Study on Measurement of Green Productivity of Tourism in the Yangtze River Economic Zone, China

Abstract

This paper introduces energy consumption and carbon emission into the analysis framework of the green productivity of tourism. By comparing and analyzing the two main methods used to evaluate the energy consumption and carbon emission estimations of tourism, namely, the "top-down" and "bottom-up" method, and considering the availability of data, the "bottom-up" method was adopted to evaluate the energy consumption and carbon emissions of tourism in the Yangtze River Economic Zone (YREZ). Then, using the Malmquist-Luenberger (ML) index in the super-efficiency data envelopment analysis (DEA) model, the green productivity of the tourism in 11 provinces and cities in the YREZ from 2006 to 2015 was measured. The empirical results show that:(1) The energy consumption and carbon emissions of tourism in the YREZ have increased steadily over the past 10 years, which has caused a certain degree of pollution to the environment, indicating that tourism is no longer a "smoke-free industry"; (2) there are significant provincial differences between the energy consumption and carbon emissions of tourism in the YREZ, with Shanghai always ranking first, while Guizhou and Yunnan ranks last, which represents that the tourism economic development level is positively correlated with the tourism energy consumption and carbon emissions; (3) the green productivity of tourism in the YREZ shows a fluctuating increasing trend in the past 10 years, and technological progress has become the main reason for its growth in green productivity; and (4) the green productivity of tourism in 11 provinces and cities in the YREZ can be divided into three types: Progressive type of tourism green development, stagnant type of tourism green development, and declining type of tourism green development. Consequently, different types of provinces should explore effective dependency paths based on their own conditions.

The Robust Causal Relationships Among Domestic Tourism Demand, Carbon Emissions, and Economic Growth in China

“…Therefore, the carbon dioxide emissions of the tourism industry should first be measured when one is analyzing the effect of tourism on carbon dioxide emissions. There are two main methods for measuring carbon dioxide emissions in the tourism industry: the bottom-up method (Tang & Abosedra, 2014), such as the input-output method (Zhong et al, 2015), and the top-down method (Liu et al, 2018). A large number of studies have gone on to investigate the relationships among tourism, carbon emissions, and economic growth.…”

A Literature Review of Contribution of Green Productivity to the Success of Business Performance

“…In the end, all these three spheres which were identified in the GP contribution areas such as Productivity, Financial and environmental will lead to maximizing profits which are considered as one of the objectives of the business organizations by making Competitive advantage in the marketplace. GP will contribute towards non-quantitative aspects such as obtaining environmental certificates such as ISO 14001 standards and other green labels which will improve the goodwill of the organization [15][16][17][18][19][20][21][22][23][24][25][26].…”

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

“…The specific recommendations are as follows. (1) Establish a mechanism to reward green technology R&D achievements in the tourism industry, and encourage industry-university-research cooperation and international exchange (Liu et al, 2018a). ( 2) Strengthen the construction of new urbanization, promote the agglomeration of tourism talent and green technologies and the optimization of industrial structure to create a favorable environment for promoting green tourism growth.…”

“…These studies incorporated environmental constraints into efficiency evaluation models, which not only helps to consider the balanced relationship between tourism economic growth and ecological environmental protection, but also realizes a static evaluation of the development quality in the tourism industry under the current production frontier. With the gradual application of the Malmquist–Luenberger (ML) productivity index in the tourism industry, some scholars have attempted to combine DEA with the ML productivity index to examine the evolution of TGP in China and the Yangtze River Economic Zone in two adjacent periods from a dynamic perspective and further decomposed the changes into technical progress and technical efficiency changes (Wang et al, 2020; Liu et al, 2018a; Li et al, 2020). Thus, the application of ML index initially realized the dynamic evaluation of TGP under the neighboring production frontier and provided an important direction for the improvement of TGP evaluation methods afterward.3.…”