Assessing the Factors Impacting Transport Usage of Mobility App Users in the National Capital Territory of Delhi, India

Round 1

Reviewer 1 Report

Manuscript ID : sustainability-1901481

Title : Assessing the factors impacting transport usage of mobility app users in the National Capital Territory of Delhi, India

 

This topic sounds very interesting because it makes the link between two essentials subjects : the transportation (which is mandatory for the whole population) and the sustainability (which is mandatory for our Earth). I think it’s an important thing to consider the digital phenomenon as a key to understand/implement/change transportation in a better ecological way. For these main reasons, I like the topic.

Authors explain with some examples, statistics, reports which is important to contextualize the research and to justify why they work on the mobile apps.

Considering the literature review, athors write a little sentence on the « Mobility-as-a-Service » which fits with this research. I think the theoretical argumentation could be enhance with a deeper explanation on « the use of mobile applications ». The MaaS should be more developed.

The authors could consider articles/researches from these literatures :

-       the « Uses and Gratification Theory » (applied here on the food delivery apps à : Ray, A., Dhir, A., Bala, P. K., & Kaur, P. (2019). Why do people use food delivery apps (FDA)? A uses and gratification theory perspective. Journal of Retailing and Consumer Services, 51, 221-230.)

-       the « Cost/benefit impacts on value perception of the app » (Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.).

It should improved the paper by examine why people will agree to use such new app dedicated to transport in India.

Considering the MaaS, authors write : « such platforms have either already been deployed or are 71 under trial in many cities across the world » : give examples ?

 

The section method/analysis is good but it can be improved.

The case study is well justified from a contextual point of view but it has not theoretical justification. Authors cite « As per the Census of India (2011) » : this information must be updated.

Concerning the « Likert’s scales », I don’t know why authors used their own scales. When authors want to develop a measure’s scale, the Churchill’s paradigm (1979) is used to identify items which will be used in surveys (with the classic process : PCA, EFA, CFA). In this research, authors choose to create their items for variables such as Transport Usage, Smartphone App Usage, Attitudes and Preferences ?. In marketing literature, it exists some scales that measure ad attitude (MacKenzie, S. B., & Lutz, R. J. (1989). An empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context. Journal of marketing, 53(2), 48-65.), brand attitude (Mitchell, A. A., & Olson, J. C. (1981). Are product attribute beliefs the only mediator of advertising effects on brand attitude?. Journal of marketing research, 18(3), 318-332.) or product attitude (Silvera, D. H., & Austad, B. (2004). Factors predicting the effectiveness of celebrity endorsement advertisements. European Journal of marketing). As an example, one of these scale could be used and adapted to preferences and attitudes.

That implies that the EFA part is not clear. We have the loadings but I do not see the scree plot or the % of variance explained that show how much dimensions the variable has. Does it mean that the 12 statements on the table 3 are relative to only one dimension of « Attitudes & Preferences of Smartphone Users towards Choice of Transport ».

From a conceptual point of view, I’m not sure that « attitudes and preferences » are the same concepts ?

The part on Latent Class Cluster Analysis is strong and very clear. The following discussion to identify classed helps to understand deeply which transport choices could be used/implemented depending these profiles and to « Assessing the factors impacting transport usage of mobility app users » (the title of this paper).

Finally, in discussion part, it could be interesting to also show your contributions regarding the existing literature and at which theoretical gap you have contributed.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

In this paper, the authors analyzed the relationship between the usage of Apps and transport modes by collecting some survey data. Some statistical analysis methods, such as Chi-square and clustering, are used. The paper is interesting and well-organized. I have the following comments that hope the authors consider.

 

1.     The authors said their survey is random sampling. But I do not think an online survey satisfies the random sampling requirement. Could the authors provide more details about the online survey, such as a comparison of socio-demographic information between the survey and the NCT of Delhi? Or the authors need to clarify that their survey is not randomly sampling.

