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Article

Beyond the Screen: How YouTube Influencers Shape Equity Investment Decisions

by
Lata Kumari Pandey
1,
Ranjit Singh
1,*,
H. Kent Baker
2 and
Habibur Rahman Laskar
3
1
Department of Management Studies, Indian Institute of Information Technology Allahabad, Prayagraj 211015, India
2
Department of Finance and Real Estate, Kogod School of Business, American University, Washington, DC 20016, USA
3
Department of Business Administration, Assam University, Silchar 788011, India
*
Author to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2025, 20(1), 15; https://doi.org/10.3390/jtaer20010015
Submission received: 12 November 2024 / Revised: 7 January 2025 / Accepted: 15 January 2025 / Published: 21 January 2025
Versions Notes

Abstract

:
This study examines how YouTube influencers can help shape equity decisions. We used a structured questionnaire with 26 questions to collect data using a purposive sample and the KMO and Bartlett tests to test the adequacy of the sample. Additionally, we used the Cronbach Alpha test to check the reliability of the questionnaire and principal component analysis to identify the factors related to YouTube influencers and their influence on equity investors. Our findings reveal a relationship between YouTube channel influencers and the financial decisions of equity investors. These factors influence credibility, influencer engagement, influencer trustworthiness, influencer investment fit, influencer’s YouTube channel promotion, and influencer-driven equity insights. This study could help investors make better decisions after learning pertinent information regarding equities. Investors can improve their investment strategies by identifying trustworthy and valuable influencer content by having a better understanding of these elements. This study provides novel insights into how digital content creators can shape equity investment decisions. However, a limitation of our study is that our findings do not show causality, only correlations between YouTube influencers and equity investments.

1. Introduction

Social media platforms such as YouTube can influence investment decisions. Investors may watch videos on social media to learn about investment options and gain insights from other investors. YouTube influencers, who are video content creators specializing in a particular domain, can affect investment decisions. They may do so by creating videos that promote specific investment products or services or by providing financial advice and guidance. It is found that investors are more likely to invest in equity after watching online videos on social media [1]. It was reported that social media can influence an individual’s attitude, social class, and decision-making process [2]. YouTube influencers can gain credibility from viewers by creating trustworthy content. This credibility can then be used to influence viewers’ investment decisions. It is found that watching YouTube channel videos can change and influence an audience’s intention and attitude toward investment and purchase decisions. This finding suggests that YouTube influencers can significantly affect investors’ decision-making processes [3]. Overall, social media platforms such as YouTube can influence investment decisions by providing investors with access to information and insights from other investors, as well as by allowing YouTube influencers to promote investment products and services or provide financial advice and guidance.
YouTube influencers have built large and engaged followings, and millions of people worldwide watch their videos. This exposure gives them considerable influence over their audiences, both in terms of the products and services they endorse and the ideas they promote [4]. YouTube is particularly popular among young people, and its influencers are often seen as trusted role models [5]. Consequently, they are a powerful force in shaping youth culture and values [6]. Furthermore, YouTube influencers can generate substantial revenue from their channels through advertising, sponsorships, and merchandise sales [7,8], making them an important part of the digital economy. They can be a force for good in society, promoting positive messages and causes, or a force for harm, spreading misinformation and promoting negative stereotypes [9]. Thus, YouTube influencers may especially affect the decisions of younger consumers and investors.
Equity investment requires a decision involving an investment’s quality. The YouTube influencer channel tries to provide real and accurate information, which is needed for investment decisions. YouTube influencers function as a source of information and can create videos that explain the basics of equity investing and more advanced concepts such as technical analysis and risk management [10,11]. They can also share their investment experiences and strategies. YouTube influencers can partner with companies to promote their equity offerings. This approach can be a particularly effective way to reach young investors, who are often more likely to invest in startups and private companies [12]. YouTube influencers can build relationships with their audiences over time, which can lead to a high level of trust and credibility [13,14,15]. Such relationships can be valuable for companies that are raising capital, as investors are more likely to invest in companies that they trust.
YouTube influencers can impact investment decisions, especially among young and inexperienced investors [16,17,18]. Measuring their influence is important to ensure that they are not misleading investors or promoting fraudulent investment opportunities. Moreover, companies that partner with YouTube influencers to promote their equity offerings need to measure this influence to assess the effectiveness of their marketing campaigns [19,20]. Companies can use this information to improve future campaigns and enhance their return on investment. YouTube content and videos act as financial advisers, which helps the investor decide on an equity investment [21].
Furthermore, policymakers need to understand the impact of YouTube influencers on equity investment to develop effective regulations and interventions to protect consumers and promote the public good [22,23]. Thus, a need exists to measure the influence level of equity investors from the YouTube Channel. After reviewing the relevant literature, we concluded that few studies examine the impact of YouTube influencers on the investment decisions of equity investors. This study attempts to fill this gap. We used equity investors who usually watch and follow YouTube channels related to equity investments and make their investment decisions on this basis. Therefore, our study aims to measure the influence level on equity investors from YouTube influencers and the factors responsible for it. We address two major research questions:
  • RQ1. What is the level of YouTube’s influence on equity investment decision-making by the equity investors who watch YouTube channels related to equity investment?
  • RQ2. What factors relate to equity investment decision-making by those who watch the YouTube channels related to equity investments?
The remainder of the paper has the following structure. Section 2 examines the relevant literature. Section 3 outlines the research methodology employed. Section 4 presents a comprehensive analysis of the findings. Section 5 discusses the study’s academic contributions, managerial and policy implications, and scope for future research. Finally, Section 6 concludes the paper.

