Assessing Adoption Factors for Additive Manufacturing: Insights from Case Studies

Round 1

Reviewer 1 Report

Generally, the manuscript that was relevant to the additive manufacturing method was very difficult to follow and the structure was far from being organized.  Before acceptance, major revision should be considered by the authors of the manuscript considering the following comments and suggestions:

1. Name and affiliation of authors are missing; Publisher template was totally ignored.
2. Authors should consider major formatting since the manuscript resembles very little to the publisher imposed template (MDPI – logistics). Also, this further negatively influences the overall revision process;
3. Abstract should be more informative. Acronyms should be defined in abstract and in manuscript body. And sentences like “Research on Additive Manufacturing provides few guidelines for adopting AM as a part of their operations” should contain compressive information. Repetitive use of words us “AM” should be avoided;
4. Once acronyms are defined, they should be used accordingly throughout the manuscript; Avoid redefining them.
5. Authors should state or discuss the motivation for choosing the Rogers and Shoemaker’s reference, since it is old while other readers could find it far from being “innovative”;
6. Vocabulary, grammar and punctuation should be revised.
7. Introduction section is well structured, while section 2 could be better condensed;
8. References should be integrated in manuscript, accordingly.
9. Since the limited data, authors consider the interview from Appendix A as reliable? Please discuss.
10. Table 1 and 2 should be more concise; It is hard to follow; Authors should take into account that the role of a table is to assist the reader’s fast understanding by organizing the data in a simple mode without adding to much text. For instance, the sentence “Customer approval process has quickened due to AM tactility which is better that 3D drawings and visualizations” could be well reduced to “quick customer approval”;
11. Please avoid numbering paragraphs in general, since it can create confusion, while those numbers are not further referred and they could be replace by bullets.
12. The sections are not numbered properly. The section 5 – discussion, is followed by “experiments” section (it is subsection of discussion?). Please reorganize the entire manuscript, at least starting from section 5.
13. Conclusions are not well described; highlighting the limitations more than what was done. What is the novelty of the work? What were the main findings? Are the findings taking into account the technological progress in AM and would they stay relevant in the future? Conclusions should refer to the main scientific purpose of the conducted overview and present concise remarks and observations.

I can review my decision after authors take my comments into consideration.

Author Response

Thank you for your comments – we have sought to address all of them in our response and edits to the paper as shown below.

 

1. Name and affiliation of authors are missing; Publisher template was totally ignored.

 

Response:  We have used the publisher template.  Logistics is a double blind review manuscript, so the name and affiliation of authors is missing on purpose.

 

1. Authors should consider major formatting since the manuscript resembles very little to the publisher imposed template (MDPI – logistics). Also, this further negatively influences the overall revision process;

 

Response:  We employed the template developed by MDPI and formatted the manuscript accordingly..

 

 

1. Abstract should be more informative. Acronyms should be defined in abstract and in manuscript body. And sentences like “Research on Additive Manufacturing provides few guidelines for adopting AM as a part of their operations” should contain compressive information. Repetitive use of words us “AM” should be avoided;

 

We have made significant edits to the abstract, and have reduced the use of AM repetitively in this section.  We have created a more informative abstract as well.

 

1. Once acronyms are defined, they should be used accordingly throughout the manuscript; Avoid redefining them.

 

We have sought to properly employ acronyms throughout the manuscript.

 

1. Authors should state or discuss the motivation for choosing the Rogers and Shoemaker’s reference, since it is old while other readers could find it far from being “innovative”;

 

We have provided a logical rationale for employing the Rogers and Shoemaker approach.

 

We chose to evaluate Additive Manufacturing technology using a “tried and true” technology adoption model that has been reliably applied in the past. Specifically, the five attributes of successful innovations developed Rogers and Shoemaker’s (1971) provide a useful lens for evaluation of AM technology. Adoption is defined as the process by which an organization migrates from considering the innovation to final implementation (Ehigie and McAndrew 2005) across the members of a social system. Briefly, Rogers and Shoemaker propose five attributes that affect the rate of technology adoption: (1) relative advantage, (2) compatibility, (3) complexity, (4) trialability, and (5) observability. We use these criteria in the context of business outcomes, to assess as set of seven AM adoption cases and establish the primary use cases that define business archetypes for successful AM adoption.

 

 

1. Vocabulary, grammar and punctuation should be revised.

 

We have revised and checked grammar and punctuation.

