Identifying Barriers to the Digitalization of China’s Real Estate Enterprises in Operations Management with an Integrated FTA–DEMATEL–ISM Approach

Round 1

Reviewer 1 Report

I found the paper extremely interesting and also robust from the point of view of the research assumptions and hypotheses and in the application of the different phases of the methodology. There are still some points to be clarified, of a different nature:

1. Methodological: clarify some aspects adopted in the application of the Delphi method
2. Iconographic apparatus: in all the figures and tables the source is not specific (if it is you, it is necessary to indicate "authors processing on software results ... version, etc.)
3. Expository clarity: it is helpful to accompany tables and figures with explanatory legends on the variables, cited with acronyms
4. Research developments: it is helpful to provide some indications on the trajectories both of methodology development on other topics/variables and of experimentation in other fields

In the attached file I have reported my observations in detail and punctually in the form of a note.

About all this, I would like to point out a major review which must be understood as a further improvement of the already high-level paper.

Comments for author File: Comments.pdf

Author Response

Dear reviewer,

Thank you very much for your review dated 11^th Dec. 2022 attaching the comments on our paper entitled “Identifying barriers to the digitalization of China’s real estate enterprises in operations management with integrated FTA-DEMATEL-ISM approach”.

My co-authors and I wish to thank you for your encouraging and thoughtful comments, which have helped us improve the paper. We have made all the changes suggested by you  and are herewith resubmitting the paper for your re-review. The changes are highlighted by using the track changes mode in MS Word.

The following are our responses to the specific points that need change as per your comments.

Point 1: Methodological: clarify some aspects adopted in the application of the Delphi method.

Response 1: Thanks for your kind and helpful advice.

Due to the long length of the first draft of the paper, we omitted the content related to the Delphi method in the revision process, which puzzled you. We have been negligent in this regard and should have placed this section in the appendix A for the reader to see. As for the specific application of Delphi method, we explain it in detail as follows.

“Appendix A:

In the process of constructing the impact factors affecting the digital operation and management of real estate enterprises, we used the Delphi method to consult the prediction opinions of expert group members through back-to-back communication. After 2 rounds of consultation, the opinions of the expert group tend to be concentrated, so as to finally determine the index system. To follow the principle of combining representativeness and authority, multi-discipline and industry understanding, 8 experts, including professors of statistical management in universities and senior executives in the real estate industry, are selected for consultation. (See the notes at the end of the text for the specific composition of personnel).

1. Questionnaire design for expert consultation

The first round of expert consultation questionnaire contains three parts. The first part is 3 first-level indicators and 19 second-level indicators of factors affecting the digitalization of real estate enterprise operation and management. The second part is the evaluation of indicators by experts, including importance score, index familiarity and index importance evaluation basis. The third part is the opinions and suggestions of experts on the design of indicators in the form of open questions. The importance of indicators is measured by the five-point Likert scoring method, with 1-5 indicating Not Important, Not Very Important, Moderately Important, Important and Very Important respectively. The experts' familiarity with the indicators is set as Familiar, More familiar, General, Less Familiar and Unfamiliar with assigned values 1, 0.8, 0.6, 0.4 and 0.2, respectively. The experts’ index judgment basis is set as Practical Experience, Theoretical Analysis, Reference and Intuitive Feeling with assigned values of 1, 0.8, 0.6 and 0.4 respectively.

2. Results of expert consultation

(1) Reliability of the questionnaire. Cronbach's coefficient is used to test the reliability of the expert consultation questionnaire by SPSS25. The reliability coefficient of the first round is 0.828, and the reliability coefficient of the second round is 0.943, indicating that the reliability of the two rounds of expert consultation questionnaire is good.

(2) Expert positivity. The questionnaire recovery rate is usually used as a reference standard to indicate the degree of importance and cooperation given by experts in this survey. The effective response rate of the questionnaires in both rounds is 100%.

