Integrating Customer Experience (CX) in Sustainable Product Life Cycle

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

After reading the entire article, I found a series of issues related to:

Abstract: The authors do not clearly present the research methodology used, the results and general conclusions of their research. I suggest the authors to present these aspects.

Introduction. The authors do not specify what gap in the specialized literature they cover through their study or how their study differs from other similar studies existing in the specialized literature and what are the main contributions of their study. I suggest the authors to specify these aspects.

Related works. Investigating the specialized literature by simply searching for keywords is not representative of the research conducted and the specialized literature covered by the authors is not eloquent enough in supporting their research. I suggest the authors to present a broader framework based on studying the concepts through the lens of a more elaborated and synthesized specialized literature.

Conclusions. The authors do not clearly present all the main contributions to the research nor the theoretical and practical implications in the chosen field. I suggest the authors to present these aspects.

Author Response

Dear Reviewer,

 

 

We kindly thank you for your attention and time and for your relevant insights.

 

We have carefully updated and detailed the article, as follows:

 

Abstract: The authors do not clearly present the research methodology used, the results and general conclusions of their research. I suggest the authors to present these aspects.

The Abstract was revised, and it includes the domain (automotive industry line 10-11), the research methodology (line 17-21), the results (line 21-23) and conclusions (lines 23-25)

 

Introduction. The authors do not specify what gap in the specialized literature they cover through their study or how their study differs from other similar studies existing in the specialized literature and what are the main contributions of their study. I suggest the authors to specify these aspects.

The Introduction has been extended with more references; this part details the gap and mains contributions (lines 57-65) and explicit the study goals (lines 67-70), as well as the article structure to better envisage the content and the contributions (lines 71-78).

 

Related works. Investigating the specialized literature by simply searching for keywords is not representative of the research conducted and the specialized literature covered by the authors is not eloquent enough in supporting their research. I suggest the authors to present a broader framework based on studying the concepts through the lens of a more elaborated and synthesized specialized literature.

The literature review has been extended (from 30 to 64 references) and better explained. The concepts of customer satisfaction, customer experience, Kano attributes, customer touchpoints in customer experience map have been detailed and, further on in the study, used to build the customer experience map in product / vehicle development. In these touchpoints the multiple surveys are conducted to determine the relevant factors for the product development.

 

Conclusions. The authors do not clearly present all the main contributions to the research nor the theoretical and practical implications in the chosen field. I suggest the authors to present these aspects.

In lines 770-788 the main contributions are summarized to allow the transfer of the study to other case studies, mainly products with high complexity and medium to long duration use.

Conclusion chapter (lines 791-820) has been redrafted and presents how the multiple questionnaires collected in different phases of product lifecycle may be integrated to develop a new model considering the meta factors with the highest aggregated relevance for the customer satisfaction, in our case price, durability and design.  

The proposed structure / generic example may be transferred and extended.

 

We are grateful for your comments, thus allowing us to better detail our work based on experience in automotive industry.

 

Sincerely,

Irina Severin

Reviewer 2 Report

Comments and Suggestions for Authors

• Please remove the appreciation from the title
• At the beginning of the abstract introduce a contextual framing before describing the aim of the research paper
• Give a brief of the employed methodology in the abstract
• The argument in the introduction needs to be supported by more updated references
• Please do not leave any part in the introduction without reference (i.e. this part need reference “The society of the XXI century is in permanent development, creating an area of interest for the major industries of the world, but also a challenge in terms of population needs. In parallel with society, technology is also advancing by influencing the development of products and services. Thus, products develop to have more convenient functions enabling competitiveness increase on the market”.
• The research aim, objectives and motive are not clear in the introduction
• The introduction is poor and need to be strengthened by more argument to illustrate the importance of the research paper, the research gap, motive, and objectives
• Change related work to literature review
• “To cover the large and diverse body of literature related to the proposed research 54 topic, a series of checks were carried out. The primary search method was purpose-focused, using keywords such as customer, customer satisfaction, customer orientation, 56 level of complaints, and customer experience.” Elaborate more on the selected database and the selected time frame
• The previous literature has unlimited number of research paper that investigate customer, customer satisfaction, customer orientation, 56 level of complaints, and customer experience, however the author only focusses on 5 studies (one of them on 2025)
• Please avoid using pullets or numbering methods (lines 120-129; 211- 227…) and employee the scientific writing methods instead
• The writing style in this piece of work is adequate as a book chapter not a research paper
• Please justify the adequacy of the sample size of 74 participants and support your arguments with references
• The employed data analysis method spss is outdated, please use updated methods such as PLS-SEM
• I can not evaluate the results or review the discussion according to the outdated data analysis technique
• The theoretical and practical implications are poorly articulated

 

 

 

Author Response

Dear Reviewer,

 

 

We kindly thank you for your attention and time and for your relevant insights.

