User-Centered Challenges and Strategic Opportunities in Automotive UX: A Mixed-Methods Analysis of User-Generated Content
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis paper explores user-centered design challenges and strategic opportunities in automotive user experience, drawing on user-generated content through a mixed-methods approach that combines Natural Language Processing and qualitative thematic analysis. And the study attempts to integrate large-scale user feedback into a conceptual user experience framework suitable for autonomous driving scenarios, which has potential applications in the automotive industry. However, the author needs to further clarify and elaborate on some details of the paper before considering publishing it. The specific problems are as follows:
- In the Introduction section, the author explains the background and motivation of the research, but it is recommended that the author add a summary diagram of the research content to facilitate readers to better understand the analytical method and the content of the conceptual framework of the paper. In addition, the fonts in the existing figures are too small and need to be adjusted.
- The authors introduce natural language processing methodology foundations in Section 1.2, which refers to many relevant references. It is suggested that the author add a literature review section, which can combine user experience, text analysis, language processing and other research directions to enrich the content of the article.
- In the Materials and Methods section, the author introduces the data and analysis methods. Although the methods used are explained, the description is too simple. It is recommended that the author further supplement the details, such as adding the principle explanation of data processing and analysis methods.
- In Section 3.2, the author reveals the challenges faced by the current user experience through qualitative analysis. It is suggested that the author further refine the results obtained from the analysis, such as statistics on the impact degree of different problems, rather than only analyzing the description of the forum.
- The overall description of the article is too condensed, making it difficult for readers to follow. The author should optimize the background, methodology, results, and other sections to improve clarity and readability. The processing in Figure 3 is acceptable. In addition, it is suggested that the author include more formulas or charts to help explain the content of the article.
Comments for author File: 
Comments.pdf
Author Response
Comment 1: In the Introduction section, the author explains the background and motivation of the research, but it is recommended that the author add a summary diagram of the research content to facilitate readers to better understand the analytical method and the content of the conceptual framework of the paper. In addition, the fonts in the existing figures are too small and need to be adjusted.
Response 1: Thank you for pointing this out. A summary diagram has been added to the Introduction section to provide readers with a clearer overview of the research workflow, including the analytical method, the core findings of the study and the outlook with empirical validation [Page 3, Lines 90-103]. Furthermore, the font size of all existing figures has been adjusted in the revised manuscript to ensure better visual clarity.
Comment 2: The authors introduce natural language processing methodology foundations in Section 1.2, which refers to many relevant references. It is suggested that the author add a literature review section, which can combine user experience, text analysis, language processing and other research directions to enrich the content of the article.
Response 2: Thank you for this valuable suggestion. In accordance with your recommendation, a dedicated Literature Review section has been added to the revised manuscript. This new section integrates UGC in research, UX and digital transformation in the automotive sector and foundations of text analysis with NLP. By consolidating these perspectives, the section provides a more coherent theoretical grounding and enriches the overall content of the work. We believe that this addition enhances the clarity and academic completeness of the manuscript [page 3, Lines 104-121].
Comment 3: In the Materials and Methods section, the author introduces the data and analysis methods. Although the methods used are explained, the description is too simple. It is recommended that the author further supplement the details, such as adding the principle explanation of data processing and analysis methods.
Response 3: Thank you for this valuable input. We agree that the initial description of the data processing and analysis methods required further elaboration. In the revised manuscript, we have expanded the Materials and Methods section by providing a more detailed explanation of the processing pipeline and analysis workflow. To enhance transparency and reproducibility, we have also included methodological details on documentation of processing routines in Jupyter Notebooks. Furthermore, we have added a paragraph discussing the accuracy and performance characteristics of the sentiment analysis models used. We also address the consideration of domain-adapted sentiment models, explaining why general-purpose models were selected for this first stage of the study [Page 6-7, Lines 238-309].
Comment 4: In Section 3.2, the author reveals the challenges faced by the current user experience through qualitative analysis. It is suggested that the author further refine the results obtained from the analysis, such as statistics on the impact degree of different problems, rather than only analyzing the description of the forum.
