBeds 0.4553

0.0190

24.0049 < 2.2e-16 0.001

NAT 0.0034 0.0010

3.4350 0.0006 0.001

HERIT 0.1063

0.0108

9.8615 < 2.2e-16 0.001

!

Despite de very high significance of all the parameters es9mated, the rela9vely low score obtained for the R-‐Squared (0.26) suggests that the es9ma9ons can be improved introducing spa?al effects.

Posi?ve rela?on between tourism demand and all the independent variables.

Panel regression without spa?al effects



Moran I tests for spa?al autocorrela?on 1st and last years of observa9ons for each variable

The results obtained reveal the existence of spa?al correla?on in all the variables (z-‐scores above the threshold of 1.96, for 5% significance level.

Territory: Exploratory Spa?al Data Analysis



Local Indicators of Spa?al Autocorrela?on cluster distribu9on based on the local G sta9s9cs


Cluster of high values (red) in Southwest European regions

Cluster of low values (blue) in Eastern European regions

Tourism demand (nights spent in accommoda9on establishments in 2012)





Cluster of high values (red) in Southwest European regions

Clusters of low values (blue) in Central / Northern European regions

Cultural resources (cultural sites classified by UNESCO in 2012)





Cluster of high values (red) in Southern European regions

Clusters of low values (blue) in Northern European regions

Natural resources (percentage of the territory in Natura 2000 in 2011)



Local Indicators of Spa?al Autocorrela?on Bivariate analysis rela9ng tourism demand with each of the independent variables


Clusters of high values for cultural assets and low tourism demand (pink) in Eastern European regions

Clusters of high values for both (red) in South Western European regions

Tourism demand and cultural heritage

“Irregular” spa?al paUerns.



Local Indicators of Spa?al Autocorrela?on Bivariate analysis rela9ng tourism demand with each of the independent variables


Clusters of high values for natural assets and low tourism demand (pink) in Eastern European regions

Clusters of high values for both (red) in South Western European regions

Tourism demand and natural resources

High number of “spa?al outliers” (high value for one variable and low for the other)



logNIT it = ρWYit + ß0 + ß1 logBEDS it + ß2 HERIT it + ß3 NAT it + uit uit = λWuit + εit W is a weights-‐matrix, defining the impacts of each region on its neighbors; (neighborhood defined by con9guity, level 2); ρ is the spa9al autoregressive coefficient (spa9al effects on the dependent variable) λ is the spa9al autocorrela9on coefficient (spa9al effects on the error term) AVer specifying the necessary tests, a model with both types of spa?al effects has been computed.

Panel regression with spa?al effects



Posi9ve overall spa?al effects (error variance + spa9al auto-‐regressive coefficient)

Posi?ve rela?on between tourism demand and all the independent variables, but not significant for natural resources.

Panel regression without spa?al effects

Parameters Estimate Std. Error t-value Pr(>|t|) Significance

Intercept 14.7480

0.2738

53.8551 < 2.2e-16 0.001

LogBeds 0.3996

0.0229

17.4585 < 2.2e-16 0.001

NAT 0.0002 0.0012

0.1783 0.86

HERIT 0.0781

0.0110

7.0969 1.3e-12 0.001

Spatial auto-regressive coefficient -0.2478 0.0260 -3.2941 0.0009 0.001

Error variance (spatial) 0.6535 0.0386 16.947 < 2.2e-16 0.001

Error variance (non spatial) 16.4451 1.9384 8.484 < 2.2e-16 0.001

!



Confirma?on of the poten?al of spa?al analysis for tourism studies. Although this kind of methodology has few applica9ons in the field of tourism, the results show the existence of spa9al paUerns in tourism demand and its determinants. The overall data presented in the beginning of this work revealed that tourism in South European regions – where natural resources play a decisive role – is s?ll very important in the European context. Nevertheless, this informa9on also showed that urban tourism (at least in some major ci9es) and the Eastern side of Europe have registered higher growth rates along the last decade, sugges9ng a shiV in travel mo?va?ons and spa?al paUerns.

Discussion



The exploratory spa?al analysis clearly revealed the existence of spa?al effects for regional tourism aUrac?veness and also for the determinants of tourism demand. The iden9fied spa9al effects are, in general, more clear in the South European regions. Regional aUrac?veness is related, not only to their natural and cultural resources, but also to the resources available in the neighbour regions This has clear implica9ons in terms of tourism promo9on and infrastructure planning (transports, accommoda9on, etc). The spa9al effects iden9fied in the space-‐?me model reveal the existence of:

-‐ a compe??ve process expressed in the nega9ve value of the spa9al autoregressive coefficient, showing that tourism demand in one region can have nega9ve consequences in the con9guous regions;

-‐ posi?ve impacts of unmodelled effects expressed in the spa9al error variance parameter (almost three 9mes higher);

-‐ overall posi?ve spa?al effects.

Discussion



Local resource management, promo?onal strategies, transport systems and accommoda?on provision can be more efficiently planned if there is some collabora?on among clusters of regions with similar characteris?cs, even if they do not belong to the same country. The analyses provides sa9sfactory results for the South European regions. For the North European regions, other kind of informa9on related to natural and cultural assets can provide more accurate results in terms of spa9al impacts, although there is not enough comparable informa9on at interna9onal level, at this moment.

Discussion



Thank you for your attention!



culture, nature and sustainable tourism development: a space-time analysis on european regions

Science

abstract tourism

tourism supply

tourism des9na9on

tourism ac9vi9es

analysis of space

european regions analysis

planning sustainable

sustainable ci9es naples