 

We have carefully updated and detailed the article, as follows:

 

• Please remove the appreciation from the title

We may delete “sustainable”, but this has been a suggestion of the Assistant Editor

 

• At the beginning of the abstract introduce a contextual framing before describing the aim of the research paper

A sentence has been introduced (line 10-11)

 

• Give a brief of the employed methodology in the abstract

We added lines 17-21 briefly explaining the survey collection and line 22-23 indicating the statistical analysis for meta factors validation.

 

• The argument in the introduction needs to be supported by more updated references

References have been extended from 30 to 64, in fact in the initial version we did not indicate all the studied references. The introduction has been extended and better argued with references.

 

• Please do not leave any part in the introduction without reference (i.e. this part need reference “The society of the XXI century is in permanent development, creating an area of interest for the major industries of the world, but also a challenge in terms of population needs. In parallel with society, technology is also advancing by influencing the development of products and services. Thus, products develop to have more convenient functions enabling competitiveness increase on the market”.

References have been inserted in 1., Introduction, 2. Literature review, 3. Customer experience definition, but in other chapters, too.

 

• The research aim, objectives and motive are not clear in the introduction

(Lines 57-79) have been added and better detail the aim of the research in the introduction. This is reiterated (lines 182-186) before drafting the customer experience map revealing the touchpoints and, further on, the questionnaires objectives (lines 221-222).

 

• The introduction is poor and need to be strengthened by more argument to illustrate the importance of the research paper, the research gap, motive, and objectives

Introduction has been extended, this part details the gap and mains contributions (lines 57-65) and explicit the study goals (lines 67-70), as well as the article structure to better envisage the content and the contributions (lines 71-78).

 

• Change related work to literature review

Updated as suggested.

 

• “To cover the large and diverse body of literature related to the proposed research topic, a series of checks were carried out. The primary search method was purpose-focused, using keywords such as customer, customer satisfaction, customer orientation, level of complaints, and customer experience.” Elaborate more on the selected database and the selected time frame

Section 2, as well as the Introduction, has been elaborated related to the list of updated references.

 

• The previous literature has unlimited number of research paper that investigate customer, customer satisfaction, customer orientation, level of complaints, and customer experience, however the author only focusses on 5 studies (one of them on 2025)

The table has aimed to emphasize the concepts evolution, actually (2025) the interest has focused on branding and organisational change based on customer satisfaction. That does not mean that the extensive body of knowledge has been not considered. An explanation has been introduced for clarification (lines 92-96).

 

• Please avoid using pullets or numbering methods (lines 120-129; 211- 227…) and employee the scientific writing methods instead

Thank you, these have been implemented in all sections.

 

• The writing style in this piece of work is adequate as a book chapter not a research paper

We hope the revision has improved the style, too.

 

• Please justify the adequacy of the sample size of 74 participants and support your arguments with references

We added (lines 663-666 and reference [48]). In fact, the meta factors (price, durability and design) identified, following the multiple surveys applied in the different phases of the product lifecycle, have been validated using ordinal regression. References [42, 43] support the method.

 

• The employed data analysis method spss is outdated, please use updated methods such as PLS-SEM

Compared to OLS regression, SEM enjoys a variety of advantages, such as the ability to analyze simultaneously, the ability to include latent variables, the ability to analyze time series data, more flexible assumptions, ability to test non-normal data, testing models with large number of equations as a whole and obtain global fit measures, ability to model mediating variables rather than additive models, ability to model error terms, and graphical modeling.

However, it is not always optimal to choose SEM over OLS regression. SEM also has disadvantages. One of the biggest concerns is its complexity, therefore researchers prefer simpler models when the fitting ability is similar. Another concern is requirement of large sample size. Over the years, a number of simulation studies have assessed the influence of variations in sample size of SEM  analyses and there is no recommended minimum sample size broadly applicable in all contexts (see for example Tomarken & Waller, 2005). Several general rules suggest the lowest reasonable sample size is 200 for relatively simple models, and for more complicated models, larger sample size will be recommended. In fact, SEM is powerful when done with adequately large sample size.

