Emotional Resonance and Buying Behavior in Live Streaming: A Study on KOL Influence and the Mediation of Purchase Intentions

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The Abstract reports that KOL characteristics positively affect users’ “pleasure, arousal, and trust,” whereas traditional PAD theory is built on pleasure, arousal, and dominance. Later in the manuscript, the PAD section reiterates the classical dimensions.

The article innovatively integrates the SOR model with PAD theory. However, it is not entirely clear how each PAD dimension (pleasure, arousal, and trust/dominance) maps onto the “organism” component in the SOR framework. Consider providing a more detailed justification and diagram that explicitly illustrates the conceptual mapping between KOL characteristics, emotional responses, and resultant purchase behaviors.

The data collected are both real-time pop-up text mining and survey questionnaires. Although this mixed-method approach is promising, details on the survey design (e.g., sample size, sampling method, response rate, and the demographic characteristics of respondents) are sparse. More transparency in these data collection methods would enhance the study’s replicability and rigor.

Although not central to the current model, consider discussing potential moderating variables (e.g., demographic differences, prior experience with live streaming commerce) that might influence the observed relationships. This can pave the way for future research directions.

In the conclusion section, articulate potential limitations of the current approach and suggest areas for further investigation. Consider adding a paragraph that outlines potential ways for future research. This could include cross-cultural comparisons, longitudinal tracking of live-streaming behavior, or exploring other mediating/moderating variables that might affect consumer behavior in e-commerce.

A revised version should address minor formatting issues (such as inconsistent spacing and punctuation). Careful proofreading will help minimize distractions for the reader.

I was greatly interested and pleased in reading this first version of the article, and the authors may be thanked and encouraged.

I give this article a favorable opinion.

Comments on the Quality of English Language

Proofreading can improve the article.

Author Response

Thank you for your review. Please check the attachment for the authors' replies. 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript addresses live streaming e-commerce, a rapidly growing field highly relevant in today’s digital marketing environment, particularly with a focus on Key Opinion Leaders (KOLs) and emotional responses driving purchasing behavior. This topic holds substantial importance for both industry practitioners and academic researchers as it bridges new technology trends to consumer psychology.

Find below some improvement suggestions that authors should work on to improve the quality of their work:

The abstract [lines 8-26] does not follow a clear structure that guides the reader through the research process. I suggest organizing the abstract into distinct parts: research purpose, methodology, key findings, and implications. This clear segmentation would help readers easily identify the study’s contributions. The transition between methodology (data mining, LDA topic modelling) and results (effect on pleasure, arousal, trust) can be improved by adding transition words or brief connecting phrases that link methodology and outcomes seamlessly.

While the abstract details the findings, it does not emphasize the significance of these findings relative to previous work. So that an improvement would be to include a sentence highlighting how the results improve our understanding of live streaming e-commerce compared to past studies, or what gap they fill

The abstract should also briefly mention any limitations or future research directions. Even a small note such as “These results provide a foundation for further exploration in dynamically changing digital marketing environments” can make the abstract more robust and informative.

The abstract contains some repetition regarding the research aims, methods, and results. For example, multiple sentences rephrase how KOL characteristics influence purchase intentions. I suggest rewriting the abstract to clearly state one time the purpose, the methodology, and the key findings, avoiding redundant phrases. There are also lengthy sentences that could be shortened to enhance readability; breaking down long sentences into two or three shorter sentences would help clarify the main points, making the abstract easier to follow by readers of all backgrounds.

Some technical terminology such as “LDA topic modelling” and “grounded theory” are mentioned in the abstract. Authors should consider adding brief definitions or simplifying the language. For example, “LDA (a technique to extract topics from text)” could be used to make it more accessible. The reference to the SOR model and PAD emotion theory is clear, but terms like “impulse purchase intentions” versus “purposeful purchase intentions” could be briefly defined to avoid confusion.  A little explanation on how these are measured or differentiated would strengthen the abstract without overwhelming the reader.

The section 1. Introduction [lines 30-123] provides a lot of information about live shopping, user behaviours, and the role of KOLs, but it sometimes lacks a clear and concise structure. For example, the discussion of the rise of live shopping and associated issues (e.g., impulsive consumption and consumer disputes) blends into the explanation of theoretical perspectives like the PAD emotion theory and SOR model without definitive sub-sections. This can make it hard for a beginner reader to identify the main argument or the key themes. I suggest organizing the introduction into clear subsections or paragraphs. Consider using headings or sub-bullets such as "Background," "Problem Statement," "Theoretical Framework," and "Research Objectives" to ensure each concept is clearly demarcated. 

The section includes many statistics and references to various issues like the increase in consumer complaints and the nuances in subjective versus objective data collection. While these are important, they might overwhelm readers not already familiar with the subject. Authors are suggested to focus on summarizing only the most relevant details and statistics that directly support the main research questions. Use simpler language to stress the significance of each point. For instance, instead of detailed statistics on complaint increases, briefly mention that consumer dissatisfaction is rising due to impulsive buying behaviours.