Response 4: Very good point! We agree that statistical quantification of the impact levels of the identified UX challenges would provide an additional layer of analytical depth. However, the primary focus of the present paper lies on an exploratory identification of user-reported issues rather than on their statistical weighting. The qualitative analysis was therefore designed to uncover thematic patterns and user needs in breadth, serving as a first conceptual foundation. We acknowledge the importance of the statistical refinement. As stated in the revised manuscript, subsequent phases of the research will incorporate empirical validation from both driver and domain experts to strengthen the empirical robustness and deepen the interpretability of the derived findings. A statistical examination will be considered in future research stages [Page 17, Lines 768-771].
Comment 5: The overall description of the article is too condensed, making it difficult for readers to follow. The author should optimize the background, methodology, results, and other sections to improve clarity and readability. The processing in Figure 3 is acceptable. In addition, it is suggested that the author include more formulas or charts to help explain the content of the article.
Response 5: Thank your for this feedback. In the revised manuscript, the background section has been expanded [Page 1-2, Lines 38-43][Page 2, Lines 80-85], the methodological explanations have been extended with additional detail [Page 6, Lines 238-284], and a dedicated literature review section has been introduced to improve clarity and contextual depth [Page 3, Lines 104-121]. Furthermore, a summary diagram has been added to the introduction to visually outline the research process and enhance reader comprehension [Page 3, Lines 90-103]. At this stage, the analytical procedure do not require formulas. Nevertheless, quantitative modelling and the inclusion of formal representations will be considered in subsequent stages of the study, particularly as the framework is further developed an empirically validated.
Reviewer 2 Report
Comments and Suggestions for AuthorsThe article is both interesting and relevant. It contains useful, practical information. Its main contribution is a comprehensive study of user-centred challenges in automotive UX, based on a mixed-methods analysis of user-generated content. The authors combined quantitative natural language processing (NLP) analysis and qualitative Mayring methodology to systematically identify key issues relating to interface complexity, driver distraction and a lack of consideration for user diversity. The article significantly advances our understanding of how digitalisation and increased functionality in cars affect safety and the intuitiveness of interactions. Another valuable aspect of the article is the strategic interaction model developed by the authors to facilitate a seamless transition from manual control to full autonomy. The article emphasises that effective automotive UX is only possible if it focuses on safety and adaptability for different user groups.
Some comments on the article:
1) The proposed model is intended to serve as a foundation for the transition to autonomous driving. However, it has not yet been supported by experimental data or field tests.
2) What is the main objective of the study? It should be clearly stated in the introduction, and the conclusion should indicate whether the objective has been achieved. Lines 56–57 state that the study's primary objective is 'to identify additional challenges and convert these insights into actionable implications'. Is this the main objective of this work? If so, the authors should provide information on how they achieved it in the 'Conclusions' section.
3) Section 4.3 discusses the main limitations of the proposed methodology. However, the 'Conclusions' section lacks information about the limits of application of the proposed methodology. This information should be added to the 'Conclusions' section.
4) What does level 5 represent in Figure 3, 'Framework for Control Strategy'?
5) Although the article emphasises the importance of safety, it does not offer any specific methods for measuring or comparing the risks associated with the identified UX issues.
6) What is the application and real-time use of your study?
Author Response
Comment 1: The proposed model is intended to serve as a foundation for the transition to autonomous driving. However, it has not yet been supported by experimental data or field tests.
Response 1: Thank you for pointing this out. We agree that the proposed theoretical model currently serves as a conceptual foundation and has not yet been validated through experimental studies or field tests in this first stage of research as it has been planned as a desk research. This limitation has been explicitly acknowledged in the revised manuscript. As outlined in the revised Conclusion section, we plan to validate the framework though interviews and surveys with both drivers and domain experts to strengthen its empirical foundation. Further empirical and simulation-based evaluations may serve as subsequent steps to assess the models applicability in real-world scenarios [Page 17, Lines 768-777].