2. Literature Review

Research finds that YouTube video advertising and influencer content can affect users’ purchase intentions, including investment decisions [4,24]. Non-professional analysts often provide stock-related videos on YouTube that investors may use to make investment decisions after careful analysis [25]. Additionally, YouTube channel influencers can influence viewers’ perceptions and attitudes toward financial products by providing videos and authentic information [26]. It is found that an awareness of security and its risks is important before investing to make wise decisions [27,28]. The study discovered that social media influencers help to arrive at a final decision of purchase and post-purchase evaluation [29]. Social media has influenced people to choose the appropriate social media payment platform for social media users [30]. It is noted that advertisements on social media influence consumer behavior toward mobile purchases [31]. Thus, social media can influence buying behavior [32].
Factors such as the composition of output, reactive outtake, proactive outtake, and the network play a key role in filtering data gathered from various social media influencers [33]. Factors related to the performance and outcome of SMEs are also decided through the different social media influence channels [34]. Financial literacy, human behavior, and social media influencer credibility help to determine the financial behavior of investors [35,36,37].
Researchers have identified four factors—content expertise, influence playfulness, satisfaction, and perceived quality of alternatives—as important in measuring the influence of YouTube channels on equity investors [6]. Generation Z is a popular target audience for YouTube channels, and financial content provided on YouTube videos can be effective in influencing their financial decisions [38]. These influencer channels upload videos related to the products and services they want to promote. Social media influencers have three dimensions: reach, relevance, and resonance, which can influence investor decisions and create awareness about financial products [39]. Brokers use YouTube influencer channels to promote equity investments by providing important video content to their followers [7,40]. YouTube video posts can significantly impact short-term financial product market prices [41]. YouTube video sentiment is a significant predictor of future price movements, and this information can be used to develop trading strategies. The stock market channels on YouTube influence investor purchase intentions and behavior [42]. According to social media user video links shared on social media platforms by other users are the most persuasive kind of recommendation, both personalized and non-personalized. This finding demonstrates the importance of social approval in influencing video trials [43]. YouTube provides a platform that has significantly shaped the digital landscape [11]. They developed and validated the first scale to measure the engagement of followers toward influencers on social media [44]. Social media experts help to filter the relevant data and provide details about the framework [45,46].
Influencer playfulness and perceived ease of use are the most important factors that influence the user’s decision to adopt mobile value services and virtual reality [47,48]. Authentic information available on social media leads to user satisfaction, as highlighted by [49,50]. Social media usage influences consumer satisfaction in the stages of information search, alternative evaluation, and post-purchase decisions [29].
YouTube has emerged as a powerful platform for influencing investment decisions, especially in equity investment. However, little research is available in this area. Our exploratory study examines the relationship between YouTube influencers and the equity investment decisions of investors in Uttar Pradesh, India. This study’s novelty lies in the fact that it is the first to examine this relationship. Unlike prior research primarily focused on consumer goods, we investigate how these digital influencers relate to financial choices. Second, by analyzing factors involving this relationship, we provide novel insights into the mechanisms through which YouTube influencers may shape equity investment behavior. This research offers valuable guidance for investors to evaluate influencer content and make more informed investment decisions. Third, this is the first study to examine the relationship of YouTube channels on equity investment decisions in the state of Uttar Pradesh, India.