 

1. Introduction section is well structured, while section 2 could be better condensed;

 

Response:  We have reduced the length of section 2, which is now more condensed.  However, we have left the description of the innovation attributes here as this is important to define.

 

1. References should be integrated in manuscript, accordingly.

 

Response:  I am unsure what you mean in this case.  We have included all references in the manuscript.

 

1. Since the limited data, authors consider the interview from Appendix A as reliable? Please discuss.

Response:  We have discussed the criteria used in selecting the cases.  We spoke to  targeted individuals who were the most knowledgeable and were involved in the selection process.  This is described in the methodology, and reprinted here.

 

We purposively selected case study firms from diverse industries and sizes that were identified a priori as having a successful adoption of AM technology (Fawcett et al. 2014). Interviews were conducted in conjunction with a subjective approach which supported the collection of information on the ‘lived experience’ of managers who were able to overcome the challenges of AM adoption, and the characteristics of this adoption that rendered it successful (Maylor and Turner 2017; Williams 2005).  As shown in Appendix B, we selected organizations that had a minimum of 3 years of experience working with AM technology, and thus had an established success record with adoption of the technology. 

 

We identified seven organizations in different markets to understand their approaches and spoke to the individuals who were the most knowledgeable within each firm. These individuals were also involved in the key decision-making process that considered the opportunities and risks associated with the AM choices they made. We included organizations that not only developed prototypes but also manufactured AM-produced finished products. We focused predominantly on smaller organizations, (some of which were embedded within a larger organization) for several reasons: (1) smaller organizations are often more nimble when it comes to adoption of new technologies, and (2) the management structure was such that we were able to speak with C-suite level individuals (subject matter experts), who were able to articulate in their own words the details and benefits of AM (Schniederjans 2017) and (3) smaller organizations were often able to articulate the risks and investment goals of AM relative to their business outcomes. The case studies were screened through initial inquiries to determine whether the users believed the use of AM was successful within their organization. This purposive case selection allowed us to extract specific attributes of the technology, yielding more significant and more meaningful results (Sykes Verma, and Hancock 2018). Note that we did not include cases in our sample where executives informed us that they had tried to use the technology but had failed.

 

 

 

 

1. Table 1 and 2 should be more concise; It is hard to follow; Authors should take into account that the role of a table is to assist the reader’s fast understanding by organizing the data in a simple mode without adding to much text. For instance, the sentence “Customer approval process has quickened due to AM tactility which is better that 3D drawings and visualizations” could be well reduced to “quick customer approval”;

Response:  We have edited Tables 1 and 2 (now Table 1 and Appendix A) to render the key points to be easily comprehended by the reader.

 

 

1. Please avoid numbering paragraphs in general, since it can create confusion, while those numbers are not further referred and they could be replace by bullets.

 

Numbering is part of the template provided by the journal, we do not have control over this.

 

1. The sections are not numbered properly. The section 5 – discussion, is followed by “experiments” section (it is subsection of discussion?). Please reorganize the entire manuscript, at least starting from section 5.

Response:  Section 5 is on Discussion.  In the original manuscript we numbered the different archetypes, but have removed the numbering to avoid confusion.

 

1. Conclusions are not well described; highlighting the limitations more than what was done. What is the novelty of the work? What were the main findings? Are the findings taking into account the technological progress in AM and would they stay relevant in the future? Conclusions should refer to the main scientific purpose of the conducted overview and present concise remarks and observations.

 

Response:  We have added a paragraph to the conclusions section that refers to the scientific purpose and key observations.

 

Our research study established some important conclusions for the field of advanced technology and in particular the growth and deployment of additive manufacturing.  We sought to understand the key market drivers that led to successful adoption of AM technology and their linkage to specific attributes of the technology using a framework innovation first put forth by Rogers and Shoemaker (1971).  Our empirical case analysis produced several important insights.  First, the case studies confirm the requirement for a strong market-focus;  AM should be adopted primarily as a “pull” requirement from well-defined customer needs.  Second, there are many different types of customer “gaps” that can be filled with AM technology.  IN particular, as customers increasingly want to visualize products before making large investments, the use of prototyping is a particularly important application.  Others include the growth of customized medical implants and surgical aids to support safer and quicker surgeries for an aging population that needs back, hip, and knee replacements.  Third, AM has a high potential to reduce complexity in supply chains, and to also support more domestic manufacturing of critical healthcare products in a crisis.  These and many other important applications have been identified.  The framework around trialability, observability, relative advantage, complexity reduction, and trialability are still very relevant.

