Does E-Commerce Construction Boost Farmers’ Incomes? Evidence from China

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This paper is good enough for this journal. It is suggested to accept the paper with revising some grammar mistakes and update the reference section.

Comments on the Quality of English Language

This paper is good enough for this journal. It is suggested to accept the paper with revising some grammar mistakes and update the reference section. 

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,

The paper presents an interesting perspective on e-commerce and its influence on farmers' income; however, it requires minor improvements.

The theoretical part of the work is well-contextualized. The references cited are up-to-date and well-correlated with the study, predominantly from recent years. The problem is clearly defined, and the three hypotheses are well-formulated.

The paper is well-structured, coherent, and logical. It contains numerous figures that significantly enhance the cognitive value of the work. The research methods are appropriately applied.

However, the research is overly econometric. Please simplify it. You seem to focus more on calculations than on explaining their meaning. I suggest moving the calculations to the appendix.

Please elaborate on what trade looked like before and after the advent of e-commerce. Also, clarify what IT tools the surveyed farmers possess. Having a mobile phone or internet access does not necessarily mean they engage in e-commerce.

Lastly, please elaborate more on the limitations of the research.

Best regards,

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The paper is an excellent contribution to the field of e-commerce research. The authors have done a solid job in conducting thorough research and presenting their findings in a clear and concise manner. One of the strengths of this paper is the introduction that clearly presents the topic and establishes the research gap and possible contributions of this research to evolving pool of knowledge. The paper also contains a comprehensive literature review that provides a solid foundation for the research. Cited sources are all related to the topic. The methodology used in this research is robust and well-explained. The data analysis and results section of the paper are well elaborated. The authors have effectively used figures, and statistical analysis to convey their findings. The presentation of the data is not only informative but also visually appealing, making it accessible to a wide range of readers.

However, the paper lacks a comprehensive discussion that could provide valuable insights into the implications of the study's findings. The authors need to link their research findings and recommendations to real-world applications and compare them to findings obtained from other research studies.

In this context I would also recommend adding more sources to compare the findings. This aspect of the paper needs to be further elaborated.

In terms of writing style and organization, the paper is well-written. The language is clear and concise, and the flow of the paper is logical, making it easy to follow the argument from introduction to conclusion.

Overall, this paper is a commendable piece of research that has the potential to advance our understanding of researched topic after some minor improvements.

Author Response

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Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

The below needs to be clearly explained so that will not confusion the reader 

4.1. Sample and Data

I am not very clear on how many datasets the author included in their study, as the result of the study in Table 1 and Table 2, figure1-2. Only, the period of years. It is not a clear dataset. But in section 5.4.2 (5.4.2. Eliminating the Influence of Special Samples) follow below “The dataset utilized in this study encompasses 638 counties classified as impoverished……so the sample and the dataset in this study a little confusion. 

The unbalanced panel data of 2419 county-level administrative districts in 30 provinces, autonomous regions, and municipalities directly under the central government in China from 2000 to 2020 are finally constructed based on the above database. Among them, Shanghai, Hong Kong, Macao, and Taiwan are not included in the sample of this paper, due to the absence of corresponding data on per capita disposable income of rural residents in these regions within the stipulated timeframe.

5.4.2. Eliminating the Influence of Special Samples

Page 13, LR 523 -528

The dataset utilized in this study encompasses 638 counties classified as impoverished, which may affect the validity of the regression results due to the pronounced dis-525 parities in economic development between impoverished and non-impoverished counties 526 and the fact that the state has originally had some policy favoritism towards impoverished counties.

I suggest that the Sample and Data should clearly explain and also below some misguided where to move.

 

As such, "The data in this paper are segmented into three distinct sections: first, the list of national-level e-commerce into rural areas comprehensive demonstration counties from 323 the years 2014 to 2020 is obtained from the official portal of the Ministry of Commerce 324 (MOFCOM), People's Republic of China. Subsequently," where is second and so on.

Author Response

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Author Response File: Author Response.pdf