Comment 2: What is the main objective of the study? It should be clearly stated in the introduction, and the conclusion should indicate whether the objective has been achieved. Lines 56–57 state that the study's primary objective is 'to identify additional challenges and convert these insights into actionable implications'. Is this the main objective of this work? If so, the authors should provide information on how they achieved it in the 'Conclusions' section.
Response 2: Yes, the stated objective – to identify additional challenges in current in-vehicle interaction and translate these insights into actionable implications – represents the main objective of this first paper. We have revised the Conclusion to clarify this focus. The Conclusion section has been expanded to explain how this objective was accomplished and how the resulting insights were consolidated into actionable implications and a conceptual framework [Page 17, Lines 747-756].
Comment 3: Section 4.3 discusses the main limitations of the proposed methodology. However, the 'Conclusions' section lacks information about the limits of application of the proposed methodology. This information should be added to the 'Conclusions' section.
Response 3: Thank you for this valuable comment. We agree that the limits of application of the proposed methodology should be made more explicit in the Conclusion section. In the revised manuscript, we have added a brief explanation outlining the methodological constraints – including the reliance on two online forums, the subjective character of the conceptual framework, and the absence of expert validation – to clarify the scope within which the findings can be interpreted [Page 17, Lines 762-766].
Comment 4: What does level 5 represent in Figure 3, 'Framework for Control Strategy'?
Response 4: Thank you for your question. Level 5 in Figure 3 corresponds to full driving automation as defined by the SAE International standard. This clarification has been added to the explanation of the framework in the revised manuscript [Page 15, Lines 667-669].
Comment 5: Although the article emphasises the importance of safety, it does not offer any specific methods for measuring or comparing the risks associated with the identified UX issues.
Response 5: Thank you for raising this important point. We agree that, although the manuscript highlights the relevance of safety within in-vehicle interaction, it does not yet provide concrete methods for measuring or comparing the safety-related risks associated with the identified UX issues. As outlined in the revised Conclusion section, future work will incorporate established safety assessment approaches and conduct structured interviews with both drivers and domain experts to systematically explore and quantify potential safety impacts. These interviews will support a more rigorous understanding of how interaction issues may affect driver performance and situational safety, thereby strengthening the validity and practical relevance of the proposed framework [Page 17, Lines 768-777].
Comment 6: What is the application and real-time use of your study?
Response 6: Thank you for raising this question. The proposed approach is intended to support early-phase development by providing a structured understanding of user needs, interaction challenges, and function relevance during the transition toward higher levels of automated driving. The framework can serve as a basis for classifying and prioritizing in-vehicle functions, thereby fostering a more systematic mindset for designing context-sensitive interaction strategies. The findings provide initial guidance for shaping future UX concepts and supporting early design decisions toward safer and more user-aligned interaction solutions. These implications represent a preliminary foundation and will require systematic validation in the subsequent phases of the study. This information has been added to the revised Conclusion section [Page 17, Lines 782-790].
Reviewer 3 Report
Comments and Suggestions for AuthorsThe paper offers a good exploration of user-centered challenges in automotive UX, combining quantitative sentiment analysis with qualitative content analysis of user-generated content. Its structure is clear, and the practical implications, such as multimodal interaction and context-sensitive function reduction, are highly relevant in the era of increasing vehicle automation. The mixed-methods approach is a strength, as it captures both measurable trends and nuanced user perspectives.
However, the study has notable limitations. The reliance on only two online forums introduces selection bias and restricts the diversity of user feedback, which limits the generalizability of findings. Methodologically, the absence of intercoder reliability checks in the qualitative analysis and the lack of discussion on NLP model accuracy reduce the rigor of the results. Furthermore, while the conceptual framework for interaction strategies is promising, it remains theoretical and unvalidated, which weakens its practical applicability.
