Analysis of the Technical and Commercial Factors That Influence the Acquisition of Hybrid Vehicles in the City of Guayaquil

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript investigates factors influencing hybrid vehicle (HV) purchase intention in in a specific Latin American urban context. The mixed-methods approach, combining consumer surveys with dealership interviews, is a strength that provides valuable multi-stakeholder insights. Key findings from the Spearman correlation analysis suggest that technical factors (technology/performance, maintenance) have a stronger association with purchase intention than commercial factors, have practical implications for policymakers and industry stakeholders in similar emerging markets. However, in its current form, the manuscript requires revisions before it can be considered for publication. The most significant concerns relate to the presentation and justification of the methodological approach, sampling bias, the clarity and depth of the results section, and conceptual confusion in variable definitions. Specific, actionable points for revision are detailed below.

1. The quantitative findings are built on a sample that has sources of bias. The sample is 87.5% male. The authors briefly mention this as a limitation in the discussion but underestimate its impact. A finding based almost exclusively on male respondents cannot be generalized to consumers or households, as vehicle purchasing is often a joint decision. This severe skew must be highlighted as a major limitation in the abstract, methodology, and discussion. The authors should re-frame their findings to reflect this.
2. In Section 4.2, the authors state: "purchase price stands out as the most decisive factor (84.2%)." This is based on descriptive statistics. In Section 4.3, the authors state: "price being the least significant factor among those analyzed." This is based on the Spearman correlation, which shows it has the weakest (though still moderate) association with purchase intention. The authors cannot claim both. They must clarify their main finding. Is it that consumers say price is important, or is it that price variation actually correlates more weakly with purchase intention than technical factors.
3. Table 6 shows Environmental Influence has a strong correlation. However, Appendix B, Question 2 (the survey item for this variable) asks about "the opinion of your social circle (family, friends, social media, or influencers)." This is a measure of Social Influence or Social Norms, not environmental concern.
4. Table 1 contains a clear technical error. It incorrectly labels "Mild hybrid vehicle" with the acronym "PHEV." A PHEV is a "Plug-in hybrid vehicle" (which is also listed correctly as a separate category). This error undermines the technical credibility of the paper and must be corrected.
5. The introduction states the aim is to analyze "technical and commercial factors," but the variables studied (like "environmental influence") seem more socio-cultural. Please clarify the definitions and categorization of factors (technical, commercial, socio-cultural) more precisely.
6. The manuscript dedicates a substantial section to the PRISMA flowchart for the literature review. While systematic reviews are valuable, the connection between this PRISMA process and the primary empirical research (surveys and interviews) is not well-explained. It is unclear how the 28 included studies directly informed the survey design or interview protocol. 

Author Response

Commet:

1. The quantitative findings are built on a sample that has sources of bias. The sample is 87.5% male. The authors briefly mention this as a limitation in the discussion but underestimate its impact. A finding based almost exclusively on male respondents cannot be generalized to consumers or households, as vehicle purchasing is often a joint decision. This severe skew must be highlighted as a major limitation in the abstract, methodology, and discussion. The authors should re-frame their findings to reflect this.

Response:

We thank them for their comments. We agree that the sample has a significant bias (87.5% male participants) and that this limits the generalizability of the findings. The survey was conducted in an environment with predominantly male attendance (Auto Show 2025 and dealerships), so the results describe primarily perceptions of males interested in vehicles and cannot be extrapolated without caution to households or the universe of consumers. We have made the following changes:

abstract: we added an explicit caveat of major limitation for gender bias and reframed the findings as valid for a male subset of potential buyers.

Methodology: we detail the sample frame (convenience sample at trade show/dealership) and report the gender distribution (87.5% male; 11.7% female; 0.8% no response).

Limitations: Elevated the gender composition to a major limitation and outlined remedies for future work (broader recruitment beyond events/dealerships, gender-balanced quotas, and/or post-stratification when benchmarks are available).

We recognize that, in the local context, attendance at fairs and interaction in dealerships is overrepresented by men; however, we present this as a reason for the bias, not as a justification for generalization.

Commet:

2. In Section 4.2, the authors state: "purchase price stands out as the most decisive factor (84.2%)." This is based on descriptive statistics. In Section 4.3, the authors state: "price being the least significant factor among those analyzed." This is based on the Spearman correlation, which shows it has the weakest (though still moderate) association with purchase intention. The authors cannot claim both. They must clarify their main finding. Is it that consumers say price is important, or is it that price variation actually correlates more weakly with purchase intention than technical factors.

