The Effect of Quality Management and Big Data Management on Customer Satisfaction in Korea’s Public Sector

Round 1

Reviewer 1 Report

No further comments

Author Response

We appreciate that the reviewer’s comments. The followings are our point-by-point responses:

• English language and style are fine/minor spell check required.

Response: Following the proposal, we reconfirmed the overall context. We also received reviews from fellow researchers.

Thank you very much.

Reviewer 2 Report

Dear author,

thank you for the improvements!

see my comments below and do not forget to have in mind my previous opinion.

1. we still do not know what kind of SME model is employed
2. you claim the H acceptance at 0.1 level, provide the literature justification for this pls, I cannot accept this argumentation in this state, l. 357-9
3. what do you mean by "product term" is totally not clear, l. 353 and next 

These are substantial issues for the study scientific credibility.

Author Response

Dear reviewer,

Thank you very much for your constructive suggestion and review.

1) we still do not know what kind of SME model is employed

Response: As shown in lines 298~299, SEM was used because this study model is an integrated model of factor analysis and regression model.

2) you claim the H acceptance at 0.1 level, provide the literature justification for this pls, I cannot accept this argumentation in this state, l. 357-9.

Response:  There are two moderation effects (Partial moderation, Full or complete moderation). Partial moderation implies that the mechanism through M (Moderation Variable) does not entirely account for the association observed between X (independent variable) and Y (dependent variable), complete moderation means that the association between X and Y is entirely accounted for by the mechanism. (Line 497,  Hayes, A. F. Introduction to Mediation, Moderation, and Conditional Process Analysis, Guilford, 2018.)

3)what do you mean by "product term" is totally not clear, l. 353 and next

Response: As you may well know, the multiplication term (or product term) of the independent factor and the adjustment factor is used to test the adjustment effect. This is a reference to the reference material.

Once again thank you very much.

Thank you and best regard.

Reviewer 3 Report

The authors addressed most of my previous comments and the current version of the manuscript looks significantly improved.

I see that there is s strong emphasis on the Korena market and this is now further stressed out in abstract, introduction and conclusions... this is important and I believe that the title should include this information. Also, given that big data are not used, you can drop the word "big" in the title.

Author Response

Dear reviewer,

Thank you very much for your reviewing manuscript. I also greatly appreciate the reviewers for their complimentary comments and constructive suggestions. I have revised manuscript that the reviewers suggested constructive contents.

1. English language and style are fine/minor spell check required. The authors addressed most of my previous comments and the current version of the manuscript looks significantly improved.                            Response: As suggested by the reviewer, I reconfirmed the overall context. I also received reviews from fellow researchers.

    2. I see that there is strong emphasis on the Koren a market and this is now further stressed out in abstract, introduction and conclusions. this is important and I believe that the title should include this information.

       Response: As suggested by the reviewer, I added relevant content to the third conclusion (Line 20-21, Line 431-435).

    3. Also, given that big data are not used, you can drop the word "big" in the title.

       Response: Thanks for the suggestion. As I said last time, the organization I belonged to requires several procedures and expressed difficulties. It was inserted into the limit that it is a research by questionnaire, not an analysis of big data. Thank you for your understanding.

Thank you very much for reviewing manuscript. Your intellectual content and advice were really helpful.

Take care of yourself.

Yours faithfully.

Reviewer 4 Report

The article deals with significant problems related to the Total Quality Management, Big data management aspects and customer satisfaction in the public sector. In this paper, the research subject is deeply discussed. I propose to improve the article and provide my comments:

 

1. The title of the paper reflects the content of the paper, please consider some modification: for example The Effect of Total Quality Management and Big Data Management on Customer Satisfaction in Korea’s Public Sector (lines 2-4, especially that Total Quality Management appears in the abstract).
2. Line 16, What is the date of research in Korea-s public sector?
3. Lines 22-23 – keywords- SEM- should be used capital letters.
4. It is worth standardized the concept connected with quality (sometimes is quality management, in other places is Total Quality Management).
5. Line 115 Big data Management - should be used capital letters
6. Line 182 TQM (Total Quality Management) – should appear earlier – for example in abstract.
7. It is worth indicate if some other authors deal with this problem and present some research results.
8. I recommend putting more emphasis on some aspects connected with the public sector (e.g. some aspects in Korea).
9. Research methods are relevant and the hypotheses are formulated in a proper way.
10. What's the software was being used for the calculation of all obtained results?
11. The presentation of the literature material is complete and logical. List of references has of the contemporary sources (not older than 5 years). I think it's a very good result, but it is worth some references from previous papers in this journal.
12. The conclusions are accurate and supported by the content.

 

 

 

Author Response

Reviewer 4.

We appreciate that the reviewer’s comments. The followings are our point-by-point responses:

 

1. The title of the paper reflects the content of the paper, please consider some modification: for example The Effect of Total Quality Management and Big Data Management on Customer Satisfaction in Korea’s Public Sector (lines 2-4, especially that Total Quality Management appears in the abstract).