Concepts such as PAD emotion theory and the SOR model are introduced in the introduction; however, the explanation might be too brief or too technical for readers without prior knowledge. Authors should introduce these theories with simple definitions and everyday examples. For instance, compare the SOR model to a simple cause-and-effect relationship in daily life (a stimulus like a catchy advertisement causes a person to feel excited, which then leads to buying a product). Similarly, explain the PAD theory as a way to understand how emotions (pleasure, arousal, and dominance) are felt by consumers during shopping.

While the introduction outlines multiple aspects like impulsive vs. purposeful buying and the role of KOLs, it does not clearly state the primary aim or what the study intends to contribute to the field. Authors should clearly list the research objectives and specify the study’s contributions in bullet form or a clearly marked statement. This approach helps ensure that readers grasp the specific research problems being addressed, as well as the importance of incorporating both user emotions and user behaviour in live streaming research. 

There are several technical terms (e.g., “PAD emotion theory,” “SOR model”) inserted in the text without accessible explanations. Authors should provide definitions or analogies in simple language immediately after introducing such terms. For example, you might mention, “The PAD emotion theory breaks down emotions into three parts: pleasure which means how happy you feel, arousal which is how excited you get, and dominance which is how in control you feel.” This can help make the content accessible to non-experts while preserving academic rigour.

The section 2. Literature Review [lines 125-247] appears scattered with diverse topics ranging from consumer behaviour in live streaming to KOL characteristics and theoretical frameworks like SOR and PAD. This makes it challenging for readers to follow the flow of ideas and identify how each piece of prior research connects to the study. I suggest dividing the literature review into clearly marked subsections such as “Consumer Behaviour in Live Streaming,” “Key Opinion Leaders (KOLs),” “Theoretical Frameworks (SOR and PAD),” etc. This will provide a roadmap for readers to easily understand the evolution and relevance of the researched topics.

Many studies or theories are mentioned individually without integrating them to build a comprehensive understanding of the research context. For example, the review touches on consumer dynamics in live streaming as well as KOLs’ influence but does not sufficiently discuss how these pieces interact or contradict one another. Authors should summarize the common themes, debates, or gaps in the literature rather than listing findings one after another. Use transition sentences to link studies and highlight how they support or challenge each other, thereby setting a foundation for the current study’s rationale.

The literature review sometimes uses domain-specific terminology (e.g., “pan-entertainment KOLs,” “information source characteristics”) without clear definitions. Authors should simplify explanations wherever possible and, when technical terms are necessary, provide short definitions or examples in everyday language. For instance, explain “pan-entertainment KOLs” as influential online personalities who engage with audiences in multiple domains, making the material accessible to beginners.

Certain parts of the review include extensive details (such as various studies’ findings on consumer attitudes and purchase behaviour) that may distract from the most relevant points.  Authors should focus on summarizing only the critical findings which directly support the research questions. Keep the review concise and ensure that each cited study is directly tied to the research’s overall narrative.

The literature review frequently reports what previous studies have found without critically evaluating their methodologies, limitations, or relevance to the current study. Authors should add a critical layer by discussing potential shortcomings or methodological gaps in earlier research. For example, highlight that while many studies have looked at KOL influence, few have integrated live pop-up text mining data to assess real-time consumer sentiment. This critical perspective not only provides balance but also reinforces the need for the current study.

The section 3. Research Design [lines 249-400] explains that live pop-up texts are collected and pre-processed by removing special characters, repetitive phrases, and short texts, but it does not clearly detail each step. For instance, the explanation mentions filtering based on text length and removing stop words without indicating why these choices were made or how they affect downstream analysis. I suggest breaking down each preprocessing step in more detail with simple examples. For instance, explain that removing emoticons and special symbols helps in getting cleaner data, which in turn improves the topic modelling process.

The description of using the Jieba segmentation tool and creating a stop words list may confuse readers who are not familiar with these techniques. Authors should simplify the explanation by briefly defining technical terms. For example, mention that “Jieba” is like a tool that helps split sentences into individual words, and stop words are common words that are removed because they do not add specific meaning.

The section outlines that web crawler technology, topic modelling through the LDA model, and a questionnaire survey are used but does not clearly explain how these different methods work together.  It might not be immediately obvious how the live pop-up data analysis relates to the questionnaire results and the overall research objective. Authors should present a simple flowchart or a structured step-by-step approach to explain how all these methods integrate into a single research design. For instance, mention that first, raw pop-up data is cleaned and processed, then the LDA model extracts topics which are later validated through a survey of users’ opinions.

While several tools (like LDA and SEM) are mentioned, the section does not clarify why these methods were selected over other potential techniques. Authors should add a brief explanation about why specific methods were chosen. For example, state that LDA was selected for its ability to reveal hidden themes in complex text data, which is useful for understanding user behaviour in live streaming, and that SEM (Structural Equation Modelling) is a powerful technique to verify the relationships between emotions and purchase intentions.

There is mention of distributing questionnaires and screening out responses with very short completion times, but details on how questions were designed or how participants were selected are missing. Authors should provide more context about the questionnaire design. Explain that the survey items were based on previous research scales and pre-tested on a small group to ensure clarity. Also, mention if the sample size was determined based on any statistical criteria and whether the target audience reflects the typical users of live streaming platforms.

