Review Reports - How Will Smart Technology Support SDG 12? An Empirical Study on Sustainability in Indian Agricultural Operations

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Summary:

This paper explores the slow adoption of smart technology in Indian agriculture and its role in achieving Sustainable Development Goal 12 (responsible consumption and production). Using a two-phase mixed-methods approach, the study first conducts qualitative interviews with 20 farmers in Karnataka, India, to identify factors influencing adoption, and then applies fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze combinations of these factors. The research connects the findings to the Diffusion of Innovation (DoI) theory, proposing that successful adoption depends on combinations of factors like technology, knowledge, experience, benefits, and reliability, rather than individual factors alone.

The study's innovation lies in extending the DoI theory by emphasizing factor combinations, with fsQCA revealing pathways where technical knowledge and experience are critical for adoption. This approach provides practical strategies for scaling smart technology in agriculture, such as co-creation and training programs.

However, limitations include a small sample size limited to one region, which may reduce generalizability, and potential subjectivity in qualitative data interpretation. The fsQCA method, while insightful, relies on fuzzy membership estimates that could be refined with larger datasets.

Lastly, the paper would benefit from minor grammatical polishing and enhanced structural clarity in sections like the literature review to improve flow and accessibility, though the core arguments are well-supported.

Comments:

The opening sentence "India is one of the fastest-growing economies in the world" is too general and does not directly address the research topic. It is recommended to rewrite it to highlight the research question.
"We adopt a two-pronged approach..." This sentence is somewhat vague. The term "two-pronged" is not standard and should be clearly stated as "mixed-methods".
The introduction could be enhanced by incorporating a more thorough discussion of recent deep learning applications in agricultural computer vision. For example, Wang et al. (2024) detailed how their YOLO-BLBE model addresses issues like outdoor illumination variations in blueberry fruit identification, which aligns with the smart technology challenges mentioned. This should be explicitly referenced to strengthen the background on technological adaptability.
Reference: Wang, C., Han, Q., Li, J., Li, C., & Zou, X. (2024). YOLO-BLBE: A Novel Model for Identifying Blueberry Fruits with Different Maturities Using the I-MSRCR Method. AGRONOMY-BASEL, 14(4), 658. https://doi.org/10.3390/agronomy14040658
"This study aims to fill this important research gap" does not clearly specify what the gap is. It is necessary to clarify the lack of literature in the preceding text.

Author Response

How will Smart Technology support SDG 12? An empirical study on Sustainability in Indian Agricultural Operations

Responses to Reviewer Comments

Reviewer 1:

Summary by the reviewer:

This paper explores the slow adoption of smart technology in Indian agriculture and its role in achieving Sustainable Development Goal 12 (responsible consumption and production). Using a two-phase mixed-methods approach, the study first conducts qualitative interviews with 20farmers in Karnataka, India, to identify factors influencing adoption, and then applies fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze combinations of these factors. The research connects the findings to the Diffusion of Innovation (DoI) theory, proposing that successful adoption depends on combinations of factors like technology, knowledge, experience, benefits, and reliability, rather than individual factors alone.

Response:

We thank this reviewer for the nice summary of our paper and highlighting the contributions. We also agree with the highlighted limitations but would like to add the following responses.

Ours is a qualitative study. The sample of 20 cases is typical for a qualitative study. Literature has qualitative studies with sample sizes much lower than 20 (sometimes as low as 3-5) and we feel that our sample size is large enough to provide validity to our findings.
As we explained in the paper, the focus on Karnataka is due to its position as one of the top Indian states in adopting smart farming. We believe this focus will help bring out useful insights compared to spreading the samples across the entire country.
We do agree that the fuzzy memberships estimation could be a source of error. However, we feel that the chance of errors are minimal because they have been estimated by the first author and specially trained field representatives based on an in-depth on-the-field assessment. This has been highlighted in Section 4.4.1 of the revised version.

In spite of our explanations, we agree with the observations of this reviewer, and we have included these two issues as the limitations of the study at the end of the paper. Please see the final paragraph of the paper.

Response: Thanks for highlighting this point. We have thoroughly proofread the revised version for clarity, improved structure. We believe that the revised version is free from any error.

Comment1:

The opening sentence "

India is one of the fastest-growing economies in the world

" is too general and does not directly address the research topic. It is recommended to rewrite it to highlight the research question."

We adopt a two-pronged approach...

" This sentence is somewhat vague. The term "two-pronged" is not standard and should be clearly stated as "mixed-methods".

