The Power of Influencers: How Does Influencer Marketing Shape Consumers’ Purchase Intentions?
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsConsumer Attitude Theory section is incomplete. No sources cited (includes an error notice).
The three hypotheses are not new but are also not stated as being applied in a new way. If others have shown their application to be true in other fields but not in light food purchase intentions, the work needs to state this explicitly and the hypotheses need to state this as well. For example, instead of "H3: Live streaming sales positively affect consumer purchase intentions", the hypothesis should be worded more like "H3: Live streaming sales positively affect consumer purchase intentions of light food products.."
Do the demographics of the survey respondents compare favorably with the demographics of the Suzhou area? What are the demographics of the sample pool that did not complete the survey? Are there significant questions about either of these (representativeness) that the reader should know about which may affect the applicability of the results to the larger Suzhou area (or to China as a whole)?
Is the model selection supported by its use in past studies of this same topic (Consumer Attitude Theory)? If so, which studies (need citations). If not, why are you choosing to depart from accepted protocol? Justification using current literature is needed.
In the abstract, you state that "To enhance consumers' purchase intentions, this study suggests that influencers should transparently disclose collaborations, provide investigative evaluations combined with social evidence and academic research to boost credibility." None of these seems to be reflected in your primary or secondary indicators in the model.
Overall, the topic is interesting, but the deployment of the study does not follow the abstract/conclusions, the literature review and model justification are incomplete, and the text requires moderate amounts of editing. I would like to see a revised version of this which corrects each of these areas.
Comments on the Quality of English LanguageWhile the majority of the text is quite understandable, many instances of awkward or hard-to-understand phrases and sentences are found. For example, lines 80-81 "Which specific influencer marketing influence consumer satisfaction with light food?" is probably trying to ask which influencing factor has the greatest effect on satisfaction with light food, but it is not grammatically correct, and it does not really make sense as a question when worded as it is. At other times, the way that the sentences are worded mislead the reader somewhat. In lines 101 and following, the text states "Investments reached $13 million in 2021 and are predicted to soar to $84.89 million by 2028. This reflects that 80% of companies plan to increase their budgets for influencer marketing ...". The previous evidence of the rise of spending on social influencer marketing in no way reflects the next claim that this shows that 80% of companies plan to increase this type of marketing budget. The article referenced may say this, but the first claim does not lead to the second. The text, then, requires a good amount of editing needed to properly word statements throughout the work.
Author Response
Dear Editor and Reviewer,
Thank you very much for taking your time, constructive comments and suggests on our manuscript. We really appreciate all your comments and suggestions. We have carefully considered the suggestions and make changes accordingly. We have tried our best to revise and improve our manuscript. The revisions and corrections can be found in the resubmitted manuscript. Please find our point-by-point responses as follows:
- Consumer Attitude Theory section is incomplete. No sources cited (includes an error notice).
Response1:Based on your suggestions, we have supplemented the Consumer Attitude Theory section. The additional content is as follows:”The Consumer Attitude Theory, as one of the core theories in the field of consumer behavior, explores the formation of consumer attitudes towards products, brands, or services, and their mechanisms of influence on purchase intentions[15,16].According to Douglass et al.(1977), attitude consists of three components: cognitive, affective, and behavioral [20]. Reed et al. (2022) proposed that the cognitive component involves individuals' cognitive evaluations and beliefs about a product or service, the affective component involves emotional responses related to the product or service, and the behavioral component includes actual purchasing and usage behavior [21].
Research indicates that consumers' cognitive evaluations of brands and products significantly influence their purchase intentions. Batra and Ahtola (1991) validated the hedonic and utilitarian components of attitude, which have varying influences across different product categories [22]. For example, consumers' trust in influencers (i.e., cognitive component) and their cognitive evaluations of influencers' expertise directly affect their attitudes towards the products recommended by influencers and their purchase intentions. Ashraf et al. (2023) demonstrated that influencers' credibility plays a crucial role in enhancing consumer trust and purchase decisions [26].
The affective component reflects consumers' emotional dependence and preferences towards a product or brand. Reed et al. (2002) studied the process of consumers forming attitudes based on external information and personal experiences, emphasizing the role of emotional responses [21]. In influencer marketing, influencers' professionalism (such as professional insights into product knowledge) can significantly impact consumers' emotional responses. Consumers are more likely to trust influencers who demonstrate high levels of professionalism, and these influencers enhance consumers' preferences and trust through sharing professional knowledge and insights, thereby influencing purchase intentions [23].
The behavioral component emphasizes consumers' actual purchasing and usage behavior, which is particularly important in influencer marketing. In the context of live streaming sales, influencers directly impact consumers' purchasing behavior through personalized and precise recommendations. Chen and Zhang (2023) found that live interaction significantly increases consumers' purchase intentions and reduces uncertainties during the purchasing process [19].” (line110 -line140)
- The three hypotheses are not new but are also not stated as being applied in a new way. If others have shown their application to be true in other fields but not in light food purchase intentions, the work needs to state this explicitly and the hypotheses need to state this as well. For example, instead of "H3: Live streaming sales positively affect consumer purchase intentions", the hypothesis should be worded more like "H3: Live streaming sales positively affect consumer purchase intentions of light food products.."