(3) The degree of expert authority. Based on the two indicators of experts' familiarity with the indicator (Q2) and experts’ judgment basis for the indicator (Q3), the average Q=(Q2+Q3)/2 is adopted. This study scores 0.85, greater than 0.7, indicating that the experts are familiar with the indicators, and the judgment is based on practical experience and theoretical analysis, which is credible.

(4) The degree of index and the optimization. In the first round of consultation, the average value of experts’ judgement is 4.250, with the coefficient 20.9%. Referring to experts’ suggestions for open questions, modifications are conducted. First, optimization is made. “digital-related system construction” and “digital management organization” are merged into “digital system and management organization”; “managers' willingness to invest” is moved from the upstream module to the midstream module; the downstream module “information mining ability of competitors” is deleted, and “the technical level of market information mining” is added. Then in the second round of consultation, the modified content was fed back to each expert, and then the evaluation was conducted again. Therefore, the index system of influencing factors for the digitalization of operation and management of real estate enterprises in this study is initially formed, including 3 first-level indicators and 18 second-level indicators.

In the FTA model analysis, the index composition of influencing factors is still used in the obstacle index system.” (Appendix A)

Point 2: Iconographic apparatus: in all the figures and tables the source is not specific (if it is you, it is necessary to indicate "authors processing on software results ... version, etc.)

Response 2: Thanks for your kind and helpful advice. We have supplemented the source information in all the charts, including data sources and supporting software.

Point 3: Expository clarity: it is helpful to accompany tables and figures with explanatory legends on the variables, cited with acronyms.

Response 3: Thanks for your helpful advice. We have added explanatory legends on the variables in Table 4-6, as is shown below.

Table 4. Disability Score Counting Table.

Note: The table is compiled according to the questionnaire data.

Table 5. Probability and Impact Score.

Note: The probability and impact score is calculated according to the questionnaire data.

Table 6. Risk Score Sheet.

Note: The risk score is calculated according to table 5.

Point 4: Research developments: it is helpful to provide some indications on the trajectories both of methodology development on other topics/variables and of experimentation in other fields.

Response 4: Thanks for your helpful advice. We have added new contents in paragraph #6 of Section 1 (Introduction), as is shown below.

“FTA (Fault Tree Analysis) is usually used to study the root cause problem of a system, and combined with the risk matrix, risk analysis is carried out to evaluate the probability of the occurrence of specific obstacles[29]. Therefore, fault tree is widely used to make a forward-looking plan for an industry. For example, the test and evaluation of safety system engineering [30], the design and operation of subway system [31], and the risk assessment of applying sensor networks to smart cities [32]. However, it is seldom used in the study of barriers to the digital operation of real estate. DEMATEL (Decision Making Trial and Evaluation Laboratory) can further evaluate the dynamic relationship between barriers, mine the causal relationship between factors, and find out the key factors [33]. Some scholars have applied it to the study of waste management barriers in smart cities [34]. ISM (Interpretative Structural Modeling Method) can make the simplest hierarchical diagram and explore the relationship between obstacles without affecting the function of the system under study [35].” (Paragraph #6 of Section 1)

Response to the specific comments in the article:

Comment 1: have there been positive increases in other sectors besides the commercial one? If yes, please, integrate with that data as well. Thanks!

Response to Comment 1：

    Thanks for your kind and helpful advice. We have added the information in paragraph #1 of Section 1 (Introduction), as is shown below.

“In 2021, China’s primary, secondary and tertiary industries have achieved growth of varying degrees. The added value of the primary industry was 8,308.6 billion yuan, representing an increase of 7.1% over 2020; The added value of the secondary industry reached 4.50904 trillion yuan, up 8.2%. Among the secondary industries, the total industrial added value reached 37,257.5 billion yuan, representing an increase of 9.6% over 2020.(Paragraph #1 of Section 1)

Comment 2: has the COVID-19 pandemic had no effect on the real estate sector?

Talk about it on p. 3, but in the introduction I think it is necessary to anticipate this them

Response to Comment 2:

Thanks for your kind advice. We have added the information about the impact of COVID-19 pandemic in paragraph #2 of Section 1 (Introduction), as is shown below.