Response:

We agree that our wording conflated two different constructs: (i) stated salience (how many respondents say a factor is decisive) versus (ii) discriminative association (how variation in a factor relates to variation in purchase intention). In our data, price is almost universally cited as decisive (84.2%), which implies high salience and low variance (a ceiling effect). Precisely because most respondents rate price as important, differences in purchase intention within the sample are less explained by price ratings than by technical attributes, which vary more across respondents. We have revised the manuscript to make this explicit, avoid the term “least significant,” and state instead that price shows the weakest monotonic association with purchase intention among the analyzed variables, while remaining highly salient. Edits were made in Sections 4.2, 4.3, the Discussion, and the Abstract

Commet:

3. Table 6 shows Environmental Influence has a strong correlation. However, Appendix B, Question 2 (the survey item for this variable) asks about "the opinion of your social circle (family, friends, social media, or influencers)." This is a measure of Social Influence or Social Norms, not environmental concern.

Response:

You are correct: Appendix B, Q2 captures Social Influence/Subjective Norms (the perceived influence of one’s social circle), not environmental concern. We have therefore re-labeled the construct throughout the manuscript from “Environmental Influence” to “Social Influence (Subjective Norms)” without altering any data or statistics. All references in Sections 4.2–4.3, Table 6, the Discussion, and Appendix B have been updated accordingly. The strong association reported in Table 6 now explicitly pertains to Social Influence, which is theoretically consistent with adoption models where subjective norms relate to purchase intention. We also clarify that “Environmental concern” is not measured by Q2 and avoid drawing environmental-attitude inferences from that item.

Commet:

4. Table 1 contains a clear technical error. It incorrectly labels "Mild hybrid vehicle" with the acronym "PHEV." A PHEV is a "Plug-in hybrid vehicle" (which is also listed correctly as a separate category). This error undermines the technical credibility of the paper and must be corrected.

Response:

We have corrected “Mild hybrid vehicle (PHEV)” to “Mild hybrid electric vehicle (MHEV)” in Table 1. No numerical results are affected.

Commet:

5. The introduction states the aim is to analyze "technical and commercial factors," but the variables studied (like "environmental influence") seem more socio-cultural. Please clarify the definitions and categorization of factors (technical, commercial, socio-cultural) more precisely.

Response:

We appreciate this observation and agree that the construction captured by Appendix B, Q2 reflects Social Influence rather than environmental concern. In this study, we grouped that item under the commercial domain for a practical reason: it was the only question covering that dimension and it operationalizes market-facing communications (word-of-mouth, social media, influencers) that firms typically activate through promotional tools. Because we did not design a multi-item socio-cultural scale, we adopted a conservative, operational classification for this dataset. We mentioned this in introduction section.

To avoid misunderstanding, we will (i) label the variable as Social Influence throughout, (ii) explicitly state in Materials and Methods that, while conceptually connected to socio-cultural norms, here it is treated as a commercial/market-communications indicator given our instrument, also mentioned in discussion. These clarifications do not affect the analyses or conclusions.

Commet:

6. The manuscript dedicates a substantial section to the PRISMA flowchart for the literature review. While systematic reviews are valuable, the connection between this PRISMA process and the primary empirical research (surveys and interviews) is not well-explained. It is unclear how the 28 included studies directly informed the survey design or interview protocol. 

Response:

The PRISMA process was not intended as a standalone systematic review of outcomes but as an input to instrument development. Specifically, the 28 included studies were used to: (i) identify and prioritize candidate constructs for our context (price, total cost of ownership, core technical attributes, charging/maintenance considerations, brand/after-sales, and Social Influence), (ii) adapt item wordings and scale formats for the survey (Likert anchors, brevity), and (iii) structure the interview topic guide (prompts mirroring the same construct set to enable triangulation). We have revised the manuscript to make this linkage explicit, added a mapping table connecting each construct to its survey item(s) and interview questions

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript presents an analysis of the technical and commercial factors influencing the acquisition of hybrid vehicles in Guayaquil. While the topic is relevant and the study addresses an important area of research, the manuscript requires significant revisions to enhance its clarity, methodological rigor, and overall coherence. The following points outline specific concerns that should be addressed to improve the quality of the paper.