The steps in the research design are described in a long continuous paragraph that may be hard to follow. I suggest authors using clearly separated bullet points or numbered lists for each step in the process to create a logical and accessible flow of the research design. This makes it easier for readers unfamiliar with research methods to understand each component and its purpose.

 

The section 4. Empirical Analysis [lines 401-624] reports reliability and validity using factor loadings, Cronbach’s alpha, CR, and AVE values, but does not explain these statistics in simple language or their importance. I suggest authors providing  a brief explanation of what each indicator means (e.g., Cronbach’s alpha indicates the consistency of the survey items) using simple everyday language so that even readers with no background in statistics can understand why these values matter. The empirical analysis should also explain why some factors (e.g., B1, D4) were removed, linking the decision to the thresholds in a straightforward manner.

The empirical analysis appears as a block of technical details (e.g., factor loadings, mediation paths) that might confuse readers. Authors should organize the presentation in a step-by-step manner. Use bullet lists or numbered steps to describe: How the model was built, which variables were tested and the significance levels (e.g., p-values) and what they imply about the hypotheses.

The mediation effects are described by mentioning various effect paths (e.g., DE1, IE1) without explaining what these symbols stand for or how they contribute to the overall model results. Authors should rewrite this part in simple language and add a brief explanation about mediation. For example, clarify that mediation means one variable explains how two other variables are connected, and list out the key mediation paths with an easy-to-follow summary.

The section briefly mentions that respondents with very short completion times were excluded, but it does not elaborate on how data quality was assured in the final analysis. I suggest adding more details on the criteria for data exclusion and provide a clearer picture of the sample size and characteristics. This will help the reader understand the robustness of the analysis.

The analysis section provides empirical outputs (e.g., supported hypotheses) but does not adequately connect these findings back to the theoretical framework. Authors should draw brief connections between the statistical outcomes and the underlying SOR and PAD theories. Indicate how the empirical results strengthen or challenge the theoretical assumptions, making the findings more relatable and easier to understand for someone without deep prior domain knowledge.

The current text combines several empirical elements (reliability tests, validity, mediation effects) into a single dense section. Authors should break the section into sub-sections with descriptive subheadings (e.g., “Reliability and Validity Tests”, “Mediation Analysis”, “Discussion of Empirical Findings”). This will improve the navigability and comprehension of the content, particularly for beginners.

The section 5. Discussion [lines 625-890] does not guide the reader through the findings in a clearly ordered manner. It is hard to follow the narrative from the initial results to broader implications and conclusions. Authors should organize the discussion in a step-by-step format. Begin with a brief restatement of key findings, then move to interpretation (explaining what these results mean in everyday language), and finally, discuss practical implications for KOLs and businesses. Clear subheadings or bullet points to separate these sections would greatly improve readability .

The discussion section does not fully explain how the empirical results relate to the theoretical predictions from the SOR and PAD models. Authors should expand the discussion by connecting the empirical findings to the core theories. For instance, explain in simple terms how the results support or contradict the expected influences of KOL characteristics on emotions and subsequent purchase behaviour. This will help readers, understand the underlying mechanisms presented in the study.

The discussion merely summarizes results without providing context on why these results are important or how they compare with previous studies. Authors should provide more background using everyday examples or analogies. For example, compare the role of KOLs to that of trusted experts in everyday decision making, helping readers visualize the connection between theory and findings. This will also help in understanding potential practical implications

The current discussion does not critically assess both strengths and limitations of the research. There is no exploration of possible reasons for discrepancies (e.g., why impulsive buying behaviour is fully mediated while purposeful buying shows partial mediation) or alternative interpretations of the data. Author should include a few bullet points discussing what might explain unexpected or less clear findings. For example, elaborate on how the unique environment of live streaming might influence emotions differently compared to traditional e-commerce, drawing simple comparisons that make the concept accessible

While some management or theoretical implications are touched upon in later sections, the discussion itself does not fully articulate what these findings mean for real-world applications or future research directions. Authors should add a section that briefly outlines practical takeaways for practitioners, such as how businesses might leverage these insights when planning live streaming sessions. Additionally, recommend areas for future research by mentioning limitations in data or methodology in a friendly and accessible manner

 When mentioning key concepts such as mediation effects or SOR models, authors should include a brief description in everyday language. This approach makes the section more accessible to readers who may not be familiar with these terms.

SECTION WITH CONCLUSIONS (NOT INCLUDED AS SUCH IN THE PAPER): There is no specific section on conclusions in this document. It is recommended to introduce a specific section to reflect the main conclusions reached. The conclusions should include: background/context of the research, research gaps, research question(s), methods, results and the study's limitation. Authors should devote attention to the implications of the paper. It might also have a specific call for action at the end.

Author Response

Thank you for your review. Please check the attachment for the authors' replies. 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

I appreciate your efforts in implementing the proposed revisions and enhancements. The manuscript has significantly elevated in terms of quality and reliability.