Analysis of Consumers’ Willingness to Pay for Honey in China
Round 1
Reviewer 1 Report
This study provides good quality data for understanding honey consumption, in particular about the consumers’ willingness to pay for honey in the Chinese mainland. I think that the results are of general interest, they may help to a better understanding of honey consumption. In addition, it can provide guidance for developing marketing strategies and increasing the level of consumer satisfaction. Overall, I recommend that the paper can be published after minor revision.
Here are some suggestions for modification,
1. The authors should state more clearly the sample selection procedure, thus letting the readers know the representativeness of the samples.
2. Table 4 should be replaced with the figure to better show the results.
3. Add the statistics software of empirical analysis in “Materials and Methods”.
4. Delete the sentence (The first limitation of this research is that the scope is limited to Jiangxi province in eastern China. In future research, the research scope can be expanded to China mainland) in the last natural paragraph of conclusions, and rewrite the last paragraph of conclusions.
5. English writing should be checked to avoid grammar errors.
Author Response
Reviewer #1: This study provides good quality data for understanding honey consumption, in particular about the consumers’ willingness to pay for honey in the Chinese mainland. I think that the results are of general interest, they may help to a better understanding of honey consumption. In addition, it can provide guidance for developing marketing strategies and increasing the level of consumer satisfaction. Overall, I recommend that the paper can be published after minor revision.
Here are some suggestions for modification,
1.The authors should state more clearly the sample selection procedure, thus letting the readers know the representativenes of the samples.
Response: Thank you,we have added relevant content.
2. Table 4 should be replaced with the figure to better show the results.
Response: Thank you for your comment, we hope to keep table 4, so that readers can get more specific digital information.
3.Add the statistics software of empirical analysis in “Materials and Methods”.
Response: Thank you, we have added statistics software of empirical analysis in “Materials and Methods”.
4.Delete the sentence (The first limitation of this research is that the scope is limited to Jiangxi province in eastern China. In future research, the research scope can be expanded to China mainland) in the last natural paragraph of conclusions, and rewrite the last paragraph of conclusions.
Response: Thank you, we have deleted the sentence and rewritten the conclusions.
5.English writing should be checked to avoid grammar errors.
Response:Thanks, we have checked the full text carefully, and ask Dr. Frederick Partridge, Dr. Qiang Huang to revise.
Reviewer 2 Report
Article is interesting and based on original dataset. The structure is clear and well-designed. However, the survey of previous studies and methodological issues can be improved. A detailed review is attached.
Comments for author File: 
Comments.pdf
Author Response
Reviewer #2: Article is interesting and based on original dataset. The structure is clear and well-designed. However, the survey of previous studies and methodological issues can be improved. A detailed review is attached.
General remarks:
1.It is suggested to clarify a few statistical methodology issue as follows:
（1）The meaning of cut1, cut2 and cut3 from Table 9 is not explained in the text,
Response:Thanks, cut1, cut2, and cut3 are the estimates of the tangent points, that is, the range of values of the dependent variable that needs to be estimated for calculation. Since "Honey Purchase Frequency" has 4 values, so cut has 3 values.
（2） The meaning of dy/dx in Table 8 is not straightforward, and should be introduced in the text,
Response:Thanks,dy/dx represents the marginal effect, which is the degree to which the dependent variable changes by one unit that causes the dependent variable.
（3） R 2 is rather low in Tables 8 and 9. If it is not a problem, necessary explanations should be Made б
Response:Thanks, Although the R2 values in Table 8 and Table 9 are relatively low, the models have passed the significance test, indicating that the model is well adapted.
（4） In Table 8, it is better to use term ‘constant’ instead of “Absolute term”
Response:Thanks, we have revised.
2.In the Section 2 “Materials and Methods”, it is suggested to add a brief outline of probit regressions used in the empirical analysis of honey consumption in Section 4.
Response:Thanks,we have added relevant content in “Materials and Methods”. In order to explore the influencing factors of whether consumption honey and honey purchase frequency, this paper constructs the following model:
（The formula of the model refers to the attachment）
buyi indicates whether the ith consumer buys honey and how often it buys. geni、agei、edui、incomei、awari、Coni indicates the gender, age, education level, monthly income, honey cognition, and confidence in domestic honey and other variables, a0 is the constant term, a1, a2, a3, a4, a5, a6 are the estimated coefficients, s is the perturbation term.
