Example of Transportation format
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Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format
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Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format Example of Transportation format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
open access Open Access
recommended Recommended

Transportation — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Development #8 of 257 up up by 5 ranks
Civil and Structural Engineering #26 of 318 up up by 6 ranks
Transportation #14 of 113 up up by 2 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 378 Published Papers | 2841 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 04/07/2020
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Related Journals

open access Open Access

Springer

Quality:  
High
CiteRatio: 3.3
SJR: 0.522
SNIP: 1.289
open access Open Access

Elsevier

Quality:  
High
CiteRatio: 5.4
SJR: 1.231
SNIP: 1.646
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 10.7
SJR: 1.645
SNIP: 2.347
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 16.5
SJR: 3.328
SNIP: 4.163

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

4.082

18% from 2018

Impact factor for Transportation from 2016 - 2019
Year Value
2019 4.082
2018 3.457
2017 3.151
2016 2.633
graph view Graph view
table view Table view

7.5

25% from 2019

CiteRatio for Transportation from 2016 - 2020
Year Value
2020 7.5
2019 6.0
2018 4.9
2017 4.7
2016 4.7
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 18% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 25% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.953

7% from 2019

SJR for Transportation from 2016 - 2020
Year Value
2020 1.953
2019 1.829
2018 1.852
2017 1.911
2016 1.671
graph view Graph view
table view Table view

2.43

15% from 2019

SNIP for Transportation from 2016 - 2020
Year Value
2020 2.43
2019 2.117
2018 2.152
2017 1.874
2016 1.809
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 7% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 15% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Transportation

Guideline source: View

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Springer

Transportation

In our first issue, published in 1972, we explained that this Journal is intended to promote the free and vigorous exchange of ideas and experience among the worldwide community actively concerned with transportation policy, planning and practice. That continues to be our miss...... Read More

Development

Civil and Structural Engineering

Transportation

Social Sciences

i
Last updated on
03 Jul 2020
i
ISSN
0049-4488
i
Impact Factor
High - 1.827
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
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Bibliography Name
SPBASIC
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Citation Type
Author Year
(Blonder et al, 1982)
i
Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

Journal Article DOI: 10.1023/A:1022558715350
The mixed logit model: the state of practice
David A. Hensher1, William H. Greene2
01 May 2003 - Transportation

Abstract:

The mixed logit model is considered to be the most promising state of the art discrete choice model currently available. Increasingly researchers and practitioners are estimating mixed logit models of various degrees of sophistication with mixtures of revealed preference and stated choice data. It is timely to review progress... The mixed logit model is considered to be the most promising state of the art discrete choice model currently available. Increasingly researchers and practitioners are estimating mixed logit models of various degrees of sophistication with mixtures of revealed preference and stated choice data. It is timely to review progress in model estimation since the learning curve is steep and the unwary are likely to fall into a chasm if not careful. These chasms are very deep indeed given the complexity of the mixed logit model. Although the theory is relatively clear, estimation and data issues are far from clear. Indeed there is a great deal of potential mis-inference consequent on trying to extract increased behavioural realism from data that are often not able to comply with the demands of mixed logit models. Possibly for the first time we now have an estimation method that requires extremely high quality data if the analyst wishes to take advantage of the extended behavioural capabilities of such models. This paper focuses on the new opportunities offered by mixed logit models and some issues to be aware of to avoid misuse of such advanced discrete choice methods by the practitioner. read more read less

Topics:

Mixed logit (77%)77% related to the paper, Discrete choice (54%)54% related to the paper, Logistic regression (50%)50% related to the paper
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1,604 Citations
Journal Article DOI: 10.1023/A:1017959825565
A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area
Ryuichi Kitamura1, Patricia L. Mokhtarian1, Laura Laidet1
01 May 1997 - Transportation

Abstract:

This study examined the effects of land use and attitudinal characteristics on travel behavior for five diverse San Francisco Bay Area neighborhoods. First, socio-economic and neighborhood characteristics were regressed against number and proportion of trips by various modes. The best models for each measure of travel behavio... This study examined the effects of land use and attitudinal characteristics on travel behavior for five diverse San Francisco Bay Area neighborhoods. First, socio-economic and neighborhood characteristics were regressed against number and proportion of trips by various modes. The best models for each measure of travel behavior confirmed that neighborhood characteristics add significant explanatory power when socio-economic differences are controlled for. Specifically, measures of residential density, public transit accessibility, mixed land use, and the presence of sidewalks are significantly associated with trip generation by mode and modal split. Second, 39 attitude statements relating to urban life were factor analyzed into eight factors: pro-environment, pro-transit, suburbanite, automotive mobility, time pressure, urban villager, TCM, and workaholic. Scores on these factors were introduced into the six best models discussed above. The relative contributions of the socio-economic, neighborhood, and attitudinal blocks of variables were assessed. While each block of variables offers some significant explanatory power to the models, the attitudinal variables explained the highest proportion of the variation in the data. The finding that attitudes are more strongly associated with travel than are land use characteristics suggests that land use policies promoting higher densities and mixtures may not alter travel demand materially unless residents' attitudes are also changed. read more read less

Topics:

Travel behavior (58%)58% related to the paper, Trip generation (55%)55% related to the paper, Mode choice (51%)51% related to the paper
980 Citations
open accessOpen access Journal Article DOI: 10.1007/BF01098788
Stated preference analysis of travel choices: the state of practice
David A. Hensher1
01 May 1994 - Transportation

Abstract:

