This page has only limited features, please log in for full access.

Unclaimed
Xin Zou
Institute of Transport Studies, Monash University, Clayton, Australia

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Research article
Published: 30 May 2021 in Planning Practice & Research
Reads 0
Downloads 0

Contemporary research on transit-oriented development (TOD) continues to progress within the context of sustainable development. Based on a scientometric analysis, this paper collected 507 articles from the Web of Science within the timespan of 1996–2021, and used VOSviewer to visually map and analyse the development of TOD studies, including yearly article distribution, main countries, organisations, highly co-cited documents, and burst keywords. We found documents with high co-citation strength in four clusters of TOD studies: impacts of TOD planning factors on transportation benefits; TOD typology, classification, and measurement; TOD contexts, experiences, difficulties, and solutions; TOD transit proximity and housing values.

ACS Style

Zhaohong Sun; Andrew Allan; Xin Zou; Derek Scrafton. Scientometric Analysis and Mapping of Transit-Oriented Development Studies. Planning Practice & Research 2021, 1 -26.

AMA Style

Zhaohong Sun, Andrew Allan, Xin Zou, Derek Scrafton. Scientometric Analysis and Mapping of Transit-Oriented Development Studies. Planning Practice & Research. 2021; ():1-26.

Chicago/Turabian Style

Zhaohong Sun; Andrew Allan; Xin Zou; Derek Scrafton. 2021. "Scientometric Analysis and Mapping of Transit-Oriented Development Studies." Planning Practice & Research , no. : 1-26.

Journal article
Published: 18 June 2020 in Accident Analysis & Prevention
Reads 0
Downloads 0

Accident Analysis & Prevention (AA&P) is a leading academic journal established in 1969 that serves as an important scientific communication platform for road safety studies. To celebrate its 50th anniversary of publishing outstanding and insightful studies, a multi-dimensional statistical and visualized analysis of the AA&P publications between 1969 and 2018 was performed using the Web of Science (WoS) Core Collection database, bibliometrics and mapping-knowledge-domain (MKD) analytical methods, and scientometric tools. It was shown that the annual number of AA&P’s publications has grown exponentially and that over the course of its development, AA&P has been a leader in the field of road safety, both in terms of innovation and dissemination. By determining its key source countries and organizations, core authors, highly co-cited published documents, and high burst-strength publications, we showed that AA&P’s areas of focus include the “effects of hazard and risk perception on driving behavior”, “crash frequency modeling analysis”, “intentional driving violations and aberrant driving behavior”, “epidemiology, assessment and prevention of road traffic injuries”, and “crash-injury severity modeling analysis”. Furthermore, the key burst papers that have played an important role in advancing research and guiding AA&P in new directions – particularly those in the fields of crash frequency and crash-injury severity modeling analyses were identified. Finally, a modified Haddon matrix in the era of intelligent, connected and autonomous transportation systems is proposed to provide new insights into the emerging generation of road safety studies.

ACS Style

Xin Zou; Hai L. Vu; Helai Huang. Fifty Years of Accident Analysis & Prevention: A Bibliometric and Scientometric Overview. Accident Analysis & Prevention 2020, 144, 105568 .

AMA Style

Xin Zou, Hai L. Vu, Helai Huang. Fifty Years of Accident Analysis & Prevention: A Bibliometric and Scientometric Overview. Accident Analysis & Prevention. 2020; 144 ():105568.

Chicago/Turabian Style

Xin Zou; Hai L. Vu; Helai Huang. 2020. "Fifty Years of Accident Analysis & Prevention: A Bibliometric and Scientometric Overview." Accident Analysis & Prevention 144, no. : 105568.

Journal article
Published: 08 April 2020 in Sustainability
Reads 0
Downloads 0

Studying the coordination of varied freight modes from the perspective of geographic regions is conducive to understanding the regional differences, and this can provide effective countermeasures and suggestions for the sustainable and coordinated development of freight transport. To reflect on the effects of regional differences in the coordination of freight modes, we divided China into four regions: The East, Central, West, and Northeast. We examined freight mode coordination in terms of region and analysed the coordination of freight modes from three aspects: one within a single freight mode system, between varied freight modes, and among freight modes and the economy in different regions. We selected 19 freight indexes based on China’s freight data from 2008 to 2017, and determined the relationship between the freight index and economic index gross domestic product (GDP) growth rate by means of stability, co-integration, and the Granger causality test. The coordination models within a single freight mode and among varied freight modes were established, and we conducted spatial autocorrelation between the freight mode and the economy. The results demonstrated that in the four regions of China, the single-freight mode had coordination of over 0.80; the coordination between waterway and aviation freight transport was over 0.83; and the coordination of varied freight modes in the Eastern region exceeded 0.78, with good overall coordination. Among the four regions, the spatial correlation between the Eastern and Western regions was not significant, while the correlation between the Central and Northeast regions was significant. The model and analysis methods established in this study were feasible and effective. In view of the universality of the model, it can be easily applied and generalized in or out of China.