The Partial Least Squares Regression procedure estimates partial least squares (PLS, also known as "projection to latent structure") regression models. PLS is a predictive technique that is an alternative to ordinary least squares (OLS) regression, canonical correlation, or structural equation modeling, and it is particularly useful when predictor variables are highly correlated or when the number of predictors exceeds the number of cases.

In summary, although SEM has various advantages over OLS regression, it also has disadvantages (is more complex and harder to interpret than regression, requires larger sample sizes for reliable results and more assumptions about data distribution and relationships) and it is not always the case that applying SEM is preferred to OLS regression. When OLS regression assumptions are satisfied, SEM and OLS regression will fit equally well.

Our data satisfies the assumptions of OLS regression well enough, and our sample size is less than 100. We also have a straightforward relationship to analyze and focus on predicting an outcome based on a few independent variables, therefore we used OLS regression rather than SEM.

Although SEM has considerable advantages over regression analysis, it does not replace it. Ultimately, the decision should be guided by the research goals, the complexity of the data, and the specific relationships you wish to explore.

[48] Tomarken, A.J., Waller, N.G. (2005). "Structural equation modeling: strengths, limitations, and misconceptions." Annual Review Of Clinical Psychology Vol. 1: 31-65.

 

• I can not evaluate the results or review the discussion according to the outdated data analysis technique

We hope the upper explanations better clarify our intentions and the method relevance. We explained in Section 6 (lines 663-666) the reasons for the statistical method choice.

 

• The theoretical and practical implications are poorly articulated

In lines 770-788 the main contributions are summarized so as to allow the transfer of the study to other case studies, mainly products with high complexity and medium to long duration use,

Conclusion chapter (lines 791-820) has been redrafted and presents how the multiple questionnaires collected in different phases of product lifecycle may be integrated to develop a new model considering the meta factors with the highest aggregated relevance for the customer satisfaction, in our case price, durability and design. The proposed structure / generic example may be transferred and extended, as detailed in last section Future developments and limitations.

 

 

We are grateful for your comments, thus allowing us to better detail our work based on experience in automotive industry.

 

Sincerely,

Irina Severin

 

Reviewer 3 Report

Comments and Suggestions for Authors

This scientific paper represents a contribution to the advancement of the Customer Experience. However, I would like to offer the following suggestions regarding several sections of the paper:

Abstract:

The abstract is sufficiently written, but could be more specific. The authors should highlight the gap, the methodology, the main findings, and their practical implications more concisely.

Introduction:

The introduction gives context but lacks a strong research gap statement. The authors should state what current literature fails to address regarding full CX integration in the product lifecycle. The introduction does not have the structure of the paper as the last paragraph. The authors should shortly elaborate on the content of each of the following sections (e.g., The remainder of the paper is structured as follows: …).

CX Integration Through Lifecycle:

Consider summarizing overlapping points across survey types. The formatting in Figures 6, 7, and 10 is inconsistent. The green color in Table 2 does not align with the previous images, which are predominantly blue, and should be changed. The section already has a lot of visual material, and should be consistent in design and formatting (applied to the whole paper).

Study results validation through statistical analysis:

The authors could include a rationale for selecting this technique over others and discuss limitations due to sample size.

 

Comments for author File: Comments.pdf

Author Response

Dear Reviewer,

 

 

We kindly thank you for your attention and time and for your relevant insights.

 

We have carefully updated and detailed the article, as follows:

 

This scientific paper represents a contribution to the advancement of the Customer Experience. However, I would like to offer the following suggestions regarding several sections of the paper:

Abstract:

The abstract is sufficiently written, but could be more specific. The authors should highlight the gap, the methodology, the main findings, and their practical implications more concisely.

The Abstract was revised, and it includes the domain (automotive industry line 10-11), the research methodology (line 17-21), the results (line 21-23) and practical implications (lines 23-25)

 

Introduction:

The introduction gives context but lacks a strong research gap statement. The authors should state what current literature fails to address regarding full CX integration in the product lifecycle. The introduction does not have the structure of the paper as the last paragraph. The authors should shortly elaborate on the content of each of the following sections (e.g., The remainder of the paper is structured as follows: …).

