Taming Disruption? Pervasive Data Analytics, Uncertainty and Policy Intervention in Disruptive Technology and its Geographic Spread

Round 1

Reviewer 1 Report

The main objective of the proposed article is to explore the concept of "Disruptive Technology" and propose a methodology capable of predicting such technologies. The contextualization of the article is very well achieved, supported by work done in the same area, which gives it a degree of scientific rigor. However, you must implement corrections and improvements.

(1) Corrections:

- Review acronyms: eg. NRC (line 50);

- Description of article structure (line 85-88, 489, 584) and sections (i.e., duplication in use of section 6);

- line 349: "... victims(people with … is one example. The ...”;

- line 414: "... and HTC's ***using ...";

- line 538: "... sales of SmartPhonesso it ..."

- line 728: "Bibliography", ???;

- Review referencing: links on line 221-222 and 454-455 (they should be in references and not in the body of the text);

- Review self-referencing: "[21] Brackin, R. Hobona, G. Jackson, M. (2012), The Connected Individual, Task 1, Advanced Geospatial Intelligence Services Research, DSTL. (available from author) ".

(2) Advice for improving the article:

- Review the article in order to synthesize the main relevant concepts that support the proposed methodology (i.e., the article contains countless reflections and statements constantly repeated throughout the text, which makes its reading tiring);

- Review and justify the use of the statement "... big data modelling and predictive analytical techniques ..." in lines 27-28. What techniques were used? After reading the article, do we wonder whether "big data analysis" makes sense in the context of the methodology tested, i.e., the volume of data analyzed is sufficiently high? If so, which one? Does the data have to be analyzed in real time? Other more "traditional" approaches (e.g., data mining, OLAP cubes, etc.) would not be sufficient to obtain the analytical result tested in the proposed methodology? ...;

- Review rigorously the use of the terms "smartphones" and "iPhones";

- Since the Uber App is available in the mobile universe of Apple and Android, the question is: Why the option to correlate the variables "Apple stores" and "Uber"? On the other hand, the article focuses on the geographical issue, and once again the question: why the mobile universe was restricted to Apple? (since its acceptance by the end user is not uniform across all continents). It is important to clarify these issues;

- Finally, it is also necessary to state clearly, how the experimentation of the proposed methodology contributes to the prediction of "Disruptive Technology".

Author Response

General Comments:

Given the time available and the divergent views, as well as the time for revision the authors have tried to reconcile the issues pragmatically. We have concentrated in addressing the issue which we think caused the first two reviewers most concern. 

The paper firstly presents a conceptual ‘unifying’ view of existing research. The second part in not intended to be a complete enactment of that research, simply an example of the potential for analysis in relation to the disruption due to technology. We have tried to make this clearer in the introduction and also make the relationship of the initial experimentation with the conceptual sections clearer in those sections.  

We have also addressed the specific comments where we can, and we thank the reviewer for  the comments. A fuller set of responses is given per reviewer below. Comments shown in blue. Comments are also present in the draft paper to indicate the relevant sections in relation to the comments (as far as is possible).

The attachment includes a revised version of the paper with track changes as well as the commentary below included (as well as the commentary from other reviewers). 

(1) Corrections:

- Review acronyms: eg. NRC (line 50);

R Brackin:  Expanded on first use

- Description of article structure (line 85-88, 489, 584) and sections (i.e., duplication in use of section 6);

R. Brackin: Conclusions misnumbered as part 7 - Corrected.

- line 349: "... victims(people with … is one example. The ...”;

R Brackin: English Revised

- line 414: "... and HTC's ***using ...";

R. Brackin: The English in this section has been revised but HTC is purely a tradename and so expansion of the acronym is not useful. 

- line 538: "... sales of SmartPhonesso it ..."

R. Brackin: Case updated to ‘smartphones’

- line 728: "Bibliography", ???;

R. Brackin: The template suggested that relevant papers to this work but ones which are not specifically referenced in the text should be captured under bibliography. This is the intention of this section. We have though concluded that it may be best to remove items not referenced in the paper.  

- Review referencing: links on line 221-222 and 454-455 (they should be in references and not in the body of the text);

R. Brackin: These were direct web references but in any case they are are now included in the references section. 

- Review self-referencing: "[21] Brackin, R. Hobona, G. Jackson, M. (2012), The Connected Individual, Task 1, Advanced Geospatial Intelligence Services Research, DSTL. (available from author) ".

R.Brackin: This item is not public. We have identified the organisation it is available from if readers wish to obtain it. 