3.It is necessary to edit for English content and clarify several parts of the text as it is mentioned in the minor remarks.
Response:Thanks,we have revised.
Minor remarks:
Line 13-14
in the Chinese mainland and to identify the main factors determining it. The survey data are derived from respondents in Jiangxi province in eastern China. Results showed that respondents mostly
Response:Thanks,it has been corrected.
line 17
common way of honey purchase is direct (sale?) from the beekeepers (44.90%). Most of the Respondents
Response: Thanks,it has been corrected.
line 36
0.23 kg per capita, which is lower than in Japan (0.37 kg), France (0.70 kg), United States
Response: Thanks,it has been corrected.
Line 42 The meaning in not clear
consumption [10], and the intrinsic attributes of traditional food were drivers [14], suggested total, 1000 questionnaires were collected, including undergraduates, and graduate students,
Response:Thanks,it has been corrected.
Lines 59-61
answers. The final number of questionnaires was 960. The statistical methods applied in the research were are as follows: descriptive statistics, t-test, ANOVA and Fisher discriminant.
Response:Thanks,it has been corrected.
Lines 68-69 It seems to better to round up numbers YUAN (314.78-1258.48 US$). According to the China Statistical Yearbook (http://www.stats.gov.cn /tjsj/ndsj/ 2021/ indexch.htm), the average monthly salary of 2020 was 6463 YUAN (4811-8115 YUAN). Most respondents with monthly income less
Response:Thanks,it has been corrected.
Line 77and 35.94% consumers think that colour is not important. With regard to types of types of honey, 50.83% respondents prefer runny honey rather than set honey (22.81%).
Response:Thanks,it has been corrected.
Lines 110-112
As it can be seen from Table 6, most of the respondents have confidence in the quality of domestic honey (87.40%) and prefer domestic honey (94.79%), but they are also worried about false fake honey on the market (76.15%). 74.48% respondents purchase and con
Response:Thanks,it has been corrected.
line 115
Characteristics
Response:Thanks,it has been corrected.
in table 6
I think that on the market there is too much false fake honey 76.15 731
Response:Thanks,it has been corrected.
Lines 118-119
In order to analyze the factors affecting honey consumption, this paper sets 2 two dependent variables (whether to buy honey, frequency of honey purchase) and 6 six independent variables (gender, age, education level, monthly income level, honey awareness, confidence in the quality of domestic honey), as shown in Table 7. 121
Response:Thanks,it has been corrected.
Line 131
attention to health, so they are more likely to buy honey. Compared with the monthly income level of 2000 yuan and ever lower or lower, consumers with monthly income of 2001-5000
Response:Thanks,it has been corrected.
lines 135-136 It is necessary to clarify of income level. This implies that the higher the income level, the greater probability of buying honey, which is in line with the law of demand in economics which means the higher the income level, the stronger the purchasing power [the stronger is demand for superior goods?.
Response:Thanks,it has been corrected.
line 164-165
In order to further analyze the impact of honey purchase channels on consumption, we selected two channels: specialty stores and online purchasing channels (facilities?) for empirical
Response:Thanks,it has been corrected.
lines 171-174
choose specialty stores to buy honey. Taking honey as a general food, the influence of the perception that honey it is a medicine on consumers' purchase of honey decisions is positive at the statistical level of 1%, which means consumers who believe that honey is a medicine have a higher probability of purchasing honey through specialty stores.
Response:Thanks,it has been corrected.
Lines 190-193
minants of honey consumption in Romania and in Croatia [8,11]. In previous studies, consumers in different countries, prefer different types of honey, for instance, Irish, German, Austrian and Swiss consumers prefer honeys with a dark colour [5,20], but Croatian consumers ones prefer honeys with a light colour [11]. In this study, most consumers 193
lines 195-197honey. Our results were mainly consistent with the previous research in terms of “determinants of consumer buying behaviour” [11,21] and “consumer attitudes towards honey” [11].The results showed that 74.48% respondents treat honey as a healthy and
Response:Thanks,it has been corrected.
lines 206-208
more than a year. The respondents mostly prefer runny honey and domestic honey, and consume honey because of its health and medical nutritious. 44.90% respondents of honey purchase is used to make it directly from the beekeepers. From the above results, we suggest to popularize honey consumption knowledge, and broaden honey consumption channels for purchasing and consuming honey
Response:Thanks,it has been corrected.
lines 211-213
The empirical findings suggest some implications useful to beekeepers and honey sales enterprises in guiding the transformation of traditional sales mode to modern sales mode one.