(1) In Table 6, "Correlation Results Between Variables," each row lists only one variable. It is unclear which specific pair of variables each correlation coefficient represents.

(2) Regarding Table 6, how were the p-values calculated? Why are they all reported as "<0.001"? Such consistently low values appear unusual. Please provide the detailed calculation process and the exact p-values.

(3) The figures and tables in the manuscript are somewhat blurry. Please replace them with clearer screenshots or higher-resolution versions.

(4) The purpose of the question, "How important is it to you that a hybrid vehicle offers 30% to 50% lower maintenance costs due to reduced engine wear, brake wear, and fewer mechanical repairs compared to conventional gasoline vehicles?" is unclear. Moreover, this statement seems inconsistent with the current reality, as hybrid vehicles typically incur higher maintenance costs.

(5) Regarding the question, "How important is the price range of hybrid vehicles in Ecuador (between $25,000 and $45,000) in influencing your purchase decision?" what is the rationale for examining the importance of price? If vehicle performance is not considered, why is this specific price range being studied? What is the objective of this question?

(6) Which questions in the survey are related to "commercial factors"? The terminology used in the title ("technical and commercial factors") appears inconsistent with that in the abstract.

(7) The symbol "ρ =" in the abstract is unclear without referring to the main text. Its meaning should be explicitly defined.

(8) What is the relationship between "purely environmental" factors and the "commercial variables" mentioned in the abstract? How are "purely environmental" factors investigated, and what variables are used? This is not clearly explained in the abstract.

(9) How is "public awareness" demonstrated in the study? The term appears only in the abstract and is not elaborated upon in the main text.

(10) Why does the study focus solely on hybrid vehicles and not include purely electric vehicles?

(11) What is the relationship between Section 4.4, "Results of Interviews with Automotive Brand Representatives," and the questionnaire analysis?

(12) Section 4.3, "Correlation Analysis and Strategic Relevance," seems to focus on analyzing correlations. However, if the study aims to identify key factors influencing users' choice of hybrid vehicles, why is the analysis limited to correlations? There is no further examination of how these factors affect purchase intention.

(13) Table 2, "Survey Table for Technical Factors," lacks references to supporting literature. What is the basis for selecting these indicators? Are they reasonable and comprehensive? How do the indicators in Table 2 relate to those in Table 3? How to cluster these factors?

Author Response

Commet:

• In Table 6, "Correlation Results Between Variables," each row lists only one variable. It is unclear which specific pair of variables each correlation coefficient represents.

Response:

Each coefficient reports a bivariate Spearman correlation between the listed factor and the dependent variable “purchase intention” (Appendix B, Q1). To avoid ambiguity, we have revised the caption, renamed the second column to “ρ with purchase intention”, and added a footnote that states the variable pair explicitly. We also keep the interpretation ranges and p-values unchanged. In the revised manuscript this appears as Table7

Commet:

(2) Regarding Table 6, how were the p-values calculated? Why are they all reported as "<0.001"? Such consistently low values appear unusual. Please provide the detailed calculation process and the exact p-values.

Response:

All bivariate Spearman rank correlations were computed in Minitab 22.4 (Minitab, LLC) using the Correlation command with the Spearman option (two-sided test, default settings; ). In line with our journal’s reporting style, p-values are displayed to three decimals; when the value is below 0.001, Minitab’s output is reported as “<0.001”. Given the sample size and effect magnitudes, all tests met this threshold.

Commet:

(3) The figures and tables in the manuscript are somewhat blurry. Please replace them with clearer screenshots or higher-resolution versions.

Response:

Resolution improved

Commet:

(4) The purpose of the question, "How important is it to you that a hybrid vehicle offers 30% to 50% lower maintenance costs due to reduced engine wear, brake wear, and fewer mechanical repairs compared to conventional gasoline vehicles?" is unclear. Moreover, this statement seems inconsistent with the current reality, as hybrid vehicles typically incur higher maintenance costs.

