A Stochastic Frontier Approach to Assessing Total Factor Productivity Change in China’s Star-Rated Hotel Industry

Abstract

Using a stochastic frontier analysis approach and a flexible translog production function considering neutral technological progress, this study assesses technical efficiency change, technological change, and scale change, and further measures the total factor productivity (TFP) change and its convergence of China’s star-rated hotel industry in 31 provinces, municipalities, and regions from 2001 to 2015. The results show that the TFP change of China’s star-rated hotel industry was generally favorable and boosted by both the technical efficiency change and technical change; nevertheless, the scale change hindered and largely caused fluctuations in the TFP change. From a regional economic perspective, the TFP change of the star-rated hotel industry in most of the eight comprehensive economic regions examined was rather stable. While few comprehensive economic regions existed absolute convergence, all of the regions showed significant conditional convergence except for the Eastern Coastal region.

The Impact of Covid-19 on Hotel Efficiency in Spain: the Case of Barcelona

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“…Nevertheless, new methods, in terms of frontier models, have been developed and came to complement the most common and classical non-frontier models. There are four frontier methods: thick frontier approach (TFA), distribution free approach (DFA), stochastic frontier approach (SFA) and data envelopment analysis (DEA) (Chen, 2007;Neves and Lourenço, 2009;Tumer, 2010) from which literature distinguishes as principal ones to analyse performance SFA and DEA (Liu and Tsai, 2021;Chen 2007;Honma and Hu, 2012). Both of them use a sample of organizations to construct Efficient Production…”

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Evaluating the tourism green productivity and its driving factors in the context of climate change

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