3. Research Methodology

This study is both descriptive and empirical. Our study investigates the relationship between YouTube channel influencers and equity investment decisions in Uttar Pradesh, India. We used multi-stage random sampling to collect the data. Multistage sampling is the most suitable sampling design for large, geographically dispersed populations because it is cost- and time-effective [51]. Moreover, equity investment across all the states of India is similar, which justifies using multi-stage random sampling because it provides more information about the subject matter [52,53]. The findings of multistage sampling can be representative of the entire population if probability sampling is used at each stage, the sample size is adequate, and the process is unbiased [37,54]. Our sampling methodology meets these conditions. We randomly chose one state (i.e., Uttar Pradesh) out of 28 states in India. Uttar Pradesh is geographically located in the Northern part of India. It is the most populated as well as populous country subdivision in the world. The large numbers of ethnic and linguistic groups, the population composition, and the people process in the state have led to it being called India in miniature.
Uttar Pradesh is the most populated state in India, with a substantial percentage of youth [55]. India had 467.0 million social media users as of January 2023, constituting 32.8% of the total population [56]. Uttar Pradesh is one of India’s largest states in both population and geographical size. With a population exceeding 240 million in 2024, Uttar Pradesh holds the distinction of being the world’s most populous sub-national entity. According to the National Family Health Survey-5, among internet users in Uttar Pradesh, 70% utilize it for social media purposes, and 71% prefer digital payments for online transactions. These youngsters are actively engaged in social media, such as YouTube, the most popular social media outlet, Instagram, and Snapchat [57].
All those investors who watch any YouTube channel related to equity investment in the state of Uttar Pradesh, India, constitute our study’s population. From the state of Uttar Pradesh’s 75 districts, we randomly chose one district, namely Prayagraj. This district has 21,223 equity investors, as per the information received from all the stock trading terminals. A pilot study of 200 investors revealed that only four regularly used YouTube channels for investment decisions. This result makes the incidence rate to be around 2% [58]. Thus, for a population of 21,223 equity investors, we estimated that approximately 425 individuals use YouTube channels to make their investment decisions. The respondent watching YouTube channels relating to equity investment was the sampling unit. Other studies also used a sample size ranging from 100 to 200 individuals to examine the influence of e-WOM on social media usage [59]. We conducted a comprehensive search to identify the maximum possible number of individuals who use YouTube channels for equity investment decisions. As a result of this effort, we identified 156 individuals. We received 112 responses, but excluded seven incomplete responses, resulting in a final sample of 105 respondents. This number represents about 25% of the estimated population of 425 YouTube-using investors, which we consider a reasonable sample size for our analysis. We used follow-up surveys and reminders to increase the sample size and reduce potential non-response bias [60]. We have a sufficient sample size to assess the influence of YouTube channels on equity investments with 105 responses. We confirmed the adequacy of our sample using the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s Test of Sphericity [61].
We developed a 26-item questionnaire to measure the influence level of equity investors from YouTube channels. A copy of the questionnaire appears in Appendix A. The questionnaire is reliable, given a Cronbach’s Alpha of 0.929, indicating good internal consistency [62]. We asked the respondents to answer the 26 questions on a five-point Likert scale, with 1 indicating strongly disagree and 5 indicating strongly agree. We reverse-coded some items in the scale, such as “The influencer’s YouTube channel is commercial”, “The influencer is an expert on the topic”, and “The congruency between the influencer’s YouTube channel and equity investment is high” to ensure the accuracy of the responses.
We used the Statistical Package for Social Science (SPSS 29—2022, Sept.) to conduct factor analysis to reduce and summarize the data. Factor analysis is a statistical method used to identify a small number of factors that represent a relationship among a set of interrelated variables. It is concerned with reducing and summarizing observed variables in terms of the common underlying dimension or factors [63]. We used varimax rotation in this study. Other studies have also used factor analysis in similar situations [64,65]. We also used descriptive statistics to analyze our data.

4. Data Analysis and Findings

Below are our study’s data analysis and findings.

4.1. YouTube’s Level of Influence on Equity Investors

Table 1 shows the item statistics for the 26 items used to measure the effect of YouTube influencers on equity investment. Appendix A provides details of these items. Overall, the mean scores for all 26 items are above 3, suggesting that viewers generally have a positive view of the influencer’s YouTube channel and are receptive to the influencer’s suggestions about equity investment. The items with the highest mean scores are “Contains advertising on the influencer’s YouTube channel” (3.6923), “The influencer’s YouTube channel is advertising” (3.4176), and “Recommend the influencer’s YouTube channel to other people” (3.3626). These results suggest that viewers value the influencer’s experience, expertise, and trustworthiness. The items with the lowest mean scores are “I rely on an influencer’s recommendation about equity investment” (3.0220), “The influencer’s YouTube channel has a good match with the equity investment” (2.9890), and “I feel comfortable in making an equity investment suggested by the channel’s influencer” (2.9231). These responses suggest that viewers are sensitive to the commercial aspects of an influencer’s YouTube channel. Overall, the item statistics suggest that YouTube influencers can positively affect viewers’ attitudes and intentions toward equity investments. However, influencers should be transparent about their commercial relationships and avoid making false or misleading claims.
As previously noted, we used a 26-item, 5-point Likert scale to measure how YouTube influencers affect equity investors. The maximum possible score was 130 (26 items × 5 points), and the minimum possible score was 26 (26 items × 1 point). To create five influence levels, we divided the range of possible scores (104 points) by 5, resulting in a step size of 20.8 points. We then added 20.8 points to the lowest possible score (26 points) to obtain the score range for the “very low” influence level (26.0 < 46.8 points). We repeated this process to create the score ranges for the other four influence levels: low (46.8 < 67.6 points), moderate (67.6 < 88.4 points), high (88.4 < 109.2 points), and very high (109.2−130 points). Other studies have used a similar methodology [66,67]. Table 2 shows the interpretation of each influence level score.
We calculated the overall influence of the respondents by adding their Likert scale scores. We then used Table 2 to interpret the overall influence level of YouTube channel videos. Table 3 shows the overall influence level of YouTube channel videos by frequency. The mean value of the scale statistics in Table 3 is 83.03, which falls within the class interval of 67.6 < 88.4. This finding indicates a moderate overall association between YouTube channel influencers and equity investors in Uttar Pradesh.