Response 2: We appreciate your professional advice. We have made adjustments to section 2.3 hypothesis section, and the revised content is as follows:”The credibility of influencers is a key factor affecting consumer purchase intentions[17,24,25,26]. Research indicates that influencers' credibility significantly influences consumers' attitudes, thereby affecting their purchase intentions. For instance, Nugroho et al. (2020) pointed out that influencers' credibility plays a crucial role in enhancing consumer trust and purchase decisions, especially on e-commerce platforms [27]. Martiningsih and Setyawan (2022) found that on the Shopee marketplace, influencers' attractiveness and expertise have a significantly positive impact on consumer purchase intentions [28]. However, there is limited research on the impact of influencers' credibility on the purchase intentions for light food products. Based on this research gap, this study proposes the following hypothesis:
H1: influencers’ credibility positively affects consumer purchase intentions of light food products.
The professionalism of influencers also affects consumer purchase intentions. Research indicates that influencers' understanding of a brand or product positively affects consumers' purchase decisions, and their rich professional knowledge has been confirmed as an important characteristic influencing purchase intentions [26,29,36]. In addition, Zaman et al. (2023) studied various characteristics of social media influencers and found that expertise has a significantly positive impact on consumer purchase intentions [30]. These findings collectively reveal the multifaceted impact of influencers' professionalism on consumer purchasing behavior, from individual characteristics to interactive effects, providing important academic insights for a deeper understanding of this field.However, there is limited research on the specific impact of professionalism on light food products. To fill this research gap, this study proposes the following hypothesis:
H2: influencers’ professionalism positively affects consumer purchase intentions of light food products.
Live streaming sales significantly impact consumers' willingness to purchase light food, a phenomenon that has been thoroughly studied in multiple aspects. Chen and Zhang (2023) found that live interactions significantly increase consumers' purchase intentions and reduce uncertainty during the purchasing process[19]. Weismueller et al. (2020) showed that advertising disclosure and source credibility on social media platforms have a significant impact on consumer purchase intentions [31]. Liu and Zhang (2024) found that consumers can interact in real time with influencers via live streaming platforms to learn about product use and purchase information, which enhances their purchase willingness[32]. In addition, Men and Zheng (2023) pointed out that the alternative learning experience obtained through live shopping reduces consumers' uncertainty regarding light food products, thereby strengthening their purchasing behavior[33]. However, it is necessary to explore its impact on the purchase intentions for light food products. Thus, this study proposes the following hypothesis:
H3: Live streaming sales positively affect consumer purchase intentions of light food products.” (line142 -line182 )
- Do the demographics of the survey respondents compare favorably with the demographics of the Suzhou area? What are the demographics of the sample pool that did not complete the survey? Are there significant questions about either of these (representativeness) that the reader should know about which may affect the applicability of the results to the larger Suzhou area (or to China as a whole)?
Response 3: We sincerely appreciate your meticulous suggestions.We employed the PPS random sampling method, conducting multiple rounds of sampling and calculating the mean for each round's results. Ultimately, we used the randomized mean of the multiple rounds of sampling. Therefore, even with the sampling method, we can ensure that the results fall within the sample interval, avoiding the issue of the sampling results lacking representativeness.
We have made revisions in the paper and provided an explanation of the sample representativeness and the reliability of the survey results. The added content is as follows:”Suzhou is an economically developed and diverse city that can provide a broadly representative sample. Additionally, the emerging light food industry has significant development potential in this city. Therefore, this study distributed questionnaires to residents of Suzhou, using the PPS random sampling method. By employing a three-stage unequal probability sampling approach, the scientific rigor and representativeness of the sample were ensured [34,35].
First, primary sampling units were randomly selected from the urban districts and county-level cities of Suzhou. Then, streets and towns were further sampled from these units. Finally, households within these streets and towns were chosen for the survey. Each stage of sampling was based on the Probability Proportional to Size (PPS) method, ensuring that the probability of selecting each sample unit was proportional to its size.To verify the representativeness of the sample, we conducted mean processing and statistical analysis of the sampling results at each stage, ensuring that the sample was consistent with the population in key demographic characteristics. Additionally, we compared the characteristics of the incomplete survey samples with those of the completed survey samples, confirming no significant differences between the two groups. This further enhanced the representativeness of our sample and the reliability of the survey results.
In the formal survey, 859 questionnaires were distributed, of which 654 were effectively recovered, yielding a response rate of 76.14%.The summary of the study sample is shown in Table 1. It can be seen that the research subjects are mainly concentrated among female users (65.14%) and those aged 18 to 35 (78.9%), reflecting that most users of social media are young female consumers. This suggests that the development potential and innovation direction of influencer marketing need to be closely aligned with the lifestyle concepts and consumption trends of young female consumers. Continuous innovation and optimization of products and services are required to meet their pursuit of a high-quality life.The data shows that the residents from the Gusu District-Pingjiang Street area make up the highest proportion, possibly due to a higher concentration of influencers in the area, leading to more active users on social media platforms. This may reflect the influence of influencers in the region and the likelihood of residents participating more on social media platforms, further emphasizing the area's importance in online marketing and brand promotion. Moreover, most respondents (71.56%) prefer to spend no more than one hour on social media platforms, suggesting an emphasis on efficient information acquisition, which is a reason behind the rise of platforms like TikTok, which focus on short videos. This requires influencers to learn how to refine the core information in their content creation and dissemination strategies and to adopt more intuitive and engaging formats, such as short videos, combined images and text, interactive live streaming, etc., to enhance the efficiency of information dissemination and audience engagement[52].Furthermore, influencers should utilize data analytics tools to deeply understand the preferences and behavioral characteristics of their target audience to develop more personalized and targeted content strategies. This can attract and maintain consumer attention in a short time and enhance the effectiveness of marketing activities.