(2) Advice for improving the article:

- Review the article in order to synthesize the main relevant concepts that support the proposed methodology (i.e., the article contains countless reflections and statements constantly repeated throughout the text, which makes its reading tiring);

R.Brackin: The authors have reviewed the paper and made subtle changes. Given the comment is very general, it is hard to address further without specifics.

- Review and justify the use of the statement "... big data modelling and predictive analytical techniques ..." in lines 27-28. What techniques were used? After reading the article, do we wonder whether "big data analysis" makes sense in the context of the methodology tested, i.e., the volume of data analyzed is sufficiently high? If so, which one? Does the data have to be analyzed in real time? Other more "traditional" approaches (e.g., data mining, OLAP cubes, etc.) would not be sufficient to obtain the analytical result tested in the proposed methodology? ...;

R Brackin: Re the statement in lines 27-28, The primary big data techniques is stated in 245-259 and the selection specifically of proxy measures is identified throughout the experiment description in section 6. The idea of scraping unformatted material and collating it, and the idea of proxy measures is we believed thoroughly described. The author’s agree that the experimentation presented in this paper does not count as ‘big data analytics’ although the term is not well defined. In fact the authors were careful to use the term ‘big data approach’ rather than big data analytics when discussing the experimentation. We have made this distinction more explicit in the paper now. The expectation is that the conceptual part of the paper provides a foundation for a series of measures and these could be executed using ‘big data’. The experiment shown was really a pre-cursor to experimentation that could without debate be called ‘big data’. See text added at 368 to qualify this.

- Review rigorously the use of the terms "smartphones" and "iPhones";

R Brackin: The authors tried to be clear on this distinction. We have reviewed it further and made some adjustments (particularly in . Hopefully it is now clearer now). (546)

- Since the Uber App is available in the mobile universe of Apple and Android, the question is: Why the option to correlate the variables "Apple stores" and "Uber"? On the other hand, the article focuses on the geographical issue, and once again the question: why the mobile universe was restricted to Apple? (since its acceptance by the end user is not uniform across all continents). It is important to clarify these issues;

R Brackin: This issue was clarified in a footnote which seems to have vanished as a result of the template. The following text has been added to the article.

“An issue which needs to be addressed is are Apple stores a valid measure of smartphone availability? Apple is only one supplier of smartphones. However since the metric required was ‘are smartphones widely distributed in the city of interest’ and Apple accounts for a significant part of the market (close to 50% over the period of study) the availability of an Apple store is a valid measure of smartphone availability (as it is unlikely that smartphone availability will be widespread without Apples presence). There are special cases which we acknowledge, but Apple store numbers is a measurable property and, on the basis of the above is a valid general proxy for smartphone availability.”  

- Finally, it is also necessary to state clearly, how the experimentation of the proposed methodology contributes to the prediction of "Disruptive Technology".

R Brackin: Text added to 383 justifies the relevance of the experimentation in sections 5 and 6.

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear authors,

I have enjoyed very much reading your paper, which I found very intriguing.
Your work addresses a very important topic. It has very ambitious objectives, and contains some interesting research ideas. However, in its current form, the paper is affected by some major weakness that should be addressed before publication.
The interpretative framework has some major problems. However, the main problem is that it does not in any way correspond to what the authors actually present in the empirical part of the paper.
Indeed, while the interpretative framework focuses on the analysis of new disruptive technologies – and suggests that big data could be used to forecast the emergence of such radical change – in the empirical part the paper analyzes the geographical spread of a product (Apple smartphone) and of a business model (Uber).

The empirical part is interesting. Therefore, I would suggest the authors to rewrite the first part to make it consistent with the second part. The relevant literature, in my opinion, is the one that deals with innovation diffusion. The research design should be adjusted accordingly.

My second major point is that in the current conceptual framework put forward by the authors, geography is very marginal. The only mention to the territorial aspects of technological change is found on page 12, and it is a very simple mention. I would recommend to the authors to elaborate more on the geographical aspects of innovation diffusion (sse, e.g. the works of Simone Strambach or Roman Martin).

I wish you good luck with your research project.

Author Response

Given the time available and the divergent views, as well as the time for revision the authors have tried to reconcile the issues pragmatically. We have concentrated in addressing the issue which we think caused the first two reviewers most concern. 

The paper firstly presents a conceptual ‘unifying’ view of existing research. The second part in not intended to be a complete enactment of that research, simply an example of the potential for analysis in relation to the disruption due to technology. We have tried to make this clearer in the introduction and also make the relationship of the initial experimentation with the conceptual sections clearer in those sections.  

We have also addressed the specific comments where we can, and we thank the reviewers for their comments and for some interesting and relevant references. A fuller set of responses is given per reviewer below. Comments shown in blue. Comments are also present in the draft paper to indicate the relevant sections in relation to the comments (as far as is possible).