ACS Style

Yuee Gao; Xin Zou; Rujia Chen; Yanli Ma; Chengjiang Li; Yaping Zhang. Freight Mode Coordination in China: From the Perspective of Regional Differences. Sustainability 2020, 12, 2996 .

AMA Style

Yuee Gao, Xin Zou, Rujia Chen, Yanli Ma, Chengjiang Li, Yaping Zhang. Freight Mode Coordination in China: From the Perspective of Regional Differences. Sustainability. 2020; 12 (7):2996.

Chicago/Turabian Style

Yuee Gao; Xin Zou; Rujia Chen; Yanli Ma; Chengjiang Li; Yaping Zhang. 2020. "Freight Mode Coordination in China: From the Perspective of Regional Differences." Sustainability 12, no. 7: 2996.

Case report
Published: 13 December 2019 in International Journal of Logistics Research and Applications
Reads 0
Downloads 0

Urban logistics is critical for realising urban economic efficiency, and its rapid development holds great potential for improving urban competitiveness. This research looked at eighteen cities in China’s Sichuan Province, analysing factors including gross regional product (GRP), total freight traffic, and revenue from postal services to build an evaluation index system of urban logistics competitiveness (ULC) based on economic-development levels, logistics-business scale and informatization levels. ULC for the eighteen sample cities was evaluated and classified through factor analysis and cluster analysis using SPSS 24.0 software. Various city groups were compared and analysed to determine spatial distributions of ULC by calculating the logistics location quotient (LQ) for each city, then using ArcGIS 10.5 to determine the evolution of spatial structure from 2004 to 2014. Through factor analysis and cluster analysis, it was found that the cities could be divided into four clusters according to their levels of comprehensive logistics competitiveness. Furthermore, spatial evolution analysis revealed that the spatial pattern of urban logistics across Sichuan was characterised by the evolution from ‘three groups and multiple nodes' to ‘one center, two poles and multiple nodes.'

ACS Style

Xin Zou; Sekhar Somenahalli; Derek Scrafton. Evaluation and analysis of urban logistics competitiveness and spatial evolution. International Journal of Logistics Research and Applications 2019, 23, 493 -507.

AMA Style

Xin Zou, Sekhar Somenahalli, Derek Scrafton. Evaluation and analysis of urban logistics competitiveness and spatial evolution. International Journal of Logistics Research and Applications. 2019; 23 (5):493-507.

Chicago/Turabian Style

Xin Zou; Sekhar Somenahalli; Derek Scrafton. 2019. "Evaluation and analysis of urban logistics competitiveness and spatial evolution." International Journal of Logistics Research and Applications 23, no. 5: 493-507.

Journal article
Published: 25 November 2019 in Sustainability
Reads 0
Downloads 0

As urbanization continues to accelerate, the number of cities and their growing populations have created problems, such as the congestion and noise related to transportation, the pollution from industry, and the difficulty of disposing of garbage. An emerging urban strategy is to make use of digital technologies and big data to help improve the quality of life of urban residents. In the past decade, more and more researchers have studied smart cities, and the number of literature in this field grows rapidly, making it “big data”. With the aim of better understanding the contexts of smart-city research, including the distribution of topics, knowledge bases, and the research frontiers in the field, this paper is based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) in the Web of Science (WoS) Core Collection, and the method used is that of comprehensive scientometric analysis and knowledge mapping in terms of diversity, time slicing, and dynamics, using VOSviewer and CiteSpace to study the literature in the field. The main research topics can be divided into three areas—“the concepts and elements of the smart city”, “the smart city and the Internet of Things”, and “the smart city of the future”—through document co-citation analysis. There are four key directions—“research objectives and development-strategy research”, “technical-support research”, “data-processing and applied research”, and “management and applied research”—analyzed using keywords co-occurrence. Finally, the research frontiers are urban-development, sustainable cities, cloud computing, artificial intelligence, integration, undertaken through keyword co-occurrence analysis.

ACS Style

Li Zhao; Zhi-Ying Tang; Xin Zou. Mapping the Knowledge Domain of Smart-City Research: A Bibliometric and Scientometric Analysis. Sustainability 2019, 11, 6648 .

AMA Style

Li Zhao, Zhi-Ying Tang, Xin Zou. Mapping the Knowledge Domain of Smart-City Research: A Bibliometric and Scientometric Analysis. Sustainability. 2019; 11 (23):6648.

Chicago/Turabian Style

Li Zhao; Zhi-Ying Tang; Xin Zou. 2019. "Mapping the Knowledge Domain of Smart-City Research: A Bibliometric and Scientometric Analysis." Sustainability 11, no. 23: 6648.