“The COVID-19 coronavirus pandemic is impacting the economy across the world, and the real estate industry are certainly not immune to this global trend[6]. Some scholars have found that COVID-19 has reduced the market value of real estate in the United States by about 47% to 62%[7], but its real estate development has decreased by 16.3% in March to April 2021 alone, and the operating capacity is 70% to 75% of the original[8]. Although COVID-19 has hit real estate investment to some extent and reduced the enthusiasm of some people’s buy houses, it is still a common consensus for most Chinese people to buy their own property due to China's large population base. In light of this fact, the demands for housing will remain strong. And crises are also opportunities. Changes in the real estate market have also prompted the transformation and upgrading of real estate enterprises. The application of visualization, big data, cloud computing and other digital technologies will help real estate enterprises obtain large quantities of data in various business links for analysis and decision-making, which will promote process standardization, reduce business costs and improve management efficiency.” (Paragraph #2 of Section 1)

Comment 3: please, insert some references

Response to Comment 3:

Thanks for your helpful advice. We have inserted references [3] and [4] in paragraph #2 of Section 1 (Introduction).

Comment 4: Could a further factor be linked to the human resources of real estate companies, which are not very digital natives? It's correct?

Response to Comment 4:

    Thanks for your helpful advice. What you said is very correct. We have added relevant information in paragraph #3 of Subsection 2.2 (Enterprise Digital Transformation), as is shown below.

“Compared with other industries, such as manufacturing, the digitalization of China’s real estate industry started late. Digitalization focuses on technology, light assets, and focuses on solving the problem of information asymmetry and efficiency. As an asset-heavy industry with a long industrial chain and asymmetric information, the real estate purchase process emphasizes personalization and experience, which makes the real estate have a certain ability to resist the passive digitalization from Internet enterprises[60]. As a result, the real estate industry has a later inflow of digital personnel on a smaller scale than other industries. At the same time, the traditional operation thinking mode of managers in the real estate industry[61] and the insufficient adaptability of employees to new technologies[60] are also impediments to the intelligentized development of industry.” (Paragraph #3 of Subsection 2.2)

Comment 5: please, already indicate here the objective and the outcome of this first phase which anticipates that of the surveys?

Response to Comment 5:

Thanks for your kind and helpful advice. We have stated the objectives and results of the first phase of the prospective investigation in paragraph #1 of Section 3 (Research Methods), as is shown below.

“The goal of the first stage is to build a digital obstacle index system for real estate enterprise operation and management. Firstly, the index system of influencing factors of digitalization of operation management of real estate enterprises is constructed through literature search and Delphi method, and then the primary indicators are clustered by using the analysis results of word cloud map. Finally, the digital obstacle index system of real estate enterprise operation and management is formed, which takes the three links in the upper, middle and lower reaches of the value chain as the second-level index, 9 clustering modules as the third-level index, and 17 primary indicators as the fourth-level index. Based on the index system, we designed the Questionnaire on the Digitalization of Operation and Management of Real Estate Enterprises to further carry out the data collection in the second stage.” (Paragraph #1 of Section 3)

Comment 6: is it (Web of Science) the only one? why not Scopus?

Response to Comment 6:

Thanks for your kind and helpful advice. Scopus is also a very important literature resource database. Though our school does not provide the database resource, we managed to obtain the permission to use the resource. We used keywords such as "real estate", "technology", and "barriers" on the Scopus database to search for literature. It was found that there were only 46 relevant literary works from 2014 to 2022. The literature works that were not related to the influencing factors were removed one by one. After screening, there were 10 papers (see Appendix 1). The content analysis mainly included information and communication technology, technical level, human capital, policy factors and other aspects. Through the comparison with the contents in able 1, it is found that the factors or obstacles mentioned in the literature can correspond to the secondary indicators (see the comparison between columns 4 and 5 in Appendix 1), which further confirms that content analysis on literature search and Delphi method are reasonable in finding the digital impact index system of real estate enterprise operations and management.

      As we have added literature from Scopus, we revised the original Figure 1.  