Stated preference (SP) methods are widely used in travel behaviour research and practice to identify behavioural responses to choice situations which are not revealed in the market, and where the attribute levels offered by existing choices are modified to such an extent that the reliability of revealed preference models as p... Stated preference (SP) methods are widely used in travel behaviour research and practice to identify behavioural responses to choice situations which are not revealed in the market, and where the attribute levels offered by existing choices are modified to such an extent that the reliability of revealed preference models as predictors of response is brought into question. This paper reviews recent developments in the application of SP models which add to their growing relevance in demand modelling and prediction. The main themes addressed include a comparative assessment of choice models and preference models, the importance of scaling when pooling different types of data, especially the appeal of SP data as an enriching strategy in the context of revealed preference models, hierarchical designs when the number of attributes make single experiments too complex for the respondent, and ways of accommodating dynamics (i.e. serial correlation and state dependence) in SP modelling. read more read less

Topics:

Preference (61%)61% related to the paper, Revealed preference (60%)60% related to the paper, Travel behavior (52%)52% related to the paper, Context (language use) (51%)51% related to the paper
View PDF
663 Citations
Journal Article DOI: 10.1007/S11116-010-9284-Y
Motivators and deterrents of bicycling: comparing influences on decisions to ride
Meghan Winters1, Gavin Davidson, Diana Kao2, Kay Teschke1
01 Jan 2011 - Transportation

Abstract:

In a survey of 1,402 current and potential cyclists in Metro Vancouver, 73 motivators and deterrents of cycling were evaluated. The top motivators, consistent among regular, frequent, occasional and potential cyclists, were: routes away from traffic noise and pollution; routes with beautiful scenery; and paths separated from ... In a survey of 1,402 current and potential cyclists in Metro Vancouver, 73 motivators and deterrents of cycling were evaluated. The top motivators, consistent among regular, frequent, occasional and potential cyclists, were: routes away from traffic noise and pollution; routes with beautiful scenery; and paths separated from traffic. In factor analysis, the 73 survey items were grouped into 15 factors. The following factors had the most influence on likelihood of cycling: safety; ease of cycling; weather conditions; route conditions; and interactions with motor vehicles. These results indicate the importance of the location and design of bicycle routes to promote cycling. read more read less

Topics:

Poison control (50%)50% related to the paper
495 Citations
Journal Article DOI: 10.1007/S11116-016-9729-Z
Dynamic ride-sharing and fleet sizing for a system of shared autonomous vehicles in Austin, Texas
Daniel J Fagnant1, Kara M. Kockelman1
01 Jan 2018 - Transportation

Abstract:

Shared autonomous (fully-automated) vehicles (SAVs) represent an emerging transportation mode for driverless and on-demand transport. Early actors include Google and Europe’s CityMobil2, who seek pilot deployments in low-speed settings. This work investigates SAVs’ potential for U.S. urban areas via multiple applications acro... Shared autonomous (fully-automated) vehicles (SAVs) represent an emerging transportation mode for driverless and on-demand transport. Early actors include Google and Europe’s CityMobil2, who seek pilot deployments in low-speed settings. This work investigates SAVs’ potential for U.S. urban areas via multiple applications across the Austin, Texas, network. This work describes advances to existing agent- and network-based SAV simulations by enabling dynamic ride-sharing (DRS, which pools multiple travelers with similar origins, destinations and departure times in the same vehicle), optimizing fleet sizing, and anticipating profitability for operators in settings with no speed limitations on the vehicles and at adoption levels below 10 % of all personal trip-making in the region. Results suggest that DRS reduces average service times (wait times plus in-vehicle travel times) and travel costs for SAV users, even after accounting for extra passenger pick-ups, drop-offs and non-direct routings. While the base-case scenario (serving 56,324 person-trips per day, on average) suggest that a fleet of SAVs allowing for DRS may result in vehicle-miles traveled (VMT) that exceed person-trip miles demanded (due to anticipatory relocations of empty vehicles, between trip calls), it is possible to reduce overall VMT as trip-making intensity (SAV membership) rises and/or DRS users become more flexible in their trip timing and routing. Indeed, DRS appears critical to avoiding new congestion problems, since VMT may increase by over 8 % without any ride-sharing. Finally, these simulation results suggest that a private fleet operator paying $70,000 per new SAV could earn a 19 % annual (long-term) return on investment while offering SAV services at $1.00 per mile for a non-shared trip (which is less than a third of Austin’s average taxi cab fare). read more read less
468 Citations
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SciSpace is a very innovative solution to the formatting problem and existing providers, such as Mendeley or Word did not really evolve in recent years.

- Andreas Frutiger, Researcher, ETH Zurich, Institute for Biomedical Engineering

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With SciSpace, you do not need a word template for Transportation.

It automatically formats your research paper to Springer formatting guidelines and citation style.

You can download a submission ready research paper in pdf, LaTeX and docx formats.

Time comparison

Time taken to format a paper and Compliance with guidelines

Plagiarism Reports via Turnitin

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Using this service, researchers can compare submissions against more than 170 million scholarly articles, a database of 70+ billion current and archived web pages. How Turnitin Integration works?

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Transportation format uses SPBASIC citation style.

Automatically format and order your citations and bibliography in a click.

SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

1. Can I write Transportation in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Transportation guidelines and auto format it.

2. Do you follow the Transportation guidelines?

Yes, the template is compliant with the Transportation guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Transportation?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Transportation citation style.

4. Can I use the Transportation templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Transportation.

5. Can I use a manuscript in Transportation that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Transportation that you can download at the end.

6. How long does it usually take you to format my papers in Transportation?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Transportation.

7. Where can I find the template for the Transportation?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Transportation's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Transportation's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Transportation an online tool or is there a desktop version?

SciSpace's Transportation is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Transportation?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Transportation?”

11. What is the output that I would get after using Transportation?

After writing your paper autoformatting in Transportation, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Transportation's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Transportation?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Transportation. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Transportation?

The 5 most common citation types in order of usage for Transportation are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Transportation?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Transportation's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Transportation in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Transportation Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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