The Introduction has been extended with more references (in fact, in the initial version we did not indicate all the studied references); this part details the gap and mains contributions (lines 57-65) and explicit the study goals (lines 67-70), as well as the article structure to better envisage the content and the contributions (lines 71-78).

 

CX Integration Through Lifecycle:

Consider summarizing overlapping points across survey types. The formatting in Figures 6, 7, and 10 is inconsistent. The green color in Table 2 does not align with the previous images, which are predominantly blue, and should be changed. The section already has a lot of visual material, and should be consistent in design and formatting (applied to the whole paper).

All tables and figures were harmonised, colours were removed from tables and journal format was respected.

Surveys are summarised in lines 267-280. Even if the survey structure may be same, applying it in different phases expends the collected information.

In lines 770-788 the main contributions are summarized to allow the transfer of the study to other case studies, mainly products with high complexity and medium to long duration use.

 

Study results validation through statistical analysis:

The authors could include a rationale for selecting this technique over others and discuss limitations due to sample size.

We explained in Section 6 (lines 663-666) the reasons for the statistical method choice and we added reference [48] that supports the method selection.

To better understand our approach, we may detail the followings:

Compared to OLS regression, SEM enjoys a variety of advantages, such as the ability to analyze simultaneously, the ability to include latent variables, the ability to analyze time series data, more flexible assumptions, ability to test non-normal data, testing models with large number of equations as a whole and obtain global fit measures, ability to model mediating variables rather than additive models, ability to model error terms, and graphical modeling.

However, it is not always optimal to choose SEM over OLS regression. SEM also has disadvantages. One of the biggest concerns is its complexity, therefore researchers prefer simpler models when the fitting ability is similar. Another concern is requirement of large sample size. Over the years, a number of simulation studies have assessed the influence of variations in sample size of SEM  analyses and there is no recommended minimum sample size broadly applicable in all contexts (see for example Tomarken & Waller, 2005). Several general rules suggest the lowest reasonable sample size is 200 for relatively simple models, and for more complicated models, larger sample size will be recommended. In fact, SEM is powerful when done with adequately large sample size.

The Partial Least Squares Regression procedure estimates partial least squares (PLS, also known as "projection to latent structure") regression models. PLS is a predictive technique that is an alternative to ordinary least squares (OLS) regression, canonical correlation, or structural equation modeling, and it is particularly useful when predictor variables are highly correlated or when the number of predictors exceeds the number of cases.

In summary, although SEM has various advantages over OLS regression, it also has disadvantages (is more complex and harder to interpret than regression, requires larger sample sizes for reliable results and more assumptions about data distribution and relationships) and it is not always the case that applying SEM is preferred to OLS regression. When OLS regression assumptions are satisfied, SEM and OLS regression will fit equally well.

Our data satisfies the assumptions of OLS regression well enough, and our sample size is less than 100. We also have a straightforward relationship to analyze and focus on predicting an outcome based on a few independent variables, therefore we used OLS regression rather than SEM.

Although SEM has considerable advantages over regression analysis, it does not replace it. Ultimately, the decision should be guided by the research goals, the complexity of the data, and the specific relationships you wish to explore.

 

We are grateful for your comments, thus allowing us to better detail our work based on experience in automotive industry.

 

Sincerely,

Irina Severin

 

Reviewer 4 Report

Comments and Suggestions for Authors

1. In the introduction, it is necessary to elaborate further on the focus of this study, which is the integration of customer experience with the product life cycle. Specifically, the rationale behind this integrated approach should be clarified, highlighting the growing importance of customer-centric strategies in product development. A more detailed comparison with previous studies is needed to emphasize this research's unique contribution and novelty. Lastly, the choice of the automobile industry as the representative case should be explained, particularly regarding its relevance, complexity, and suitability for analyzing the full scope of the product life cycle and customer experience.
2. Given the diverse nature of automobile sub-segments, considering the purpose of this study, it is essential to specify how customer experience evolves throughout the product life cycle within a particular sub-segment. This includes detailing the changes in customer satisfaction levels across different life cycle stages. Additionally, a minor but necessary correction is required: Figure 1 appears duplicated and should be revised accordingly.
3. In the conclusion, the implications of this study should be clearly articulated by comparing the analytical results with those of prior research, thereby underscoring the study’s unique contribution to the existing literature on customer experience and product life cycle integration. This comparative perspective will help to position the research within a broader academic context. Furthermore, the study should offer practical insights by proposing actionable strategies that practitioners can adopt to enhance customer satisfaction across different product life cycle stages. These recommendations should be directly applicable, reflecting the realities of industry operations and supporting more effective customer-focused decision-making in practice.