Response:

The survey item is not a factual claim about every market; it is a stated-importance scenario calculated to our local context in Guayaquil. Before fielding, we reviewed technical sheets, consulted dealership service schedules, and interviewed local experts, who indicated that routine maintenance over a 3–5-year horizon (e.g., fewer brake pad replacements due to regenerative braking, longer intervals with engine-off usage) can be meaningfully lower than for comparable ICE models. We acknowledge that this relationship may differ in other economies depending on labor costs, parts availability, and warranty coverage, and that some hybrid components can increase unscheduled repair costs in certain settings. To avoid misunderstanding, we clarify in Materials and Methods that the item measures perceived importance under a locally supported scenario about routine maintenance (excluding battery replacement)

Commet:

(5) Regarding the question, "How important is the price range of hybrid vehicles in Ecuador (between $25,000 and $45,000) in influencing your purchase decision?" what is the rationale for examining the importance of price? If vehicle performance is not considered, why is this specific price range being studied? What is the objective of this question?

Response:

We examine purchase price because it is consistently identified—both in our literature scoping and in local expert consultations—as a primary commercial driver of adoption. The range USD 25,000–45,000 reflects the prevailing transaction prices of mainstream hybrid models in Ecuador at the time of data collection, providing respondents with a realistic budget anchor. The item’s objective is not to test price–performance trade-offs (those technical attributes are assessed elsewhere in the instrument), but to measure the stated importance of price within the locally relevant band that buyers face. To avoid misunderstanding, we now state explicitly that performance is held constant at typical segment levels for this question in Material and Methods section

Commet:

(6) Which questions in the survey are related to "commercial factors"? The terminology used in the title ("technical and commercial factors") appears inconsistent with that in the abstract.

Response:

In the revised manuscript we keep the scope aligned with the title— “technical and commercial determinants”—already reflected in the Abstract (lines 7–10) and in the factors listed there (Social Influence, Public Policies, Purchase Price) The survey items that operationalize commercial factors are Appendix B:

• Q5: Public policies / tax exemptions.
• Q6: Purchase price (USD 25,000–45,000).
• Q2: Social Influence—treated in this study as a market-communications (commercial) indicator at the interface with socio-cultural norms (Appendix B; and mapped in Methods/Table 2).

This classification is consistent with the Methods section, where “commercial factors” include purchase price and government policies (among others).

Regarding the Abstract–title alignment: the revised Abstract already states that the study analyzes technical and commercial determinants (lines 7–10) and reports results for price and public policies (commercial) alongside technical attributes and Social Influence (treated as a market-communications indicator).

Commet:

(7) The symbol "ρ =" in the abstract is unclear without referring to the main text. Its meaning should be explicitly defined.

Response:

We agree that the symbol should be defined at first mention. We have revised the Abstract to state “Spearman’s rank correlation coefficient (ρ)” before reporting the values, and we added ρ to the Abbreviations list for consistency. No analyses or results changed.

Commet:

(8) What is the relationship between "purely environmental" factors and the "commercial variables" mentioned in the abstract? How are "purely environmental" factors investigated, and what variables are used? This is not clearly explained in the abstract.

Response:

In the revised manuscript we analyze technical and commercial determinants only. We do not model purely environmental attitudes as standalone variables in this instrument. Earlier drafts used the label “Environmental Influence,” which we have corrected to Social Influence (Subjective Norms) and treated as a commercial indicator of market communications and peer signals. The Abstract has been edited to reflect this scope, and a brief note in Methods clarifies that purely environmental attitudes were not measured as separate constructs. No analyses or results changed.

Commet:

(9) How is "public awareness" demonstrated in the study? The term appears only in the abstract and is not elaborated upon in the main text.

Response:

We agree that the earlier wording was ambiguous. The term public awareness in the Abstract has been replaced with public policy instruments with information campaigns, which aligns with the variables measured in the study. We did not administer a standalone public awareness scale. The commercial set includes public policy incentives (tax or fee exemptions), purchase price, and social influence treated as market communications. We added a short scope note in Methods to make this explicit. No analyses or results changed.

Commet:

(10) Why does the study focus solely on hybrid vehicles and not include purely electric vehicles?

Response:

We intentionally limited the scope to hybrid vehicles for three reasons. First, during the study period the market share of purely electric vehicles in Ecuador was marginal, which would not support a representative sample or stable estimates. Second, our instrument was calibrated to hybrid specific attributes and local purchasing conditions (for example routine maintenance, interaction with the internal combustion engine, and the price band used in the survey). Including battery electric vehicles would require different constructs such as home charging access, public charging reliability, and range management, which would confound the interpretation of our hybrid results. Third, the price band in the questionnaire reflects current transaction prices of mainstream hybrid models; battery electric models follow a different distribution in this market. For these reasons we chose depth over breadth and reserved battery electric vehicles for a separate, dedicated study. We have added a brief scope note in the Introduction and Methods to make this explicit.

