Productivity in the Hotel Industry: An Order-α Malmquist Productivity Indicator

Abstract

In the literature, it is highlighted that the deterministic nature of the data envelopment analysis–based productivity measures makes them sensitive to sample characteristics. However, the majority of the related empirical studies ignore the potential bias in their data envelopment analysis–based productivity estimations. This article illustrates how the order-α quantile-type estimators can be applied to construct a robust version of the Malmquist productivity indices. Using the order-α estimators, we construct a Malmquist productivity index alongside with two well-known decompositions. The proposed productivity indicator is less sensitive to potential outliers and extreme values. Then, as an illustrative example, we apply the quantile-type productivity index on a sample of 270 hotels operating in the Balearic Islands over the period 2004-2013. The productivity levels alongside with their components are analyzed during the global financial crisis period.

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

“…Data envelopment analysis (DEA), a commonly used data-driven tool, has been used by many scholars to evaluate the efficiency of the tourism industry (Chaabouni, 2019; Li and Liu, 2022) and business performance of tourism enterprises (Köksal and Aksu, 2007; Hwang and Chang, 2003). The combination of data envelopment analysis technique and the Malmquist index can be further used to evaluate the evolution of TTFP (Tzeremes and Tzeremes, 2021; Assaf, 2011; Zuo and Bao, 2008). However, current systematic research on the TGP still lacks sufficient attention and may, to some extent, ignore the changes in the intertemporal production frontier and undesirable outputs of the tourism industry.…”

Analysing the linkage between total factor productivity and tourism growth in Latin American countries

“…Moreover, TFP accounts for the degree of technological development, as a result, it has a direct impact on economic growth but as an exogenous factor. Lastly, based on endogenous growth theories, TFP is a crucial element of economic growth via technological change which is a vital component of TFP (Romer, 1986; Lucas, 1988; Tzeremes and Tzeremes, 2021). Thus, either neoclassical or endogenous growth models state that the TFP index may increase economic growth in the long run period.…”