Response:Thanks,it has been corrected.
Lines 217-220
be expanded to China mainland. The second limitation, there are some factors that may influence honey consumption are not considered, such as consumer’s motivation, cultural practices, consumer familiarity or experience with the honey etc. Future research should be considered account for these factors as much as possible.
Response:Thanks,it has been corrected.
Line 237 It is likely that the initial date is missed
Wu, J.; Diao, Q. Y. Study on the development strategy of China's bee industry from [?] to 2050. China Agricultural Science 236 and Technology Press: Beijing, China, 2004; pp. 11-12. (In Chinese) 237
Response:Thanks,it has been corrected.
Reviewer 3 Report
The paper contributes to the topic of consumers’ willingness to pay for honey in China. The topic is great and I endorse the authors for such contribution. However, the content of the paper requires some manipulations before acceptance. So, the following comments have to be considered before acceptance:
- The major drawback of the paper is its perspective to review the literature of the topic. I want the author to delineate the boundaries of the work and meticulously review recent and related papers. I presented the following works to help the authors for literature review. So, please read them and cite in detail:
- Yormirzoev, M., Li, T., & Teuber, R. (2021). Consumers’ willingness to pay for organic versus all‐natural milk–Does certification make a difference?. International Journal of Consumer Studies, 45(5), 1020-1029.
- Zarandi, M. F., Soltanzadeh, S., Mohammadi, A., & Castillo, O. (2019). Designing a general type-2 fuzzy expert system for diagnosis of depression. Applied Soft Computing, 80, 329-341.
- Soltanzadeh, S., Zarandi, M. H. F., & Astanjin, M. B. (2016). A hybrid fuzzy clustering approach for fertile and unfertile analysis. In 2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) (pp. 1-6). IEEE.
- Delaram, J., Houshamand, M., Ashtiani, F., & Valilai, O. F. (2021). A utility-based matching mechanism for stable and optimal resource allocation in cloud manufacturing platforms using deferred acceptance algorithm. Journal of Manufacturing Systems, 60, 569-584.
- Delaram, J., Houshamand, M., Ashtiani, F., & Fatahi Valilai, O. (2022). Development of public cloud manufacturing markets: a mechanism design approach. International Journal of Systems Science: Operations & Logistics, 1-27.
2. The term “China” in keywords does not seem suitable. Please replace it with a more appropriate one, such as: Utility theory, consumer utility, etc.
3. The findings of the paper should be augmented. You can summarize the results and present them within a table. Also, adding a managerial insight framework (or guideline) can enhance the quality of the paper.
4. If you used any software for calculations of the models, please refer to it in Section 2.
5. In section 3.1, you described the data model, but did not addressed how the participants are selected. Please make clarification.
6. In Table 4, the paper presents the descriptive analysis of consumers' attributes to the relative importance of honey characteristics. How you achieve this set of characteristics? Did you conduct a study to determine them? or used from another resource? Please make clarification.
7. As the paper gathered data using questionaries, the verification and validation of the model should be tested using Cronbach's alpha.
8. What method or methods used for ranking and grading the characteristics? Using multi-criteria decision-making methods? Please make clarification and provide further detail.
9. In Table 8, please recheck “Absolute term”, it seems wrong.
10. Please consider multi-criteria decision-making models and methods as future works and note to the end of conclusion section.
Author Response
Reviewer #3: The paper contributes to the topic of consumers’ willingness to pay for honey in China. The topic is great and I endorse the authors for such contribution. However, the content of the paper requires some manipulations before acceptance. So, the following comments have to be considered before acceptance:
1.The major drawback of the paper is its perspective to review the literature of the topic. I want the author to delineate the boundaries of the work and meticulously review recent and related papers. I presented the following works to help the authors for literature review. So, please read them and cite in detail:
Yormirzoev, M., Li, T., & Teuber, R. (2021). Consumers’ willingness to pay for organic versus all‐natural milk–Does certification make a difference? International Journal of Consumer Studies, 45(5), 1020-1029.
Zarandi, M. F., Soltanzadeh, S., Mohammadi, A., & Castillo, O. (2019). Designing a general type-2 fuzzy expert system for diagnosis of depression. Applied Soft Computing, 80, 329-341.
Soltanzadeh, S., Zarandi, M. H. F., & Astanjin, M. B. (2016). A hybrid fuzzy clustering approach for fertile and unfertile analysis. In 2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) (pp. 1-6). IEEE.
