Ranking tourism market performance in EMU countries: results of PROMETHEE – GAIA approach





tourism, performance, European Monetary Union, PROMETHEE – GAIA model


Using data from 19 countries of the European Monetary Union (EMU), this paper examines the nature of tourism performance and the ranking of countries according to given parameters in tourism in the period 2012-2017. As tourism cannot be analyzed as an isolated scientific discipline, it is necessary to use a multidimensional and multicriteria approach when studying and researching this field. For this reason, this paper implements a simple methodology for measuring tourism performance in EMU countries using the multicriteria PROMETHEE – GAIA decision model. The paper will, through the analysis of 8 parameters important for the development and evaluation of the tourism industries (number of foreign tourists, number of domestic tourists, quantity of hotel accommodation, cost of living, air pollution, population density, length of railway and number of airports), rank the mentioned countries and provide a deeper analysis of individual parameters. For the entire period of observing and reviewing the performance of the tourism industry, the results of the paper will outline the performance evaluation as well as policy recommendations and conclusions for further consideration and analysis.


Andreopoulou, Z. S., Tsekouropoulos, G., Koliouska, C., & Koutroumanidis, T. (2014). Internet marketing for sustainable development and rural tourism. International Journal of Business Information Systems (IJBIS), 16(4), 446-461. https://doi.org/10.1504/IJBIS.2014.063931

Antanasijevi?, D., Pocajt, V., Risti?, M., & Peri?-Gruji?, A. (2017). A differential multi-criteria analysis for the assessment of sustainability performance of European countries: Beyond country ranking. Journal of cleaner production, 165, 213-220. https://doi.org/10.1016/j.jclepro.2017.07.131

Assaf, G., & Tsionas, E. (2015). Incorporating destination quality into the measurement of tourism performance: A Bayesian approach. Tourism Management, 49, 58-71. https://doi.org/10.1016/j.tourman.2015.02.003

Brans, J. P. (1982). 'L'ingéniérie de la decision; Elaboration d'instruments d'aide à la décision. Méthode PROMETHEE' [The engineering of the decision; Development of decision support tools. PROMETHEE method]. In R. Nadeau and M. Landry (Eds.), L’aide ? la décision: Nature, Instruments et Perspectives d’Avenir (183-213). Canada, Québec: Presses de l’Université Laval.

Brans, J. P., Mareschal, B., & Vincke, P. (1984). PROMETHEE: A new family of outranking methods in multi-criteria analysis. In J. P. Brans (Ed.), Operational Research '84 (pp. 447-490). North-Holland, Amsterdam.

Brans, J. P., Mareschal, B. & Vincke, P. (1986). How to decide with PROMETHEE GAIA Software (pp. 1-5). Brussel: ULB and VUB Brussels Universitie, Vrije Universiteit Brussel.

Brans, J. P., & Vincke, P. (1985). A preference ranking organisation method: The PROMETHEE method for MCDM. Management Science, 31(6), 647-656.

Corbet, S., O’Connell, J., Efthymiou, M., Guiomard, C., & Lucey, B. (2019). The impact of terrorism on European tourism. Annals of Tourism Research, 75, 1-17. https://doi.org/10.1016/j.annals.2018.12.012

Despotovi?, D., & Durkali?, D. (2017). Analysis of budget deficit in the candidate countries for EU membership. Serbian Journal of Management, 12(2), 237-253. https://doi.org/10.5937/sjm12-14122

Eurostat. (2019a). Number, 1 night or over, outbound. Retrieved October 18, 2019 from http://appsso.eurostat.ec.europa.eu/nui/submitViewTableAction.do

Eurostat. (2019b). Number, 1 night or over, domestic. Retrieved October 18, 2019 from http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=tour_dem_tntot&lang=en

Eurostat. (2019c). Number of establishments, bedrooms and bed-places. Retrieved October 18, 2019 from http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=tour_cap_nat&lang=en

Eurostat. (2019d). Comparative price levels. Retrieved October 18, 2019 from http://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&plugin=1&language=en&pcode=tec00120

Ferrante, M., Magno, L., & De Cantis, S. (2018). Measuring tourism seasonality across European countries. Tourism Management, 68, 220-235. https://doi.org/10.1016/j.tourman.2018.03.015

Fura, B., Wojnar, J., & Kasprzyk, B. (2017). Ranking and classification of EU countries regarding their levels of implementation of the Europe 2020 strategy. Journal of cleaner production, 165, 968-979. https://doi.org/10.1016/j.jclepro.2017.07.088

Gavrilovi?, Z., & Maksimovi?, M. (2018). Green innovations in the tourism sector. Strategic Management, 23(1), 36-42. https://doi.org/10.5937/StraMan1801036G

Gil Pareja, S., Llorca Vivero, R., & Martínez Serrano, J. A. (2007). The effect of EMU on tourism. Review of International Economics, 15(2), 302-312. https://doi.org/10.1111/j.1467-9396.2006.00620.x