Reviewer 2 Report

The authors should have addressed the following comments for the possible publication. 

• Line 4 (Abstract) - Additive manufacturing is used afterward AM is used. So mention the acronym of additive manufacturing as AM in the bracket before its first use. 
• The proposed article is a kind of review article; hence the introduction part should contain the background, significance, and motivation of the study. It should also include the research questions and research goal. Restructure the introduction part accordingly. 
• Section 3 of the article directly starts with the description of previous literature. But the research design should start with the research methodology. Since it must have a firm base through which the present study is carried out. 
• Figure 1 and Figure 2 can be restructured. It should convey its intended meaning. 
• Results are not in line with the paper flow. Also, the review paper may not include the result section. It should have the heading as discussion, to be described as pointwise in line with the research questions.  
• Table 1 can be moved to the Annex. 
• Case studies can be better described if it contains the diagrammatic representation of the proposed methodology or study. 

TO RESOLVE THE ABOVE COMMENTS KINDLY REFER TO THE FOLLOWING ARTICLES BUT ARE NOT LIMITED TO THEM ONLY. 

• lessandro Liberati, Douglas G. Altman, Jennifer Tetzlaff, Cynthia Mulrow, Peter C. Gøtzsche, John P.A. Ioannidis, Mike Clarke, P.J. Devereaux, Jos Kleijnen, David Moher, "The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration", Journal of Clinical Epidemiology, Volume 62, Issue 10, 2009, Pages e1-e34, ISSN 0895-4356, https://doi.org/10.1016/j.jclinepi.2009.06.006.
• Rethlefsen, M.L., Kirtley, S., Waffenschmidt, S. et al. PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Syst Rev 10, 39 (2021). https://doi.org/10.1186/s13643-020-01542-z
• Namoun, A.; Alshanqiti, A. Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review. Appl. Sci. 2021, 11, 237. https://doi.org/10.3390/app11010237
• S. Sayyad, S. Kumar, A. Bongale, P. Kamat, S. Patil and K. Kotecha, "Data-Driven Remaining Useful Life Estimation for Milling Process: Sensors, Algorithms, Datasets, and Future Directions," in IEEE Access, vol. 9, pp. 110255-110286, 2021, doi: 10.1109/ACCESS.2021.3101284.
• Warke, V.; Kumar, S.; Bongale, A.; Kotecha, K. Sustainable Development of Smart Manufacturing Driven by the Digital Twin Framework: A Statistical Analysis. Sustainability 2021, 13, 10139. https://doi.org/10.3390/su131810139

 

Author Response

Thank you for your comments – we have sought to address all of them in our response and edits to the paper as shown below.

 

The authors should have addressed the following comments for the possible publication. 

• Line 4 (Abstract) - Additive manufacturing is used afterward AM is used. So mention the acronym of additive manufacturing as AM in the bracket before its first use. 

Response:  We have used the acronym after the first mention of Additive Manufacturing

• The proposed article is a kind of review article; hence the introduction part should contain the background, significance, and motivation of the study. It should also include the research questions and research goal. Restructure the introduction part accordingly. 

Response:  We have modified the introduction to the paper as follows.

 

We chose to evaluate AM technology using a “tried and true” technology adoption model that has been reliably applied in the past. Specifically, the five attributes of successful innovations developed Rogers and Shoemaker’s (1971) provide a useful lens for evaluation of AM technology. Adoption is defined as the process by which an organization migrates from considering the innovation to final implementation (Ehigie and McAndrew 2005) across the members of a social system. Briefly, Rogers and Shoemaker propose five attributes that affect the rate of technology adoption: (1) relative advantage, (2) compatibility, (3) complexity, (4) trialability, and (5) observability. We use these criteria in the context of business outcomes, to assess as set of seven AM adoption cases and establish the primary use cases that define business archetypes for successful AM adoption.

 

 

In addition, we link the two propositions coming out of the research to the two primary research questions identified in the outset of the introduction section:

 

• Section 3 of the article directly starts with the description of previous literature. But the research design should start with the research methodology. Since it must have a firm base through which the present study is carried out. 

Response:  We have modified the research methodology section to begin with a discussion of the research design approach, and follow this up with a rational for why this approach is appropriate.

