Benchmarking International Tourism Destinations

Abstract

Industry productivity growth measures the contribution to the growth of the economy that an industry delivers. Benchmarking international tourism destinations in respect of their productivity is often avoided due to the difference in tourism characteristics between destinations. This paper introduces a novel approach to destination benchmarking that is theoretically motivated to account for this problem. The benchmarking framework proposed uses separate groups of countries with similar characteristics to construct a metafrontier that envelops these groups, and as such represents the world tourism industry. The paper confirms that ignoring heterogeneity (that is, differences in destination characteristics) can lead to bias in the productivity rankings of different countries. The results show that North American and European countries lead the world tourism industry in terms of productivity growth, while African countries lag behind. On average, most African countries are also not catching up with the world tourism industry. The outcome is development of a robust and comprehensive benchmarking methodology that can provide governments and national tourism offices with an accurate assessment of their international tourism performance.

Productivity Evaluation of Tourism and Culture for Sustainable Economic Development: Analyzing South Korea’s Metropolitan Regions

“…The evaluation of the tourism industry's performance has been discussed since the 1990s [46]. Many different methodological approaches have been constructed, such as the stochastic translog frontier [47], Luenberger productivity indicator [46,48], return on asset and return on investment [49], Malmquist frontier index [50], the DEA [51][52][53][54][55][56][57][58][59], and MPI [11,35,36,[60][61][62]. However, traditionally, DEA has been the most popular approach to evaluate operation and management efficiency and has focused primarily on small-scale hospitality and tourism businesses like hotels [54,55,63], restaurants [57][58][59], and travel agencies and departments [53,64].…”

Evaluating the performance drivers of French ski resorts: A hierarchical approach

“…DEA has been used extensively to examine the performance and benchmarking in the tourism sector (Assaf & Dwyer, 2013;Assaf & Josiassen, 2016). However, few contributions using the hierarchical category DEA model are available in the literature.…”

ESM-VT Yöntemi ile Uluslararası Destinasyonların Turizm Sektörü Etkinliğinin Değerlendirilmesi (Evaluation of the Tourism Sector Effectiveness of International Tourism Destinations with ESM-VT Method)

“…(Pestana, et al, 2011;Cracolici, et al, 2008;Luo, et al, 2014;Barros & Alves, 2004). Studies evaluating the effectiveness and efficiency of the tourism sector at the macro level are rather limited (Assaf & Dwyer, 2013;Hadad, et al, 2012). However, the efficiency of the tourism sector of a country in long term (especially the ability of the sector in achieving maximum output from a given input set) significantly affects the international market share and profitability (Hadad, et al, 2012, p. 932).…”

“…For this reason, the input sources and economic outputs of the tourism production-consumption process should be analyzed by comprehensive destination efficiency analyses (Fuchs, 2004). At the same time, efficiency analyses provide quantitative information about the sector and thereby reduce the subjectivity by comparing the the performance of those in the sector (Assaf & Dwyer, 2013).…”