Before                                            After

Based on the above, we have updated the information in paragraph #1 of Subsection 3.1 (The establishment of indicator system in the digitalization of real-estate management), as is shown below.

“Relevant literature search was conducted using two major literature databases, namely CNKI in China, Web of Science and Scopus.” “a total of 530 references were collected” (Paragraph #1 of Subsection 3.1)

Appendix Content Analysis of Literature

Comment 7: Have you only mentioned the Delphi method: I ask you to integrate with the punctualization of some choices made to apply Delphi, for example how many experts, their role, how many rounds, how has convergence have been achieved statistically?

Response to comment 7:

Thanks for your kind advice. Due to the long length of the first draft of the paper, we omitted the content related to the Delphi method in the revision process, which puzzled you. We have been negligent in this regard and should have placed this section in the Appendix A for the reader to see. As for the specific application of Delphi method, we explain it in detail as follows.

“Appendix A

In the process of constructing the impact factors affecting the digital operation and management of real estate enterprises, we used the Delphi method to consult the prediction opinions of expert group members through back-to-back communication. After 2 rounds of consultation, the opinions of the expert group tend to be concentrated, so as to finally determine the index system. To follow the principle of combining representativeness and authority, multi-discipline and industry understanding, 8 experts, including professors of statistical management in universities and senior executives in the real estate industry, are selected for consultation. (See the notes at the end of the text for the specific composition of personnel).

1. Questionnaire design for expert consultation

The first round of expert consultation questionnaire contains three parts. The first part is 3 first-level indicators and 19 second-level indicators of factors affecting the digitalization of real estate enterprise operation and management. The second part is the evaluation of indicators by experts, including importance score, index familiarity and index importance evaluation basis. The third part is the opinions and suggestions of experts on the design of indicators in the form of open questions. The importance of indicators is measured by the five-point Likert scoring method, with 1-5 indicating Not Important, Not Very Important, Moderately Important, Important and Very Important respectively. The experts' familiarity with the indicators is set as Familiar, More familiar, General, Less Familiar and Unfamiliar with assigned values 1, 0.8, 0.6, 0.4 and 0.2, respectively. The experts’ index judgment basis is set as Practical Experience, Theoretical Analysis, Reference and Intuitive Feeling with assigned values of 1, 0.8, 0.6 and 0.4 respectively.

2. Results of expert consultation

(1) Reliability of the questionnaire. Cronbach's coefficient is used to test the reliability of the expert consultation questionnaire by SPSS25. The reliability coefficient of the first round is 0.828, and the reliability coefficient of the second round is 0.943, indicating that the reliability of the two rounds of expert consultation questionnaire is good.

(2) Expert positivity. The questionnaire recovery rate is usually used as a reference standard to indicate the degree of importance and cooperation given by experts in this survey. The effective response rate of the questionnaires in both rounds is 100%.

(3) The degree of expert authority. Based on the two indicators of experts' familiarity with the indicator (Q2) and experts’ judgment basis for the indicator (Q3), the average Q=(Q2+Q3)/2 is adopted. This study scores 0.85, greater than 0.7, indicating that the experts are familiar with the indicators, and the judgment is based on practical experience and theoretical analysis, which is credible.

(4) The degree of index and the optimization. In the first round of consultation, the average value of experts’ judgement is 4.250, with the coefficient 20.9%. Referring to experts’ suggestions for open questions, modifications are conducted. First, optimization is made. “digital-related system construction” and “digital management organization” are merged into “digital system and management organization”; “managers' willingness to invest” is moved from the upstream module to the midstream module; the downstream module “information mining ability of competitors” is deleted, and “the technical level of market information mining” is added. Then in the second round of consultation, the modified content was fed back to each expert, and then the evaluation was conducted again. Therefore, the index system of influencing factors for the digitalization of operation and management of real estate enterprises in this study is initially formed, including 3 first-level indicators and 18 second-level indicators.

In the FTA model analysis, the index composition of influencing factors is still used in the obstacle index system.” (Appendix A)

Comment 8: please, reflect on the opportunity to include the empty questionnaire model in the Annexes

Response to comment 8:

Thanks for your kind and helpful advice. We have added the questionnaire model in the Appendix B, as is shown below.