 

We purposively selected case study firms from diverse industries and sizes that were identified a priori as having a successful adoption of AM technology (Fawcett et al. 2014). Interviews were conducted in conjunction with a subjective approach which supported the collection of information on the ‘lived experience’ of managers who were able to overcome the challenges of AM adoption, and the characteristics of this adoption that rendered it successful (Maylor and Turner 2017; Williams 2005).  As shown in Appendix A, we selected organizations that had a minimum of 3 years of experience working with AM technology, and thus had an established success record with adoption of the technology.  This enabled a detailed analysis of the outcomes and performance characteristics which supported successful AM adoption.

 

• Figure 1 and Figure 2 can be restructured. It should convey its intended meaning. 

Response:  We have re-written Figures 1 and 2 to communicate with greater brevity.  However, it is important to describe the rationale and what was happening in each firm that addressed the relevant adoption of innovation criteria in the framework.

• Results are not in line with the paper flow. Also, the review paper may not include the result section. It should have the heading as discussion, to be described as pointwise in line with the research questions.  

Response:  We have re-named Section 4:  Discussion of Cases Examined and Section 5:  Tying Cases to Archetypes, to align with your suggestion.

 

• Table 1 can be moved to the Annex. 

Response:  We have moved Table 1 to the Annex.

• Case studies can be better described if it contains the diagrammatic representation of the proposed methodology or study. 

Response:  We have sought to capture the key criteria for each of the case studies.  Further elaboration of the specific details of the cases were not deemed to offer additional insights beyond the primary elements included in the manuscript.

TO RESOLVE THE ABOVE COMMENTS KINDLY REFER TO THE FOLLOWING ARTICLES BUT ARE NOT LIMITED TO THEM ONLY. 

Response:  We did not add these publications to the references, as we did not understand immediately how they pertain to the general topic of additive manufacturing and market requirements.  These papes appear to be focused on a variety of different topics including health care interventions, PRISMA, student performance, milling process sensors, and digital twin applications in sustainability.  Given the lack of overlap of these topics with our current paper, we decided not to include these references, unless the reviewer can provide us with further details on their relevance and what sections of the manuscript can benefit from these additional insights.

• lessandro Liberati, Douglas G. Altman, Jennifer Tetzlaff, Cynthia Mulrow, Peter C. Gøtzsche, John P.A. Ioannidis, Mike Clarke, P.J. Devereaux, Jos Kleijnen, David Moher, "The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration", Journal of Clinical Epidemiology, Volume 62, Issue 10, 2009, Pages e1-e34, ISSN 0895-4356, https://doi.org/10.1016/j.jclinepi.2009.06.006.
• Rethlefsen, M.L., Kirtley, S., Waffenschmidt, S. et al.PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Syst Rev 10, 39 (2021). https://doi.org/10.1186/s13643-020-01542-z
• Namoun, A.; Alshanqiti, A. Predicting Student Performance Using Data Mining and Learning Analytics Techniques: A Systematic Literature Review.  Sci.2021, 11, 237. https://doi.org/10.3390/app11010237
• Sayyad, S. Kumar, A. Bongale, P. Kamat, S. Patil and K. Kotecha, "Data-Driven Remaining Useful Life Estimation for Milling Process: Sensors, Algorithms, Datasets, and Future Directions," in IEEE Access, vol. 9, pp. 110255-110286, 2021, doi: 10.1109/ACCESS.2021.3101284.
• Warke, V.; Kumar, S.; Bongale, A.; Kotecha, K. Sustainable Development of Smart Manufacturing Driven by the Digital Twin Framework: A Statistical Analysis. Sustainability2021, 13, 10139. https://doi.org/10.3390/su131810139

Reviewer 3 Report

[Scope]: The paper is not comprehensive and does not provide a rigorous overview of many topics that fall under “Assessing Adoption Factors for Additive Manufacturing”. For example, the relationship of Additive Manufacturing (AM) with other manufacturing processes and methods in the context of adoption has not been considered.

 

[Contribution]: The paper does not offer a big picture of the matter to the reader, nor does it identify trends in the field. Authors should mention substantially related review papers, identify gaps, and establish their own contributions. Also, the provided method in this paper is almost the five principles of innovation adoption introduced by Rogers and Shoemaker (1971) and author(s) implemented that in the context of Additive Manufacturing with minor changes in assessing purposes. I found many sentences in section 2.2 verbose and unnecessary, especially sentences related to the five principles of innovation adoption. Also, I couldn’t find any rigid evaluation of the provided method of assessing adoption factors.