Commet:

(11) What is the relationship between Section 4.4, "Results of Interviews with Automotive Brand Representatives," and the questionnaire analysis?

Response:

Section 4.4 is not a stand-alone narrative. It is the qualitative strand that integrates with the questionnaire results in Sections 4.2–4.3. The interviews use the same construct set as the survey (price, public policies, technical attributes, maintenance, social influence) and were designed to explain, contextualize, and bound the quantitative patterns rather than to re-estimate effects. We have added (i) a short integration note in Methods describing the convergent design, and (ii) an opening paragraph in Section 4.4 that states the link to Sections 4.2–4.3

Commet:

(12) Section 4.3, "Correlation Analysis and Strategic Relevance," seems to focus on analyzing correlations. However, if the study aims to identify key factors influencing users' choice of hybrid vehicles, why is the analysis limited to correlations? There is no further examination of how these factors affect purchase intention.

Response:

Section 4.3 quantifies how each factor relates to the dependent variable purchase intention through bivariate Spearman rank correlations (two sided, computed in Minitab 22.4) and interprets ρ as a prioritization signal for decision making in this market. We have revised the opening of Section 4.3 and the table caption to state explicitly that each coefficient is between the listed factor and purchase intention. Our aim is to identify which factors are most closely associated with intention in this sample, not to claim causal effects. Because the survey uses single item indicators and several factors are interrelated, we intentionally refrain from multivariable modeling in this paper to avoid unstable coefficients. We have already added footnotes and references to this in one of your previous comments

Commet:

(13) Table 2, "Survey Table for Technical Factors," lacks references to supporting literature. What is the basis for selecting these indicators? Are they reasonable and comprehensive? How do the indicators in Table 2 relate to those in Table 3? How to cluster these factors?

Response:

Thank you for the opportunity to clarify. The technical indicators in Table 2  were pre specified through a PRISMA guided scoping of the literature, a review of manufacturer technical sheets and local service schedules, and expert input from dealership and academic practitioners. This process led us to a compact set that is reasonable for the local hybrid market and comprehensive for our survey length.

Reviewer 3 Report

Comments and Suggestions for Authors

All comments are here.

The article “Analysis of the technical and commercial factors that influence the acquisition of Hybrid Vehicles in the city of Guayaquil” written by  Emerson Altamirano-Cañizares et al. offers a comprehensive and empirically grounded analysis of the factors influencing hybrid vehicle adoption in Guayaquil, addressing a topic of growing relevance for sustainable urban mobility in emerging economies. The study’s mixed-methods design, combined with quantitative validation through Spearman’s correlation, provides a solid methodological framework for identifying key determinants of purchase decisions. From a policy and business perspective, the study provides actionable insights. It effectively highlights how public awareness gaps limit the impact of existing incentives and calls for coordinated public–private communication strategies and infrastructure investments—particularly in charging networks—to accelerate adoption. The recommendations for targeted public education campaigns and strategic deployment of charging stations are well-founded and directly applicable to local governance and industry stakeholders. The research also contributes conceptually to the diffusion of innovations framework, contextualizing it within the Ecuadorian market by integrating local economic and informational variables. This theoretical refinement enhances the study’s academic value and relevance to scholars studying technology adoption in developing contexts.

However, I have some reservations about the reliability of the adopted methodology. The authors conducted surveys among 384 respondents. Statistical studies often rely on a sample size of at least 1,000 people, as this provides a reasonable compromise between research costs and the reliability and precision of results. From a statistical theory perspective, sample size determines the estimation error (the so-called margin of error). For a sample of n = 1,000, at a 95% confidence level, the margin of error for the proportion is approximately ±3%. This is considered sufficiently precise in most social studies and surveys. If the number of respondents is reduced to 384, this value increases to approximately ±5.0%. Furthermore, the study lacks information regarding the methods for validating the survey results. The authors did not specify how they assessed whether respondents answered the questions reliably. Furthermore, they used a 5-point Likert scale in the survey, whereas a 7-point equivalent is recommended today. A separate issue is the assessment of the Sperman correlation coefficient. In the manuscript (L. 420-423), the authors provide values ​​that are underestimated compared to typical literature data (see https://www.statstutor.ac.uk/resources/uploaded/spearmans.pdf). For example, in the case of ρ = 0.35, the authors assume a moderate correlation, while in reality, we are dealing with a weak correlation. I have the impression that these values ​​were deliberately underestimated to better align with the authors' theses. Nevertheless, I am not dismissing this work as a whole, as it may have some contribution to the broader topic of electromobility. However, I would ask for a more cautious approach to theses, e.g., "It was evident ..." (L. 504); it would be safer to write something like "It can be assumed that ...". I believe that, after such corrections, the submitted manuscript could be suitable for publication in WEVJ. Below is a list of additional comments:

