A review on the factors influencing the adoption of new mobility technologies and services: autonomous vehicle, drone, micromobility and mobility as a service

New mobility technologies and services could address a series of transport-related problems such as pollution, congestion, unpleasant travel experiences, as well as first- and last-mile in-connectivity. Understanding the key factors influencing adoption and enablers is critical to the rollout of the new mobility technologies and services. The objective of this paper is to conduct a systematic review of the new mobility technologies and services, especially on autonomous vehicles, drones, micromobility and Mobility as a Service (MaaS). The ultimate goal is to gain a deeper insight into the factors that affect the adoption or preferences of these technologies and services and thus provide policy implications at the strategic level. The results of the review identified several (1) shared, (2) exclusive, (3) opposing and (4) mixed impacts factors that strongly influence the uptake of new mobilities. The synthesised finding will contribute to policy decisions, particularly regarding the sequencing of the launch and development priorities of new mobility technologies and services. To encourage the uptake of new mobility technologies and services, further promotion would benefit from (1) embedding a spatio-temporal perspective, (2) undertaking a careful market segmentation and (3) a careful segmentation of technology and services based on features, application contexts and purposes

catena-Poly[[dimethyl­tin(IV)]-μ-cis-cyclo­hexane-1,2-dicarboxyl­ato]

The title complex, [Sn(CH3)2(C8H10O4)]n, was synthesized from cis-cyclo­hexane-1,2-dicarboxylic acid and dimethyl­tin dichloride. The complex has a bridging bis-bidentate carboxyl­ate group resulting in a zig-zag chain structure parallel to [001]. The Sn atom is six-coordinated and displays a distorted octa­hedral geometry

Neighbourhood satisfaction in rural resettlement residential communities: the case of Suqian, China

Against the background of large-scale urbanisation and rural land expropriation, rural resettlement residential housing has been built to accommodate local rural residents in the peripheral areas of China. To explore the context-specific policy implications for improving neighbourhood satisfaction (NS) of residents in rural resettlement residential communities (RRRCs), this paper examines the determinants of NS, and their spatial effects, in rural resettlement residential neighbourhoods using Suqian, in Jiangsu Province, as a case study. This study contributes to the current literature in two ways: it constitutes the first attempt to examine NS among RRRCs; second, our spatial model helps to gain further understanding of horizontal and vertical spatial dependence effects. Our results indicate that income, gender, age, family structure, number of years living in a community, transport and architectural age all have significant effects on NS in RRRCs

Perceived sustainable urbanization based on geographically hierarchical data structures in Nanjing, China

Concentrating on geographically hierarchical data structures and using large-scale satisfaction survey data in Nanjing, this study employs Bayesian spatial multilevel model (MLM) to evaluate Nanjing’s perceived sustainable urbanization. In this study, we consider the geographically hierarchical data structures and the city’s individual perceptions of sustainable urbanization to explore the effect of environment and self-rated health on perceived sustainable urbanization, controlling for individual sociodemographic attributes and household. Through clarifying the spatial dependence and heterogeneity, this paper provides a flexible framework for assessing sustainable urbanization and dealing with the geographical hierarchical data. In particular, by drawing on existing studies, our questionnaire is more representative of the overall characteristics of Nanjing’s population than census data, which can be helpful for understanding whether urbanization is sustainable from individual perspective and further for correcting practices. Based on a survey of 10,077 questionnaires, this paper finds the geographically hierarchical data structures have significantly influenced the evaluation of sustainable urbanization, and the Bayesian spatial MLM is an effective tool for evaluating China’s sustainable urbanization. In particular, this paper takes spatial effects into consideration and compares the geographically hierarchical data. Results show that spatial patterns significantly influence the assessment of sustainable urbanization, and perceived pollution, age, education level, and income are the four key factors influencing individual perceived sustainable urbanization

Banning diesel vehicles in London: Is 2040 too Late?

Air pollution contributes to 9400 deaths annually in London and diesel vehicles are considered a major source of lethal air pollutants. Consequently, the UK government announced its intention to ban diesel vehicles by 2040 to achieve a sustainable zero-carbon road transport system. Since no empirical studies have used a bottom-up approach to seek Londoners’ views, it is therefore worth investigating the public opinion regarding this forthcoming ban. This paper aims to fill this research gap by taking London as a case study. A survey was designed, and fieldwork was conducted to distribute questionnaires to Londoners. Completed questionnaires were analysed using both quantitative and qualitative methods. The findings revealed that the majority of Londoners would be in favour of the ban if they were sufficiently exposed to the appropriate sources of information and were favourably disposed towards environmental protection measures. The results also showed that Londoners were more likely to switch to electric vehicles (EVs) if they were offered generous incentives and encouraged to use scrappage schemes. The present study makes a strong case for enforcing the ban well before 2040. The significance of this research is to provide clearer signals regarding the future of diesel vehicles, which in turn will strengthen the EV policy and uptake