Response:

We thank the reviewer for these useful comments. We have modified the abstract to reflect these changes. We have rewritten the first sentence to highlight our focus on smart farming in India.

Comment 2:

The introduction could be enhanced by incorporating a more thorough discussion of recent deep learning applications in agricultural computer vision. For example, Wang et al. (2024) detailed how their YOLO-BLBE model addresses issues like outdoor illumination variations in blue berry fruit identification, which aligns with the smart technology challenges mentioned. This should be explicitly referenced to strengthen the background on technological adaptability.

Reference: Wang, C., Han, Q., Li, J., Li, C., & Zou, X. (2024). YOLO-BLBE: A Novel Model for Identifying Blueberry Fruits with Different Maturities Using the I-MSRCR Method. AGRONOMY-BASEL, 14(4), 658. https://doi.org/10.3390/agronomy14040658"

Comment 3:

This study aims to fill this important research gap

" does not clearly specify what the gap is. It is necessary to clarify the lack of literature in the preceding text.

Response:

Thanks for giving opportunity to elaborate research gap to highlight the importance of this research.

We have modified the article to improve its structure. We have used the journal article from Wang et al., (2024) and Mohan et al., (2023) to clearly specify the gap (see pages 2- 3).

For example, in page 3 we have introduced Wang et al, 2024’s article to strengthen the arguments on research gap.

“Recent article from [11] Wang et al (2024), developed a technology-based model, namely, YOLO-BLBE model using multi-scale Retinex with color restoration method to identify maturity of blueberry fruits. On the other hand [2] Mohan et al., (2023), suggested a postharvest loss management using a simple temperature control option”

Comment 3:

This study aims to fill this important research gap

" does not clearly specify what the gap is. It is necessary to clarify the lack of literature in the preceding text.

Response:

We thank this reviewer again for this comment. We have explained the research gap clearly by highlighting the two aspects of the gap in the revised version. Please see the last page in Page 3(just before research questions) in the revised version.

Finally, we thank the editor and the reviewers for their support and insightful comments. We feel that the overall quality of the paper has improved as a result of revisions. We do hope that the revised version is acceptable for publication in the journal Sustainability.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The paper examines how smart technologies can support SDG 12 in Indian agriculture by conducting qualitative interviews with 20 farmers in Karnataka (2021), grouped into four adoption segments, and employing fuzzy-set QCA to model configurations of six factors associated with “adoption.” The authors map interview themes to Diffusion of Innovations constructs and argue that combinations of factors best explain adoption. In the reported solutions, Technical Knowledge and Experience appear in all configurations. Several pathways with consistency 0.7 and modest coverage are presented. The paper’s practical thrust is to prioritize training, peer demonstrations, and co-creation to accelerate adoption and reduce waste and resource use aligned with SDG 12.
Drawbacks:
1. Potential selection bias: proximity to agri-tech vendors and programs may overstate openness to technology relative to more remote districts.
2. Table of calibrated cases appears to include 21 rows after stating 20 interviews. Some cells are marked “x” (missing), yet the treatment of missing values in calibration/analysis is not specified.
3. Membership scores (0-1) for conditions and the outcome are presented without transparent anchors or a calibration method, making replication and interpretability difficult.
4. The “necessary condition” conclusion is based on an unusually stringent dual threshold, which is not standard practice in fsQCA and may incorrectly reject plausible necessary conditions.
5. Frequency cutoff, handling of limited diversity, solution type, contradictory configurations, raw vs. unique coverage, and robustness checks are not fully reported.
6. DoI-aligned constructs are inferred from interviews rather than measured with validated scales. No inter-coder reliability or triangulation is reported.
7. The claim that the study “extends DoI” by emphasizing configurations over single factors is overstated. Configurational and contingency perspectives on innovation adoption are established. The paper would benefit from positioning as a contextualized, empirical configurational test rather than a theoretical extension.
8. No direct SDG 12 indicators are measured. As a result, the sustainability impact remains hypothetical rather than demonstrated.
Recommendations:
1. Scale up to a multi-state, stratified sample with at least n=150-300 survey respondents, followed by purposive qualitative deep-dives.
2. Specify frequency cutoffs, treatment of logical remainders, solution type, raw/unique coverage, and contradictory configurations.
3. Complement with Necessary Condition Analysis (NCA) to test bottlenecks, and cross-validate findings with a regression/PLS-SEM benchmark to check convergent insights.
4. Disentangle Reliability from Complexity and Experience. Consider modeling Capability as a higher-order construct that subsumes technical knowledge and Experience.
5. Reconcile the 20 vs. 21 case count. Document how “x” values were handled. Release an anonymized calibration table and codebook.
6. Collect pre/post or matched-control outcome metrics: water use per hectare, fertilizer intensity, energy use, labor hours, post-harvest losses, and net margins. Where RCTs are infeasible, implement quasi-experimental designs.
7. Reframe as a configurational account of agri-tech adoption in smallholder contexts, emphasizing the practical insight that Tech Knowledge + Experience are quasi-universal enablers, with Benefits/Financials moderating.
8. Situate novelty in the Indian smallholder setting and the policy design implications.