4.2. Factor Analysis

To perform factor analysis, we first tested the adequacy of the sample using the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test. The KMO test measures the data’s internal consistency, while Bartlett’s test tests for the presence of significant correlations between the variables. If both tests are significant, it suggests that the data are suitable for factor analysis, and the variables can be summarized with a few factors. Both tests aim to ensure that factor analysis can be performed efficiently with the original variables. It is recommended that the KMO measure of sampling adequacy should be greater than 0.5 for satisfactory factor analysis [61]. The KMO value in this study is 0.853, indicating that the sample size is adequate for factor analysis.
Table 4 shows that the p-value for Bartlett’s test of sphericity is 0, which is less than the significance level of 0.05. This finding indicates that the data are suitable for factor analysis, given a significant correlation between the variables. We used eigenvalues to identify the number of factors and measure the variance in all the variables that are explained by each factor. Factors with eigenvalues less than 1 contribute little to explaining the variation in the data and can be ignored as redundant with more important factors.
Table 5 shows that six factors have eigenvalues greater than 1. These six factors explain 68.196% of the total variability, indicating that they are the most important factors in the data. Although the identified factors explaining over 62% of variability, our factor analysis demonstrates a stronger model, accounting for more than 68% of the observed variance [64,68]. Therefore, there are six components for principal component analysis (PCA).
We used PCA to find which variables most strongly correlate with each component (i.e., to identify the numbers that are large in magnitude). This process helps identify the low correlation variables with the component. Table 6 shows the rotated component matrix, where larger correlations are in boldface. Appendix B, Appendix C, Appendix D, Appendix E and Appendix F show the inter-item correlation matrices for each factor’s item. Cronbach’s Alpha for Factors 1–5 is 0.840, 0.864, 0.863, 0.766, and 0.712, respectively. For Factor 6, which consists of a single item, Cronbach’s Alpha could not be computed. Influencer-driven equity investment is Factor 6, which is reasonably explained with one item. Values exceeding 0.70 for Cronbach’s Alpha generally indicate acceptable internal consistency (reliability), suggesting that the items effectively measure the underlying latent constructs.

5. Discussion

RQ1 intends to quantify the extent of YouTube channel influence on equity investors. The findings presented in Table 2 and Table 3 indicate that YouTube channels have a moderate association with equity investors’ decisions. This finding aligns with [22,69]. In line with this view, it is asserted that social media channels exert a notable influence on online investors and traders [70]. The majority of users obtain investment information and news about equity crowdfunding on different social media [71,72]. Thus, social media plays an important role when making decisions about equity investment. It emphasized that social media also influences the investment decisions and preferences of retail investors [73]. It is highlighted that social media influencer help to determine investor’s decisions toward investment [74].
RQ2 seeks to identify the factors responsible for influencing equity investors. Table 5 and Table 6 reveal six factors: (1) Influencer Credibility, (2) Influencer Engagement, (3) Influencer Trustworthiness, (4) Influencer Investment Fit, (5) Influencer’s YouTube Channel Promotion, and (6) Influencer-Driven Equity Insights. Items with similar factor loadings were grouped with the factors where their loading was highest. This grouping was further supported by the conceptual alignment of each item with the corresponding factor. Additionally, we calculated the Cronbach’s Alpha value for each factor. Including items with similar factor loading maintained reliability above the threshold limit, indicating that we appropriately classified the factors [75].
  • Influencer Credibility refers to an influencer’s ability to affect viewer behavior and perceptions and create a strong emotional bond. Piñeiro-Chousa et al. It is important to note that investor profile analysis is important for assessing the quality of influence in the stock market [76]. The content expertise is a key factor that helps in establishing influencer credibility [6].
  • Influencer Engagement refers to the set of emotions, beliefs, and experiences that the audience acquires about a particular object, person, thing, or event. Evidence shows that watching videos, posts, and updates on social media can change consumer or audience attitudes toward financial services [77]. Social media influencers can engage the users to have a positive effect on consumer attitudes, directly influencing purchase and investment intentions. It discovers that entertainment features can engage users and have a strong impact on consumer attitudes toward any social media brand [78]. Our findings are aligning and similar [26]. It was found that social media engagement is a driving factor in influencing the impact of influencers [6].
  • Influencer Trustworthiness refers to the depth and accuracy of the information and insights contained in a piece of content. Some factors like promotional content, peer effects between contributors, biases of contributors, and self-selection influence the quality of user-generated content on social media and consequently influence the trustworthiness of the influencers [79]. The importance of influencers’ credibility was also emphasized by [35].
  • Influencer Investment Fit refers to information that gives investors a detailed understanding of equity. It is noted that security analyst reports released on the YouTube channel are associated with market returns, suggesting that they help to set stock market prices [80]. Social media experts help to filter the relevant data and provide details about the framework [45,46].
  • Influencer’s YouTube Channel Promotion refers to the activities that help the channel earn a profit now and in the future. The study revealed that some influencers try to change public behavior or influence public opinion [81]. It was reported that organizations collaborate with influencers during content production, often leading to commercial partnerships [82]. The similar findings were reported by [6,30].
  • Influencer-Driven Equity Insights refer to essential advice for investors who are planning to invest in equity. The study identified two moderators − risk propensity and stockholders’ opinions—that can create a gap between the behavior and intentions of retail investors [83]. They also identify financial and non-financial factors influencing equity investment intention and measure its impact on equity investment behavior. Investors may find that making informed decisions is difficult due to the manipulation of social media content and their inability to distinguish between genuine and sponsored market advice [22]. The findings regarding the importance of content expertise align with the concept of influencer-driven equity insight [6].