The obtained data underwent reliability, validity, and chi-square tests, yielding reliability coefficients of 0.932, 0.858, and 0.902, all of which are greater than 0.8, indicating a high level of reliability in the research data. In the validity analysis, the KMO value was 0.957, and Bartlett's test of sphericity produced an approximate chi-square of 6338.878, with df=276 and a p-value of 0.000, indicating high validity of the data. The chi-square test results showed a significant difference between whether respondents had purchased light food and whether they became interested and continued to search for related information (X²=13.707, P=0.000), indicating a significant correlation between the two variables. The results demonstrate that the data is reliable and valid, and that the survey results are both authentic and credible.”(line187 -line239)
- Is the model selection supported by its use in past studies of this same topic (Consumer Attitude Theory)? If so, which studies (need citations). If not, why are you choosing to depart from accepted protocol? Justification using current literature is needed.
Response 4: Thank you for your suggestion. Our research found that currently, there are indeed not many studies combining the fuzzy comprehensive evaluation model and Consumer Attitude Theory. However, theoretically, this combination is reasonable and represents a new attempt in our paper. It not only enriches consumer behavior and marketing theories but also provides new insights and methods for understanding the role of influencers in digital marketing.
Based on your suggestions, we have made relevant improvements. After adjusting the content, the text was added is
”3.2. Model selection
Using descriptive statistical methods to analyze consumer characteristics on trend-setting platforms as a preliminary exploration. In this study, we have identified the use of Consumer Attitude Theory. Given the complexity of the factors influencing consumer purchase intentions, such as influencers' professional insights, objective recommendations, and the layout style of live streaming sales, these factors often possess fuzziness and uncertainty, making them difficult to measure with simple numerical values. Therefore, it is essential to establish a quantitative model suitable for this theory to comprehensively consider these factors.
Consumer Attitude Theory plays an important role in explaining consumer behavior and decision-making processes. For example, Minchev (2021) summarized the formation and impact of consumer attitudes in purchase decisions, focusing on the internal and external factors influencing attitudes in classic behavioral models and demonstrating the importance of attitudes in consumer behavior and purchase decisions [37]. Cerceloiu et al.(2021) used the three components of cognition, affect, and behavior to analyze consumer attitudes towards private education services, revealing the critical role of attitudes in consumer decision-making[38]. These studies mainly employed statistical methods such as Structural Equation Modeling (SEM) or Regression Analysis to analyze the impact of consumer attitudes on purchase intentions.
The fuzzy comprehensive evaluation model can quantify and evaluate ambiguous and difficult-to-quantify factors, translating consumers' purchase intentions into specific numerical values[39][40]. This allows for a more comprehensive consideration of consumers' experiences and attitudes on recommendation platforms, and more accurately reflects the formation mechanism of consumer purchase intentions [41]. For instance, Han et al. (2021) used the fuzzy comprehensive evaluation method to assess consumer energy efficiency, demonstrating the effectiveness of this method in handling complex evaluation problems [42]. Li (2021) analyzed consumer decision-making power using a BP neural network and fuzzy comprehensive evaluation model. The study combined fuzzy reasoning and neural networks to predict consumer purchase intentions, showcasing the effectiveness of the fuzzy comprehensive evaluation method in addressing the uncertainty in consumer decision-making [43]. Consumer Attitude Theory involves multiple influencing factors, and the fuzzy comprehensive evaluation model can comprehensively evaluate the relative importance and overall effects of these factors. Additionally, compared to traditional statistical methods, the fuzzy comprehensive evaluation model offers greater flexibility and adaptability in handling nonlinear and complex systems, better reflecting the dynamic changes in consumer behavior.
In summary, although there is currently no literature explicitly using the fuzzy comprehensive evaluation model under the Consumer Attitude Theory, studies using these two methods separately have been widely applied and validated in related fields. Therefore, this study chooses to combine the Consumer Attitude Theory with the fuzzy comprehensive evaluation model to explore the impact of influencer marketing on consumers' purchase intentions. The Consumer Attitude Theory provides a theoretical framework for understanding consumer attitudes and behaviors, while the fuzzy comprehensive evaluation model offers a tool for handling multiple indicators and uncertain information. By combining these two methods, we can innovate both theoretically and methodologically, providing a more comprehensive analysis of consumer attitudes.Figure 2. shows the intersection of Consumer Attitude Theory and the Fuzzy Comprehensive Evaluation Model, highlighting the theoretical foundation of the research methodology.
Figure 2. Illustration of the Combination of Consumer Attitude Theory and Fuzzy Comprehensive Evaluation Model.【】
The new references are as follows:
1.Minchev, A. An examination of attitudes in some widespread models of consumer behaviour. ИНСТИТУТ ЗА ИКОНОМИЧЕСКИ ИЗСЛЕДВАНИЯ БЪЛГАРСКА АКАДЕМИЯ НА НАУКИТЕ 2021, 73.
2.Cerceloiu, Mădălin Lucian, and Valentina Iuliana Diaconu. Consumer Attitude in the Context of Private Education Services. 5th International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2021 2021,2683-5991.