Author Response

How will Smart Technology support SDG 12? An empirical study on Sustainability in Indian Agricultural Operations

Responses to Reviewer Comments

Reviewer 2:

Drawbacks:

Potential selection bias: proximity to agri-tech vendors and programs may overstate openness to technology relative to more remote districts.

Response: Thanks for highlighting this point. We have collected data from the users and non-users of technology for agriculture. The interview data has not included agri-tech vendors. Our sample size of 20 is fairly large for a qualitative study and hence we are confident that the issue of selection bias is minimal.

Table of calibrated cases appears to include 21 rows after stating 20 interviews. Some cells are marked “x” (missing), yet the treatment of missing values in calibration/analysis is not specified.

Response: We apologize for this oversight. We have removed the 21^st row from the table (Table 5). If no response was provided by farmers, we represented this through ‘x’ This case has been treated equivalent to non-adoption with a membership value of zero.

Membership scores (0-1) for conditions and the outcome are presented without transparent anchors or a calibration method, making replication and interpretability difficult.

Response:

We thank this reviewer for highlighting this important point. In the revised version of the article, we have explained the procedure followed to record these scores. At the beginning of Section 4.4.1 (pages 19-20 of the revised version), we have newly introduced the following sentences.

The responses of the interviewees highlighted their level of importance for specific variables, say adoption, technology, knowledge, experience, benefit, reliability and financial benefits. These are expressed in their usage of words. To do this exercise, we used insights from trained local representatives who supported the interview process. For example, if a farmer mentions about highly appreciating the smart technology, a membership score of 0.8 was assigned while the membership of 1 was used if a farmer is confident of fully adopting the smart technology. If no response was provided, we represented this through ‘x’ This case is treated equivalent to non-adoption with a membership value of zero.

The “necessary condition” conclusion is based on an unusually stringent dual threshold, which is not standard practice in fsQCA and may incorrectly reject plausible necessary conditions.
Frequency cutoff, handling of limited diversity, solution type, contradictory configurations, raw vs. unique coverage, and robustness checks are not fully reported.

Response:

While we agree with the views of this reviewer, we wish to highlight that the literature on the application of fsQCA is not standard and has many approaches. We have followed one of the recent step-by-step guides for fsQCA suggested by Saridakis et al. [24]. We have clearly explained our step-by-step approach in Section 2.2 and followed these steps while presenting our results in Section 4.4. Many papers in the literature, such as the following, follow the presentation similar to Saridakis et al. [24], which we have also followed in this paper.

Roshan, R., Balodi, K. C., Datta, S., Kumar, A., & Upadhyay, A. (2024). Circular economy startups and digital entrepreneurial ecosystems. Business Strategy and the Environment, 33(5), 4843-4860.
Cantele, S., Russo, I., Kirchoff, J. F., & Valcozzena, S. (2023). Supply chain agility and sustainability performance: A configurational approach to sustainable supply chain management practices. Journal of Cleaner Production, 414, 137493.
Roh, S., Haddoud, M. Y., Onjewu, A. K. E., Jang, H., & Thai, V. (2025). Revisiting the impact of container port service quality on customer satisfaction: A configuration approach. Transport Policy, 162, 221-231.

DoI-aligned constructs are inferred from interviews rather than measured with validated scales. No inter-coder reliability or triangulation is reported.

Response:

Since our interviews have provided rich qualitative data, we had to infer the link to specific DoI constructs by matching the responses of our interviewees with the definitions of relevant DoI construct. We have explained this matching process in Section 4.2 using the quotes presented in Section 4.1. Both the authors agreed on this matching process. The matching shown in Figure 2 has been agreed by both the authors.

The claim that the study “extends DoI” by emphasizing configurations over single factors is overstated. Configurational and contingency perspectives on innovation adoption are established. The paper would benefit from positioning as a contextualized, empirical configurational test rather than a theoretical extension.