1. In the abstract, it might be more appropriate to state that the p-value was less than 0.001 for all cases, suggesting that the study had sufficient statistical power. It should be noted, however, that this does not imply the resultant uncertainty of the obtained results, as it merely highlights the model's fit to the data;
2. Quality of Fig. 1 is rather poor – it is very blurry;
3. I would suggest reversing the order of sections 2 and 3. Initially, I wanted to say that the authors did not conduct a full literature review, but merely provided information regarding the current state of knowledge on the topic of the work. However, after reviewing the methodology section, I understood that they conducted a literature review in accordance with the PRISMA standard;
4. I would appreciate a correction to Table 1, as its current version is difficult to read. Individual bullet points in the General Characteristic column blend together. Furthermore, the FCEV description uses the symbol "." twice. I would also suggest including information about the data source in the table description, rather than duplicating it several times within the table itself (e.g., you could add "... on the basis of [22]");
5. In L.146 please use subscript in CO₂;
6. In some cases, the captions of figures and tables are too laconic, which may be inconvenient for some readers;
7. Figure 2 is terribly sloppy. The individual rectangles are not only different sizes but also unevenly spaced. Furthermore, in some places, the lines overlap the text.
8. The way lists are written in the text (e.g. L.272-275; L.347-350; L.355 - 360) is incorrect - compare with the layout of this review;
9. The data from subsection 4.1 could be usefully illustrated using a pie chart.

Author Response

Commet:

However, I have some reservations about the reliability of the adopted methodology. The authors conducted surveys among 384 respondents. Statistical studies often rely on a sample size of at least 1,000 people, as this provides a reasonable compromise between research costs and the reliability and precision of results. From a statistical theory perspective, sample size determines the estimation error (the so-called margin of error). For a sample of n = 1,000, at a 95% confidence level, the margin of error for the proportion is approximately ±3%. This is considered sufficiently precise in most social studies and surveys. If the number of respondents is reduced to 384, this value increases to approximately ±5.0%. Furthermore, the study lacks information regarding the methods for validating the survey results. The authors did not specify how they assessed whether respondents answered the questions reliably. Furthermore, they used a 5-point Likert scale in the survey, whereas a 7-point equivalent is recommended today.

Response:

We clarify and document four aspects:

1. Sample size and precision. Our targetable population was filtered to potential buyers; using the finite-population formula with and 95% confidence yields , which we report and show in the manuscript (eq. and inputs). As we use a convenience frame (auto show and dealerships), we treat the classical margin-of-error as a design target rather than an inferential guarantee and frame results as associations within this sample, not city-wide estimates. We now state this explicitly in Methods.
2. Validation and reliability. The instrument’s content was built from literature, technical sheets and local schedules, then expert-judged for clarity, relevance and coherence; we conducted a preliminary survey to refine items; and internal consistency is Cronbach’s α = 0.83 (95% CI 0.80–0.86) with item diagnostics, all now summarized in Methods/Results.
3. What the correlations measure. Section 4.3 already analyzes bivariate Spearman correlations with purchase intention and labels the table accordingly; we added a brief note in the section and table footnote to make the dependent variable explicit and to record that calculations were performed in Minitab 22.4.
4. Scale choice (5-point vs 7-point). The survey uses a 5-point Likert (Appendix B). We kept 5 points after the pre-fielding step to reduce respondent burden at an in-person event, maintain anchor clarity, and because reliability was high (α=0.83). We add a one-sentence justification in Methods and acknowledge that a 7-point variant could be explored in future work.

Commet:

A separate issue is the assessment of the Sperman correlation coefficient. In the manuscript (L. 420-423), the authors provide values ​​that are underestimated compared to typical literature data (see https://www.statstutor.ac.uk/resources/uploaded/spearmans.pdf). For example, in the case of ρ = 0.35, the authors assume a moderate correlation, while in reality, we are dealing with a weak correlation. I have the impression that these values ​​were deliberately underestimated to better align with the authors' theses. Nevertheless, I am not dismissing this work as a whole, as it may have some contribution to the broader topic of electromobility.