 

[Research Design]: Paper says that 7 different organizations have been chosen in order to be evaluated for the case study, in this regard some notes should be considered for improvement:

·      The number of interviews is not sufficient, in some organizations (Toys Co., Hospital, Life Sciences, and Electric Co.) only 1 researcher was present.

·      The reasons for choosing each company for the case study in assessing additive manufacturing adoption should be clearly explained. The reviewer can find some general adjustments in section 4, but it’s not in detail.

·      In the case study section, the state of companies using additive manufacturing should be clearly explained; How long have they been using this technology? What is proportion of using additive manufacturing for producing one single unit of product? And questions like this show the current status of AM technology in each company.

·      In section 3, paragraph 3, author(s) state(s) that “we did not include cases in our sample where executives informed us that they had tried to use the technology but had failed.” If only companies with good experience using additive manufacturing are taken into account the results of assessments and case studies cannot be valid.

·      Poor demonstration of the interview process and data collection. Sufficient information is not provided in this section 3, Data Collection.

[Miscellaneous]:

·      [long sentences]: Some sentences are too long and should break down for an easier read. For example, in section 3, page 8, paragraph 1: “In this manner, a pattern emerged that dictated the unique sets of adoption at- tributes that emerged in each case, which were then used to create a “business archetype” that defined the ecosystem associated with each business use case.”

·      [lack of proper conjunction and transition]: Proper conjunctions and smooth transition are required for some parts of the paper. For example, section 5, page 13, paragraph 1.

 

 

References

Rogers, E. M., & Shoemaker, F. F. (1971). Communication of Innovations; A Cross-Cultural Approach.

Author Response

Thank you for your comments – we have sought to address all of them in our response and edits to the paper as shown below.

 

[Scope]: The paper is not comprehensive and does not provide a rigorous overview of many topics that fall under “Assessing Adoption Factors for Additive Manufacturing”. For example, the relationship of Additive Manufacturing (AM) with other manufacturing processes and methods in the context of adoption has not been considered.

 

Response:  We respectfully disagree.  We have provided multiple discussion items in Table 1 that compare the benefits of AM to standard manufacturing processes, and the appropriate market niche that is being filled by AM that is not met by traditional manufacturing.  This was the primary focus on the paper, and we did not seek to provide a direct comparison of the relationship of Additive Manufacturing (AM) with other manufacturing processes and methods.  Rather we sought to understand how organizations would adopt AM to meet a “market pull” requirement.

 

[Contribution]: The paper does not offer a big picture of the matter to the reader, nor does it identify trends in the field. Authors should mention substantially related review papers, identify gaps, and establish their own contributions. Also, the provided method in this paper is almost the five principles of innovation adoption introduced by Rogers and Shoemaker (1971) and author(s) implemented that in the context of Additive Manufacturing with minor changes in assessing purposes. I found many sentences in section 2.2 verbose and unnecessary, especially sentences related to the five principles of innovation adoption. Also, I couldn’t find any rigid evaluation of the provided method of assessing adoption factors.

 

Response:  We have consolidated Section 2 of the manuscript significantly, and have sought to offer a “big picture” of the research design to the reader.  The rationale for using the Rogers and Shoemaker approach is also captured in the paragraph added below.

 

We chose to evaluate AM technology using a “tried and true” technology adoption model that has been reliably applied in the past, but has not been applied to AM technology. Specifically, the five attributes of successful innovations developed Rogers and Shoemaker’s (1971) provide a useful lens for evaluation of AM technology. Adoption is defined as the process by which an organization migrates from considering the innovation to final implementation (Ehigie and McAndrew 2005) across the members of a social system. Briefly, Rogers and Shoemaker propose five attributes that affect the rate of technology adoption: (1) relative advantage, (2) compatibility, (3) complexity, (4) trialability, and (5) observability. We use these criteria in the context of business outcomes, to assess as set of seven AM adoption cases and establish the primary use cases that define business archetypes for successful AM adoption.

 

 

 

[Research Design]: Paper says that 7 different organizations have been chosen in order to be evaluated for the case study, in this regard some notes should be considered for improvement:

• The number of interviews is not sufficient, in some organizations (Toys Co., Hospital, Life Sciences, and Electric Co.) only 1 researcher was present.

 

Response:  We deliberately selected companies that met the criteria of having at least 3 years of experience successfully adopting AM.  This is a limited population, and we were unable to identify more organizations that met this criteria.

 

• The reasons for choosing each company for the case study in assessing additive manufacturing adoption should be clearly explained. The reviewer can find some general adjustments in section 4, but it’s not in detail.

