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The aim of this paper is to scrutinize smart biking in the context of gendered innovations and sustainable transport. Based on media representations, interviews, reports and surveys, the paper situates the establishment of the Chinese biking company Mobike in the landscapes of recent innovation strategies. What are the gendered implications of shared biking and Mobike design and technology? Does Mobike provide a challenge to the car-centric developments of urban mobility in China? What are the broader lessons to be learned in terms of sustainable urban transport? The Mobike company rolled out its first waves of bikes in the streets in Shanghai and Beijing in 2016, since when smart biking has spread like wildfire, particularly in China, but also in other countries around the globe. This paper contributes to situating and analyzing innovative practices related to gender and sustainability. Mobike was invented by a woman, Hu Weiwei, who set out to address the pressing needs of urban residents in respect of more convenient, sustainable and efficient modes of transport. It is argued that Mobike should be seen as an experimental case of disruptive gendered innovations that feeds into the challenges of sustainable urban transport and social equality.

Three-dimensional (3-D) spatial data of a transportation infrastructure contain useful information for civil engineering applications, including as-built documentation, on-site safety enhancements, and progress monitoring. Several techniques have been developed for acquiring 3-D point coordinates of infrastructure, such as laser scanning. Although the method yields accurate results, the high device costs and human effort required render the process infeasible for generic applications in the construction industry. A quick and reliable approach, which is based on the principles of stereo vision, is proposed for generating a depth map of an infrastructure. Initially, two images are captured by two similar stereo cameras at the scene of the infrastructure. A Harris feature detector is used to extract feature points from the first view, and an innovative adaptive window-matching technique is used to compute feature point correspondences in the second view. A robust algorithm computes the nonfeature point correspondences. Thus, the correspondences of all the points in the scene are obtained. After all correspondences have been obtained, the geometric principles of stereo vision are used to generate a dense depth map of the scene. The proposed algorithm has been tested on several data sets, and results illustrate its potential for stereo correspondence and depth map generation.

Policymakers as well as corporate managers want to know how to gain the lead and benefit from a paradigmatic shift in technology. This paper develops and uses a combined policy and firm-level theoretical framework to derive policy implications from a case study of the development of battery, hybrid and fuel cell electric vehicles (BEVs, HEVs and FCVs) in Japan. Among the implications of the study, it is argued that Japanese national policy has so far had a limited direct role in the electrification of vehicles; this has been very largely decided and carried out in-house at the automakers. Policymakers need to consider this as well as the inherently international nature of the automotive industry. One key factor behind Toyota's and Honda's early and sustained lead in the electrification trajectory is the intense and in some aspects quite specific type of competition on the domestic market, which has nurtured firms with a strong product development capability. Finally, it is argued that the proposed theoretical framework contributes to a more balanced view of the role of policy in this potential paradigmatic shift in technology in a mature industry, compared to traditional policy or firm-level approaches.

Demand-side management and demand response are proposed as a means to solve different objectives in smart grids, such as, e.g., maximizing self-consumption of a house or peak shaving. Crucial components in these approaches are load shiftable/steerable devices, so-called smart appliances. Although several studies already use these devices and determine how to use their flexibility, their impact on — or value for — the overall system is not studied. This paper provides a methodology to calculate the value of flexibility of smart devices. The methodology makes it possible to quantitatively compare the impact of these devices for different kinds of objectives. The developed methodology is applied in a case study to compare the flexibility of white goods, home batteries and electric vehicles. The results indicate among others that smart white goods may not always be that important for smart grids.

Freight demand (FD) is closely related to industrial structure (IS), and the determination of this relationship is conducive to the development of the transport industry. This research proposed an input–output structural decomposition analysis (IO-SDA) model to explain the growth of FD with the changes in economic aggregate, structural factor, transport demand intensity, and industry connection. This method enables us to quantify and compare the contribution of industrial development to FD growth of five freight modes and determine the role of the structural factor in the growth of FD. An empirical study was conducted based on China’s 2002 to 2017 input–output tables. The results showed that the construction industry was the most important sector leading to the growth of FD, and the role of the service industry in promoting the growth of FD became more evident. There was a clear trend of concentration to the road freight industry, which may undermine the coordination of the transport industry. The structural factor became an important factor in reducing FD in 2007 to 2017. Based on the findings, it is suggested that China should promote the upgrading of IS and emphasize the importance of green road transport and multimodal transport.