Response:

Our qualitative labels for correlation strength were not chosen ad hoc. They follow Cohen’s conventional effect-size guidelines for correlations—small , medium , large —which are widely used in behavioral and social research. Under this convention, a coefficient around ρ ≈ 0.35 is described as “medium/moderate.” See Cohen’s Statistical Power Analysis for the Behavioral Sciences (2nd ed., Routledge; DOI: 10.4324/9780203771587) and Cohen’s “A Power Primer” (Psychological Bulletin, 1992; DOI: 10.1037/0033-2909.112.1.155). Taylor & Francis+1

We recognize that different guides adopt different bands (for example, the Statstutor sheet the reviewer cited uses another scheme), which can lead to apparent discrepancies in adjectives even when the numerical coefficients are identical.

 

Commet:

However, I would ask for a more cautious approach to theses, e.g., "It was evident ..." (L. 504); it would be safer to write something like "It can be assumed that ...". I believe that, after such corrections, the submitted manuscript could be suitable for publication in WEVJ. Below is a list of additional comments:

Response:

We have revised phrasing across the Abstract, Results, and Discussion to avoid overstatement and to reflect association-based evidence. Specifically, we replaced assertive formulations (e.g., “It was evident…”, “clearly shows”, “proves”) with cautious alternatives (e.g., “the evidence suggests…”, “indicates”, “can be assumed within this sample”). We also added qualifiers such as “within this male-dominated sample” and “based on the observed associations” where appropriate

Commet:

In the abstract, it might be more appropriate to state that the p-value was less than 0.001 for all cases, suggesting that the study had sufficient statistical power. It should be noted, however, that this does not imply the resultant uncertainty of the obtained results, as it merely highlights the model's fit to the data;

Response:

Thank you for the suggestion. We have revised the abstract to state that all two-sided tests yielded , which is consistent with adequate statistical power given . We also add a brief caution that statistical significance does not convey effect magnitude or overall uncertainty, and that interpretation relies on the reported Spearman’s and the observed ordering of factors. Calculations were performed in Minitab 22.4

Commet:

Quality of Fig. 1 is rather poor – it is very blurry;

Response:

Resolution improved

Commet:

I would suggest reversing the order of sections 2 and 3. Initially, I wanted to say that the authors did not conduct a full literature review, but merely provided information regarding the current state of knowledge on the topic of the work. However, after reviewing the methodology section, I understood that they conducted a literature review in accordance with the PRISMA standard;

Response:

To avoid the initial ambiguity, we have reordered the sections so that the Methods (including the PRISMA-guided scoping and its link to the instrument) appear before the literature synthesis. The new order is:

• Section 2. Materials and Methods (with a brief summary of the PRISMA process and a pointer to the Supplementary flowchart);
• Section 3. Background and Literature Synthesis (summary of the 28 studies informed by Section 2).

We also added one bridging sentence at the start of Section 3 to state that it synthesizes the evidence identified via the PRISMA process described in Section 2

Commet:

I would appreciate a correction to Table 1, as its current version is difficult to read. Individual bullet points in the General Characteristic column blend together. Furthermore, the FCEV description uses the symbol "." twice. I would also suggest including information about the data source in the table description, rather than duplicating it several times within the table itself (e.g., you could add "... on the basis of [22]");

Response:

We have reformatted Table 1 (now table 6) to improve readability by using a structured bullet list within a wide column, increased row spacing, and consistent punctuation. The duplicated period in the FCEV description has been removed. We also consolidated the data source into the table caption (“based on [22]”) and removed repeated citations inside the cells.

Commet:

In L.146 please use subscript in CO2;

Response:

It changed

Commet:

In some cases, the captions of figures and tables are too laconic, which may be inconvenient for some readers;

Response:

Our initial choice was to keep captions concise to avoid duplicating material already explained in the surrounding text and to maintain a clear layout. Following the review, we expanded captions where additional context genuinely aids reading—for example, we now include what the item shows, why it matters, the data source, and brief reading guidance (and we consolidated sources in the caption “Note” to avoid repetition inside cells).