3.Vivek, K., Subbarao, K., Routray, W. et al. Application of Fuzzy Logic in Sensory Evaluation of Food Products: a Comprehensive Study. Food Bioprocess Technol 2020,13, 1-29
4.FAN Juhua. Evaluation of Online Shopping Consumer Satisfaction Based on Fuzzy Comprehensive Evaluation Method. Market Research 2017, 6, 31-32.
5.Han, S., Xu, P., Li, Y., Ji, S., Han, D., Yang, L. Energy efficiency evaluation of consumer based on fuzzy comprehensive evaluation method. In IOP Conference Series: Earth and Environmental Science 2021,784, 012006.
6.Li, W. Consumer Decision-Making Power Based on BP Neural Network and Fuzzy Mathematical Model. Wireless Communications and Mobile Computing 2021 2021, 1-9.
- In the abstract, you state that "To enhance consumers' purchase intentions, this study suggests that influencers should transparently disclose collaborations, provide investigative evaluations combined with social evidence and academic research to boost credibility." None of these seems to be reflected in your primary or secondary indicators in the model.
Response 5: Based on your advice, we have made modifications to the abstract and section 5.1, 'Influencers’ credibility & purchase intentions'. The revised content is as follows:
”This study suggests that influencers should transparently disclose their collaborations with brands, showcase the positive experiences of other users, and use relevant research and data to support their product recommendations in order to enhance their credibility.” (line27 - line30)
“Thus, establishing trust and transparency is key for influencers.Research indicates that consumers are more inclined to trust influencers who transparently disclose their collaborations with brands and provide objective evaluations[55]. Disclosing these collaborations helps to enhance consumer trust, thereby increasing their purchase intentions. ” (line481 - line485)
Others：
Regarding the language issues you mentioned, we have reviewed and indeed found some unclear expressions. We sought professional translation and editing services, and we believe the language has significantly improved. For example, we revised lines 82-83 to “Which influencer marketing factors influence consumer satisfaction with light food? ” and lines 104-105 to “This reflects an ongoing increase in budget allocation for influencer marketing in the future, further emphasizing its key role in modern brand strategies.”
Thanks again!
Sincerely,
Yiming Chen, Zhaoyue Qin, Yue Yan, and Yi Huang
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThe manuscript examines the effects of influencer creditility, professionalisam, and live-steam marketing satisfaction on consumer purchase intentions, revealing that consumers tend to relay more on influencers' objectives recommendations and professional insights rather then just direct interaction experiences when making purchase decisions.
In 2.3. Hypotheses name the passage Research hypotheses and do not have to have 2.3.1., 2.3.2, 2.3.3. You need to explain hypotheses better with more references from the last five years.
In passage 3. Research Design you do not need to explain Suzhou only Sample and Data Collection. Why did you chose this sample? The authors need to analyze descriptive statistics in Table 1.
The authors need to explain from the previous researches why did they decided to chose the fuzzy comprehensive evaluation model. Who use this model in the past?
In model construction the authors must explain why did they selected those 3 categories. They need to have arguments from the previous research.
The authors must write passage Research Methodology.
In Discussion and findings, the results should be compared with other results from influencer marketing context.
In Conclusion the authors should give an overview of theoretical and practical implications. Why are results important?
Comments on the Quality of English LanguageThe Manuscript needs proofreading.
Author Response
Dear Editor and Reviewer,
We feel great thanks for your professional review work on our manuscript. As you are concerned, there are several problems that need to be addressed.According to your nice suggestions, we have made extensive corrections to our previous draft, the detailed corrections are listed below.
1.In 2.3. Hypotheses name the passage Research hypotheses and do not have to have 2.3.1., 2.3.2, 2.3.3. You need to explain hypotheses better with more references from the last five years.
Response 1: We sincerely thank the reviewer for careful reading.As suggested by you, we have adjusted the numbering and added more references to explain the hypotheses. The revised content is as follows:
“2.3. Hypotheses
The credibility of influencers is a key factor affecting consumer purchase intentions[17,24,25,26]. Research indicates that influencers' credibility significantly influences consumers' attitudes, thereby affecting their purchase intentions. For instance, Nugroho et al. (2020) pointed out that influencers' credibility plays a crucial role in enhancing consumer trust and purchase decisions, especially on e-commerce platforms [27]. Martiningsih and Setyawan (2022) found that on the Shopee marketplace, influencers' attractiveness and expertise have a significantly positive impact on consumer purchase intentions [28]. However, there is limited research on the impact of influencers' credibility on the purchase intentions for light food products. Based on this research gap, this study proposes the following hypothesis:
H1: influencers’ credibility positively affects consumer purchase intentions of light food products.
The professionalism of influencers also affects consumer purchase intentions. Research indicates that influencers' understanding of a brand or product positively affects consumers' purchase decisions, and their rich professional knowledge has been confirmed as an important characteristic influencing purchase intentions [26,29,36]. In addition, Zaman et al. (2023) studied various characteristics of social media influencers and found that expertise has a significantly positive impact on consumer purchase intentions [30]. These findings collectively reveal the multifaceted impact of influencers' professionalism on consumer purchasing behavior, from individual characteristics to interactive effects, providing important academic insights for a deeper understanding of this field.However, there is limited research on the specific impact of professionalism on light food products. To fill this research gap, this study proposes the following hypothesis:
H2: influencers’ professionalism positively affects consumer purchase intentions of light food products.