Review
Published: 05 September 2019 in Accident Analysis & Prevention
Reads 0
Downloads 0

As a way of obtaining a visual expression of knowledge, mapping knowledge domain (MKD) provides a vision-based analytic approach to scientometric analysis which can be used to reveal an academic community, the structure of its networks, and the dynamic development of a discipline. This study, based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) articles on road safety, employs the bibliometric tools VOSviewer and CitNetExplorer to create maps of author co-citation, document co-citation, citation networks, analyze the core authors and classic documents supporting road safety studies and show the citation context and development of such studies. It shows that road safety studies clustered mainly into four groups, whose we will refer to as “effects of driving psychology and behavior on road safety”, “causation, frequency and injury severity analysis of road crashes”, “epidemiology, assessment and prevention of road traffic injury”, and “effects of driver risk factors on driver performance and road safety”, respectively. Through our analysis, the core publications and their citation relationships were quickly located and explored, and “crash frequency modeling analysis” has been identified to be the core research topic in road safety studies, with spatial statistical analysis technique emerging as a frontier of this topic.

ACS Style

Xin Zou; Hai L. Vu. Mapping the knowledge domain of road safety studies: A scientometric analysis. Accident Analysis & Prevention 2019, 132, 105243 .

AMA Style

Xin Zou, Hai L. Vu. Mapping the knowledge domain of road safety studies: A scientometric analysis. Accident Analysis & Prevention. 2019; 132 ():105243.

Chicago/Turabian Style

Xin Zou; Hai L. Vu. 2019. "Mapping the knowledge domain of road safety studies: A scientometric analysis." Accident Analysis & Prevention 132, no. : 105243.

Journal article
Published: 01 September 2018 in Accident Analysis & Prevention
Reads 0
Downloads 0

Mapping knowledge domain (MKD) is an important application of visualization technology in Bibliometrics, which has been extensively applied in psychology, medicine, and information science. In this paper we conduct a systematic analysis of the development trend on road safety studies based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) articles published between 2000 and 2018 using the MKD software tools VOSviewer and Sci2 Tool. Based on our analysis, we first present the annual numbers of articles, origin countries, main research organizations and groups as well as the source journals on road safety studies. We then report the collaborations among the main research organizations and groups using co-authorship analysis. Furthermore, we adopt the document co-citation analysis, keywords co-occurrence analysis, and burst detection analysis to visually explore the knowledge bases, topic distribution, research fronts and research trends on road safety studies. The proposed approach based on the visualized analysis of MKD can be used to establish a reference information and research basis for the application and development of methods in the domain of road safety studies. In particular, our results show that the knowledge bases (classical documents) of road safety studies in the last two decades have focused on five major areas of “Crash Frequency Data Analysis”, “Driver Behavior Questionnaire”, “Safety in Numbers for Walkers and Bicyclists”, “Road Traffic Injury and Prevention”, and “Driving Speed and Road Crashes”. Among the research topics, the five dominant clusters are “Causation and Injury Severity Analysis of Road Accidents”, “Epidemiologic Study and Prevention of Road Traffic Injury”, “Intelligent Transportation System and Active Safety”, “Young drivers’ driving behavior and psychology”, and “Older drivers’ psychological and physiological characteristics”. Finally, the burst keywords in research trends include Cycling, Intelligent Transportation Systems, and Distraction.

ACS Style

Xin Zou; Wen Long Yue; Hai L. Vu. Visualization and analysis of mapping knowledge domain of road safety studies. Accident Analysis & Prevention 2018, 118, 131 -145.

AMA Style

Xin Zou, Wen Long Yue, Hai L. Vu. Visualization and analysis of mapping knowledge domain of road safety studies. Accident Analysis & Prevention. 2018; 118 ():131-145.

Chicago/Turabian Style

Xin Zou; Wen Long Yue; Hai L. Vu. 2018. "Visualization and analysis of mapping knowledge domain of road safety studies." Accident Analysis & Prevention 118, no. : 131-145.

Research article
Published: 12 December 2017 in Journal of Advanced Transportation
Reads 0
Downloads 0

Based on an overall consideration of factors affecting road safety evaluations, the Bayesian network theory based on probability risk analysis was applied to the causation analysis of road accidents. By taking Adelaide Central Business District (CBD) in South Australia as a case, the Bayesian network structure was established by integrating K2 algorithm with experts’ knowledge, and Expectation-Maximization algorithm that could process missing data was adopted to conduct the parameter learning in Netica, thereby establishing the Bayesian network model for the causation analysis of road accidents. Then Netica was used to carry out posterior probability reasoning, the most probable explanation, and inferential analysis. The results showed that the Bayesian network model could effectively explore the complex logical relation in road accidents and express the uncertain relation among related variables. The model not only can quantitatively predict the probability of an accident in certain road traffic condition but also can find the key reasons and the most unfavorable state combination which leads to the occurrence of an accident. The results of the study can provide theoretical support for urban road management authorities to thoroughly analyse the induction factors of road accidents and then establish basis in improving the safety performance of the urban road traffic system.

ACS Style

Xin Zou; Wen Long Yue. A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica. Journal of Advanced Transportation 2017, 2017, 1 -18.

AMA Style

Xin Zou, Wen Long Yue. A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica. Journal of Advanced Transportation. 2017; 2017 ():1-18.

Chicago/Turabian Style

Xin Zou; Wen Long Yue. 2017. "A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica." Journal of Advanced Transportation 2017, no. : 1-18.