For items whose content is fully described in the adjacent paragraphs (e.g., mechanism diagrams or taxonomy tables), we kept captions succinct by design so the manuscript remains readable and non-redundant. We believe this strikes a good balance between accessibility and economy of presentation.

Commet:

Figure 2 is terribly sloppy. The individual rectangles are not only different sizes but also unevenly spaced. Furthermore, in some places, the lines overlap the text.

Response:

It was improved

Commet:

The way lists are written in the text (e.g. L.272-275; L.347-350; L.355 - 360) is incorrect - compare with the layout of this review;

Response:

We have standardized list formatting throughout the manuscript. Informal dash-led sequences were replaced with proper LaTeX list environments: (i) inline enumerations inside a paragraph when the items form a single sentence, and (ii) display enumerations when items merit line breaks. We also unified punctuation (semicolon between items, period at the end of the last item). These edits improve readability only; no content was changed. The affected passages around L.272–275, L.347–350, and L.355–360 were updated accordingly.

 

Commet:

The data from subsection 4.1 could be usefully illustrated using a pie chart.

Response:

We have added a pie chart (Fig. 4) that visualizes the §4.1 distribution with labels and percentages (and ).

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

As for response to these two comments, please add data and data source to justify the statements in the response.

 

(4) The purpose of the question, "How important is it to you that a hybrid vehicle offers 30% to 50% lower maintenance costs due to reduced engine wear, brake wear, and fewer mechanical repairs compared to conventional gasoline vehicles?" is unclear. Moreover, this statement seems inconsistent with the current reality, as hybrid vehicles typically incur higher maintenance costs.

And (10) Why does the study focus solely on hybrid vehicles and not include purely electric vehicles?

Author Response

Comment:

The purpose of the question, "How important is it to you that a hybrid vehicle offers 30% to 50% lower maintenance costs due to reduced engine wear, brake wear, and fewer mechanical repairs compared to conventional gasoline vehicles?" is unclear. Moreover, this statement seems inconsistent with the current reality, as hybrid vehicles typically incur higher maintenance costs.

Response:

The survey item is not a factual claim about every market; it is a stated-importance scenario calculated to our local context in Guayaquil. Before fielding, we reviewed technical sheets, consulted dealership service schedules, and interviewed local experts, who indicated that routine maintenance over a 3–5-year horizon (e.g., fewer brake pad replacements due to regenerative braking, longer intervals with engine-off usage) can be meaningfully lower than for comparable ICE models. We acknowledge that this relationship may differ in other economies depending on labor costs, parts availability, and warranty coverage, and that some hybrid components can increase unscheduled repair costs in certain settings. To avoid misunderstanding, we clarify in Materials and Methods (pp. 9-10)that the item measures perceived importance under a locally supported scenario about routine maintenance (excluding battery replacement)

Comment:

Why does the study focus solely on hybrid vehicles and not include purely electric vehicles?

Response:

We intentionally limited the scope to hybrid vehicles for three reasons. First, during the study period the market share of purely electric vehicles in Ecuador was marginal, which would not support a representative sample or stable estimates. Second, our instrument was calibrated to hybrid specific attributes and local purchasing conditions (for example routine maintenance, interaction with the internal combustion engine, and the price band used in the survey). Including battery electric vehicles would require different constructs such as home charging access, public charging reliability, and range management, which would confound the interpretation of our hybrid results. Third, the price band in the questionnaire reflects current transaction prices of mainstream hybrid models; battery electric models follow a different distribution in this market. For these reasons we chose depth over breadth and reserved battery electric vehicles for a separate, dedicated study. We have added a brief scope note in the Introduction and Methods (pp. 3, 10) to make this explicit. 

Reviewer 3 Report

Comments and Suggestions for Authors

The authors comprehensively addressed my comments and objections. Their responses addressed my main concerns regarding the reviewed work. Furthermore, the manuscript has been significantly improved compared to the original. As I wrote in my previous review, I believe this work has innovative aspects and contributes to the topic of electromobility development. In my opinion, the manuscript in its current form is suitable for publication. Well done!

Author Response

Comment:

The authors comprehensively addressed my comments and objections. Their responses addressed my main concerns regarding the reviewed work. Furthermore, the manuscript has been significantly improved compared to the original. As I wrote in my previous review, I believe this work has innovative aspects and contributes to the topic of electromobility development. In my opinion, the manuscript in its current form is suitable for publication. Well done!

Response:

Thanks!

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you.