 

Response:  We have modified the research methodology section to begin with a discussion of the research design approach, and follow this up with a rational for why this approach is appropriate.

 

 

We purposively selected case study firms from diverse industries and sizes that were identified a priori as having a successful adoption of AM technology (Fawcett et al. 2014). Interviews were conducted in conjunction with a subjective approach which supported the collection of information on the ‘lived experience’ of managers who were able to overcome the challenges of AM adoption, and the characteristics of this adoption that rendered it successful (Maylor and Turner 2017; Williams 2005).  As shown in Appendix B, we selected organizations that had a minimum of 3 years of experience working with AM technology, and thus had an established success record with adoption of the technology.  This enabled a detailed analysis of the outcomes and performance characteristics which supported successful AM adoption.

 

• In the case study section, the state of companies using additive manufacturing should be clearly explained; How long have they been using this technology? What is proportion of using additive manufacturing for producing one single unit of product? And questions like this show the current status of AM technology in each company.

 

Response:  We have added a column to the table showing the length of time the technology has been used.  None of the companies used the technology for a single unit of product – as described in Table 1, all of them used the product for customized applications for multiple customers.

 

• In section 3, paragraph 3, author(s) state(s) that “we did not include cases in our sample where executives informed us that they had tried to use the technology but had failed.” If only companies with good experience using additive manufacturing are taken into account the results of assessments and case studies cannot be valid.

 

Response: We respectfully disagree.  We sought to examine the critical success factor that led to the “successful adoption of innovation”.  There are many existing studies that show why AM failed, but none that capture the key elements studied in the current study, which is unique and novel.

 

• Poor demonstration of the interview process and data collection. Sufficient information is not provided in this section 3, Data Collection.

Response:  We have provided the following details on the interview process and data analysis.

 

 

 

Data Collection: An interview protocol was developed to ask the case study businesses about their AM use (including their products and customers), benefits and drawbacks, cost analyses and impacts, and the effects on product design and manufacturing. The interview protocol covered how the organizations were using AM, the rationale of why they chose to do so, and the nature of how they used it. The questions contained within the protocol were derived from the five adoption attributes to explain technology adoption (Barratt, Choi, and Li 2011; Handfield and Pagell 1995). Each attribute provides indications about determinants to support adoption and offers a basis for comparing traditional manufacturing approaches to AM (Oettmeier and Hofmann 2017; Rogers 2004). The protocol was piloted by the research team to assess its suitability and modified to provide clarity on the questions posed. Five researchers conducted the qualitative investigation into the adoption of the technology adding to the richness of the data interpretation (Eisenhardt 1989). Further details of the interviews are given in Appendix B. Each interview was accompanied by a detailed discussion explaining how the technology is being used, followed up by detailed questions on the market forces that drove the innovation adoption.

Data Analysis: Interviews were transcribed and coded by the researchers. Included within each case were quotes and accounts from interviewees describing and illuminating the points being made. After completing the case studies, the results were written up and reviewed by the authors.

 

[Miscellaneous]:

• [long sentences]: Some sentences are too long and should break down for an easier read. For example, in section 3, page 8, paragraph 1: “In this manner, a pattern emerged that dictated the unique sets of adoption at- tributes that emerged in each case, which were then used to create a “business archetype” that defined the ecosystem associated with each business use case.”

 

Response:  We have sought to address these issues. This sentence has now been changed to read “Patterns emerged that dictated the unique sets of adoption attributes for each case, and these were then used to create a corresponding “business archetype”.”

 

• [lack of proper conjunction and transition]: Proper conjunctions and smooth transition are required for some parts of the paper. For example, section 5, page 13, paragraph 1.

 

Response: We have simplified the text in Section 5 and revised the grammar throughout in this version.

 

 

References

Rogers, E. M., & Shoemaker, F. F. (1971). Communication of Innovations; A Cross-Cultural Approach.

 

Round 2

Reviewer 1 Report

Comprehensive response of the mentioned issues were addressed by the authors. 

Reviewer 3 Report

Thanks for addressing previous comments and your responses in detail.

[Scope]: The paper is not comprehensive and does not provide a rigorous overview of many topics that fall under “Assessing Adoption Factors for Additive Manufacturing”. For example, the relationship of Additive Manufacturing (AM) with other manufacturing processes and methods in the context of adoption has not been considered.

