Decomposition of tourism greenhouse gas emissions: Revealing the dynamics between tourism economic growth,technological efficiency,and carbon emissions

This study proposes an analytical framework for decomposing the national tourism carbon footprint and carbon efficiency to identify the dynamics between economic growth, technological efficiency, and environmental externality. Using the environmentally extended input–output model and decomposition methods, tourism carbon changes are decomposed into the economic factors of total consumption and purchasing patterns, and the production factors of industry input structure and technological improvement. This macro-level approach provides a basis for 1) assessing whether total tourism emissions increase in direct proportion to tourism consumption over time, 2) tracing the underlying determinants and their effects on tourism emissions expansion and eco-efficiency performance, and 3) comparing the carbon performance of the tourism industry against the national average. Based on the example of Taiwan, the results demonstrate that we are a long way from the goal of using the technological efficiencies of production to offset tourism-based carbon emissions.     

The dynamics of tourism’s carbon footprint in Beijing,China

Abstract

Beijing is an important hub for global tourism, but the extent of tourism’s contribution to Beijing’s carbon footprint remains unclear. We integrated an environmentally extended multiregional input–output model and the tourism satellite account in a study to estimate the dynamics of Beijing’s tourism-related carbon footprint in the post-financial crisis period. Our findings indicate that from 2007 to 2012, whereas the carbon footprint of inbound tourists in Beijing steadily decreased, that of domestic tourists increased. The composition of carbon footprints for the consumption activities of inbound and domestic tourists differed substantially. We also traced the spatial distribution of carbon sources associated with tourism consumption in Beijing. In light of our findings, we offer recommendations to target the adoption of low-carbon consumption patterns by domestic tourists, and energy optimization of service suppliers by increasing energy use efficiency and the renewable energy ratio. In addition, we recommend that public and government should seek to lower energy costs and reduce carbon emissions throughout the life cycle of commodities. We conclude that the government and tourism authorities should actively promote carbon and wider environmental awareness, and that producers must seek to improve the efficiency of their energy use by reducing carbon emissions at source.     

Ecological footprint analysis of road transport related to tourism activity: The case for Lanzarote Island

This work tries to evaluate road transport usage in Lanzarote Island and its implications for sustainable tourism development. The methodology followed here is the ecological footprint indicator. Its evaluation is based on projections of trip matrix estimated for Lanzarote Island. This study allows us to determine, in an approximate way, the environmental impact (that is, the contribution to climate change) of car usage on the island. Besides, it permits to extract some important conclusions about the trade-off existing between the need of individual mobility and tourism development in Lanzarote Island.     

Blockchain technology framework: Current and future perspectives for the tourism industry

Blockchain's ability to increase the level of disintermediation in tourism represents this technology's most effective influence on the industry. The advent of online travel agencies has changed tourism's market structure by transferring power from suppliers to consumers. This paper aims to develop a blockchain-based framework for the tourism industry by employing a qualitative method that uses the semi-structured interview to determine how domain experts conceive the future of intermediaries were the tourism industry to adopt blockchain technology. The results show that when taking into account blockchain's influence on businesses, blockchain is considered an appropriate technology for eliminating mediators from the tourism industry's supply chain and also for banning new mediators from gaining access to this industry, thereby removing intermediaries from the tourism market.     

Quantifying Spanish tourism's carbon footprint: the contributions of residents and visitors: a longitudinal study

This paper develops and explains an input–output model to quantify the carbon footprint linked to residents' and visitors' tourist consumption in the Spanish economy between 1995 and 2007, thus offering a rare longitudinal review of a national carbon footprint. Two measures are calculated: a domestic one similar to the producer responsibility criterion and a total measure that includes imported intermediate and final goods, similar to the consumer responsibility measure. The important role of tourism in Spain explains why its domestic carbon footprint represented 10.6% of total CO₂ emissions in 2007. Visiting tourists represented 47% of this figure, households 36%, business tourism represented 14% and public administration expenditures 3%. By industry, transport (26%) was positioned as the highest emitter in 2007, with hotels and restaurants the second (21%) (benefitting indirectly from energy and environmental efficiency improvements over the period). The Spanish reliance on imported oil products and the growing importance of foreign-based air services has caused the total carbon footprint of tourism to increase by more than 100%. Therefore, climate change mitigation plans must include imports, and action must take place through the whole global production chain and in the transport sector, particularly air transport. Future mitigation policies are discussed.     

From vulnerability to transformation: a framework for assessing the vulnerability and resilience of tourism destinations

Tourism is a key driver of global socio-economic progress. However, its sustainability is at risk from multiple shocks and hazards that threaten livelihoods. Surprisingly little is known about the complex drivers of destination vulnerability, leading to the creation and application of ineffective resilience-building solutions. The paper presents the Destination Sustainability Framework (DSF) designed to assess destination vulnerability and resilience, and support successful resilience-building initiatives. Holistic in nature, the DSF comprises: (1) the shock(s) or stressor(s); (2) the interconnected dimensions of vulnerability – exposure, sensitivity, and system adaptiveness; (3) the dynamic feedback loops that express the multiple outcomes of actions taken (or not); (4) the contextualised root causes that shape destinations and their characteristics; (5) the various spatial scales; and (6) multiple timeframes within which social-ecological change occurs. This innovative framework is significant because it's the first framework to chart the complex manifestation of vulnerability and resilience in tourism destinations. Further, it brings tourism sustainability research in line with wider debates on achieving sustainability within the dynamic coupled human–environment system, doing so through the inclusion of insights from contemporary systems approaches, including chaos–complexity theory, vulnerability approaches, sustainability science, resilience thinking, along with the geographies of scale, place and time.     

A piecewise linear approach to modeling and forecasting demand for Macau tourism

In this paper, we construct and use a piecewise linear method to model and forecast, on a monthly basis, the demand for Macau tourism. Data over the period January 1991–December 2005 and a seasonally adjusted series for tourism demand are used. The study examines 4 forecasting horizons ranging from 6 to 24 months in advance. Mean absolute percentage errors and root mean square errors are adopted as criteria for evaluating the accuracy of the forecasting exercises. Finally, the forecasts of piecewise linear model are compared with those of autoregressive trend model, seasonal autoregressive integrated moving average and its arch-rival fractionally integrated autoregressive moving average models. The piecewise linear model is more accurate than the three benchmark models tested and the improvement is practically significant.     

Fuzzy Rasch model in TOPSIS: A new approach for generating fuzzy numbers to assess the competitiveness of the tourism industries in Asian countries

This study proposes a novel approach, the Fuzzy Rasch model, which combines Item Response Theory (IRT) and fuzzy set theory. This paper applies the Fuzzy Rasch model in Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to analyse the Tourism Destination Competitiveness (TDC) of nine Asian countries: China, Hong Kong, Japan, Korea, Malaysia, Singapore, Taiwan, Thailand and the Philippines. The study was conducted in 2009 using 6 criteria and 15 indices. The results demonstrate the feasibility of applying the Fuzzy Rasch model in TOPSIS to analyse TDC in Asian countries. In addition, the proposed model also provides an effective means of applying the MCDM method to study TDC. Furthermore, in 2009, the Asian countries were ranked from most to least competitive as follows: China, Japan, Hong Kong, Malaysia, Thailand, Singapore, Taiwan, Korea and the Philippines.