Live streaming sales significantly impact consumers' willingness to purchase light food, a phenomenon that has been thoroughly studied in multiple aspects. Chen and Zhang (2023) found that live interactions significantly increase consumers' purchase intentions and reduce uncertainty during the purchasing process[19]. Weismueller et al. (2020) showed that advertising disclosure and source credibility on social media platforms have a significant impact on consumer purchase intentions [31]. Liu and Zhang (2024) found that consumers can interact in real time with influencers via live streaming platforms to learn about product use and purchase information, which enhances their purchase willingness[32]. In addition, Men and Zheng (2023) pointed out that the alternative learning experience obtained through live shopping reduces consumers' uncertainty regarding light food products, thereby strengthening their purchasing behavior[33]. However, it is necessary to explore its impact on the purchase intentions for light food products. Thus, this study proposes the following hypothesis:
H3: Live streaming sales positively affect consumer purchase intentions of light food products.”(line141 -line182）
The new references are as follows:
1.Nugroho, D. R., Linardi, J. K., Setyawati, A., & Firadus, M. I. The Effect of Influencer Credibility Towards Consumer Trust in E-Commerce and Purchase Intention of Low-Cost Carrier Ticket. Proceedings of the International Conference on Economics and Business Studies (ICOEBS 2020) 2022,3, 582-589.
2.Martiningsih, D. A., & Setyawan, A. A. The impact of influencers’credibility towards purchase intention. In International Conference on Economics and Business Studies (ICOEBS 2022) . Atlantis Press 2022,196-204.
3.Zaman, S. A. A., Anwar, A., & Haque, I. U. Examining the Mediating Effect of Online Engagement and Online Reviews: The Influence of Influencer Credibility on Consumer Purchase Intentions. Pakistan Business Review 2023,24,389-410.
4.Weismueller, J., Harrigan, P., Wang, S., & Soutar, G. Influencer Endorsements: How Advertising Disclosure and Source Credibility Affect Consumer Purchase Intention on Social Media. Australasian Marketing Journal 2020,28, 160-170.
2.In passage 3. Research Design you do not need to explain Suzhou only Sample and Data Collection. Why did you chose this sample? The authors need to analyze descriptive statistics in Table 1.
Response 2: According to your suggestions, we have removed the explanation of Suzhou and added the reasons for selecting the sample. The content is as follows:”Suzhou is an economically developed and diverse city that can provide a broadly representative sample. Additionally, the emerging light food industry has significant development potential in this city. Therefore, this study distributed questionnaires to residents of Suzhou, using the PPS random sampling method. By employing a three-stage unequal probability sampling approach, the scientific rigor and representativeness of the sample were ensured [34,35].
First, primary sampling units were randomly selected from the urban districts and county-level cities of Suzhou. Then, streets and towns were further sampled from these units. Finally, households within these streets and towns were chosen for the survey. Each stage of sampling was based on the Probability Proportional to Size (PPS) method, ensuring that the probability of selecting each sample unit was proportional to its size.To verify the representativeness of the sample, we conducted mean processing and statistical analysis of the sampling results at each stage, ensuring that the sample was consistent with the population in key demographic characteristics. Additionally, we compared the characteristics of the incomplete survey samples with those of the completed survey samples, confirming no significant differences between the two groups. This further enhanced the representativeness of our sample and the reliability of the survey results.”(line187 -line204)
We have added the following content regarding the descriptive statistics analysis of Table 1.:”In the formal survey, 859 questionnaires were distributed, of which 654 were effectively recovered, yielding a response rate of 76.14%.The summary of the study sample is shown in Table 1. It can be seen that the research subjects are mainly concentrated among female users (65.14%) and those aged 18 to 35 (78.9%), reflecting that most users of social media are young female consumers. This suggests that the development potential and innovation direction of influencer marketing need to be closely aligned with the lifestyle concepts and consumption trends of young female consumers. Continuous innovation and optimization of products and services are required to meet their pursuit of a high-quality life.The data shows that the residents from the Gusu District-Pingjiang Street area make up the highest proportion, possibly due to a higher concentration of influencers in the area, leading to more active users on social media platforms. This may reflect the influence of influencers in the region and the likelihood of residents participating more on social media platforms, further emphasizing the area's importance in online marketing and brand promotion. Moreover, most respondents (71.56%) prefer to spend no more than one hour on social media platforms, suggesting an emphasis on efficient information acquisition, which is a reason behind the rise of platforms like TikTok, which focus on short videos. This requires influencers to learn how to refine the core information in their content creation and dissemination strategies and to adopt more intuitive and engaging formats, such as short videos, combined images and text, interactive live streaming, etc., to enhance the efficiency of information dissemination and audience engagement[52].Furthermore, influencers should utilize data analytics tools to deeply understand the preferences and behavioral characteristics of their target audience to develop more personalized and targeted content strategies. This can attract and maintain consumer attention in a short time and enhance the effectiveness of marketing activities. ” (line205 -line229)
3.The authors need to explain from the previous researches why did they decided to chose the fuzzy comprehensive evaluation model. Who use this model in the past?