 

Response:  We respectfully disagree.  We have provided multiple discussion items in Table 1 that compare the benefits of AM to standard manufacturing processes, and the appropriate market niche that is being filled by AM that is not met by traditional manufacturing.  This was the primary focus on the paper, and we did not seek to provide a direct comparison of the relationship of Additive Manufacturing (AM) with other manufacturing processes and methods.  Rather we sought to understand how organizations would adopt AM to meet a “market pull” requirement.

 

** Comment: My concern is not addressed well in your response. I’m looking for the “relationship of Additive Manufacturing (AM) with other manufacturing processes”, in other words when a company wants to adopt new manufacturing process(in this case is AM), they should figure out what is the best fit of different type of AM in their system and that’s the missing point in the paper. Moreover, the company should plan and choose among 7 types of AM such as VAT Photopolymerisation, Material Jetting, Binder Jetting, Material Extrusion, Powder Bed Fusion, Sheet Lamination, and Directed Energy Deposition. Each of these types of AM has its own parameters and characteristics which are important when you want to adopt them in the current system.

For similar paper in this field, look at this paper: Nollet, L. J. E. (2017). Factors influencing the adoption decision of metal additive manufacturing technologies (Master's thesis, University of Twente). When in section 2.1 they explain adoption decisions in three different elements of a firm’s context.

 

 

 

[Contribution]: The paper does not offer a big picture of the matter to the reader, nor does it identify trends in the field. Authors should mention substantially related review papers, identify gaps, and establish their own contributions. Also, the provided method in this paper is almost the five principles of innovation adoption introduced by Rogers and Shoemaker (1971) and author(s) implemented that in the context of Additive Manufacturing with minor changes in assessing purposes. I found many sentences in section 2.2 verbose and unnecessary, especially sentences related to the five principles of innovation adoption. Also, I couldn’t find any rigid evaluation of the provided method of assessing adoption factors.

 

Response:  We have consolidated Section 2 of the manuscript significantly, and have sought to offer a “big picture” of the research design to the reader.  The rationale for using the Rogers and Shoemaker approach is also captured in the paragraph added below.

 

 

 

We chose to evaluate AM technology using a “tried and true” technology adoption model that has been reliably applied in the past, but has not been applied to AM technology. Specifically, the five attributes of successful innovations developed Rogers and Shoemaker’s (1971) provide a useful lens for evaluation of AM technology. Adoption is defined as the process by which an organization migrates from considering the innovation to final implementation (Ehigie and McAndrew 2005) across the members of a social system. Briefly, Rogers and Shoemaker propose five attributes that affect the rate of technology adoption: (1) relative advantage, (2) compatibility, (3) complexity, (4) trialability, and (5) observability. We use these criteria in the context of business outcomes, to assess as set of seven AM adoption cases and establish the primary use cases that define business archetypes for successful AM adoption.

 

** Comment: Respectfully, I still believe that the research does not offer a novel study to readers and methodology is mainly coming from the Rogers and Shoemaker (1971) studies and also Oettmeier and Hofmann (2017) provides the results of an empirical study among 195 firms which is a comprehensive study over the AM adoption. When I as a reviewer compare the results of previous works with the intended study over 7 different organizations, I can not find a great contribution to the literature.

 

 

 

[Research Design]: Paper says that 7 different organizations have been chosen in order to be evaluated for the case study, in this regard some notes should be considered for improvement:

• The number of interviews is not sufficient, in some organizations (Toys Co., Hospital, Life Sciences, and Electric Co.) only 1 researcher was present.

 

Response:  We deliberately selected companies that met the criteria of having at least 3 years of experience successfully adopting AM.  This is a limited population, and we were unable to identify more organizations that met this criteria.

 ** Comment: Respectfully disagree with this statement, you can use online surveys to potentially increase the number of firms involve in your study. Again, look at Oettmeier and Hofmann (2017) when they have done the similar study with more than 100 companies.

• The reasons for choosing each company for the case study in assessing additive manufacturing adoption should be clearly explained. The reviewer can find some general adjustments in section 4, but it’s not in detail.

 

Response:  We have modified the research methodology section to begin with a discussion of the research design approach, and follow this up with a rational for why this approach is appropriate.

