Rated 3.5 of 5.
Level of importance:
Rated 4 of 5.
Level of validity:
Rated 3 of 5.
Level of completeness:
Rated 3 of 5.
Level of comprehensibility:
Rated 4 of 5.
|I work currently with two of the authors of this article. I report to one of these authors directly in my work; they also supervised my Ph.D. six years ago.|
|Keywords:||COM-B, Moment of change, Climate change, COVID-19, People and their environment, Behaviour change|
In general, this is a useful commentary bringing together current mobility information and behaviour-change psychology to provide policy recommendations for transportation in the context of COVID-19 and climate change. The evidence-gathering to inform the commentary is a strong feature of the article, but also a potential weakness in so far as the limits of evidence from trends are not always acknowledged in the arguments that follow from them.
Sections 2 and 5: EV trends and COVID-19. You acknowledged the limitations of inferences from trends alone in section 6. A specific instance of this limitation is in section 2. Namely, trends in EV purchasing are difficult to link to the COVID 19 pandemic, a priori. This requires you to present either empirical evidence or a plausible argument to support such a link. If either (or both) of these are available, please present them to the reader alongside the information about EV trends in section 2. If neither are available, then please acknowledge a reason for including this information in the article other than a cause-effect or correlational link. For instance, could EV trends be relevant in terms of a moment of change afforded for EV adoption (which would help to justify inclusion of section 5.3., which seems to have little to do with COVID-19)?
Page 4: paragraph beginning "In April 2020, COVID-19 associated restrictions [...]" is a bit awkward, because the reader is probably expecting treatments at the national level (given the previous text), so to return to the global level at this stage is confusing. I suggest indicating this discursion using language (e.g., beginning with a clause like "Globally, ..." or "In a global context..." or "Concerning global COVID 19 associated restrictions...")
Section 2.1.: the information presented in 2.1. is lacking the close numerical/detailed support that is available in sections 2.2. and 2.3. For a 'data-based commentary', descriptions such as 'almost doubled', 'some', 'has decreased', 'an increased use of', etc., are not informative unless supported with clear and accurate evidence from the sources, because an 'increase' may be by a single unit and 'almost doubled' can be negligible if the original number was a single unit. Similarly, for subjective descriptors such as 'low' (p.4.) it is especially important to present information demonstrating why (in your opinion, which you want the reader to share) such descriptors are being used, rather than more neutral ones. I acknowledge that this may be due to the limitations of the evidence you have available (which seems to often be grey literature), in which case these limitations should be reported alongside this summary of 'data'.
Page 6: final paragraph of section 2.3. There should be a clear statement of the time period for this statistic; as this is a single-sentence paragraph, it may also be an opportunity for comment on issues to do with linking EV trends and COVID 19, mentioned above?
Page 8: "Government restrictions on [...] transport." It would be useful to have factual information on the effectiveness and or extent of these measures. I realise that Appendix 3 gives a useful overview on measures in general and their timing, but adding information on these measures specifically would support this argument about opportunities for public transport. (If there is not strong evidence on efficacy or information on extent of measures and their consequences, then perhaps qualify these as 'good ideas' rather than as events that were known to provide such opportunities.)
Page 9: "for example with the use of low-traffic neighbourhoods, [...] motivation for using private transport." It would be useful to support this by citing evidence of the efficacy of such measures.
Page 10: "Employees working from home reduce their transport-related behaviours." This may be so in practice, but it does not follow invariably, as commuting is not the only purpose of travel. A slight re-phrasing (e.g., reduced commuting) would be prudent.
Section 5.1.: it would be worth acknowledging that not all work can be done from home, this text applying mostly to 'white collar' work. This may be increasingly more relevant in the countries focused upon in this article, with ongoing shifts towards service and technology sector employment, but there remains a necessary and substantially subset of people for whom work is location-based or travel-based by necessity. This may be worth a sentence to acknowledge, perhaps providing statistics about capabilities of reductions (i.e., how many people can work from home), if they are available.
Page 10: "Intentions to use private vehicles more, after restrictions end, were identified, and sales of Electric Vehicles increased in all three countries." Given that this is a review of evidence, it would do no harm to remind the reader of the previously cited evidence for these points by citing it again.
Please provide a complete reference for van Hagen, M., & Ton, D. (2020). Corona’s impact on the behavior of train passengers. This information is insufficient for identifying the source in question.