Response 3: Thank you for your valuable comments and suggestions on our paper. Based on your feedback, we have added the following content to the paper:
“3.2. Model selection
Using descriptive statistical methods to analyze consumer characteristics on trend-setting platforms as a preliminary exploration. In this study, we have identified the use of Consumer Attitude Theory. Given the complexity of the factors influencing consumer purchase intentions, such as influencers' professional insights, objective recommendations, and the layout style of live streaming sales, these factors often possess fuzziness and uncertainty, making them difficult to measure with simple numerical values. Therefore, it is essential to establish a quantitative model suitable for this theory to comprehensively consider these factors.
Consumer Attitude Theory plays an important role in explaining consumer behavior and decision-making processes. For example, Minchev (2021) summarized the formation and impact of consumer attitudes in purchase decisions, focusing on the internal and external factors influencing attitudes in classic behavioral models and demonstrating the importance of attitudes in consumer behavior and purchase decisions [37]. Cerceloiu et al.(2021) used the three components of cognition, affect, and behavior to analyze consumer attitudes towards private education services, revealing the critical role of attitudes in consumer decision-making[38]. These studies mainly employed statistical methods such as Structural Equation Modeling (SEM) or Regression Analysis to analyze the impact of consumer attitudes on purchase intentions.
The fuzzy comprehensive evaluation model can quantify and evaluate ambiguous and difficult-to-quantify factors, translating consumers' purchase intentions into specific numerical values[39][40]. This allows for a more comprehensive consideration of consumers' experiences and attitudes on recommendation platforms, and more accurately reflects the formation mechanism of consumer purchase intentions [41]. For instance, Han et al. (2021) used the fuzzy comprehensive evaluation method to assess consumer energy efficiency, demonstrating the effectiveness of this method in handling complex evaluation problems [42]. Li (2021) analyzed consumer decision-making power using a BP neural network and fuzzy comprehensive evaluation model. The study combined fuzzy reasoning and neural networks to predict consumer purchase intentions, showcasing the effectiveness of the fuzzy comprehensive evaluation method in addressing the uncertainty in consumer decision-making [43]. Consumer Attitude Theory involves multiple influencing factors, and the fuzzy comprehensive evaluation model can comprehensively evaluate the relative importance and overall effects of these factors. Additionally, compared to traditional statistical methods, the fuzzy comprehensive evaluation model offers greater flexibility and adaptability in handling nonlinear and complex systems, better reflecting the dynamic changes in consumer behavior.
In summary, although there is currently no literature explicitly using the fuzzy comprehensive evaluation model under the Consumer Attitude Theory, studies using these two methods separately have been widely applied and validated in related fields. Therefore, this study chooses to combine the Consumer Attitude Theory with the fuzzy comprehensive evaluation model to explore the impact of influencer marketing on consumers' purchase intentions. The Consumer Attitude Theory provides a theoretical framework for understanding consumer attitudes and behaviors, while the fuzzy comprehensive evaluation model offers a tool for handling multiple indicators and uncertain information. By combining these two methods, we can innovate both theoretically and methodologically, providing a more comprehensive analysis of consumer attitudes.Figure 2. shows the intersection of Consumer Attitude Theory and the Fuzzy Comprehensive Evaluation Model, highlighting the theoretical foundation of the research methodology.
Figure 2. Illustration of the Combination of Consumer Attitude Theory and Fuzzy Comprehensive Evaluation Model.”(line241 -line293)
The new references are as follows:
1.Minchev, A. An examination of attitudes in some widespread models of consumer behaviour. ИНСТИТУТ ЗА ИКОНОМИЧЕСКИ ИЗСЛЕДВАНИЯ БЪЛГАРСКА АКАДЕМИЯ НА НАУКИТЕ 2021, 73.
2.Cerceloiu, Mădălin Lucian, and Valentina Iuliana Diaconu. Consumer Attitude in the Context of Private Education Services. 5th International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2021 2021,2683-5991.
3.Vivek, K., Subbarao, K., Routray, W. et al. Application of Fuzzy Logic in Sensory Evaluation of Food Products: a Comprehensive Study. Food Bioprocess Technol 2020,13, 1-29
4.FAN Juhua. Evaluation of Online Shopping Consumer Satisfaction Based on Fuzzy Comprehensive Evaluation Method. Market Research 2017, 6, 31-32.
5.Han, S., Xu, P., Li, Y., Ji, S., Han, D., Yang, L. Energy efficiency evaluation of consumer based on fuzzy comprehensive evaluation method. In IOP Conference Series: Earth and Environmental Science 2021,784, 012006.
6.Li, W. Consumer Decision-Making Power Based on BP Neural Network and Fuzzy Mathematical Model. Wireless Communications and Mobile Computing 2021 2021, 1-9.
4.In model construction the authors must explain why did they selected those 3 categories. They need to have arguments from the previous research.
Response 4:Based on your suggestions, we have provided an explanation in section 3.4, 'Model construction'. The additional content is as follows:”Trust is a key factor in the consumer decision-making process. When consumers develop a sense of trust in influencers, they are more inclined to believe the information and recommendations provided by the influencers, thereby increasing their willingness to purchase the products recommended by them. This trust can stem from the influencers' sharing of genuine consumption experiences, objective evaluations, and high-quality content. Sokolova and Kefi (2019) found that there is a significant positive correlation between influencer credibility and consumers' purchase intentions [44]. Tiwari et al. (2024) also pointed out that influencers can enhance audience identification and purchase intentions through planning, entertaining presentations, and authentic experiences [45].