Response: As suggested by the reviewer, we changed title like this.

        Before) The Effect of Quality Management and Big Data Management on    Customer Satisfaction on Public Sector

                 After) The Effect of Quality Management and Big Data Management on Customer Satisfaction in Korea’s Public Sector

2. Line 16, What is the date of research in Korea-s public sector?

Response: As suggested by the reviewer, we inserted sentence like this (“The survey was conducted between August 1 and August 30, 2019.”) in the line 17~18.

3. Lines 22-23 – keywords- SEM- should be used capital letters.

Response: As far as I know, Sustainability's editorial rules say that it is written in abstract key words.

4. It is worth standardized the concept connected with quality (sometimes is quality management, in other places is Total Quality Management).

Response: Considering the reviewer's suggestion and research model, I tried to unify it with the word total quality management.

5. Line 115 Big data Management - should be used capital letters.

Response: As suggested by the reviewer, we changed capital letter in line 119 (2.2 Big data Management).

6. Line 182 TQM (Total Quality Management) – should appear earlier – for example in abstract.

Response: As suggested by the reviewer, we inserted it in the abstract part (line 10). “Total quality management is the source of quality management activities and customer satisfaction.”

7. It is worth indicate if some other authors deal with this problem and present some research results.

Response: As suggested by the reviewer, the content that total quality management is the source of quality management activities and customer satisfaction has been fully covered in the theoretical background through literature review. It was also verified through empirical analysis and covered in the conclusion part.

8. I recommend putting more emphasis on some aspects connected with the public sector (e.g. some aspects in Korea).

Response: As suggested by the reviewer, we inserted this sentence in conclusion part (line 427-430). And add on the big data usage related future innovation in Korea’s public sector (Line 444-446, “As the accumulation and utilization of big data in the public sector of Korea increases, it will be possible to create smart machine learning and artificial intelligence and create innovative new services.”)

9. Research methods are relevant and the hypotheses are formulated in a proper way.

   Response: Thanks to the reviewers.

10. What's the software was being used for the calculation of all obtained results?

Response: Structural equation model analysis was performed using R's Lavaan program. This is on lines 304-306.

11. The presentation of the literature material is complete and logical. List of references has of the contemporary sources (not older than 5 years). I think it's a very good result, but it is worth some references from previous papers in this journal.

Response: The reason why the recent references are mainly mentioned is that they were suggested by a reviewer of the last time and were largely reflected. I would be grateful if you could understand my situation.

12. The conclusions are accurate and supported by the content.

       Response: Thanks to the reviewers.

 

    Yours faithfully,

Reviewer 5 Report

I fully agree with the hypotheses that were presented in the article. However, I have doubts about the examination and whether it allows hypothesis verification. I miss survey questions. The content indicates that the surveys were directed to institutions and not directly to clients. How was customer satisfaction measured and who answered such a question? The research model itself does not raise my reservations, similarly with statistical methods. I have doubts about the survey itself. I do not know whether the survey on both customer service (operational level of the organization) and strategic decisions (correspondingly higher level in the structure of the organization) can be directed to one respondent.

Author Response

Reviewer 5

We appreciate that the reviewer’s comments. The followings are our point-by-point responses:

1. I fully agree with the hypotheses that were presented in the article. However, I have doubts about the examination and whether it allows hypothesis verification. I miss survey questions.

Response: Thank you for your question and intellectual content. This study adopted the survey method for empirical analysis of the research model (line 222, Figure 3). The operational definition of each factor is presented, and the measurement variables and questions for each factor are explained in detail in 4.1 survey and measurement part (line 268~287).

2. The content indicates that the surveys were directed to institutions and not directly to clients. How was customer satisfaction measured and who answered such a question? The research model itself does not raise my reservations, similarly with statistical methods. I have doubts about the survey itself.

Response: As the reviewer pointed out, this survey is a sampling survey of the public sector in Korea. Respondents carried out big data-based quality management and were in charge of the department in charge, and they responded to the customer's satisfaction because they are at the contact point of external customers (Line 292-294). This response could cause bias and was included in the study's limitations (Line 447-450).

3. I do not know whether the survey on both customer service (operational level of the organization) and strategic decisions (correspondingly higher level in the structure of the organization) can be directed to one respondent.

Response: I deleted the existing content and refined it a little more like line 292-294 (Respondents were responsible for conducting big data-based quality management or for quality management strategic planning departments.)  

 

Yours faithfully,

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

The paper addresses an interesting topic and it is well structured. However, there are weak points. Please go through the following suggestions and questions and address them to produce a stronger submission.