Response:

We thank this reviewer for helping us to position our results properly. We have replaced the mentions of “extending the DoI theory” to “providing a contextual empirical configurational test of the DoI theory in Indian smart farming context” in four places in the revised version (last sentence in the abstract and the second last paragraph (in 2 places) and the last paragraph of Section 1 Introduction).

No direct SDG 12 indicators are measured. As a result, the sustainability impact remains hypothetical rather than demonstrated.

Response:

We have not asked questions that specifically mentioned SDG12, but asked questions that would help us to link the interviewee responses to the goal. Our mapping of the interview questions that link to RQ5 on SDG12 are described in Table 1. Thus we feel that link to SDG 12 has been built into our research by design and is not hypothetical. We agree that we could have included questions linking to responsible production and consumption, but we feel that this would have affected the focus of the study on the adoption of technology in smart farming. In line with this comment from this reviewer, we have highlighted a stronger link to SDG 12 as a scope for future research. Please see the last paragraph of the paper.

Recommendations:

Scale up to a multi-state, stratified sample with at least n=150-300 survey respondents, followed by purposive qualitative deep-dives.

Response:

Our research followed a qualitative approach and hence our sample size is limited to 20. We do agree that future research could confirm our findings using a questionnaire survey. We have highlighted this scope for future quantitative study in the last paragraph of the paper.

Specify frequency cutoffs, treatment of logical remainders, solution type, raw/unique coverage, and contradictory configurations.

Complement with Necessary Condition Analysis (NCA) to test bottlenecks, and cross-validate findings with a regression/PLS-SEM benchmark to check convergent insights.

Response:

As we highlighted earlier, we followed a different approach – the step-by-step guide suggested by Saridakis et al. [24]. We have explained the steps in Section 2.2 and followed the steps in Section 4.4.

Disentangle Reliability from Complexity and Experience. Consider modeling Capability as a higher-order construct that subsumes technical knowledge and Experience.

Response:

We appreciate the new insights from this reviewer. However, we think our original interpretations of linking quotes from farmers to the specific DoI constructs are correct. We have explained this matching process in Section 4.2 using the quotes presented in Section 4.1. Both the authors agreed on this matching process. The matching shown in Figure 2 has been agreed by both the authors.

Reconcile the 20 vs. 21 case count. Document how “x” values were handled. Release an anonymized calibration table and codebook.

Response: We thank the reviewer for highlighting this point. We have considered only 20 responses for this research. The line 21 is the repetition of 20. We accept this error, and we have removed Row 21 in the revised version.

If no response was provided by a farmer, we represented this through ‘x’ This case is treated equivalent to non-adoption with a membership value of zero.

The coding process has been explained in the first paragraph of Section 4.4.1 of the revised version (page 20).

Collect pre/post or matched-control outcome metrics: water use per hectare, fertilizer intensity, energy use, labor hours, post-harvest losses, and net margins. Where RCTs are infeasible, implement quasi-experimental designs.

Response:

This is an interesting observation. However, since our study is primarily qualitative, we have not collected such quantitative data.

Reframe as a configurational account of agri-tech adoption in smallholder contexts, emphasizing the practical insight that Tech Knowledge + Experience are quasi-universal enablers, with Benefits/Financials moderating.

Response:

This is another interesting observation. However, we feel that such design options are not necessary for a qualitative study. Our study has followed the standard practices adopted in a typical qualitative research study.

Situate novelty in the Indian smallholder setting and the policy design implications.

Response:

Thanks again for this observation. Our practical contributions have been explained in a separate sub-section in the last section on conclusions. The research propositions explain the results of our study in smart farming policy context.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

According to the title, this study should address how smart technology will support SDG12; however, it fails to mention that it is based on a case study from India. To conduct the study, the authors surveyed 20 farmers in Karnataka, India, in 2021 (the state with the most Agritech start-ups). The paper contains useful data, but it is poorly organized. Sections are too broad and overlapping. For example, the introduction (4 pages) includes an overview of other studies rather than introducing readers to the topic and narrowing the focus. This is even less necessary given that you already have a literature overview. Also, the first two paragraphs on page 3 (Introduction) are about methods. The first two sections of the Literature review, on the other hand, are about global issues, with definitions of IoT and technologies (for the introduction). You are referring to the gap in the middle of this section, which represents the end of the introduction. At the end of 2.1, you repeat what you did. 2.2 is for methods and should be more concise. Readers are more interested in a description of the approach than a review of studies that use it. In 3.2, you repeat what was previously said. You have another 3.2 (twop times the same numbering) heading that deals with data collection (as with 3.1).