5.1. Academic Contributions

Our study makes several contributions regarding how YouTube influencers are associated with equity investment decisions. First, we develop a scale to measure the influence of YouTube influencers on equity investors. Second, we identify six factors related to the YouTube channel that influence equity investors: (1) Influencer Credibility, (2) Influencer Engagement, (3) Influencer Trustworthiness, (4) Influencer Investment Fit, (5) Influencer’s YouTube Channel Promotion, and (6) Influencer-Driven Equity Insights. This granular analysis provides a deeper understanding of the mechanisms through which YouTube influencers impact investment behavior. The study expands upon existing research by focusing specifically on YouTube as a platform for influencer-driven equity investment decisions. Identifying specific factors that contribute to influencer influence within the context of equity investment and linking these factors to the existing literature on social media influence, consumer behavior, and financial decision-making. This study attempts to integrate social media content with behavioral finance. Integrating these contributions advances academic discourse and provides actionable insights for equity investors and YouTube channel influencers.

5.2. Managerial Implications

To promote equity investment, stock brokerage firms can use YouTube channel influencers to create high-quality, informative videos that appeal to different investors. These videos can educate investors about equity investments and help them make informed decisions [28,84]. Attractive YouTube videos can influence or even manipulate investors’ behavior and decisions [42]. Firms should tailor their content to different types of investors. For example, firms should create different videos for novice and experienced investors, and those with specific investment goals. The firm’s manager should partner with trusted influencers. Finally, managers should promote their videos using social media and their firm’s website. They can use targeted ads to reach specific audiences.

5.3. Policy Implications

Based on our findings, we suggest that the government use YouTube channel influencers to promote equity investments. Policy-making agencies should create a program to recruit and train expert analysts to provide useful information about equity investments on YouTube channels. The government should collaborate with YouTube channels to promote responsible content creation, and their implementation should align with credible financial content, which protects from speculative or misleading material. Financial influencers on different social media platforms should be certified. This step would help to raise awareness among potential investors and build trust in the government’s commitment to promoting equity investments. Efforts should be made to educate people about equity investments by providing them with training to handle or manage high-risk scenarios [84]. Once they are trained to handle and manage the high-risk scenario, the government can promote an equity investment culture more easily and these individuals will act as entrepreneurship–culture initiators and adaptors [85]. Cultivating an equity investment culture among the public can thus promote entrepreneurship [86].
Policymakers should also consider providing financial support to YouTube channel influencers who create high-quality content about equity investments while monitoring and penalizing misleading content. Such support would help to ensure that investors have access to reliable information and motivate influencers to continue creating authentic content about equity. Regulations are needed to ensure that YouTube channel influencers disclose any conflicts of interest and that their content is accurate and unbiased. Such regulation would help to protect investors from fraud and scams, benefiting both the government and investors.

5.4. Limitations and Potential Enhancements

Despite our study’s contributions, it has limitations. Because this study is exploratory, we cannot generalize our findings to the entire population of equity investors in India due to the small sample size or to other equity investors. A larger sample size would allow for more generalizable conclusions and a better understanding of the factors influencing equity investors. Furthermore, the small sample size increases the likelihood of biased responses, necessitating a larger and more diverse sample. The study’s focus on Uttar Pradesh, India, limits the understanding of how YouTube channel influence may vary across different regions in the country. Expanding the study to include a wider range of geographical locations would provide insights into regional variations in YouTube channel influence.
Another limitation is that we did not examine the influence of YouTube channels on equity investors based on demographic factors like gender, age, occupation, education, and investment experience. Gathering and analyzing such factors could reveal important insights, including patterns and differences [87].
Third, we conducted our study during a limited timeframe. A longitudinal study would track the influence of YouTube channels over time, providing valuable insights into the evolution of YouTube influencers regarding equity investments.
Fourth, we used only primary data obtained from a questionnaire. Qualitative research methods, such as interviews and focus groups, could provide a deeper understanding of the motivations and decision-making processes of equity investors who are influenced by YouTube channels [88].
Fifth, our study explains only 69.196% of the cumulative explained variance. Thus, some of the variance remains unexplained. Adding more items could help improve the generalizability of our findings by increasing the percentage of explained variance.
A sixth extension of our study would be to investigate how YouTube spreads financial literacy and inclusion by considering the factors identified by [89]. Various variables are associated with YouTube’s influence on equity investment and not all of these variables are equally important. The relationship between the parameters and Social Network Analysis can be used to determine this association as previously carried out by [90,91,92,93]. Moreover, discriminant analysis can be used to predict user behavior, as performed by [94].
Finally, our study does not employ causal inference methods. Factor analysis and descriptive statistics only reveal correlations, not causation. Future research on this topic can use tools other than factor analysis, such as regression analysis, structural equation modeling, and AI-driven tools, to analyze a causal relationship between YouTube’s influencers and their “effect” on equity investors. The comments on the YouTube channel can also be studied using sentiment analysis and topic modeling [95].

