The enablers, opportunities and challenges of electric vehicle adoption in Qatar: A systematic review of the literature and assessment of progress toward transportation transformation targets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Governments around the world are working to reduce greenhouse gas emissions, and the transportation system is focal to the transition toward more renewable energy sources. The State of Qatar has transitioned buses in its public transportation system to be fully electric and has set a 2030 target for 10% of all new sales of vehicles to be electric vehicles (EVs). Although constrained by data limitations, this paper synthesizes and assesses the evidence and makes recommendations to support the transportation transition. OBJECTIVE: This paper assesses the available evidence on EV transitions in Qatar, identifying enablers and barriers through the use of a systematic literature review and data obtained from government sources within Qatar. METHODS: The systematic literature review was conducted in March of 2023 using two academic databases (Scopus and Web of Science). Only English language peer-reviewed articles, books, and conference proceedings pertaining to Qatar and EVs or EV charging stations were included. No resources were identified on an Arabic language database. RESULTS: The systematic review process identified 26 relevant publications, which is synthesized and critically assessed into the following thematic clusters: (a) assessments related to the electrical grid and diversifying the energy mix, (b) the planning and distribution of charging stations, and (c) knowledge, attitudes, and behaviors as it relates to the socio-cultural dimensions of EV adoption. DISCUSSION: The authors conclude that to meet the 2030 target, the State of Qatar must improve data collection for monitoring, rapidly expand charging station infrastructure, enable private sector engagement, and raise awareness regarding EVs to change consumer perception and choices. They explore the specific policy interventions that these domains require for the country to meet its transportation transition objectives. OTHER: This review received no funding, and the authors have no registration name or number to declare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it