In the introduction, you state that agriculture accounts for a sizable portion of India's exports, while only selecting 5 farmers from each category of the four-segmented survey. Why no more? How did you come up with the metrics in Tabs 5, 6, and 7. You have one more review in 4.3 (the Section that should deal with data analysis and findings). In the first two chapters of section 5 (further directions), you summarize what you did in this study (please refrain from doing so). The conclusion section is too long and unclear. The references are not as suggested by the journal. You have links inserted into manuscript text. You use percent, per cent, and % throughout the text. DoI, or DOI? Please use the third person and avoid the first person in your writing. It is not true that the BRICS nations are not classified as high-income countries. I have many more minor complaints, but your text lacks line numbering, so I can not pinpoint them. You could use more recent papers in the field to cite, such as https://doi.org/10.3390/en18020416. I encourage you to revise your paper to be more concise, with content that will not overlap among sections. The study contains material, but it must be properly organized, which it is currently not.

Author Response

How will Smart Technology support SDG 12? An empirical study on Sustainability in Indian Agricultural Operations

Responses to Reviewer Comments

Review 3:

According to the title, this study should address how smart technology will support SDG12; however, it fails to mention that it is based on a case study from India. To conduct the study, the authors surveyed 20 farmers in Karnataka, India, in 2021 (the state with the most Agritech start-ups). The paper contains useful data, but it is poorly organized.

Response:

Thanks for this observation. We have modified the title to reflect this comment. “How will Smart Technology support SDG 12? An empirical study on Sustainability in Indian Agricultural Operations”

We collected data through interviews from farmers -users (fully adopted, partially adopted) and non-users (willing to adopt and not willing to adopt) of technology. The data is categorized into four different segments (see Table 2).

Sections are too broad and overlapping. For example, the introduction (4 pages) includes an overview of other studies rather than introducing readers to the topic and narrowing the focus. This is even less necessary given that you already have a literature overview. Also, the first two paragraphs on page 3(Introduction) are about methods. The first two sections of the Literature review, on the other hand, are about global issues, with definitions of IoT and technologies (for the introduction). You are referring to the gap in the middle of this section, which represents the end of the introduction. At the end of 2.1, you repeat what you did. 2.2 is for methods and should be more concise . Readers are more interested in a description of the approach than a review of studies that use it. In 3.2, you repeat what was previously said. You have another 3.2 (twop times the same numbering) heading that deals with data collection (as with 3.1).

Response:

We improved the revised version in line with the reviewer’s comments. The section 1 is introducing the topic and the research gap, Section 2 is providing background of Indian agriculture sector and Fuzzy-Set Qualitative Comparative Analysis (fsQCA). Section 3 includes research design and the data collection. All these are highlighted in the revised version.

In the introduction, you state that agriculture accounts for a sizable portion of India's exports, while only selecting 5 farmers from each category of the four-segmented survey. Why no more? How did you come up with the metrics in Tabs 5, 6, and 7.

Response:

We identified four segments after local field visits and then interviews were conducted in these four categories. The length of the interview and the depth of the questions are highly time consuming and we decided to stop with five farmers in each category as there is not much new information was emerging later. This has been explained well in Section 3.3 of the revised version.

The steps we followed in implementing fsQCA (Tables 5, 6 and 7) are based on the step-by-step guide for fsQCA suggested by Saridakis et al. [24]. These steps have been explained in Section 2.2 and applied in creating Tables 5, 6 and 7.

You have one more review in 4.3 (the Section that should deal with data analysis and findings). In the first two chapters of section 5(further directions), you summarize what you did in this study (please refrain from doing so). The conclusion section is too long and unclear. papers in the field to cite, such as https://doi.org/10.3390/en18020416. I encourage you to revise your paper to be more concise, with content that will not overlap among sections. The study contains material, but it must be properly organized, which it is currently not.

Response:

As we highlighted at the introduction section (third last paragraph), we did not use any theoretical underpinning for designing our qualitative study. Hence, no theory was discussed at the literature survey section (Section 2). However, the results of our qualitative study provided additional insights linking our results with the tents of the Diffusion of Innovation (DoI) theory. Hence, we had to briefly introduce this theory in Section 4.3 to help interested readers.

Thanks for the comments on Section 5. We have tidied the section and removed repetitions. We have also strengthened Section 6 on conclusions.

The references are not as suggested by the journal. You have links inserted into manuscript text. You use percent, per cent, and % throughout thetext. DoI, or DOI? Please use the third person and avoid the first person in your writing. It is not true that the BRICS nations are not classified as high-income countries. I have many more minor complaints, but your text lacks line numbering, so I can not pinpoint them. You could use more recent

Response:

We have modified the reference format. We have consistently used DoI in the revised version. Thanks for the observation on percentage. We modified the terms in the revised version as follows:

Now we have used only ‘percent’ and ‘%’.