Another critical gap lies in the literature integration. The paper focuses heavily on UX and NLP but overlooks simulation-based approaches that could complement its findings. Simulation frameworks, such as those developed by this team [1] , offer robust methods for validating interaction strategies under dynamic and safety-critical conditions. His work on distributed simulation, interoperability standards (IEEE HLA), and virtual reality integration could significantly strengthen the paper by providing a pathway for empirical testing and scalability. Including these references would position the study within the broader context of digital twins and human-in-the-loop simulation, enhancing its relevance for future automotive UX research.
In summary, while the paper makes a valuable contribution, addressing these limitations particularly by incorporating simulation-based perspectives would improve its methodological robustness and practical impact. Future work should explore integrating simulation approaches to validate the proposed framework and ensure adaptability across diverse driving contexts.
[1] G Zacharewicz, A Pirayesh-Neghab, M Seregni, Y Ducq, G Doumeingts. Simulation-Based Enterprise Management: Model Driven from Business Process to Simulation. Guide to Simulation-Based Disciplines: Advancing Our Computational Future …
Author Response
Comment 1: However, the study has notable limitations. The reliance on only two online forums introduces selection bias and restricts the diversity of user feedback, which limits the generalizability of findings. Methodologically, the absence of intercoder reliability checks in the qualitative analysis and the lack of discussion on NLP model accuracy reduce the rigor of the results. Furthermore, while the conceptual framework for interaction strategies is promising, it remains theoretical and unvalidated, which weakens its practical applicability.
Response 1: Thank you for pointing this out. We fully agree with this comment.
In the revised manuscript, we explicitly address the selection bias introduced by relying on only two online forums and clarify that this restricts the diversity of user perspectives and, consequently, the generalizability of the findings. To mitigate this limitation, future work will include additional data sources - including further international forums to validate the first stage findings and explore potential cross-cultural differences [Page 16, Lines 720-728].
Regarding methodological rigor, the absence of intercoder reliability check is already acknowledged in the limitations section. As next step, we plan to conduct follow-up interviews and surveys with both drivers and domain experts validate the initial subjective insights and to further deepen the empirical foundation of the findings [Page 17, Lines 766-771]. Intercoder checks with then be incorporated.
To address the concern about NLP model accuracy, we have added a short clarification in the Materials and Methods section that give insights about the two sentiment analysis models used [Page 6, Lines 265-273].
The conceptual framework for control strategy has been explicitly identified as preliminary and theoretical. We now clarify in the Limitations and Conclusions Sections that the framework originated from user feedback and requires further validation. To ensure the robustness and practical applicability of the conceptual framework, subsequent research will involve targeted evaluations. The next steps aim to substantiate or refine the framework and thereby strengthen its empirical foundation [Page 16, Lines 741-743, Page 17, Lines 771-774].
Comment 2: Another critical gap lies in the literature integration. The paper focuses heavily on UX and NLP but overlooks simulation-based approaches that could complement its findings. Simulation frameworks, such as those developed by this team [1] , offer robust methods for validating interaction strategies under dynamic and safety-critical conditions. His work on distributed simulation, interoperability standards (IEEE HLA), and virtual reality integration could significantly strengthen the paper by providing a pathway for empirical testing and scalability. Including these references would position the study within the broader context of digital twins and human-in-the-loop simulation, enhancing its relevance for future automotive UX research. In summary, while the paper makes a valuable contribution, addressing these limitations particularly by incorporating simulation-based perspectives would improve its methodological robustness and practical impact. Future work should explore integrating simulation approaches to validate the proposed framework and ensure adaptability across diverse driving contexts. In summary, while the paper makes a valuable contribution, addressing these limitations particularly by incorporating simulation-based perspectives would improve its methodological robustness and practical impact. Future work should explore integrating simulation approaches to validate the proposed framework and ensure adaptability across diverse driving contexts.