The attachment includes a revised paper with track changes on and some comments in line. It also includes a commentary on all the comments from the three reviewers at the end (an exact copy of the text below for each review. 

We thank you for your comments on the paper and hope the attached addresses them. 

Specific Comments

I have enjoyed very much reading your paper, which I found very intriguing.

Your work addresses a very important topic. It has very ambitious objectives, and contains some interesting research ideas. However, in its current form, the paper is affected by some major weakness that should be addressed before publication.

The interpretative framework has some major problems. However, the main problem is that it does not in any way correspond to what the authors actually present in the empirical part of the paper.

R Brackin: Lines 71-85 do explain how the geographic element is included, and explain the relevance of the example provided in the second part of the paper.

We are not clear as to the issue in relation to the interpretive framework. Other reviewers do not see an issue here. In relation to the discordance of the two parts of the paper, we have reinforced the message with the paragraph added at 383 which tries to at least address this to some degree (given the time constraints).

Indeed, while the interpretative framework focuses on the analysis of new disruptive technologies – and suggests that big data could be used to forecast the emergence of such radical change – in the empirical part the paper analyzes the geographical spread of a product (Apple smartphone) and of a business model (Uber).

R Brackin: As above. We do expect to bring forward two papers which expand on the big data approach and elaborate the empirical part of the research. The intention of the initial experimentation given in the second part of the paper was to provide an initial example of the sort of metrics we were considering. The text added to 383 and 399 tries to make this clear.

The empirical part is interesting. Therefore, I would suggest the authors to rewrite the first part to make it consistent with the second part. The relevant literature, in my opinion, is the one that deals with innovation diffusion. The research design should be adjusted accordingly.

R Brackin: As above, there is unfortunately far too little time to achieve this revision (10 days). We have now qualified the purpose of the empirical component a little more. Hopefully this is sufficient.

My second major point is that in the current conceptual framework put forward by the authors, geography is very marginal. The only mention to the territorial aspects of technological change is found on page 12, and it is a very simple mention. I would recommend to the authors to elaborate more on the geographical aspects of innovation diffusion (sse, e.g. the works of Simone Strambach or Roman Martin).

R Brackin: We agree geography is not brought out although it is a key part of the concept and framework we have been developing to implement a broader experiment. Geography represents a driver for two aspects of model (Arthur’s anatomy). We expand time variations but don’t describe the geographic variations of elements in Arthur’s technology anatomy. The reviewer identifies valuable research in relation to one aspect (the spread of innovation geographically). We have included text describing this and two references mentioned and an additional one cited in one of those.  We expect this to be sufficient to make the link needed.

Author Response File: Author Response.pdf

Reviewer 3 Report

General Evaluation:
A. This paper has outlined research related to assessing future technology trends and looked at 586 how these trends could be monitored using big data approaches.  described some of the key 587 underpinning theoretical research, particularly from Arthur and Christensen on both the anatomy of  technology and the typical developmental aspects of technology which cause disruption

B. The research work covered in the paper is very interesting area. This research work well organized, presented and the hypothesis is well defended with clear experimentation and results. The proposed algorithm not only achieves superior accuracy but also exhibits a higher level of stability.
See the following comments:
1. Check the language of the paper by native speaker, and fix the error mistakes.
2. You should make the ABSTRACT more clear. You should make your proposed method more clearly in the ABSTRACT alongside with the obtained results (the results you got it and what is the situation of your results in comparison with other published methods).
3. Check the last paragraph in the introduction section before the paper organization and make sure to deliver your idea clear. The last paragraph before the end of section one should contains at least the follows:
a. The proposed methods clearly what is the main differences between the proposed algorithm and the others
b. How the contributions were done.
c. The problem that have been solved in this research.
d. The general results that you have been got.
e. a detailed discussion on the literature is required, even though the following suitable references should be added in the reference section.
- A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria. Design Automation for Embedded Systems, 1-22.
- A framework for risk assessment, management and evaluation: Economic tool for quantifying risks in supply chain. Future Generation Computer Systems, 90, 489-502.
- Towards a Reuse Strategic Decision Pattern Framework–from Theories to Practices. Information Systems Frontiers, 1-18.
- A group decision making framework based on neutrosophic VIKOR approach for e-government website evaluation. Journal of Intelligent & Fuzzy Systems, 34(6), 4213-4224.
4. Be stable when used the terms like paper, study, Make it in a uniform style.
5. Check the first paragraph in the section 2.
6. Some paragraphs are not well aligned.
7. Check all figures of the whole paper.
8. Discussions of the results should be more detailed
9. Please check figure 16.
10. In the text some paragraph is too long, it's better to split into 2 or 3 paragraphs, and each paragraph focuses on a main area or point.
11. Identified research gaps and contribution of the proposed study should be elaborated.