According to World Bank Income classification, BRICS nations are classified as middle to high-income countries as they have developing economy. (see page 2)

We have proofread the revised version and removed any error.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors Dear Authors, This paper addresses an important and topical topic, namely the adoption of smart technologies in Indian agriculture and their potential contribution to achieving SDG 12. However, in its current form, the scientific paper requires revisions to meet the scientific and editorial standards of the journal. The observations below are formulated with the aim of supporting the authors in strengthening the scientific rigor and clarity of presentation. 1. Positioning of the contribution in the specialized literature
The authors state that there are no similar “comprehensive” academic studies in the context of Indian agriculture. This statement is formulated too generally and is not supported by a systematic review of the literature. Furthermore, the scientific paper does not sufficiently discuss/research the international literature, where there are already studies on the adoption of smart technologies in agriculture, based on theories such as Diffusion of Innovation and on qualitative or configurational methods. It is recommended:
Rewording “scaopari research” in a more precise manner;
Clear delimitation of novelty (e.g. specific geographical context or methodological combination);
Explicit integration of relevant international literature. 2. Clarity of methodology and sample definition
Although the methodology is described at a general level, essential details are missing that allow the validity of the results to be assessed. In particular, a rigorous clarification of the sample used is required. Authors are encouraged to explicitly specify:
The total number of respondents included in the analysis.
The number of farms or orchards investigated.
The selection and exclusion criteria;
The distribution of respondents by age group, location (urban/rural), and type of farm; The limits of generalizability of the results obtained.
These clarifications are essential to support the statements made at the national level (India). 3. Tables, data, and traceability of results
The manuscript contains several tables (Tables 2–7) which include classifications, percentages, age groups, and numerical values. In its current form, it is not sufficiently clear:
How these values were obtained;
Whether they result from raw data, aggregations, or interpretations of interviews;
What empirical basis supports the presented distributions? To improve scientific rigor, it is recommended to:
Clearly explain how individual responses were transformed into tabular values.
Justify each table by explicit reference to the collected data.
Avoid presenting percentages or distributions without clear statistical or methodological support. 4. Application of the fsQCA method
The use of fsQCA is interesting and suitable for configurational analysis, but the current description raises some methodological questions. In particular:
The calibration process of fuzzy sets is not sufficiently explained.
Treating missing values as non-membership requires methodological justification.
The small sample of respondents requires an explicit discussion of the paper's limitations.
A better description of these aspects can increase the credibility of the scientific paper. 5. Structure of results and conclusions The paper would benefit from:
A clearly delimited Results section, in which the main findings are presented concisely;
A Conclusions section that explicitly synthesizes the validated results, rather than merely summarizing general discussions.
The link to SDG 12 should be formulated based on the results obtained, avoiding general or declarative statements. 6. Editorial and presentation aspects Authors are asked to pay special attention to compliance with the journal template:
Figures are oversized and, in some cases, exceed the graphic frame.
Tables do not comply with the journal's format requirements.
The text contains graphic highlights (color, bold, underline) that should be removed.
The abstract exceeds the maximum word limit.
The paper is not written on the original template, or some elements were deleted from it. Title Consistency: Authors are requested to ensure full consistency between the title of the manuscript and the title provided in the referencing system. Currently, the peer-reviewed paper explicitly specifies “Indian Agricultural Operations,” while the registered title is more general. Clarification and harmonization of the title is necessary and will improve the transparency of the geographical scope of the study and avoid potential confusion for readers and indexing. Conclusions
The scientific paper has good potential, but requires revisions to increase the methodological rigor, clarify the empirical basis of the results, and improve the academic presentation. The above observations are offered constructively and may guide the authors towards a significantly improved version of the paper.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 5 Report

Comments and Suggestions for Authors

The authors define research questions, which is a good starting point. However, they fail to mention the search string, the databases they consulted for their research. What were the inclusion/exclusion criteria? How many papers met actually these criteria? All these information is required to reproduce the search, but missing in the current version of the manuscript.

Table 1 is unclear. What is the relation between Interview question, Research question and theory? The column "Theory" comprises research questions. What kind of theory? The headers should have meaningful labels. The table must be self-explaining.

Tbale 4 faces a similar problem. The 4th column is called "Investment". Does it m ean who is funding? or who is suppoed to be funding according to response? To be clarified. The authors point out age "20-50", implying almost all Farmers. This segmentation does not have much merit. THe segmentation must be made much narrower.