“Appendix B

Questionnaire on digitalization of operation and management of real estate enterprises

Dear friends: with the continuous development of technology, the real estate industry has brought a fortune to the global economy. However, at present, real estate enterprises are still using traditional management methods. We guess that through the innovation of the digital value chain that meets the requirements of the industry, the operation and management of real estate enterprises will be promoted, the core value chain of my country's real estate enterprises will be optimized, and the core competitiveness will be continuously improved to achieve efficient operation. Therefore, we are conducting a survey on the current situation of digital value chain innovation of real estate companies and the obstacles they face, and would like to invite you to take a few minutes to help answer this questionnaire.

This questionnaire is anonymous, and all the data are only used for statistical analysis. Your opinions are very important to our research. We sincerely hope that you will take time out of your busy schedule to assist us in completing this questionnaire. There is no right or wrong question option, please fill in the answer according to the actual situation. Sincerely thanks for your support and help!

1. Basic information
2. Your gender:
3. Male
4. Female

2. Your age:
3. 20-30 years old
4. 31-40 years old
5. 41-50 years old
6. over 51 years old

3. Your education level:
4. High school and below
5. Specialty
6. Undergraduate
7. Postgraduate and above

4. Your occupation:
5. Top management team
6. Investor
7. Designer
8. Financier

  E Marketing planner

1. Project staff
2. Developer
3. Cost buyer
4. Operator
5. Commercial operator
6. Property staff
7. Other personnel

5. Your years of experience in real estate:
6. Under 5 years

  B 5-10 years (excluding 10 years)

1. 10-20 years (excluding 20 years)
2. 20 years and above

6. Your monthly income:
7. Below 8000 yuan
8. 8000-20000 yuan
9. 20001-50000 yuan
10. 50,000 yuan and above
11. Keep secret

7. The province you work in is _____

8. Annual sales of your company:
9. 200 billion and above
10. 100-200 billion (excluding 200 billion)
11. 50-100 billion (excluding 100 billion)
12. 10 billion-50 billion (excluding 50 billion)
13. Less than 10 billion

9. Your institution is affiliated with:
10. Group
11. Area
12. City
13. Project

10. Is your company a listed company?
11. Yes
12. No

1. Current situation cognition
2. How much do you know about digital real estate?
3. Do not know
4. Not sure
5. General understanding
6. Comprehension
7. Know very well

12. Which of the following digital technologies do you know? (multiple choice)
13. Artificial Intelligence (AI)
14. Big Data
15. Virtual Reality System (VR)
16. Cloud Computing Technology
17. Software as a Service (SaaS)
18. Augmented Reality (AR)
19. Blockchain
20. Wearable Gadgets/Devices
21. UAV, Automatic Control System
22. Internet of Things
23. 3D Printing
24. 3D Scanning
25. Others

13. Is your company currently using digital technology? (Answer: "No" skip to question 15)
14. Yes
15. No
16. Do not know

14. What digital technologies does your company use?
15. Artificial Intelligence (AI)
16. Big Data
17. Virtual Reality System (VR)
18. Cloud Computing Technology
19. Software as a Service (SaaS)
20. Augmented Reality (AR)
21. Blockchain
22. Wearable Gadgets/Devices
23. UAV, Automatic Control System
24. Internet of Things
25. 3D Printing
26. 3D Scanning
27. Others

15. Is your company willing to use digital technology? (Answer: "No" skip to question 17)
16. Yes
17. No

16. What digital technologies is your company willing to use? (Multiple choice)
17. Artificial Intelligence (AI)
18. Big Data
19. Virtual Reality System (VR)
20. Cloud Computing Technology
21. Software as a Service (SaaS)
22. Augmented Reality (AR)
23. Blockchain
24. Wearable Gadgets/Devices
25. UAV, Automatic Control System
26. Internet of Things
27. 3D Printing
28. 3D Scanning
29. Others

