By Akimasa Fujiwara (auth.), Akimasa Fujiwara, Junyi Zhang (eds.)
This ebook goals to supply a very good figuring out of and viewpoint on sustainable delivery in Asia through targeting financial, environmental, and social sustainability. it really is broadly stated that the present state of affairs and traits in shipping should not consistently sustainable in Asia, due partially to the fast-growing economic climate and the staggering pace of urbanization in addition to least-mature governance. As crucial study fabric, the ebook presents robust aid for coverage makers and planners by way of comprehensively protecting 3 teams of recommendations, characterised by way of the phrases “avoid” (e.g., city shape layout and regulate of vehicle ownership), “shift” (e.g., setting up accomplished transportation structures and extending public transportation structures for either intracity and intercity travel), and “improve” (e.g., redecorate of paratransit process, low-emission automobiles, clever transportation platforms, and eco-life). those are elaborated within the ebook along attention of the uncertainty of coverage results sooner or later. The booklet can also be beneficial for students and scientists as a result of the assorted methodologies provided and proposed herein. between these are the four-step version with complete suggestions mechanisms, the bi-level programming version with sustainability objectives, info envelopment research and stochastic frontier research methods, structural equation types, discrete and/or non-stop selection types, copula-based types, survival versions, and using hazard types with temporary reminiscence. utilizing facts amassed from greater than ten Asian towns, together with these in either constructed and constructing countries, the pathway to sustainable shipping in Asia progressively turns into clear.
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Extra info for Sustainable Transport Studies in Asia
This justifies introducing state dependence. All other parameters are significant and have the expected signs. These results suggest the validity of the proposed model structure. However, the model is not sufficiently accurate. There may be several reasons for this. The limited sample size (46 cities in this study) can be regarded as the major reason. Because it is usually difficult to collect the relevant data, especially time series data at the city level, more efficient estimation methods should be developed for small sample sizes.
Cluster analysis was used to identify the groups in this study. The Euclidean distance was calculated on the basis of infrastructure development, such as the road length per capita and the distance travelled by PT per capita. 3). Note that for the reason described in the following section, developing cities (defined as cities with GDPs of less than $10,000 per capita at each time point) are not included in the reference sets. Investment in the transport infrastructure is irreversible because it is not realistic to assume that developed cities that have invested well in their transport infrastructure would reduce their mobility level as occurs in developing cities, even if developing cities are identified as more efficient because their energy consumption is less excessive.
However, existing SFA and DEA models based on the simple ratio between input and output cannot accommodate the heterogeneous structure of energy consumption in detail. Thus, a new EE model is required to cope with this methodological issue. Responding to the above problems, this study proposes a new cause–effect structure of energy consumption based on the DEA cost-efficiency model (Camanho and Dyson 2005; Fukuyama and Weber 2003). To reflect the intercity diversity of transport systems, all cities will be divided into homogeneous groups before model estimation.