 

 

We purposively selected case study firms from diverse industries and sizes that were identified a priori as having a successful adoption of AM technology (Fawcett et al. 2014). Interviews were conducted in conjunction with a subjective approach which supported the collection of information on the ‘lived experience’ of managers who were able to overcome the challenges of AM adoption, and the characteristics of this adoption that rendered it successful (Maylor and Turner 2017; Williams 2005).  As shown in Appendix B, we selected organizations that had a minimum of 3 years of experience working with AM technology, and thus had an established success record with adoption of the technology.  This enabled a detailed analysis of the outcomes and performance characteristics which supported successful AM adoption.

** Comment: issue is solved. 

• In the case study section, the state of companies using additive manufacturing should be clearly explained; How long have they been using this technology? What is proportion of using additive manufacturing for producing one single unit of product? And questions like this show the current status of AM technology in each company.

 

Response:  We have added a column to the table showing the length of time the technology has been used.  None of the companies used the technology for a single unit of product – as described in Table 1, all of them used the product for customized applications for multiple customers.

 ** Comment: issue is solved. 

 

• In section 3, paragraph 3, author(s) state(s) that “we did not include cases in our sample where executives informed us that they had tried to use the technology but had failed.” If only companies with good experience using additive manufacturing are taken into account the results of assessments and case studies cannot be valid.

 

Response: We respectfully disagree.  We sought to examine the critical success factor that led to the “successful adoption of innovation”.  There are many existing studies that show why AM failed, but none that capture the key elements studied in the current study, which is unique and novel.

 ** Comment: I believe companies with fail experience in AM adoption can be added to the study and being interviewed to figure out if there was a potential reason in their companies which led to failure.

 

• Poor demonstration of the interview process and data collection. Sufficient information is not provided in this section 3, Data Collection.

Response:  We have provided the following details on the interview process and data analysis.

 

 

 

Data Collection: An interview protocol was developed to ask the case study businesses about their AM use (including their products and customers), benefits and drawbacks, cost analyses and impacts, and the effects on product design and manufacturing. The interview protocol covered how the organizations were using AM, the rationale of why they chose to do so, and the nature of how they used it. The questions contained within the protocol were derived from the five adoption attributes to explain technology adoption (Barratt, Choi, and Li 2011; Handfield and Pagell 1995). Each attribute provides indications about determinants to support adoption and offers a basis for comparing traditional manufacturing approaches to AM (Oettmeier and Hofmann 2017; Rogers 2004). The protocol was piloted by the research team to assess its suitability and modified to provide clarity on the questions posed. Five researchers conducted the qualitative investigation into the adoption of the technology adding to the richness of the data interpretation (Eisenhardt 1989). Further details of the interviews are given in Appendix B. Each interview was accompanied by a detailed discussion explaining how the technology is being used, followed up by detailed questions on the market forces that drove the innovation adoption.

Data Analysis: Interviews were transcribed and coded by the researchers. Included within each case were quotes and accounts from interviewees describing and illuminating the points being made. After completing the case studies, the results were written up and reviewed by the authors.

 ** Comment: Absence of below items have made the data collection section poor:

1.     Questions in the interview

2.     Detail information about the company (number of employee, Annual Sale, AM technology adoption status,…)

3.     Mathematical evaluation over the data collection and surveys to make sure that questions in the interview

4.     Miss of numerical results of the interviews; classifying the leading adoption factors and measuring the number of common answers in interviews could be one potential numerical example.

[Miscellaneous]:

• [long sentences]: Some sentences are too long and should break down for an easier read. For example, in section 3, page 8, paragraph 1: “In this manner, a pattern emerged that dictated the unique sets of adoption at- tributes that emerged in each case, which were then used to create a “business archetype” that defined the ecosystem associated with each business use case.”

 

Response:  We have sought to address these issues. This sentence has now been changed to read “Patterns emerged that dictated the unique sets of adoption attributes for each case, and these were then used to create a corresponding “business archetype”.”

** Comment: issue is solved.

 

• [lack of proper conjunction and transition]: Proper conjunctions and smooth transition are required for some parts of the paper. For example, section 5, page 13, paragraph 1.

 

Response: We have simplified the text in Section 5 and revised the grammar throughout in this version.

 ** Comment: issue is solved.

 

 

References

Rogers, E. M., & Shoemaker, F. F. (1971). Communication of Innovations; A Cross-Cultural Approach.

Nollet, L. J. E. (2017). Factors influencing the adoption decision of metal additive manufacturing technologies (Master's thesis, University of Twente).

Oettmeier, K., & Hofmann, E. (2017). Additive manufacturing technology adoption: an empirical analysis of general and supply chain-related determinants. Journal of Business Economics, 87(1), 97-124.