6. Conclusions

Investors are increasingly using social media platforms to make equity investment decisions. This exploratory study had two aims: (1) to measure the influence level of equity investors from YouTube influencers (RQ1) and (2) to identify the factors associated with this influence (RQ2). Regarding our first objective, we conclude that YouTube influencers have a moderate association with the equity investments of our sample investors. Regarding our second objective, we identify six factors relating to this association: (1) the influencer’s credibility, (2) the influencer’s engagement, (3) the influencer’s trustworthiness, (4) the influencer’s investment fit, (5) the influencer’s YouTube channel promotion, and (6) influencer-driven equity insight. These variables explain 68.196% of the total variation from the collected data, so other factors still need to be identified.
Although YouTube influencers can provide valuable information and insights, investors must remain vigilant against potential bias and manipulation. As one of the most visited platforms on the web, YouTube is a breeding ground for influencers who leverage their audience to promote their interests. All the identified factors significantly influence equity investors’ decisions. However, these factors could vary depending on the individual investor’s risk tolerance, investment objectives, and other personal considerations.

Author Contributions

Conceptualization, L.K.P. and R.S.; methodology, R.S.; software, R.S.; validation, L.K.P., R.S. and H.K.B.; formal analysis, L.K.P. and H.R.L.; investigation, R.S.; resources, H.K.B.; data curation, L.K.P., R.S. and H.K.B.; writing—original draft preparation, L.K.P. and R.S.; writing—review and editing, L.K.P., R.S., H.K.B. and H.R.L.; visualization, L.K.P. and H.R.L.; supervision, R.S. and H.K.B.; project administration, R.S.; funding acquisition, L.K.P. and H.R.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available within in the article.

Acknowledgments

The first author thanks the Ministry of Education, Government of India, for providing financial assistance (fellowship) during her Ph.D.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. List of Items in Questionnaire.
Table A1. List of Items in Questionnaire.
Variable NumberItem Statistics Citation
Variable 1The influencer’s YouTube channel matches the equity investment well.[37,92]
Variable 2The compatibility between the influencer’s YouTube channel and equity investment is high.[96]
Variable 3The alignment between the influencer’s YouTube channel and equity investment is high.[26]
Variable 4The congruency between the influencer’s YouTube channel and equity investment is high.[26]
Variable 5The influencer’s YouTube channel is commercial.[26]
Variable 6The influencer’s YouTube channel contains advertising.[7]
Variable 7The influencer’s YouTube channel is advertising.[26,40]
Variable 8The influencer’s YouTube videos are trustworthy.[97]
Variable 9The influencer is honest.[98,97]
Variable 10The influencer is an expert on the topic[99]
Variable 11The influencer’s experience is sufficient for equity investments[27]
Variable 12YouTube videos are likable by the target audience.[30,99]
Variable 13The influencer’s YouTube videos are pleasant.[7]
Variable 14An influencer’s YouTube videos are interesting.[100]
Variable 15I have a favorable opinion of the influencer.[101,102]
Variable 16I intend to follow an influencer’s YouTube channel in the near future.[103]
Variable 17I continue to follow an influencer’s YouTube channel.[104]
Variable 18I look for new content published on the influencer’s YouTube channel.[105]
Variable 19I feel comfortable making an equity investment suggested by the channel’s influencer.[106]
Variable 20I do not hesitate to consider the influencer’s suggestions on equity investments.[26,107]
Variable 21I feel secure in following an influencer’s suggestions about an equity investment.[26,108]
Variable 22I rely on the influencer’s recommendations about equity investments.[109]
Variable 23I recommend the influencer’s YouTube channel to others.[7]
Variable 24I provide positive comments about the influencer’s YouTube channel to others.[110,111]
Variable 25I recommend the influencer’s YouTube channel to friends and relatives interested in equity investments.[26]
Variable 26I seldom miss an opportunity to tell others interested in equity investment about the influencer’s YouTube channel.[99,112]

Appendix B

Table A2. Inter-Item Correlation Matrix for Factor 1.
Table A2. Inter-Item Correlation Matrix for Factor 1.
VAR00004VAR00010VAR00011VAR00012VAR00013VAR00009
VAR000041.0000.3790.3100.4560.2940.299
VAR000100.3791.0000.6960.6380.4690.470
VAR000110.3100.6961.0000.6330.4340.052
VAR000120.4560.6380.6331.0000.5900.351
VAR000130.2940.4690.4340.5901.0000.372
VAR000090.2990.4700.5240.3510.3721.000

