Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A review of consumer preferences of and interactions with electric vehicle charging infrastructure
2018558 citationsScott Hardman, Alan Jenn et al.Transportation Research Part D Transport and Environmentprofile →
The rise of electric vehicles—2020 status and future expectations
2021273 citationsAlan Jenn, Gil Tal et al.profile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
citations ·
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This map shows the geographic impact of Gil Tal'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 Gil Tal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gil Tal more than expected).
This network shows the impact of papers produced by Gil Tal. 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 Gil Tal. The network helps show where Gil Tal may publish in the future.
Co-authorship network of co-authors of Gil Tal
This figure shows the co-authorship network connecting the top 25 collaborators of Gil Tal.
A scholar is included among the top collaborators of Gil Tal 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 Gil Tal. Gil Tal is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sprei, Frances, et al.. (2019). Electrification of vehicle miles travelled within the household context. Chalmers Research (Chalmers University of Technology).2 indexed citations
9.
Ji, Wei & Gil Tal. (2019). Exploring the Value of Clean Air Vehicles High Occupancy Lane Access In California. Transportation Research Board 98th Annual MeetingTransportation Research Board.3 indexed citations
10.
Tal, Gil, et al.. (2018). Motivations and Barriers Associated with the Adoption of Battery Electric Vehicles in Beijing: A Multinomial Logit Model Approach. eScholarship (California Digital Library).3 indexed citations
11.
Tal, Gil, et al.. (2017). Introduction of China Plug-in Electric Vehicle Market and an Exploration of Factors Associated with Choice of Plug-in Electric Vehicle. Transportation Research Board 96th Annual MeetingTransportation Research Board.1 indexed citations
12.
Tal, Gil, et al.. (2017). Modeling the Choice of Plug-in Electric Vehicles in California: A Nested Logit Approach. Transportation Research Board 96th Annual MeetingTransportation Research Board.2 indexed citations
13.
Nicholas, Michael & Gil Tal. (2016). EVMT in the Household Fleet: Integrating Battery Electric Vehicles into Household Travel. Transportation Research Board 95th Annual MeetingTransportation Research Board.1 indexed citations
14.
Nicholas, Michael & Gil Tal. (2015). Charging for Charging at Work: Increasing the Availability of Charging Through Pricing. Transportation Research Board 94th Annual MeetingTransportation Research Board.11 indexed citations
15.
Nicholas, Michael, et al.. (2013). California Statewide Charging Survey: What Do Drivers Want?. Transportation Research Board 92nd Annual MeetingTransportation Research Board.6 indexed citations
16.
Nicholas, Michael, et al.. (2012). DC Fast as the Only Public Charging Option? Scenario Testing from GPS-Tracked Vehicles. Transportation Research Board 91st Annual MeetingTransportation Research Board.22 indexed citations
17.
Tal, Gil. (2008). Overestimation Reduction in Forecasting Telecommuting as a TDM Policy. eScholarship (California Digital Library).4 indexed citations
18.
Tal, Gil & Susan Handy. (2008). Children’s Biking for Nonschool Purposes: Getting to Soccer Games in Davis, California. RePEc: Research Papers in Economics.1 indexed citations
19.
Tal, Gil & Susan Handy. (2008). Children’s Bicycling to After-School Activities: The Case of the Davis AYSO Bike-to-Soccer Program. eScholarship (California Digital Library).
20.
Tal, Gil & Susan Handy. (2005). The Travel Behavior of Immigrants and Race/Ethnicity Groups: An Analysis of the 2001 National Household Transportation Survey. eScholarship (California Digital Library).8 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.