Chiang Fu

814 total citations
23 papers, 632 citations indexed

About

Chiang Fu is a scholar working on Transportation, Safety, Risk, Reliability and Quality and Economics and Econometrics. According to data from OpenAlex, Chiang Fu has authored 23 papers receiving a total of 632 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Transportation, 10 papers in Safety, Risk, Reliability and Quality and 9 papers in Economics and Econometrics. Recurrent topics in Chiang Fu's work include Urban Transport and Accessibility (15 papers), Traffic and Road Safety (10 papers) and Transportation Planning and Optimization (9 papers). Chiang Fu is often cited by papers focused on Urban Transport and Accessibility (15 papers), Traffic and Road Safety (10 papers) and Transportation Planning and Optimization (9 papers). Chiang Fu collaborates with scholars based in Taiwan. Chiang Fu's co-authors include Yu‐Chiun Chiou, Chieh-Hua Wen, David Emanuel Andersson, Oliver Feng-Yeu Shyr, Wei-Chung Wang, Ching‐Fu Chen, Wei‐Ning Wu, Yu‐Chun Chen, Barbara T.H. Yen and Rong‐Chang Jou and has published in prestigious journals such as Accident Analysis & Prevention, Transportation Research Part A Policy and Practice and Transportation Research Part E Logistics and Transportation Review.

In The Last Decade

Chiang Fu

21 papers receiving 606 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chiang Fu Taiwan 12 396 286 158 114 114 23 632
Nima Golshani United States 12 445 1.1× 205 0.7× 82 0.5× 49 0.4× 98 0.9× 26 769
Thanapong Champahom Thailand 17 442 1.1× 593 2.1× 37 0.2× 261 2.3× 151 1.3× 94 901
Xuehao Chu United States 14 812 2.1× 267 0.9× 190 1.2× 72 0.6× 171 1.5× 42 978
Jason Lemp United States 9 261 0.7× 164 0.6× 72 0.5× 69 0.6× 94 0.8× 26 409
Begoña Guirao Spain 18 654 1.7× 168 0.6× 97 0.6× 45 0.4× 208 1.8× 62 925
Thomas J. Zlatoper United States 10 134 0.3× 188 0.7× 178 1.1× 46 0.4× 47 0.4× 21 506
Mahmudur Rahman Fatmi Canada 15 468 1.2× 94 0.3× 118 0.7× 26 0.2× 84 0.7× 68 685
Luis Márquez Colombia 14 341 0.9× 151 0.5× 129 0.8× 29 0.3× 112 1.0× 48 571
Ana Margarita Larrañaga Brazil 14 702 1.8× 189 0.7× 69 0.4× 36 0.3× 245 2.1× 41 848
Sabreena Anowar United States 15 500 1.3× 124 0.4× 97 0.6× 49 0.4× 151 1.3× 36 705

Countries citing papers authored by Chiang Fu

Since Specialization
Citations

This map shows the geographic impact of Chiang Fu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chiang Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chiang Fu more than expected).

Fields of papers citing papers by Chiang Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chiang Fu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chiang Fu. The network helps show where Chiang Fu may publish in the future.

Co-authorship network of co-authors of Chiang Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Chiang Fu. A scholar is included among the top collaborators of Chiang Fu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chiang Fu. Chiang Fu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Fu, Chiang, et al.. (2024). Studying older adults’ willingness to relocate and change transport mode with the random bivariate generalized ordered probit. Transportation Research Part A Policy and Practice. 191. 104322–104322.
3.
Fu, Chiang, et al.. (2024). The analysis of the shared bike usage pattern: Application of survival model to Taiwan YouBike. 10. 100125–100125. 1 indexed citations
4.
Fu, Chiang, et al.. (2023). A study on rose-window instability in a dielectric droplet exposed to corona discharge. Journal of Mechanics. 39. 491–499.
5.
Chen, Ching‐Fu, et al.. (2023). Exploring electric moped sharing preferences with integrated choice and latent variable approach. Transportation Research Part D Transport and Environment. 121. 103837–103837. 11 indexed citations
6.
Yen, Barbara T.H., Chiang Fu, & Yu‐Chiun Chiou. (2022). Young Drivers’ Preferences for Gamification Schemes Toward Safer Driving Behaviors: A Pilot Study. Transportation Research Record Journal of the Transportation Research Board. 2676(8). 279–291. 5 indexed citations
7.
Fu, Chiang, et al.. (2020). Modelling two-vehicle crash severity by generalized estimating equations. Accident Analysis & Prevention. 148. 105841–105841. 14 indexed citations
8.
Chiou, Yu‐Chiun, et al.. (2017). Freeway crash frequency modeling under time-of-day distribution. Transportation research procedia. 25. 664–676. 3 indexed citations
9.
Chiou, Yu‐Chiun & Chiang Fu. (2017). Responses of drivers and motorcyclists to congestion charge. Transportation research procedia. 25. 2957–2969. 11 indexed citations
10.
Wen, Chieh-Hua, Wei‐Ning Wu, & Chiang Fu. (2017). Preferences for alternative travel arrangements in case of major flight delays: Evidence from choice experiments with prospect theory. Transport Policy. 83. 111–119. 22 indexed citations
11.
Chiou, Yu‐Chiun & Chiang Fu. (2015). Modeling crash frequency and severity with spatiotemporal dependence. Analytic Methods in Accident Research. 5-6. 43–58. 53 indexed citations
12.
Chiou, Yu‐Chiun, et al.. (2014). Incorporating spatial dependence in simultaneously modeling crash frequency and severity. Analytic Methods in Accident Research. 2. 1–11. 60 indexed citations
13.
Chiou, Yu‐Chiun, et al.. (2013). Reprint of “Modeling two-vehicle crash severity by a bivariate generalized ordered probit approach”. Accident Analysis & Prevention. 61. 97–106. 19 indexed citations
14.
Chiou, Yu‐Chiun, et al.. (2012). Modeling two-vehicle crash severity by a bivariate generalized ordered probit approach. Accident Analysis & Prevention. 51. 175–184. 64 indexed citations
15.
Chiou, Yu‐Chiun & Chiang Fu. (2012). Modeling crash frequency and severity using multinomial-generalized Poisson model with error components. Accident Analysis & Prevention. 50. 73–82. 71 indexed citations
16.
Chiou, Yu‐Chiun, et al.. (2012). The adoption behaviours of freeway electronic toll collection: A latent class modelling approach. Transportation Research Part E Logistics and Transportation Review. 49(1). 266–280. 8 indexed citations
17.
Wen, Chieh-Hua, et al.. (2012). A latent class generalised nested logit model and its application to modelling carrier choice with market segmentation. Transportmetrica A Transport Science. 9(8). 675–694. 12 indexed citations
18.
Wen, Chieh-Hua, Wei-Chung Wang, & Chiang Fu. (2011). Latent class nested logit model for analyzing high-speed rail access mode choice. Transportation Research Part E Logistics and Transportation Review. 48(2). 545–554. 94 indexed citations
19.
Lu, Jin-Long, et al.. (2008). THE STUDY OF PRICE ACCEPT THRESHOLD FOR THE ??LUE HIGHWAY??TOUR OF THE NORTH-EAST REGION IN TAIWAN. Journal of marine science and technology. 16(4). 3 indexed citations
20.
Andersson, David Emanuel, Oliver Feng-Yeu Shyr, & Chiang Fu. (2008). Does high-speed rail accessibility influence residential property prices? Hedonic estimates from southern Taiwan. Journal of Transport Geography. 18(1). 166–174. 136 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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