Xiang et al. (2016) found through their research that professionalism has a significant impact on quasi-social activities [46]. Kenny et al. (1990) pointed out that marketers, through deep insights and professional knowledge about the product, can greatly promote consumers' purchase intentions; the higher the professional quality, the more likely it is to enhance consumers' final purchasing behavior [47]. In the field of influencer marketing, the professionalism of influencers symbolizes capability and qualification. Consumers are more inclined to purchase products promoted by highly professional influencers. Kim et al. (2022) believe that the professionalism and interactivity displayed by influencers can establish a positive image, thereby significantly enhancing consumers' purchase intentions [48]. Additionally, Ashraf et al. (2023) found that interactions between influencers and consumers can also strengthen consumers' purchase intentions [26].
Live streaming sales, as a new shopping method, offer visibility and interactivity. Platforms also provide personalized recommendations based on individual preferences. The ecological environment of different live streaming rooms varies due to the host's attitude, behavior, and personal charm. These differences can affect consumers' shopping perceptions and purchase intentions [49,50].
Based on the above analysis and Consumer Attitude Theory, this paper selected 3 sections and 9 indicators for evaluation.These are grouped as follows: influencers’ credibility (u1), which includes influencers’ user experience (x1), influencers’ objective recommendations (x2), and influencers’ content presentation quality (x3); influencers’ professionalism (u2), encompassing influencers’ knowledge of product details (y1), influencers’ professional opinions (y2), and influencers’ interactive feedback (y3); and Satisfaction with live-stream marketing (u3), which consists of personalized promotion in the live-stream (z1), layout style of the live-stream (z2), and the atmosphere of the live-stream (z3). This framework establishes a fuzzy evaluation system as shown in Table 2:” (line294 - line341)
The new references are as follows:
1.Sokolova, K., Kefi, H. Instagram and YouTube bloggers promote it, why should I buy? How credibility and parasocial interaction influence purchase intentions. Journal of retailing and consumer services 2020,53, 101742.
2.Tiwari, A., Kumar, A., Kant, R., Jaiswal, D. Impact of fashion influencers on consumers' purchase intentions: theory of planned behaviour and mediation of attitude. Journal of Fashion Marketing and Management: An International Journal 2024, 28, 209-225.
3.Xiang, L., Zheng, X., Lee, M. K., Zhao, D. Exploring consumers’ impulse buying behavior on social commerce platform: The role of parasocial interaction. International journal of information management 2016, 36,333-347.
4.Kenny K Chan, Shekhar Misra. Characteristics of the opinion leader:a new dimension. Journal of Advertising 1990, 19,53-60
5.Kim, H. J., Chan-Olmsted, S. Influencer Marketing and Social Commerce: exploring the role of influencer communities in predicting usage intent. Journal of Interactive Advertising 2022,22, 249-268.
6.Zhu, P., Liu, Z., Li, X., Jiang, X., Zhu, M. X. The influences of livestreaming on online purchase intention: examining platform characteristics and consumer psychology. Industrial Management & Data Systems 2023, 123, 862-885.
7.Shang, Q., Ma, H., Wang, C., Gao, L. Effects of background fitting of e-commerce live streaming on consumers’purchase intentions: a cognitive-affective perspective. Psychology Research and Behavior Management 2023, 149-168.
5.The authors must write passage Research Methodology.
Response 5: We feel great thanks for your professional review work on our article. Based on your suggestions, we have added section 3.3, 'Research Methodology'.After adjusting the content, the text was added is ”This study employs the fuzzy comprehensive evaluation method to explore the impact of influencer marketing on consumers' willingness to purchase light food products. First, the evaluation factor set and evaluation grade set are determined. Then, the entropy weight method is used to calculate the weight values of each dimension. Next, a fuzzy comprehensive evaluation matrix is constructed, and a fuzzy comprehensive evaluation is conducted. Finally, through normalization, the normalized fuzzy comprehensive evaluation results are analyzed to determine the membership degree of the evaluated object in each evaluation grade, ultimately leading to the overall evaluation conclusion.” (line294 - line303)
6.In Discussion and findings, the results should be compared with other results from influencer marketing context.
Response 6:Based on your suggestions, we have made modifications to section 6, 'Discussion'. The revised content is as follows:”This paper systematically explores the impact of influencer marketing on consumer purchase intentions in the era of social media, with empirical analysis focusing on the light food market. Utilizing data from 654 consumers in Suzhou, a comprehensive evaluation system was established using Consumer Attitude Theory and a fuzzy comprehensive evaluation model, creating an integrated evaluation system covering influencer credibility, professionalism, and satisfaction with live-stream marketing. This study quantifies how these factors influence the consumer decision-making process, offering valuable insights into consumer attitudes and preferences towards influencer marketing.
The study examines the effects of influencer credibility, professionalism, and live-stream marketing satisfaction on consumer purchase intentions, revealing that consumers tend to rely more on influencers' objective recommendations and professional insights rather than just direct interaction experiences when making purchase decisions. These findings align with the research of Hu et al. (2020), who noted that consumer purchase intentions increasingly depend on the credibility and expertise of influencers[56]. This contrasts with the views of Miglė et al.(2023), who suggest that consumer purchase intentions are primarily influenced by the personal charm and interactive experiences of influencers[57].