Delaram, J., Houshamand, M., Ashtiani, F., & Valilai, O. F. (2021). A utility-based matching mechanism for stable and optimal resource allocation in cloud manufacturing platforms using deferred acceptance algorithm. Journal of Manufacturing Systems, 60, 569-584.
Delaram, J., Houshamand, M., Ashtiani, F., & Fatahi Valilai, O. (2022). Development of public cloud manufacturing markets: a mechanism design approach. International Journal of Systems Science: Operations & Logistics, 1-27.
Response:Thank you very much for your comments.We have added the following latest relevant literature in “Introduction” and “Conclusions”.
20.Wojciechowska-Solis, J.; Barska, A. Exploring the preferences of consumers’ organic products in aspects of sustainable consumption: the case of the Polish consumer. Agriculture.2021, 11, 138.
21.Yormirzoev, M.; Li, T.; Teuber, R. Consumers’ willingness to pay for organic versus all‐natural milk–Does certification make a difference? International Journal of Consumer Studies,2021,45(5), 1020-1029.
22.Huang, W.S.; Kuo, H.Y.; Tung, S.Y.; Chen, H.S. Assessing consumer preferences for suboptimal food: application of a choice experiment in citrus fruit retail. Foods, 2021, 10, 15.
25.Delaram, J.; Houshamand, M.;Ashtiani, F.; Valilai, O. F.A utility-based matching mechanism for stable and optimal resource allocation in cloud manufacturing platforms using deferred acceptance algorithm. Journal of Manufacturing Systems,2021, 60, 569-584.
26.Delaram, J.; Houshamand, M.; Ashtiani, F.; Fatahi Valilai, O. Development of public cloud manufacturing markets: a mechanism design approach. International Journal of Systems Science: Operations & Logistics, 2022,1-27.
27.Soltanzadeh, S.; Zarandi, M. H. F.; Astanjin, M. B. A hybrid fuzzy clustering approach for fertile and unfertile analysis. In 2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS),IEEE.2016,pp.1-6.
28.Zarandi, M. F.; Soltanzadeh, S.; Mohammadi, A.; Castillo, O. Designing a general type-2 fuzzy expert system for diagnosis of depression. Applied Soft Computing, 2019,80, 329-341.
2.The term “China” in keywords does not seem suitable. Please replace it with a more appropriate one, such as: Utility theory, consumer utility, etc.
Response:Thanks, we have deleted “China” in keywords, and have added “consumer utility” in keywords.
3.The findings of the paper should be augmented. You can summarize the results and present them within a table. Also, adding a managerial insight framework (or guideline) can enhance the quality of the paper.
Response:Thank you very much for your comments.We have added the some relevant contents in “Results” .
4.If you used any software for calculations of the models, please refer to it in Section 2.
Response: Thanks, we have added software for calculations of the model in Section 2.
5.In section 3.1, you described the data model, but did not addressed how the participants are selected. Please make clarification.
Response: Thanks,we counted 960 valid questionnaires, the result shows Table 1.
6.In Table 4, the paper presents the descriptive analysis of consumers' attributes to the relative importance of honey characteristics. How you achieve this set of characteristics? Did you conduct a study to determine them? or used from another resource? Please make clarification.
Response:Thanks, our questionnaire includes the contents(Characteristics) in Table 4.
7.As the paper gathered data using questionaries, the verification and validation of the model should be tested using Cronbach's alpha.
Response:Thanks,the reliability analysis of the questionnaire showed that Cronbach's Alpha was 0.765, which was greater than 0.7, indicating that the reliability of the questionnaire was good.
8.What method or methods used for ranking and grading the characteristics? Using multi-criteria decision-making methods? Please make clarification and provide further detail.
Response:Thanks, the basic idea of Fisher's discriminant is projection, in which k groups of m elements are projected in a certain direction so that the projected groups are separated from each other as much as possible, and the way to measure the separation between groups as much as possible is based on the idea of one-dimensional analysis of variance.
9.In Table 8, please recheck “Absolute term”, it seems wrong.
Response:Thanks, we use term ‘constant’ instead of “Absolute term”.
10.Please consider multi-criteria decision-making models and methods as future works and note to the end of conclusion section.
Response:Thanks,we have added this contents in conclusion section.
Round 2
Reviewer 3 Report
The paper is revised based on the comments. It is acceptable in the current form.