Please use more formal language, e.g. “By 50 managing customer-related big data, you can discover not only the potential needs of customers but 51 also customer wishes.” -->”By managing customer-related big data, ONE can discover not only the potential needs of customers but also customer wishes.” Also, Reference the text better. Statements as this one should provide evidence of examples using big data to achieve such a decision-making goal. Since the paper talks about big data revolution and decision making, please improve upon the literature by mentioning in the text some state-of-the-art machine learning methods and models which nowadays accompany and process these data. For example, in the field os customer satisfaction, administration in public sectors, etc., you may want to mention very recent studies as those by Moodley R., et al, e.g. see DOIs: 10.3390/app10093116, 10.1002/int.22039, 10.1016/j.jretconser.2019.101940. Please reference the narrative a bit better.

“Our research comprises three objectives.” –> please formulate the three objectives in a clear way. As far as I understand, the third point os not an objective of this study, but just the implications of a final goal. Objectives are intermediate steps to achieve a goal, e.g. to create a model, please re-elaborate and clarify better.

“(Employee Orientation thought, Customer orientation thought, 208 and participation in Decision making)” → uniform capitalisation

The Methodology section should introduce the statistical test adopted and motivate their use over other methods and approaches.

The author makes large use of the expression big-data but it is not clear if this research actually uses large volumes of data. Can you please clarify this further in the draft? Where are the big data used and what is their source? I understand test have been run by collecting data via a survey but this is not big-data. Can you please clarify it further in the narrative?

Apart from very simple regression, what other tests are used in the literature? What options have you considered before choosing the proposed methodology?

Please make sure conclusion refer to the obtained numerical results.

There are some typos, e.g. "We developed research model" → "We developed a research model, so perform a linguistic check.

 

Reviewer 2 Report

First of all, I see the studied issue as interesting, I mean the big data techniques implementation along with QM and citizens satisfaction in the public sector. Unfortunately I cannot accept the conclusions and justification driven from the data and statistical methods utilization. In this state of the study I cannot see any reasonable way to improve it.

See my specific comments below:

1. the statement from the abstract is not justified by field data: "usage level of big data has the moderation effect between total quality leadership and quality management"
2. this calls into question the wording of the study title
3. in Table 1, exchange factors, why in the public sector there is only one way exchange, what about taxes, etc.?
4. the literature study is very modest, insufficient, too few literature sources have been identified
5. when hypothesizing some influence, e.g. a big data on QM activities you need to present how this influence can be, sources should support it, especially how the moderation might look like
6. analytical thinking and management by data are totally not clear as tools/variables of big data (by the way you can practice management by data and analytical thinking without Big Data technologies)
7. the reliability of SEM model, as the whole, has not been proven, the literature acceptance levels need to be cited, the kind of SEM modeling clearly specified
8. H3, crucial for the study, cannot be accepted, so, this calls into question the mainstream narrative of this study, note that there a minus estimator appeared 
9. the statement "a higher level of big data management is greater quality management" cannot be accepted
10. this is not acceptable concluding on Organizational Culture, this is a separate management construct which can be referred to as an auxiliary if has not been studied directly, indeed
11. the discussion part along with conclusions provide very little insights, and generally are very flat  

Reviewer 3 Report

 

 

 

 The Effect of Quality Management and Big Data 2 Management on Customer Satisfaction on Public 3 Sector

 

Thank you for the opportunity to revise the paper titled: “The Effect of Quality Management and Big Data 2 Management on Customer Satisfaction on Public 3 Sector”

 

In this paper the author(s) study the application of total quality management based on big data management in the public sector and the moderating factor between total quality leadership and quality management.  Empirically, they rely on   SEM (Structural Equation Model) analysis using data 250 sample.

 

First of all I would like to congratulate the author(s) for an interesting article. The paper makes a nice contribution to the field and addresses a relevant topic nowadays. As some suggestions for the author(s), I have some suggestions:

 

• First, I would recommend indicating in the title, abstract and intro that your focus is on Korea, as this is informative for the reader. Something such as adding at the end of the current title: “evidence from the Chinese market” or anything alike.

 

• Related to the previous point, to what extent can the results be extrapolable to other contexts? Which country characteristics may make the results change in other locations?

 

• I think the paper would benefit from a more comprehensive use of references. Especially in the theory section, there are many statements without reference and in fact not many references overall. The arguments would be better justified with some additional support.

 

• Please indicate the source for all the Figures.

 

• The correlation between total quality leadership and quality management seems a bit high. Is it possible to address this somehow? Any alternate variable is available? This would be indeed useful to show the robustness of the results to alternative model specifications.

 

• The limitations section seems very underdeveloped. I recommend the author(s) to develop it further, especially to suggest potential avenues for further research that arise from your paper and that can be useful for inspiring other researchers.

 

• As a minor thing, please do not capitalize in the introduction the word “A” in First, A research model.

 

 

I hope the author(s) find my comments useful and constructive and I wish them luck with their paper.