Jovanovi?, S. (2019). Green hotels as a new trend in the function of sustainable development and competitiveness improvement. Economics of Sustainable Development, 3(1), 1-7. https://doi.org/10.5937/ESD1901001J

Kova?i?, M. (2010). Selecting the location of a nautical tourism port by applying PROMETHEE and GAIA methods case study–Croatian northern Adriatic. Promet-Traffic & Transportation, 22(5), 341-351. https://doi.org/10.7307/ptt.v22i5.199

Laki?evi?, M., & Durkali?, D. (2018). Measurement of Tourism Market Performance in EU Countries: Results of Promethee-Gaia Approach. In D. Cvijanovi? et al. (Eds.). Tourism in Function of Development of the Republic of Serbia – ?ourism in the Era of Digital Transformation. Thematic Proceedings II (pp. 99-116). Vrnja?ka Banja: Faculty of Hotel Management and Tourism in Vrnja?ka Banja.

Mendola, D., & Volo, S. (2017). Building composite indicators in tourism studies: Measurements and applications in tourism destination competitiveness. Tourism Management, 59, 541-553. https://doi.org/10.1016/j.tourman.2016.08.011

Michailidis, A., & Chatzitheodoridis, F. (2006). Scenarios analysis of tourism destinations. Journal of Social Sciences, 2(2), 41-47.

Mir?eti?, V., Vukoti?, S., & Cvijanovi?, D. (2019). The concept of business clusters and its impact on tourism business improvement. Economics of Agriculture, 66(3), 851-868. https://doi.org/10.5937/ekoPolj1903851M

Obradovi?, S., Fedajev, A., & Nikoli?, ?. (2012). Analysis of business environment using the multi-criteria approach: Case of Balkan's transition economies. Serbian Journal of Management, 7(1), 37-52. https://doi.org/10.5937/sjm1201037O

Pestana, B., Laurent, B., Nicolas, P., Elisabeth, R., Bernardin, S., & Assaf, A. (2011). Performance of French destinations: Tourism attraction perspectives. Tourism Management, 32, 141-146. https://doi.org/10.1016/j.tourman.2010.01.015

Ranjan, R., Chatterjee, P., & Chakraborty, S. (2016). Performance evaluation of Indian states in tourism using an integrated PROMETHEE-GAIA approach. Opsearch, 53(1), 63-84. https://doi.org/10.1007/s12597-015-0225-6

Seabra, C., Reis, P., & Abrantes, J. (2020). The influence of terrorism in tourism arrivals: A longitudinal approach in a Mediterranean country. Annals of Tourism Research, 80, 102811. https://doi.org/10.1016/j.annals.2019.102811

Silva, E., Ghodsi, Z., Ghodsi, M., Heravi, S., & Hassani, H. (2017). Cross country relations in European tourist arrivals. Annals of Tourism Research, 63, 151-168. https://doi.org/10.1016/j.annals.2017.01.012

Silva, F., Herrera, M., Rosina, K., Barranco, R., Freire, S., & Schiavina, M. (2018). Analysing spatiotemporal patterns of tourism in Europe at high-resolution with conventional and big data sources. Tourism Management, 68, 101-115. https://doi.org/10.1016/j.tourman.2018.02.020

Šuši?, V., & ?or?evi?, D. Ž. (2019). Modern tendencies of international tourism development. Ekonomika, 65(2), 27-37. https://doi.org/10.5937/ekonomika1902027S

Teki?, T. (2018). Development of B2C e-commerce in the European Union countries. Anali Ekonomskog fakulteta u Subotici, 54(40), 171-182. https://doi.org/10.5937/AnEkSub1840171T

United Nations World Tourism Organization (UNWTO). (2017). UNWTO Annual Report 2017. Retrieved October 28, 2019 from https://www.e-unwto.org/doi/pdf/10.18111/9789284419807

United Nations World Tourism Organization (UNWTO). (2019). International Tourism Highlights, 2019 Edition. Retrieved November 14, 2019 from https://www.e-unwto.org/doi/pdf/10.18111/9789284421152

World Aero Data. (2019). Airports by Country. Retrieved October 18, 2019 from http://worldaerodata.com/countries/

World Bank. (2019a). PM2.5 air pollution, annual exposure (micrograms per cubic meter). Retrieved October 18, 2019 from https://data.worldbank.org/indicator/EN.ATM.PM25.MC.M3

World Bank. (2019b). Population density (people per sq. km of land area). Retrieved October 18, 2019 from https://data.worldbank.org/indicator/EN.POP.DNST

World Bank. (2019c). Rail lines (total route-km). Retrieved October 18, 2019 from https://data.worldbank.org/indicator/IS.RRS.TOTL.KM?page=6




How to Cite

Durkalic, D. ., Furtula, S. ., & Borisavljevic, K. . (2019). Ranking tourism market performance in EMU countries: results of PROMETHEE – GAIA approach. Hotel and Tourism Management, 7(2), 67–76. https://doi.org/10.5937/menhottur1902067D



Original Scientific Papers