User Participation Behavior in Crowdsourcing Platforms: Impact of Information Signaling Theory

Round 1

Reviewer 1 Report

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Comments for author File: Comments.docx

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

This paper discussing the issue about user participation behavior and crowdsourcing community is interesting and novel.

The set of sample data in Table1 is rich and valuable.

There are some suggestions for this paper. The authors will need to enhance the discussion quantity and quality for this paper.

1.      The authors will need to check for grammar carefully. (Row 249, … and the data were standardized; Row 295, As shown in Table 5, Columns 2 …; Row 295,Based on the results shown in Column 2, we observe a positive and significant association between the online reputation and the user participation behavior(β = 0.03, p < 0.01). Thus, Hypothesis 1, which predicts a positive effect on the user participation behavior, is supported. Meanwhile, we observe a positive and significant association between the salary comparison and the user participation behavior(β = 0.063, p < 0.01). Thus, Hypothesis 3, which predicts a positive effect on the user participation behavior, is supported; Row 299, Equation 3to 6outline our empirical models for hypotheses 2 and hypotheses; Row 306, Based on the results shown in Column 2; Row 314, Thus, Hypothesis 2, which…; Row 323, The result is contrary to H2;…………………………………..).

2.      The English abbreviation is only used once. (Row 240, …as follows: “single reward(SR)”; “multiperson reward(MR)”; “tendering task(TT)”; employment task(ET)”; “piece-rate reward(PR)”; and “direct employment(DE).”)

3.      Please explain how this value is generated? (Row 321, The mediation effect accounts for -3.75% of the total effect; ; The mediation effect accounts for 26.8% of the total effect. )

4.      mediating effect

 Independent variable     Mediating variable (Significant)

 Independent variable      Dependent variable (Significant)

 Mediating variable      Dependent variable (Significant)

 Independent variable + Mediating variable     Dependent variable (Significant)

Table 6 cannot show the above results.

5.      Table 7. Significance analysis of the direct and indirect effects.

     H2 Direct Effect (Supported) & Indirect Effect (Supported) But Direct Effect+ Indirect Effect (No Supported)

The result is not logical.

6.      moderating effect

 Independent variable      Dependent variable (Significant)

 Independent variable + Moderating variable     Dependent variable (Significant)

 Independent variable + Moderator variable      Dependent variable (Significant)

 Independent variable + Moderator variable + Interactions      Dependent variable (Significant)

Table 8 and Table 9 cannot show the above results.

 Moreover      

Equation (7) ~ (14) have nothing to do with IT (Interpersonal trust), but Table 8 and Table 9 show that the moderating effect are related to IT (Interpersonal trust).

7.      About Practical implications

The three points of practical implication are very valuable, but they need to be cited form empirical models and data results.

8.      About data analysis tools

In the face of multiple variables, SEM (structural equation model) can explain the mediating effect and moderating effect better than regression analysis.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

The paper presents an interesting topic an is well written. While the methods and empirical presentation are easy to understand the relevance to "Sustainability" audience could be improved. Findings should more clearly adress Sustainability issues and have implications on Sustainability. Also, methods and results lack of methods article. I would urge authors to more clearly state that you follow guidelines of quantitative models. Please look into Pesämaa et al., (2021) and say you follow that article. I would also say Sustainability is a rather applied journal and some of the equations and mathematical demonstrations seems excessive. 

References

Pesämaa, O., Zwikael, O., HairJr, J., & Huemann, M. (2021). Publishing quantitative papers with rigor and transparency. International Journal of Project Management. 39(3), 217-222.

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Comments for Response 1:

• The original manuscript Row 249：

Finally, we obtained 28,887 valid sample data, and the data were standardized.

• The original manuscript Row 295：

As shown in Table 5, Columns 2 and 3 show the OLS regression results. Column 2 adds the influence of the online reputation on the user participation behavior. Column 3 adds the influence of the salary comparison on the user participation behavior.

Based on the results shown in Column 2, we find that there is a significant positive correlation between online reputation and user participation behavior (β=0.03, p<0.01). Thus, Hypothesis 1, which predicts a positive effect on the user participation behavior, is supported. Meanwhile, we observed that there is a positive and significant correlation between salary comparison and user participation behavior (β=0.063, p<0.01). Thus, Hypothesis 3, which predicts a positive effect on the user participation behavior, is supported. (Capitalization issues)

• The original manuscript Row 299：

Equation (1) to (6) outline our empirical models for hypotheses 2 and hypotheses 4.

(Capitalization issues)

• The original manuscript Row 306：

Based on the results shown in Column 2, we observed a positive and significant association between the online reputation and the user participation behavior (β=0.03, p<0.01). (Capitalization issues)

• The original manuscript Row 314：

Thus, Hypothesis 2, which predicts a positive mediating role between online reputation and user participation behavior, is not supported. (Capitalization issues)

• The original manuscript Row 323：

The results were contrary to that of H2. Therefore, as shown in Table 7, hypothesis 2 is not supported. (English abbreviation and capitalization issues)

In addition to the above, the content of the article has other similar problems.

5. Increase the discussion of positively moderates the positive correlation, negatively moderates the positive correlation, positively moderates the negative correlation, and negatively moderates the negative correlation, and then citing more literature the more supports your point of view about hypothesis 5 and hypothesis 6.

6. Increase the discussion of positively moderates the positive correlation, negatively moderates the positive correlation, positively moderates the negative correlation, and negatively moderates the negative correlation, and then citing more literature the more supports your point of view about hypothesis 5 and hypothesis 6.

8. For the rigor of the article, I suggest adding SEM analysis results to “Empirical models and data results”. You can compare the similarities or differences with regression analysis and increase your own research contributions.

Author Response

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Author Response File: Author Response.pdf