Appendix C

Table A3. Inter-Item Correlation Matrix for Factor 2.
Table A3. Inter-Item Correlation Matrix for Factor 2.
VAR00024VAR00025VAR00026VAR00023VAR00021VAR00022
VAR000241.0000.5800.5470.5820.4570.374
VAR000250.5801.0000.6650.6020.4640.519
VAR000260.5470.6651.0000.5540.4070.496
VAR000230.5820.6020.5541.0000.4470.521
VAR000210.4570.4640.4070.4471.0000.496
VAR000220.3740.5190.4960.5210.4961.000

Appendix D

Table A4. Inter-Item Correlation Matrix for Factor 3.
Table A4. Inter-Item Correlation Matrix for Factor 3.
VAR00008VAR00018VAR00017VAR00019VAR00003VAR00014VAR00015
VAR000081.0000.4010.5920.4810.5020.4850.543
VAR000180.4011.0000.5820.4140.3780.5060.476
VAR000170.5920.5821.0000.5070.5220.4650.548
VAR000190.4810.4140.5071.0000.4010.4090.356
VAR000030.5020.3780.5220.4011.0000.3610.432
VAR000140.4850.5060.4650.4090.3611.0000.589
VAR000150.5430.4760.5480.3560.4320.5891.000

Appendix E

Table A5. Inter-Item Correlation Matrix for Factor 4.
Table A5. Inter-Item Correlation Matrix for Factor 4.
VAR00002VAR00001VAR00004
VAR000021.0000.6730.429
VAR000010.6731.0000.463
VAR000040.4290.4631.000

Appendix F

Table A6. Inter-Item Correlation Matrix for Factor 5.
Table A6. Inter-Item Correlation Matrix for Factor 5.
VAR00006VAR00007VAR00005
VAR000061.0000.5810.274
VAR000070.5811.0000.362
VAR000050.2740.3621.000

