Analyzing Efficiency of Tourism Industry in Korea using DEA and Malmquist Productivity Index : 2010-2017 The census on Basic Characteristics of Tourism Establishments

Joun, Hyojae

doi:10.31336/jtlr.2019.4.31.4.425

Cited by 1 publication

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“…For Asia, a number of studies have emerged over the last decade adopting this kind of approach, prominent among which is the application of Honma and Hu (2012), who perform a double efficiency analysis, comparing results from the stochastic frontier model and DEA on a sample of hotels in Japan; and Oukil et al (2016) who posit a conditioned efficiency model analysing a sample of hotels in Oman. More recently, Joun (2019) worked with Malmquist indices in the tourist industry in Korea. Finally, although at a global scale, Mendieta-Peñalver et al (2018) analysed international hotel chains.…”

Section: Literature Reviewmentioning

confidence: 99%

Clustering and country destination performance at a global scale: Determining factors of tourism competitiveness

2021

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Our aim is to evaluate the efficiency of tourist destinations at a global scale, considering 140 countries and drawing on World Economic Forum 2019 data. The approach follows three stages. First, we try to solve the problem of sample heterogeneity through cluster analysis to obtain homogeneous groups of countries. Second, we apply data envelopment analysis to evaluate countries’ efficiency as tourist destinations, considering a territorially based virtual production function which optimizes the flow of revenue from international tourism grounded on a set of inputs such as accommodation capacity, employment of tourist sector and volume of tourist arrivals. Finally, we identify which external factors might determine tourism efficiency by using bootstrap truncated regression analysis. We obtain two groups of countries which evidence differential levels of competitiveness. Rather than natural resources, cultural heritage in a broad sense seems to act as factor that enhances tourism efficiency.

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