Research has found that the credibility of influencers has a significant positive impact on consumer purchase intentions for light food products. This result is consistent with the study by Weismueller et al. (2020), which found that advertising disclosure and source credibility significantly affect consumer purchase intentions, especially on social media platforms [31]. Chetioui et al. (2020) studied the influence of fashion influencers on consumer brand attitudes and purchase intentions, finding that influencer trustworthiness and content quality significantly impact consumer purchase intentions [58]. These studies indicate that the influence of influencers' credibility is consistent across different product categories and markets.
We found that the professionalism of influencers positively affects consumers' willingness to purchase light food products. This is consistent with the findings of Hughes et al. (2019), who, through empirical research on social media influencers, discovered that bloggers' expertise and blog content significantly affect online brand engagement and purchase intentions [59]. Additionally, Belanche et al. (2021) studied the impact of influencer-consumer-product fit on purchase intentions, finding that high fit significantly enhances consumers' product attitudes and purchase intentions [60]. These findings collectively reveal the multifaceted impact of influencers' professionalism on consumer purchasing behavior.
Furthermore, this paper reveals that live streaming sales play a significant role in enhancing consumer purchase intentions, consistent with the views of Qin et al.[61]. Han et al. (2020) support this finding in their study of the impact of advertising disclosure on consumer purchase intentions, discovering that clear advertising disclosure reduces consumer purchase intentions, while subtle advertising disclosure is more effective [62]. Furthermore, Gomes et al. (2022) studied the impact of digital influencer marketing on consumer purchase intentions for fashion products, finding that content quality and pseudo-social interaction significantly influence purchase intentions [63]. These studies indicate that the effectiveness of live streaming sales is consistent across different product categories and markets. However, despite consumer satisfaction with personalized pushes and precise marketing in live streams, the ratings for layout style and atmosphere remain generally low. This supplements the findings of Jerry et al.(2023), who discovered that the dynamic features of live streams, atmospheric cues, and perceived interactivity significantly affect consumers' immersive experiences and social interactions, subsequently influencing purchase intentions[64]. ”(line555 - line605)
7.In Conclusion the authors should give an overview of theoretical and practical implications. Why are results important?
Response 7:Following your suggestions, we have added a new section titled “7. Implications and Limitations.” The additional content is as follows:
“7. Implications and Limitations
7.1. theoretical implications
This study makes significant theoretical contributions in several areas. Firstly, by combining Consumer Attitude Theory and the fuzzy comprehensive evaluation model, we systematically explored the impact of influencer marketing on consumer purchase intentions, filling a gap in previous research. Secondly, this study expanded the application of the fuzzy comprehensive evaluation model in consumer behavior analysis, demonstrating its effectiveness in addressing complex evaluation problems. Through empirical analysis of 654 consumers, the results showed that influencer trustworthiness, professionalism, and satisfaction with live-streaming sales have a significant positive effect on enhancing consumer purchase intentions. Lastly, the research revealed the comprehensive impact of multiple factors on consumer purchase intentions, providing practical guidance for brands in formulating digital marketing strategies. This study not only enriches the theories of consumer behavior and marketing but also offers new insights and methods for understanding the role of influencers in digital marketing.
7.2. practical implications
This study provides significant insights, offering specific strategic guidance for influencers and brands to enhance their competitiveness and influence in the market. For influencers, transparency and objectivity are key to enhancing trustworthiness. Influencers should maintain transparency during the marketing process and provide genuine usage experiences and objective evaluations. Additionally, influencers need to continuously improve their professional knowledge, thoroughly understand the products they recommend, and offer detailed product information and professional insights. This not only enhances the credibility and persuasiveness of their recommendations but also effectively meets consumers' demand for high-quality content, further increasing their market influence.
For brands, personalization and precise targeting play a crucial role in live-streaming sales. Utilizing big data analysis and personalized recommendation algorithms to provide precise product recommendations based on consumers' purchase history and behavior patterns can significantly enhance the personalization of the shopping experience[65,66]. Brands can fully leverage these technical means to deliver the right products to the right consumers at the right time, thereby increasing purchase conversion rates. Additionally, brands should focus on collaborating with influencers, selecting those who align with the brand image and product characteristics to promote their products, further enhancing brand awareness and reputation. These strategies not only help increase consumers' purchase intentions but also provide strong support for brands to win more loyal customers in a highly competitive market. By effectively combining the influence of influencers with the technological advantages of brands, both parties can achieve mutual benefits and occupy a more advantageous position in the market.
7.3.Limitations and Further Study
Although this study provides some meaningful conclusions, there are still some limitations.. First, the sample consists of residents from Suzhou city, which may present regional and sample biases, suggesting that future research could expand the sample size to verify the universality and robustness of the results. Second, this study lacks a deeper theoretical support and explanation of consumer purchase intentions. Hence, future studies will combine more empirical data and case analyses to further explore the underlying reasons and mechanisms of consumer behavior. Moreover, integrating theoretical and methodological contributions from other fields such as psychology, sociology, and communication studies could provide a deeper analysis of the cognitive and perceptual processes and the underlying psychological and social mechanisms in consumer behavior towards influencer marketing, thereby enhancing the depth and breadth of the research and offering theoretical support for more effective marketing strategies.” (line606 -line659)
Thanks again!
Sincerely,
Yiming Chen, Zhaoyue Qin, Yue Yan, and Yi Huang
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThank you for the revisions and your kindness in your responses to my concerns and suggestions.