17. What impact does your company hope to bring to the company by adopting digital technology?
18. Improve productivity
19. More standardized operation
20. Broaden information dissemination channels
21. Diversification of sales channels
22. Reduce manufacturing cost
23. Strengthen risk control
24. Others

III. Barriers to digital technology

18. [Matrix Scale Questions] The barriers your company encounters when using digital technology, or the reasons for not using digital technology, please choose according to the actual situation. (1-5 indicates the degree from low to high)

19. Do you have any specific examples or any other details to share with us regarding the adoption of digital technology in real estate business? (This can include barriers not discussed in the questionnaire, or other information that you think could help this research)” (Appendix B)

Comment 9: Please, for a clearer navigation in the structure of the paper, I recommend also indicating the paragraphs where these phases and these technical passages were addressed.

Response to comment 9:

Thanks for your kind and helpful advice. We have added the information in paragraph #3 of Subsection 3.4 (Construction of DEMATEL-ISM in the digitalization of operations management of real-estate enterprises), as is shown below.

“In the DEMATEL stage, based on the questionnaire data of the index system collected above, the direct influence matrix is established and normalized in Sub-section 4.3.1. In Sub-section 4.3.2, the comprehensive influence matrix and the overall influence matrix as well as the four indexes of influence degree, influence degree, centrality degree and cause degree are calculated. Based on the calculation of the overall influence matrix and reachability matrix of ISM stage in Sub-section 4.3.3, a multi-level hierarchical structural model is constructed and analyzed in Sub-section 4.3.5 after the primary obstacle degree elements is allocated in Sub-section 4.3.4.” (Paragraph #3 of Subsection 3.4)

Comment 10: It could also be useful to indicate future developments of the method or if there are prospects for "preventive" application to analyze other central themes of the real estate market.

Response to comment 10:

Thanks for your kind and helpful advice. We have added the information in paragraph #7 of Section 5 (Conclusions), as is shown below.

“As for the analysis of the dynamic relationship between obstacle degrees, this study only uses classical DEMATEL, and different DEMATEL models, such as fuzzy DEMATEL and gray DEMATEL, can be explored in the future. At present, this method is used to study the barriers to digital operation in China's real estate industry, and it can be applied to the real estate industry of other countries or the field of business process management of real estate in the future.” (Paragraph #7 of Section 5)

Author Response File: Author Response.docx

Reviewer 2 Report

This was a very interesting read! I only have a few minor suggestions to make:

1. I would suggest an additional round of proofreading, to eliminate the few remaining formulation errors (e.g., "In the last two and three decades [...]" should probably read "In the last two or three decades [...]" (R102); "[...] and should pay attention to the incentive [incentives?] and guidance role [guiding role?] of performance evaluation guidance [the word 'guidance' appears twice in the same sentence] (R112-113); "The study will be conducted from [in?] three stages" (R170-171), etc.).

2. I would recommend spelling the acronyms the first time they appear in the text, especially for the FTA, DEMATEL and ISM methods.

3. Why are the four specific rules of the FTA important (Equations (1), (2), (3), and (4)? A short explanation might help the reader to better understand why the authors singled these rules out and not the others.

4. Some section titles are capitalised throughout (e.g., "2.2 Enterprise Digital Transformation"), while others use a sentence capitalisation (e.g., "2.1 Enterprise operations management". Capitalisation should be consistent throughout the text.

5. The first DEMATEL step in Figure 4 might contain a spelling error: "Determine the system [?] evaluation index system". Furthermore, I would have liked a bit more context for "Extent of the affected [what?]".

6. Figure 5a should either have the percentage sign (%) on the pie chart, or in the title (e.g., "The posts of respondents, in per cent"). As for Figure 5b, the resolution seems to be quite low, and I was unable to read the text clearly.

7. In Figure 7, should the title perhaps read "Willingness to Use [instead of "Using"] Digital Technology"?

8. In Figure 10, I would have liked to read more about the five levels and their groupings into "Surface direct barriers", "Middle-level [Mid-level?] indirect barriers", and "Deep root barriers".