The caption of Table 7 does not explain the table either. How are the presented coverage and consistency defined?

Finally, the authors should mention the limitation of their study? (and its impact)

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors, the work remains poorly organized, and if published without corrections, it will harm the journal's reputation. I recommend that the manuscript be examined by an experienced contributor and then resubmitted. During this stage, the previous comments were not addressed properly, and it is difficult for the paper to be properly organized with the assistance of reviewers.

1) Your manuscript does not contain line numbering, so it is hard to pinpoint all the remarks

2) The manuscript still contains URL links instead of references

3) Please maintain a scientific tone by avoiding terms such as enormous, huge, and fully. For the scientific readers, it is irrelevant what the news headlines in India are; it is relevant what is occurring there.

4) Please use only USD as currency

5) It is not a reference that discusses; it is the author/s. Please use name/s with reference

6) Please rewrite this properly: „We have our main research aim specific to the Indian agricultural sector:...“

In the introduction section, again, you have methods: „We employed a mixed methods approach to answer these research questions. First, in Phase 1, we conducted ... „ This is for methods not for introduction.

THE PAPER DOES NOT HAVE A METHODS SECTION!

7) The first two pages are your introduction section are too broad. You have three pages of introduction. Please reduce that by focusing your work on the topic. The section does not have scientific soundness, especially the content of the first page. These sections are off-topic and too broad. It should be checked by the contributors with scientific experience.

8) You still use „percent and %“. Please maintain a scientific approach and Use %

9) What is the point of this claim, for example: „According to the World Bank Income classification, BRICS nations are classified as middle to high-income countries as they have developed economies“. How does this relate to anything in your paper? First of all, the claim has no point. Second, the claim is not true as it is your false interpretation of the chart, not a claim by the World Bank. I direct the authors to check the list of 10 BRICS countries and their income classification.

10) Section 2.1 is just another introduction. This is a better introduction than the 1.0

11) Please cite the same papers based on contemporary and smart farming, as: https://doi.org/10.3390/en18020416

12) Just look at these claims: „Truth Table is the heart of a QCA“, „Agriculture is a way of life, culture, and heritage for many families ... “ This is not scientific writing. Manuscript has to be checked and corrected by experienced contributr/s.

13) „As mentioned earlier“ ... so why mention it again? This is one of the unwanted phrases in scientific expression

14) What is the point of the bolded text in section 4.

15) On page 16, you claim: „The first observation is our ability ...“ You observed your ability? This is why the text has to be checked by someone with scientific experience

16) Page 16: „This has helped us to confirm...“ This study is not about you. Please maintain a scientific and neutral tone

17) Page 16: „Thus, we feel...“ no comment. How you felt is not of the reader's concern. Please maintain an objective tone and use third-person expressions

18) Page 18: „DoI theory has helped us to understand. “ This study is not about you. Please have that in mind. It would be much easier to maintain an objective tone if you used the third-person expression.

19) Why are some words underlined in your text?

20) In 4.4. Instead of results, you explain methods as well (what is reliability, experience, Bernefit, etc).

21) In future discussions, you summarize what you did in your study. This is not a proper text for this section

22) „Technology is the backbone of India’s development in various fields.“ Is this different in other countries? The first paragraph of the Conclusion section looks like another introduction paragraph.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors Dear Authors,
Congratulations for the work invested in the review. The responses to the observations from the first round are consistent, and the current version of the paper is visibly improved in terms of methodological clarity, structure and general coherence. A genuine effort to address the comments received is observed. To improve the scientific quality of the article, some clarifications and minor adjustments are recommended, presented below. Observations for improvement
The statements regarding the novelty of the study should be better grounded by positioning the study against the international literature and by clearly delimiting what is novel beyond the local context.. Even if the contribution is relevant in the chosen context, it is recommended:
A better explicit reporting on the relevant international literature;
A clear delimitation of the novelty as particular to the context (India/Karnataka) and/or the methodological combination used;
Avoid absolute formulations that cannot be directly supported.
The study is presented as having been conducted in the period 2021–2023, it would be useful to:
Explicitly mention the limitations related to the timeliness of the data;
Briefly update the specialized literature up to the time of submission of the manuscript, in order to anchor the results in the recent context. Although the presentation has improved, an even clearer delimitation between the empirical results obtained and their interpretations would help the reader to follow the main contribution of the study more easily.
Please check the formatting of the figures carefully. In the current version, in some cases (e.g. Figure 2), elements in the margin or line numbering visually interfere with the figure itself, affecting readability. A reframing/resizing of the figures would solve this problem.