Author Response

Dear Reviewer,

 

 

We kindly thank you for your attention and time and for your relevant insights.

 

We have carefully updated and detailed the article, as follows:

 

1. In the introduction, it is necessary to elaborate further on the focus of this study, which is the integration of customer experience with the product life cycle. Specifically, the rationale behind this integrated approach should be clarified, highlighting the growing importance of customer-centric strategies in product development. A more detailed comparison with previous studies is needed to emphasize this research's unique contribution and novelty. Lastly, the choice of the automobile industry as the representative case should be explained, particularly regarding its relevance, complexity, and suitability for analyzing the full scope of the product life cycle and customer experience.

 

The Introduction has been extended with more references; this part details the gap and mains contributions (lines 57-65) and explicit the study goals (lines 67-70), as well as the article structure to better envisage the content and the contributions (lines 71-78).

(Lines 57-79) have been added and better detail the aim of the research in the introduction. This is reiterated (lines 182-186) before drafting the customer experience map revealing the touchpoints and, further on, the questionnaires objectives (lines 221-222).

The literature review has been extended (from 30 to 64 references) and better explained. The concepts of customer satisfaction, customer experience, Kano attributes, customer touchpoints in customer experience map have been detailed and, further on in the study, used to build the customer experience map in product / vehicle development. In these touchpoints the multiple surveys are conducted to determine the relevant factors for the product development.

The reason for automotive industry selection has been explicit in lines 62-70 and considered relevant for a product with high complexity and medium-long term duration use.

 

 

1. Given the diverse nature of automobile sub-segments, considering the purpose of this study, it is essential to specify how customer experience evolves throughout the product life cycle within a particular sub-segment. This includes detailing the changes in customer satisfaction levels across different life cycle stages. Additionally, a minor but necessary correction is required: Figure 1 appears duplicated and should be revised accordingly.

 

All section 5 presents customer satisfaction evolution throughout the product life cycle, the defined research questions (lines 221-222) explored indeed this evolution.

The summary of applied tools is given in lines 267-280.

The prospecting survey aimed to identify the segment the most relevant and, in the next step, to associate the customer profile in order to search the priority factors to focus on, considering that for a new model approximately 50% is planned from existing vehicle in production. That’s to identify what customers are mostly interested in.

Upstream survey integrates customer complaints internally registered from products in -use to explore deeper the areas for improvement.

The launch preparation survey is applied with 10 prototypes tested by employees to report, from a more professional perspective, the vehicle performance and to identify strengths, weaknesses and improvement opportunities.

Post launch investigation is applied in the first month of the vehicle use and is correlated with incident alerts.  

Lifecycle survey is implemented for the period between 12 months and 36 months of vehicle usage when the input for durability and reliability is desired.

The study revealed that the meta factors price, durability and design are determinant predictors for the overall customer satisfaction. Even if more reasons for unsatisfaction were identified, the most relevant framed into these meta factors.

We tried to demonstrate that for a product with high complexity, the manufacturer should concentrate on identifying the relevant factors for the overall customer satisfaction.

 

 

1. In the conclusion, the implications of this study should be clearly articulated by comparing the analytical results with those of prior research, thereby underscoring the study’s unique contribution to the existing literature on customer experience and product life cycle integration. This comparative perspective will help to position the research within a broader academic context. Furthermore, the study should offer practical insights by proposing actionable strategies that practitioners can adopt to enhance customer satisfaction across different product life cycle stages. These recommendations should be directly applicable, reflecting the realities of industry operations and supporting more effective customer-focused decision-making in practice.

 

We appreciate your valuable insights. We elaborated more in detail results interpretation (lines 770-787), the Conclusion section and Future developments and limitations.

We consider that companies actionable strategies exceed our study, but the sequence of potential phases to better valorise customer experience to develop companies’ capabilities have been highlighted lines 150-186.

This approach may be a good continuation in future research. Thank you very much!

 

 

We are grateful for your comments, thus allowing us to better detail our work based on experience in automotive industry.

 

Sincerely,

Irina Severin

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you to the authors for implementing all the suggestions indicated.

Reviewer 2 Report

Comments and Suggestions for Authors

accepted