Author Response

Dear reviewer,

Thank you very much for your review dated 11^th Dec. 2022 attaching the comments on our paper entitled “Identifying barriers to the digitalization of China’s real estate enterprises in operations management with integrated FTA-DEMATEL-ISM approach”.

My co-authors and I wish to thank you for your encouraging and thoughtful comments, which have helped us improve the paper. We have made all the changes suggested by you  and are herewith resubmitting the paper for your re-review. The changes are highlighted by using the track changes mode in MS Word.

The following are our responses to the specific points that need change as per your comments.

Point 1: I would suggest an additional round of proofreading, to eliminate the few remaining formulation errors (e.g., "In the last two and three decades [...]" should probably read "In the last two or three decades [...]" (R102); "[...] and should pay attention to the incentive [incentives?] and guidance role [guiding role?] of performance evaluation guidance [the word 'guidance' appears twice in the same sentence] (R112-113); "The study will be conducted from [in?] three stages" (R170-171), etc.).

Response 1: Thanks for your kind and helpful advice. All the above mentioned parts have been modified, and an additional round of proofreading has been carried out on the full text, as is shown below.

“In the last two or three decades, social and economic development has seen mod-ern businesses expand their production capacities and modernize their operations.” (Paragraph #3 of Subsection 2.1)

“They also need to reasonably layout all aspects of the operation management process based on their own development, implement refined operations management pro-grams based on their internal business chain and external value chain, and should pay attention to the incentive and guiding role of performance evaluation guidance” (Paragraph #3 of Subsection 2.1)

“The study will be conducted in three stages.” (Paragraph #1 of Section 3)

Point 2: I would recommend spelling the acronyms the first time they appear in the text, especially for the FTA, DEMATEL and ISM methods.

Response 2: Thanks for your kind and helpful advice. We have modified this in paragraph #6 of Section 1(Introduction), as is shown below.

“Fault Tree Analysis (FTA) is usually used to study the root cause problem of a system, and combined with the risk matrix, risk analysis is carried out to evaluate the probability of the occurrence of specific obstacles[29]. Therefore, fault tree is widely used to make a forward-looking plan for an industry. For example, the test and evaluation of safety system engineering[30], the design and operation of subway system[31], and the risk assessment of applying sensor networks to smart cities[32]. However, it is seldom used in the study of barriers to the digital operation of real estate. Decision Making Trial and Evaluation Laboratory (DEMATEL) can further evaluate the dynamic relationship between barriers, mine the causal relationship between factors, and find out the key factors[33]. Some scholars have applied it to the study of waste management barriers in smart cities[34]. Interpretative Structural Modeling Method (ISM) can make the simplest hierarchical diagram and explore the relationship between obstacles without affecting the function of the system under study[35].” (Paragraph #6 of Section 1)

Point 3: Why are the four specific rules of the FTA important (Equations (1), (2), (3), and (4)? A short explanation might help the reader to better understand why the authors singled these rules out and not the others.

Response 3: Thanks for your kind and helpful advice. Because Equations (1), (2), (3), and (4) are the basic rules of Boolean algebra, most of the other derived rules are derived from these four basic rules, that’s why it is used in this paper.

Point 4: Some section titles are capitalised throughout (e.g., "2.2 Enterprise Digital Transformation"), while others use a sentence capitalisation (e.g., "2.1 Enterprise operations management". Capitalisation should be consistent throughout the text.

Response 4: Thanks for your kind and helpful advice. We have unified the section titles to be capitalized throughout, as is shown below.

“Enterprise Operations Management” (The title of Subsection 2.1)

“The Establishment of Indicator System in the Digitalization of Real-estate Management” (The title of Subsection 3.1)

“Questionnaire Design and Reliability Test” (The title of Subsection 3.2)

“FTA Barriers Degree Model Construction in the Digitalization of Real-estate Enterprises” (The title of Subsection 3.3)

“Establishment of Index System of Obstacle Degree” (The title of Subsection 3.3.2)

“Construction of DEMATEL-ISM in the Digitalization of Operations Management of Real-estate Enterprises” (The title of Subsection 3.4)

“Demographics of Respondents” (The title of Subsection 4.1.1)

“Adoption Intention of Digital Technology” (The title of Subsection 4.1.3)

“Calculation of the Total-influence Matrix” (The title of Subsection 4.3.2)

Point 5: The first DEMATEL step in Figure 4 might contain a spelling error: "Determine the system [?] evaluation index system". Furthermore, I would have liked a bit more context for "Extent of the affected [what?]".