Response 2: Thank you for this valuable comment. We agree that integrating simulation-based approaches represents an important opportunity to strengthen methodological rigor and broaden the applicability of the proposed framework. While the current paper focuses primarily on UX and NLP perspectives using existing content (desk research), we recognize the relevance of simulation-based approaches for validating interaction strategies und er dynamic and safety-critical conditions. We incorporate this perspective into future work [Page 17, Lines 771-777].
Reviewer 4 Report
Comments and Suggestions for AuthorsThe paper employs natural language processing and qualitative content analysis to investigate users’ key pain points in automotive UX/UI interactions, and proposes an interaction-strategy model with practical relevance. Still, several minor details warrant attention. The relevant recommendations are as follows:
- Why are MotorTalk and StackExchange chosen as the only two data sources? Are other platforms with more active user participation considered?
- The NLP sentiment analysis employed a general-purpose model, was domain adaptation (such as fine-tuning on an automotive corpus) ever considered?
- Does feature fading account for the potential loss of users’ sense of control? Could it induce anxiety or distrust?
- It is recommended that a few counter-examples or negative cases be added to the Discussion section to strengthen the argumentative tension.
Author Response
Comment 1: Why are MotorTalk and StackExchange chosen as the only two data sources? Are other platforms with more active user participation considered?
Response 1: Thank you for pointing this out. The choice was guided by their high thematic relevance, active and diverse user communities, and public availability of their content. The two forums provide a solid foundation for the first analysis phase of this study [Page 6, Lines 238-239]. Nevertheless, we acknowledge that this choice introduces limitations. Therefore future work is planned to incorporate additional data sources, including further international forums, to validate the the initial first-stage findings and to identify potential cross-cultural differences. This perspective has been integrated into the revised manuscript [Page 17, Lines 766-768].
Comment 2: The NLP sentiment analysis employed a general-purpose model, was domain adaptation (such as fine-tuning on an automotive corpus) ever considered?
Response 2: This is a very good question. Although domain adaption was considered, general models were ultimately selected for the analysis. The examined forums do not primarily rely on specialized technical terminology but instead reflect users general impressions and everyday experiences. Consequently, broad and well-established models were deemed more suitable for capturing the overall sentiment due to their universally superior reliability. This perspective has been integrated into the revised manuscript [Page 6, Lines 273-277].
Comment 3: Does feature fading account for the potential loss of users’ sense of control? Could it induce anxiety or distrust?
Response 3: Thank you for pointing this out. This aspect of a potential loss of perceived control through feature fading has been incorporated into the revised manuscript. We acknowledge that this implication require further detailed validation and must be examined in future work. To address this, upcoming phases of the study will include interviews and surveys with both drivers and domain experts to assess these potential effects in greater depth [Page 13, Line 598-601].
Comment 4: It is recommended that a few counter-examples or negative cases be added to the Discussion section to strengthen the argumentative tension.
Response 4: Thank you for this helpful recommendation. To address your comment, several counter-examples and contrasting user statements have been integrated into the revised manuscript. These examples illustrate opposing perspectives and thereby strengthen the argumentative tension within the Discussion section [Page 12, Lines 543-559].
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe authors improved the manuscript and the overall quality improved significantly. And the authors also gave a satisfactory reply to the comments, and the efforts made to solve the previous problems are worthy of recognition. Therefore, the manuscript can be considered for acceptance.
Comments for author File: Comments.pdf
Author Response
Thank you for your review!
Reviewer 3 Report
Comments and Suggestions for AuthorsThe paper is now in a good state.
Just some minor redundancies in phrasing (e.g., “context-sensitive, safety-oriented, and adapted to the diversity of users” appears multiple times).
Some sentences are long and could be split for clarity (e.g., in Discussion section lines 554–555).
Ensure consistent tense: Results and Discussion occasionally mix present and past tense.
Check figure captions: Ensure all figures have descriptive captions (Figure 2 and Figure 4 could be more explanatory).
Verify table alignment for Tables 1 and 2 (percentages should include % symbol for clarity).
Some URLs in references (e.g., [4], [5]) are very long; consider shortening with DOI or official short links.