2.     The authors summarized the variables considered in the survey. This is very good. Can the authors provide a survey questionnaire as an appendix?

3.     It is better to change the title of section 2.1 from ‘Case study’ to ‘Study area’.

4.     Although ICT is changing people’s life. However, this change is not always positive. For example, more information may increase travel costs. Such a phenomenon can be called information paradox. Some studies have reported the information paradox observed in experiments, such as route-choice experiments (Rapoport et al., 2014) and mode-choice experiments (Yang et al., 2022). The authors should discuss the potential adverse effects of ICT.

5.     The emergence of autonomous vehicles will change people’s travel behavior. Autonomous vehicles are also viewed as an excellent way to increase fuel efficiency (Wadud et al., 2016). Many studies have investigated the effects of autonomous vehicles on people’s attitudes, such as Kyriakidis et al. (2015), Hudson et al., (2019), Gkartzonikas et al., (2019) and Xing et al., (2021). The authors should discuss the potential effects of autonomous vehicles on people’s travel mode choices.

 

 

Reference

 

Rapoport, A., Gisches, E. J., Daniel, T., & Lindsey, R. (2014). Pre-trip information and route-choice decisions with stochastic travel conditions: Experiment. Transportation Research Part B: Methodological, 68, 154-172.

Yang, Y., Han, X., Jiang, R., Jia, B., & Gao, Z. Y. (2022). Competition and coordination in public transport: A mode choice experiment. Transportation Research Part C: Emerging Technologies, 143, 103858.

Wadud, Z., MacKenzie, D., & Leiby, P. (2016). Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles. Transportation Research Part A: Policy and Practice, 86, 1-18.

Gkartzonikas, C., & Gkritza, K. (2019). What have we learned? A review of stated preference and choice studies on autonomous vehicles. Transportation Research Part C: Emerging Technologies, 98, 323-337.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

The authors used latent class cluster analysis to empirically investigate the impacts of mobility apps on transport mode usage patterns in Delhi by classifying users into latent classes based on socioeconomic characteristics, attitudes/preferences, smartphone app usage, and mode usage pattern. It brings some novelty to the scientific community and the results are satisfactory. Nevertheless, I still have some concerns as below.

Major concerns:

1. The abstract is not well structured, making it difficult to get a full understanding of the research content of the paper. More than half of the abstract content describes the background of the study without detailing the research methods, findings, and conclusions. Please reorganize the content of the abstract to meet the requirements of a scientific paper.

2. The introduction is not well structured and it is difficult to understand the paper fully based on the introductory section. The presentation of the research methodology as well as the hypothesis is missing. And, it is recommended to describe the research gap in a more focused way.

3. It is suggested to add the contribution of this paper in the introduction.

4. The paper lacks a literature review section, which makes the innovative points of the paper lack credibility.

5. Overall, the structure of the article is a bit loose, and there is no linkage between the different chapters. This makes the article not very readable and credible. The authors emphasize throughout the article that exploring the impact of smartphones on travel preferences is important for sustainable transportation, but there is no logical relationship between them. It is recommended that the authors revise the paper to make the overall logical relationship stronger.

6. This paper empirically investigates the impact of mobile apps on the usage patterns of transport modes in Delhi, but the study is still not deep enough and the summary made in the conclusion is not cohesive enough.

7. In the conclusion, the authors should add a description of the limitations of this work and the direction of future work.

Minor concerns:

1. Some of the statements in the paper are difficult to understand and it is suggested to improve the language.

I hope these comments help the authors to improve the paper further.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

I have no further comments.

Reviewer 3 Report

It is very unfortunate that the author's revision is not satisfactory enough.

The authors have made detailed and informative work in that paper, with a lot of work and well-revised writing. However, the article is not innovative enough. "It has been found that younger users with higher education, more smartphone experience, medium to high household income and lower vehicle ownership have a very high probability of being classified as a multimodal traveller." The conclusion is a well-known finding using an improved method and lacks innovation. Moreover, this improved method is not theoretically innovative.