Please correct the title in the paper, which differs from the one in the reference system, as there is currently a discrepancy regarding the geographical delimitation (India).

Author Response

Dear Authors,
Congratulations for the work invested in the review. The responses to the observations from the first round are consistent, and the current version of the paper is visibly improved in terms of methodological clarity, structure and general coherence. A genuine effort to address the comments received is observed. To improve the scientific quality of the article, some clarifications and minor adjustments are recommended, presented below.

Response: We thank this reviewer for his/her positive comments.

Observations for improvement
The statements regarding the novelty of the study should be better grounded by positioning the study against the international literature and by clearly delimiting what is novel beyond the local context.. Even if the contribution is relevant in the chosen context, it is recommended:
A better explicit reporting on the relevant international literature;
A clear delimitation of the novelty as particular to the context (India/Karnataka) and/or the methodological combination used;

Response: We appreciate this comment. However, we feel that we have already used international literature while highlighting the novelty and contribution of the paper. Specifically, we have references from Serbia (Ref [1]), UK (Ref [8]) and China (Ref [11]), in addition to references from India. In addition, we have added latest references published in 2025 (Ref. 2-4). The novelty of the paper and its two contributions have been highlighted in the Introduction section just before presentation of the research questions. Further, the novelty of the research stemming from the concept of technology adoption in agricultural sector of rural India is further explained in practical contribution in section 6.2 of the R3 version.

Avoid absolute formulations that cannot be directly supported.
The study is presented as having been conducted in the period 2021–2023, it would be useful to:
Explicitly mention the limitations related to the timeliness of the data;

Response: Thanks for highlighting this point. In the revised version of the article, we added this as one of the limitations. Please see page 20, lines 786-788 of the R3 version.

Briefly update the specialized literature up to the time of submission of the manuscript, in order to anchor the results in the recent context. Although the presentation has improved, an even clearer delimitation between the empirical results obtained and their interpretations would help the reader to follow the main contribution of the study more easily.

Response: The field of use of smart technologies in agriculture is a rapidly evolving field with new references almost every day. In line with this comment of this reviewer, we have included three latest references (Refs. 2-4]).

Please check the formatting of the figures carefully. In the current version, in some cases (e.g. Figure 2), elements in the margin or line numbering visually interfere with the figure itself, affecting readability. A reframing/resizing of the figures would solve this problem.

Response: Now, Figure 2 is aligned with the page. We hope the revised version has better readability.

Please correct the title in the paper, which differs from the one in the reference system, as there is currently a discrepancy regarding the geographical delimitation (India).

Response: Title of the article is “How will Smart Technology support SDG 12? An empirical study on Sustainability in Indian Agricultural Operations”. We have used this title consistently in all the other places. We hope this will be changed in the journal’s referencing system.

Author Response File: Author Response.pdf

Reviewer 5 Report

Comments and Suggestions for Authors

Quality has hardly improved.

1) The reviewer requested search strings, databases, and inclusion/exclusion criteria to ensure the research is reproducible. The authors declined to provide this information, stating that their work is a qualitative study focused on primary data and not a systematic literature review. Even if the work does not follow a systematic approach, the reader must be able to reproduce the literature search, which is currently not possible. To be done.

2) The reviewer noted that Table 1 was unclear and that headers should have more meaningful labels to be self-explaining. While the authors explained the use of the "Theory" heading in their response, they did not update the Table captions. The tables must be self-explaining, which they are currently not, either. Still to be done for Table 1 and Table 4.

Author Response

Quality has hardly improved.

Response: We have improved the article in line with the comments of this reviewer and four more reviewers. We are confident that the revised R3 version has better quality.

Response: We fully understand the importance of systematic review. In this research, we have tried to capture the value of smart technology in agriculture supply chain. While we searched the literature, we used a comprehensive term combining several modern technologies to achieve good literature review on this topic. We further have clarified this in page-2, lines 59-64.

In section 2, while we discussed a detailed methodology, we also mentioned that the literature is conducted to study the Indian agriculture scenario in the presence of technology. These are further explained in Section 2.1.

Response: Table 1 is representing the interview instruments. It has included 10 interview questions and showing how these questions are related to Research questions RQ1-RQ5. In line with this comment, we have modified the caption of Table 1 and its column headers.

Table 4 has been improved to include the terms used such as Farm size and Technology adoption, in detail. This is further explained in section 4.2, page 13, lines 447-452. The caption for this table has been modified to capture the table meaningfully.