Response 5: Thank you for your kind and helpful advice. We have made modifications for Figure 4 in Subsection 3.4 (Construction of DEMATEL-ISM in the digitalization of operations management of real-estate enterprises) The meaning of “Extent of the affected” is the same as “Influenced degree” in formula 12, indicating the degree of influence of each element on other elements. We expressed it uniformly as “Influenced degree” and modify it in Figure 4, as is shown below.

Before                                           After

Figure 4. The DEMATEL-ISM method operation flow chart

Point 6: Figure 5a should either have the percentage sign (%) on the pie chart, or in the title (e.g., "The posts of respondents, in per cent"). As for Figure 5b, the resolution seems to be quite low, and I was unable to read the text clearly.

Response 6: Thank you for your kind and helpful advice. We have indicated the units in the captions of Figure 5a, Figure 5b and have revised Figure 5b in Subsection 4.1.1, as is shown below.

• The posts of respondents (in percent)

Figure 5. The demographics of the respondents

Point 7: In Figure 7, should the title perhaps read "Willingness to Use [instead of "Using"] Digital Technology"?

Response 7: Thank you for your kind and helpful advice. We have modified the title of Figure 7 to "Willingness to Use Digital Technology" in the Subsection 4.1.3, as is shown below.

Before                                           After

Figure 7. The adoption intention chart of digital technologies

Point 8:  In Figure 10, I would have liked to read more about the five levels and their groupings into "Surface direct barriers", "Middle-level [Mid-level?] indirect barriers", and "Deep root barriers".

Response 8: Thanks for your kind and helpful advice. We have performed further analysis on Figure 10 in paragraph #2 to #6 of Subsection 4.1.3, as is shown below.

“The direct influence of the surface layer is mainly composed of the elements of the fifth and fourth layers. Among them, the fifth layer is the two elements of “poor cooperation between stakeholder enterprises (S₁₂)” and “lack of advanced technology in market information mining (S₁₆)”, which are called the external link of the real estate enterprise. The former (S₁₂) indicates the ability of cooperation between the real estate enterprise itself and other related enterprises. The latter (S₁₆) indicates whether real estate enterprises can use digital technology to timely tap and master external opportunities and customer needs in the real estate market.

The fourth layer consists of three elements: lack of data management and data repository (S₇), poor organization and coordination of various departments within the enterprise (S₁₃) and enterprises’ lack of sufficient dynamic sales information (S₁₄) , which are called the internal links of real estate enterprises, mainly showing the construction of real estate enterprises' own database and the application of digital technology to achieve more effective coordination of departments and more accurate grasp of sales information. From the perspective of the relationship between the two layers of direct influence on the surface, the three elements of the fourth layer have a significant impact on the market information mining ability of the fifth layer. On the one hand, it reflects whether the real estate enterprises can use advanced digital technology to mine, store and develop market information. On the other hand, it shows whether the real estate enterprises can first grasp the sales information from the perspective of the supply side, and carry out the smooth transmission and sharing of information among departments, and expand to the information mining of the demand side on this basis. The coordination level of internal departments at the fourth layer has a great impact on the cooperation ability of external stakeholders of the real estate enterprises at the fifth layer, which is more realistic. From the perspective of the underlying impact path, the cooperation ability between different enterprise entities is also affected by the “insufficiency of industry regulations, standards and supervision (S₁₅)” in the first layer. Therefore, it can be seen that the standard and healthy development of the industry as a whole is the cornerstone to ensure good cooperation among all subjects in the industry.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

I really appreciated the changes and additions (now very punctual). For me it is now publishable