Author Response

Thank you for your positive review of the paper. Others raised more significant concerns.

Given the time available and the divergent views, as well as the time for revision the authors have tried to reconcile the issues pragmatically. We have concentrated in addressing the issue which we think caused the first two reviewers most concern. 

The paper firstly presents a conceptual ‘unifying’ view of existing research. The second part in not intended to be a complete enactment of that research, simply an example of the potential for analysis in relation to the disruption due to technology. We have tried to make this clearer in the introduction and also make the relationship of the initial experimentation with the conceptual sections clearer in those sections.  

We have also addressed the specific comments where we can, and we thank the reviewers for their comments and for some interesting and relevant references. A fuller set of responses is given per reviewer below. Comments shown in blue. Comments are also present in the draft paper to indicate the relevant sections in relation to the comments (as far as is possible).

Attached is the revised paper with track changes. The three reviewers comments are also collected at the end. (The text is identical to that given below). 

General Evaluation:

A. This paper has outlined research related to assessing future technology trends and looked at 586 how these trends could be monitored using big data approaches.  described some of the key 587 underpinning theoretical research, particularly from Arthur and Christensen on both the anatomy of  technology and the typical developmental aspects of technology which cause disruption

B. The research work covered in the paper is very interesting area. This research work well organized, presented and the hypothesis is well defended with clear experimentation and results. The proposed algorithm not only achieves superior accuracy but also exhibits a higher level of stability.

R, Brackin: Thank you. The authors appreciate these positive comments.

See the following comments:

1.     Check the language of the paper by native speaker, and fix the error mistakes.

R Brackin: There were a small number of typographic issues in the reviewed submission due to the very short time in which the paper was restructured to fit this journal template.  All authors are native English speaking. It has been reviewed again.

2. You should make the ABSTRACT more clear. You should make your proposed method more clearly in the ABSTRACT alongside with the obtained results (the results you got it and what is the situation of your results in comparison with other published methods).

R Brackin: The authors have reviewed the abstract and tried to address the comments made:

3. Check the last paragraph in the introduction section before the paper organization and make sure to deliver your idea clear. The last paragraph before the end of section one should contains at least the follows:

Firstly, the statement in this paragraph which suggests the work is specifically about the empirical results included has been revised. Other points addressed below.

a. The proposed methods clearly what is the main differences between the proposed algorithm and the others

b. How the contributions were done.

R. Brackin. We are not sure what this means.

c. The problem that have been solved in this research.

R. Brackin. See Conclusion for summary

d. The general results that you have been got.

e. a detailed discussion on the literature is required, even though the following suitable references should be added in the reference section.

- A hybrid approach of neutrosophic sets and DEMATEL method for developing supplier selection criteria. Design Automation for Embedded Systems, 1-22.

- A framework for risk assessment, management and evaluation: Economic tool for quantifying risks in supply chain. Future Generation Computer Systems, 90, 489-502.

- Towards a Reuse Strategic Decision Pattern Framework–from Theories to Practices. Information Systems Frontiers, 1-18.

- A group decision making framework based on neutrosophic VIKOR approach for e-government website evaluation. Journal of Intelligent & Fuzzy Systems, 34(6), 4213-4224.

We thank the reviewer for the attached references. The review cycle time constraints has limited our ability to review the initial experiment against the attached approaches. However, they do look valuable and we will certainly consider them in relation to the on-going research.

4. Be stable when used the terms like paper, study, Make it in a uniform style.

R. Brackin. Reviewed and minor changes made. However we believe we have been consistent in using ‘paper’ unless we are talking specifically about the case study in chapter 5.

5. Check the first paragraph in the section 2.

R. Brackin: Noted above, we have checked this and revised.

6. Some paragraphs are not well aligned.

7. Check all figures of the whole paper.

8. Discussions of the results should be more detailed

R. Brackin: Unfortunately time has precluded this. But as stated it is really only an initial experiment.

9. Please check figure 16.

10. In the text some paragraph is too long, it's better to split into 2 or 3 paragraphs, and each paragraph focuses on a main area or point.

R. Brackin: Again, noted but there is too little time to effect significant change here.

11. Identified research gaps and contribution of the proposed study should be elaborated.

R. Brackin: We have further extended the conclusions to cover this aspect a little better.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Thank you for your feedback in the review report,

and the improvement made in the article.

Reviewer 2 Report

No additional comments