Rejected from Transportation Research Part C? Where to Submit Next

This guide was checked on July 17, 2026 against current ScienceDirect TR-C pages, the TR-C Guide for Authors, Elsevier Article Transfer Service information, and adjacent Manusights TR-C pages.

Source-supported facts used here:

• ScienceDirect says TR-C publishes high-quality scholarly research on development, applications, and implications of emerging technologies in transportation systems.
• TR-C is not interested in individual technologies per se; it is interested in implications for planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components.
• Elsevier highlights impacts of emerging technologies on transportation system performance, including monitoring, efficiency, safety, reliability, resource consumption, and the environment.
• ScienceDirect lists topic areas including multimodal and intermodal transportation, on-demand transport, intelligent transportation systems, traffic and demand management, real-time operations, connected and autonomous vehicles, logistics, railways, resource and infrastructure management, aviation, pedestrians, and soft modes.
• ScienceDirect lists ISSN 0968-090X and online ISSN 1879-2359.
• TR-C submissions use Elsevier Editorial Manager at www.editorialmanager.com/trc.
• The TR-C Guide for Authors says the abstract word limit is 250 words and article highlights should be 3 to 5 bullet points, each a maximum of 85 characters including spaces.
• Elsevier's Article Transfer Service can recommend alternative journals after an unsuccessful submission, considering scope, readership, article type, acceptance rates, and previous-transfer performance.
• Recent ScienceDirect records include a neural-network travel-demand and scheduling model (DOI: 10.1016/J.TRC.2025.105512), long short-term memory traffic-speed prediction (DOI: 10.1016/J.TRC.2015.03.014), and drone-assisted parcel-delivery optimization (DOI: 10.1016/J.TRC.2015.03.005).

Facts intentionally avoided or caveated:

• No current acceptance rate, desk-rejection rate, median review time, APC amount, or appeal-success rate is stated as official.
• Existing Manusights TR-C pages were used for contradiction checks and internal routing, not as source of truth for volatile facts.
• This page uses official public facts plus Manusights review-pattern analysis. We did not use private acceptance-rate data, unpublished editor communications, or live search-position claims.

The rejection is useful only if you translate it into a route.

The central question is whether TR-C rejected the journal-family route or the transportation-system proof. Route problems can move quickly. Proof problems follow the manuscript.

Do not choose the next journal by prestige label. Choose it by what the rejected manuscript actually proves.

Recent and well-known TR-C article records show the range a rejected manuscript is competing with. A neural-network travel-demand and scheduling paper used the technology to model activity, destination, and mode-choice decisions across daily schedules. A long short-term memory traffic-speed paper tied the model to traffic prediction. A drone-assisted parcel-delivery paper connected optimization to a concrete logistics operation.

The pattern is not "AI equals TR-C." The pattern is technology plus transportation-system consequence. If the manuscript is a neural network with transportation data but no system decision, retarget or repair. If it is optimization theory with a generic transport example, TR-B or Transportation Science may be cleaner. If it is a deployment or ITS engineering benchmark, IEEE T-ITS may be the better reader.

Also check the compression test before retargeting. If the paper cannot state its transportation-system contribution inside a 250-word abstract and 3 to 5 85-character highlights, the rejected file probably still has a contribution-focus problem, not only a journal-name problem.

Accept transfer when:

• the rejection was mainly about TR-family fit, not weak evidence;
• the suggested journal owns the manuscript's real center of gravity;
• the abstract, cover letter, and first figure can be adjusted without hiding the original concern;
• the data and benchmark package is already credible.

Pause before accepting transfer when:

• the rejection questioned whether the technology changes any transportation-system outcome;
• reviewers or editors flagged weak baselines, missing ablation, thin simulation, or no external dataset;
• data cannot be shared and the limitation is not explained;
• the manuscript is generic AI, optimization, or logistics work wearing a TR-C label;
• the new journal would ask for the same benchmark, transferability, or reproducibility evidence.

A transfer offer saves upload friction. It does not repair a weak transportation claim.

In our pre-submission review work with Transportation Research Part C manuscripts, the recurring rejection risk is not weak computation in the abstract. It is the mismatch between an emerging-technology claim and a transportation-system consequence that reviewers can audit.

Five failure patterns decide the next route.

Technology demo without system consequence. The paper describes AI, sensing, CAV, V2X, reinforcement learning, simulation, ride-sharing, electric mobility, or platform technology, but the figures show only prediction loss, algorithm speed, or local improvement. TR-C asks what changes for planning, operation, safety, reliability, monitoring, resource consumption, or environmental performance. Repair means putting the transportation-system metric in the abstract and first figure.

Generic algorithm with a transportation dataset. A model trained on traffic, transit, mobility, logistics, or GPS data is not automatically a TR-C paper. If the method could be swapped into finance, energy, or healthcare with little change, the transportation contribution is probably too thin. Retarget to an AI venue or rebuild the manuscript around a transportation decision.

TR-family misrouting. Some rejected TR-C papers are good papers for TR-B, TR-D, or TR-E. A methodological optimization paper, emissions-focused paper, or logistics paper should not be forced into emerging technologies just because the implementation uses software. Routing is not a downgrade when it gets the right reviewer pool.

Benchmarking and transferability gap. TR-C reviewers expect realistic baselines, ablations, simulation validity, external or cross-network tests where possible, and an honest data availability statement. A single city, one simulator setting, or one proprietary dataset can still work, but only if the paper explains transfer limits.

Open-data story treated as compliance. The data and code statement is part of the editorial argument. If operator agreements, privacy, commercial restrictions, or sensor access prevent sharing, say so and provide enough derived data, pseudocode, calibration detail, or reproducibility pathway for the claim to be evaluated.

The Manusights information gain for this page is the routing distinction. A rejected TR-C manuscript is usually one of three things: an emerging-technology transportation paper that needs stronger evidence, a Transportation Research family paper for a different Part, or a generic technology paper using transportation as the testbed. The next submission should not begin until the authors know which one they have.