Abstract This paper traces the historical evolution and spatial disparity of CO2 emissions from passenger transport in China. The general trends of CO2 emissions from four passenger transport modes are estimated by both the distance-based and fuel-based methods. The results suggest that CO2 emissions from road transport represented the leading source of passenger transport CO2 emissions in China. Moreover, they have continued to grow rapidly. Air transport was the second largest contributor since 1998. Emissions from rail and water transport have remained relatively stable with lower emission intensity. At the provincial level, great regional disparity was noticeable, especially in road transport. Moreover, the decomposition analysis shows that income growth was the principal factor leading to the growth of passenger transport CO2 emissions in China for both the 1949–1979 and 1980–2009 periods. The second most important factor was increased transport intensity and modal shifts for the former and the latter period, respectively. The main factor contributed to emission reduction was the lower emission intensity supported by policies, although the effect was weak. In the future, more policies to encourage modal shifts toward sustainable transport modes and travel reduction should be encouraged.

Quantitative life cycle sustainable assessment requires a complex and multidimensional understanding, which cannot be fully covered by the current portfolio of reductionist-oriented tools. Therefore, there is a dire need on a new generation of modeling tools and approaches that can quantitatively assess the economic, social, and environmental dimensions of sustainability in an integrated way. To this end, this research aims to present a practical and novel approach for (1) broadening the existing life cycle sustainability assessment (LCSA) framework by considering macrolevel environmental, economic, and social impacts (termed as the triple bottom line), simultaneously, (2) deepening the existing LCSA framework by capturing the complex dynamic relationships between social, environmental, and economic indicators through causal loop modeling, (3) understanding the dynamic complexity of transportation sustainability for the triple bottom line impacts of alternative vehicles, and finally (4) investigating the impacts of various vehicle-specific scenarios as a novel approach for selection of a macrolevel functional unit considering all of the complex interactions in the environmental, social, and economic aspects. To alleviate these research objectives, we presented a novel methodology to quantify macrolevel social, economic, and environmental impacts of passenger vehicles from an integrated system analysis perspective. An integrated dynamic LCSA model is utilized to analyze the environmental, economic, and social life cycle impact as well as life cycle cost of alternative vehicles in the USA. System dynamics modeling is developed to simulate the US passenger transportation system and its interactions with economy, the environment, and society. Analysis covers manufacturing and operation phase impacts of internal combustion vehicles (ICVs), hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). In total, seven macrolevel indicators are selected; global warming potential, particulate matter formation, photochemical oxidant formation, vehicle ownership cost, contribution to gross domestic product, employment generation, and human health impacts. Additionally, contribution of vehicle choices to global atmospheric temperature rise and public welfare is investigated. BEVs are found to be a better alternative for most of sustainability impact categories. While some of the benefits such as contribution to employment and GDP, CO2 emission reduction potential of BEVs become greater toward 2050, other sustainability indicators including vehicle ownership cost and human health impacts of BEVs are higher than the other vehicle types on 2010s and 2020s. While the impact shares of manufacturing and operation phases are similar in the early years of 2010s, the contribution of manufacturing phase becomes higher as the vehicle performances increase toward 2050. Analysis results revealed that the US transportation sector, alone, cannot reduce the rapidly increasing atmospheric temperature and the negative impacts of the global climate change, even though the entire fleet is replaced with BEVs. Reducing the atmospheric climate change requires much more ambitious targets and international collaborative efforts. The use of different vehicle types has a small impact on public welfare, which is a function of income, education, and life expectancy indexes. The authors strongly recommend that the dynamic complex and mutual interactions between sustainability indicators should be considered for the future LCSA framework. This approach will be critical to deepen the existing LCSA framework and to go beyond the current LCSA understanding, which provide a snapshot analysis with an isolated view of all pillars of sustainability. Overall, this research is a first empirical study and an important attempt toward developing integrated and dynamic LCSA framework for sustainable transportation research.

In this paper, we present a new method to operationalize social barriers for innovative technologies. Technical feasibility and economic viability are no guarantee for the development and take-off of an innovation. We combine insights from multi-level perspective (MLP) and technological innovation systems (TIS) theory to develop a framework for the identification and evaluation of actor-centred barriers. We illustrate the method through an application to catenary hybrid truck (CHT) technology in Germany. Relevant stakeholders were identified via document research and subsequent network analysis, and then approached to fill out a survey. Additional data was gathered using semi-structured interviews with key actors, and content analysis. We show how the implementation of CHT may be hampered by resistance from the regime and by a lack of focused expectations and lobbying within the niche.

Global Environment Facility (GEF) support for World Bank sustainable transport activities is described. An overview is presented of current GEF strategy for sustainable transport, which reflects a shift beyond individual technology interventions toward broader objectives, including modal shift, demand management, and land use planning. Ongoing GEF projects that exemplify this shift are reviewed by examining projects in Latin America and Asia whose aim is improving public transport, nonmotorized programs, and institutional capacity related to sustainable transport. The major lessons that can be drawn from these projects, most of which are still at an early stage, is that local authorities are often enthusiastic about getting involved in programs that simultaneously address key transportation concerns in their cities (such as access, safety, congestion, local air quality) and result in less overall energy use and greenhouse gas emissions. Much can be achieved as long as project communications and promotion are addressed and carefully targeted at decision makers and potential beneficiaries.