I'm not sure but ensure all references follow MDPI style (e.g., italics for journal names, proper capitalization).
NLP section: Clarify why domain adaptation was considered but not implemented (currently mentioned briefly).
Qualitative analysis: Explicitly state why intercoder reliability was omitted (currently implied but could be clearer).
Figure 4 (Framework for Control Strategy): Ensure axis labels are legible and color contrast meets accessibility standards.
Important final point: The paper provide a good coverage, but consider adding a note on potential bias from translation (German → English).
Author Response
Comment 1: Just some minor redundancies in phrasing (e.g., “context-sensitive, safety-oriented, and adapted to the diversity of users” appears multiple times).
Some sentences are long and could be split for clarity (e.g., in Discussion section lines 554–555).
Ensure consistent tense: Results and Discussion occasionally mix present and past tense.
Response 1: Thank you very much for the constructive feedback. Some redundant phrasing has been revised to improve stylistic variation. In addition, long sentences, particularly in the Discussion section, have been split to enhance readability and clarity. Finally, we have reviewed the entire Results and Discussion sections to ensure consistent use of present tense [page 7-17, lines 330-776].
Comment 2: Check figure captions: Ensure all figures have descriptive captions (Figure 2 and Figure 4 could be more explanatory).
Verify table alignment for Tables 1 and 2 (percentages should include % symbol for clarity).
Response 2: Thank you for the valuable feedback. We have revised the figure captions to provide clearer and more descriptive explanations of each figures content and purpose. In addition, we reviewed the formatting of Tables 1 and 2 to ensure full compliance with the MDPI template and corrected the alignment issues. The percentages values now consistently include the % symbol [page 8, lines 342-343].
Comment 3: Some URLs in references (e.g., [4], [5]) are very long; consider shortening with DOI or official short links.
I'm not sure but ensure all references follow MDPI style (e.g., italics for journal names, proper capitalization).
Response 3: Thank you for the helpful remark. The URLs have been reviewed and several were updated to ensure accuracy. In addition, the official Applied Sciences reference style provided by MDPI (Multidisciplinary Digital Publishing Institute) has now been selected and correctly applied via Zotero. Unfortunately, some URLs are still long and there is no shorter version available (we don't want to use URL shorteners as these are often prone to phising etc.)
Comment 4: NLP section: Clarify why domain adaptation was considered but not implemented (currently mentioned briefly).
Qualitative analysis: Explicitly state why intercoder reliability was omitted (currently implied but could be clearer).
Response 4: Thank you for these comments. In the revised NLP section, we clarified that domain adaption was considered but not implemented because it would require a large, domain-specific annotated dataset that is not available and creating such a corpus was beyond the scope of this study. Existing domain-adapted sentiment models that could be reused are typically optimized for narrowly defined domains – such as specific technical documentations – and therefore do not align well with the conversational and heterogenous language found in user forum discussions [page 6, lines 274-281].
For the qualitative analysis, we explicitly state that intercoder reliability was omitted because the study followed an exploratory approach in which categories were still evolving [page 7, lines 315-319]. However, it is a good point and will be analyzed in upcoming studies.
Comment 5: Figure 4 (Framework for Control Strategy): Ensure axis labels are legible and color contrast meets accessibility standards.
Response 5: Thank you for this comment. Figure 4 has been revised to ensure full compliance with accessibility and readability requirements. Specifically, the contrast of the axis labels was increased to improve legibility. In addition, all color elements were adjusted to meet MDPI standard, including the removal of gradients [page 16, line 698 ].
Comment 6: Important final point: The paper provide a good coverage, but consider adding a note on potential bias from translation (German → English).
Response 6: Thank you for bringing up this point. We have incorporated a note acknowledging the potential bias arising from translation of the German text into English. This clarification has been added to the revised manuscript [page 7, lines 326-327]
Reviewer 4 Report
Comments and Suggestions for Authorsaccept
Author Response
Thank you for your review