The association between urban public transport infrastructure and social equity and spatial accessibility within the urban environment: An investigation of Tramlink in London

The pursuit of sustainability has been at the forefront of contemporary planning initiatives. However, most recent research has focused on the environmental and economic aspects of developing sustainable urban environment, whilst largely neglecting the social aspects. Contemporary political thinking in the UK often disregards the potential of the urban infrastructure to improve social equity. The aim of this study was to analyse the impact of transport infrastructure on a variety of social measures, in an empirical and ideologically unbiased fashion, using both quantitative and qualitative methods. We selected “Tramlink” as a case study: a light-rail system in the London Borough of Croydon which began operation in 2000. We used quantitative methods, including advanced spatial statistics, to produce a more detailed analysis of social equity than has been previously published. This acknowledges that determining localised issues can produce more informed and effective policy interventions. Our results demonstrate that the physical properties of transport infrastructure and the non-physical attributes of society, in combination, help to create opportunities for individuals to succeed. We also find that in order to reduce the negative effects of austerity, public money could be more effectively spent if diverted to areas that are most in need which can be highlighted through localised investigations

Towards sustainability: An assessment of an urbanisation bubble in China using a hierarchical - stochastic multicriteria acceptability analysis - Choquet integral method

Urbanisation bubbles have become an increasingly serious problem. Attention has been paid to the speed of urbanisation; however, the issue of quality has been neglected, particularly in the case of China. Therefore, the aim of this research is to evaluate China’s urbanisation bubbles by employing a hierarchical - stochastic multicriteria acceptability analysis (SMAA) - Choquet integral method. In order to highlight regional disparities, we measure the urbanisation bubbles at a provincial level. Our study aggregates the urbanisation bubble indices using the Choquet integral preference model, and considers the interactions between various indicators. Furthermore, robust ordinal regression and SMAA are applied to resolve the robustness issues associated with the entire set of weights assigned to the urbanisation bubble composite indicator. In addition, by employing a multiple criteria hierarchy process, the study aggregates urbanisation bubble indices not only at the comprehensive level, but also at the intermediate levels of the hierarchy. Our findings suggest that the ranking of urbanisation bubbles is positively related to the level of regional development. This study contributes to the evaluation of regional urbanisation and sustainable development

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

<p>Abstract</p> <p>Background</p> <p>Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand.</p> <p>Results</p> <p>EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data.</p> <p>Conclusion</p> <p>EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from <url>http://www.ezarray.com/</url>.</p

Towards a network perspective of transit resilience: an intra-urban study of Greater London

In recent years, the popularity of “resilience” has exploded in both academic and policy discourse. However, current transit resilience research only focuses on infrastructure resilience, giving little consideration to its interaction with passengers. Moreover, even for transit infrastructure resilience, there is no comprehensive framework for assessing resilience to reflect its scale-sensitive attributes. Therefore, to make cities and transit systems move from a vulnerable state to a more resilient one, this thesis seeks to advance our understanding of transit resilience performance from macro, meso and micro levels, focusing on the interactions between infrastructure and passengers. Additionally, this research is motivated by the need to bridge the theoretical gap between the transport network and complex network science disciplines. This research draws on a multiple-level framework to investigate stations' roles in maintaining London transit resilience at macro, meso and micro levels from a network perspective. At macro level, this research examines the overall transit resilience performance by using percolation modelling and fault tolerance. At meso level, resilience as a sub-network feature is examined by unravelling the travel structure and identifying the stations' roles in maintaining resilience within and beyond metropolitan levels through community detection and Z-P scores. This research evaluates each station’s role in maintaining resilience based on resilience and criticality matrix at micro level. In addition, this research seeks to answer for whom we should build resilience by including the transport equity analysis. In line with the conceptual framework, this research develops an R package1, ResilienceNet, which provides a reproducible and accessible tool to examine transit resilience at multiple levels. Three research findings can be derived from this research. First, the London transit is resilient against random disruption but relatively vulnerable to centrality-based attacks. The conventional network approach would understate or overstate the resilience performance at the macro level. Second, the empirical results justify the necessity to include an evaluation of resilience at the meso level, as the role of stations for ensuring resilience varies differently within and beyond sub-city communities. Third, at the micro-level, this research identifies 25 stations and some vulnerable groups, such as young and low-income groups, which are more likely to be affected by transit disruptions and need more attention. The results derived through analysis could be used to facilitate transport and urban planning at multiple levels, thus moving cities and transit systems from a vulnerable to a more resilient state