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Table 1. Items Statistics. This table shows the item statistics for the 26 items used to measure the effect of YouTube influencers on equity investment.
Table 1. Items Statistics. This table shows the item statistics for the 26 items used to measure the effect of YouTube influencers on equity investment.
Item StatisticsMeanSD
The influencer’s YouTube channel contains advertising.3.69231.13228
The influencer’s YouTube channel is advertising.3.41761.18383
I recommend the influencer’s YouTube channel to others.3.36261.03834
I provide positive comments about the influencer’s YouTube channel to others.3.34070.99129
The influencer’s experience is sufficient regarding equity investments.3.29671.14012
The influencer’s YouTube videos are pleasant.3.28571.10841
YouTube videos are likable by the target audience.3.28571.08818
The influencer is an expert on the topic.3.27471.14568
The influencer’s YouTube channel is commercial.3.26371.16271
An influencer’s YouTube videos are interesting.3.25271.16040
I intend to follow an influencer’s YouTube channel in the near future.3.25271.01755
I continue to follow an influencer’s YouTube channel.3.21981.00887
I look for new content published on the influencer’s YouTube channel.3.19781.00244
I recommend the influencer’s YouTube channel to friends and relatives interested in equity investments.3.15381.06378
I seldom miss an opportunity to tell others interested in equity investment about the influencer’s YouTube channel.3.14291.02817
The influencer is honest.3.10990.88758
The influencer’s YouTube videos are trustworthy.3.09891.05467
I have a favorable opinion of the influencer.3.09891.00061
The compatibility between the influencer’s YouTube channel and equity investment is high.3.08790.95042
The congruency between the influencer’s YouTube channel and equity investment is high.3.08790.95042
I feel secure in following an influencer’s suggestions about an equity investment.3.07691.05652
I do not hesitate to consider the influencer’s suggestions on equity investments.3.06591.12351
The alignment between the influencer’s YouTube channel and equity investment is high.3.03300.98263
I rely on the influencer’s recommendations about equity investments.3.02200.97728
The influencer’s YouTube channel matches the equity investment well.2.98901.12046
I feel comfortable making an equity investment suggested by the channel’s influencer.2.92310.93370
Source: compiled from the questionnaire.
Table 2. Interpretation of Influence Level Scores. This table shows the interpretation of each influence level score. It provides a range-based interpretation of the table’s factor loadings.
Table 2. Interpretation of Influence Level Scores. This table shows the interpretation of each influence level score. It provides a range-based interpretation of the table’s factor loadings.
RangeInterpretation
26 < 46.8Very low influence
46.8 < 67.6Low influence
67.6 < 88.4Moderate influence
88.4 < 109.2High influence
109.2–130.0Very high influence
Source: compiled by the authors.
Table 3. The Overall Influence Level. This table shows the overall influence level of YouTube channel videos by frequency. The mean value of the scale statistics in Table 3 is 83.03, which falls within the class interval of 67.6 < 88.4.
Table 3. The Overall Influence Level. This table shows the overall influence level of YouTube channel videos by frequency. The mean value of the scale statistics in Table 3 is 83.03, which falls within the class interval of 67.6 < 88.4.
Level of InfluenceFrequencyPercent
Very low influence 10.95
Low influence1615.23
Moderate influence4441.90
High influence4038.09
Very high influence43.80
Overall mean83.03
Standard deviation27.31
Source: compiled from the questionnaire.
Table 4. The Kaiser–Meyer–Olkin (KMO) and Bartlett’s Test. This table shows that the p-value for Bartlett’s test of sphericity is 0, which is less than the significance level of 0.05, and tested the Kaiser–Meyer–Olkin (KMO) to measure sample adequacy for factor analysis.
Table 4. The Kaiser–Meyer–Olkin (KMO) and Bartlett’s Test. This table shows that the p-value for Bartlett’s test of sphericity is 0, which is less than the significance level of 0.05, and tested the Kaiser–Meyer–Olkin (KMO) to measure sample adequacy for factor analysis.
Kaiser–Meyer–Olkin Measure of Sampling Adequacy0.853
Bartlett’s Test of SphericityApproximate Chi-square1398.005
Degrees of freedom325
Significance0
Source: compiled from the questionnaire.
Table 5. Total Variance Explained. The variance ratio is the percentage of the variance attributed to each selected component. This information helps to assess the effectiveness of the dimension reduction technique used in capturing the data’s underlying structure.
Table 5. Total Variance Explained. The variance ratio is the percentage of the variance attributed to each selected component. This information helps to assess the effectiveness of the dimension reduction technique used in capturing the data’s underlying structure.
ComponentInitial Eigenvalues Extraction Sums of Squared LoadingsRotation Sums of Squared Loadings
Total% of
Variance		Cumulative %Total% of
Variance		Cumulative %Total% of
Variance		Cumulative %
110.08438.78738.78710.08438.78738.7873.69014.19214.192
22.2538.66747.4532.2538.66747.4533.68314.16728.358
31.8617.15854.6111.8617.15854.6113.24812.49240.850
41.3075.02759.6381.3075.02759.6382.69010.34751.197
51.1284.33963.9771.1284.33963.9772.3388.99160.189
61.0974.21968.1961.0974.21968.1962.0828.00768.196
70.9223.54671.742
80.8663.33175.072
90.7512.88777.959
100.7142.74680.705
110.6052.32783.032
120.5762.21785.248
130.5151.98087.228
140.4551.74988.977
150.3981.53390.510
160.3851.48091.990
170.3561.37193.360
180.2831.08994.449
190.2651.02095.469
200.2510.96696.435
210.2210.85197.286
220.1710.65897.945
230.1580.60898.553
240.1360.52399.076
250.1310.50399.579
260.1090.421100.000
Source: compiled from the questionnaire.
Table 6. The Rotated Component Matrix. This table summarizes the results of a questionnaire investigating the factors influencing viewers’ investment decisions based on an influencer’s YouTube channel. It analyzes the relationships between various aspects of the influencer’s and viewers’ attitudes and equity investment behavior.
Table 6. The Rotated Component Matrix. This table summarizes the results of a questionnaire investigating the factors influencing viewers’ investment decisions based on an influencer’s YouTube channel. It analyzes the relationships between various aspects of the influencer’s and viewers’ attitudes and equity investment behavior.
Component
123456
Influence CredibilityExperience of the influencer.0.7770.2540.0310.2720.002−0.153
The expertise of the influencer on the topic.0.7650.3570.1430.16−0.0080.014
The influencer’s YouTube videos are interesting.0.7440.3050.0890.1110.2670.204
The influencer’s YouTube videos are pleasant.0.6360.0320.409−0.0930.2870.259
The influencer is honest.0.5270.0830.2270.447−0.1660.012
The congruency between the influencer’s YouTube channel and equity investment is high. 0.490−0.0180.0910.3340.0300.475
Influencer Engagement Providing positive comments about the influencer’s YouTube channel to others.0.2140.7950.0590.191−0.018−0.041
Seldom missing an opportunity to tell others interested in equity investment about the influencer’s YouTube channel.0.2000.7280.279−0.082−0.0470.227
Recommending the influencer’s YouTube channel to my friends and relatives interested in equity investments.0.3770.6830.2790.200−0.0370.112
Recommending the influencer’s YouTube channel to others.0.2010.5910.0740.4930.1430.233
Feeling secure in following an influencer’s suggestions about equity investments.0.0180.5170.1060.3270.030.442
Relying on the influencer’s recommendations about equity investment.0.0450.4020.3930.282−0.1270.365
Influencer TrustworthinessThe influencer’s YouTube videos are trustworthy.0.1100.3200.6220.3870.196−0.058
Looking for new content published on the influencer’s YouTube channel.0.3480.1870.5990.0940.0750.323
Continue to follow this influencer’s YouTube channel.0.2110.5840.5910.1190.0790.135
Feeling comfortable in making an equity investment as suggested by the influencer on the channel.−0.0530.1830.5900.2310.0480.495
The alignment between the influencer’s YouTube channel and equity investment is high.0.2670.1620.5570.417−0.0980.110
YouTube videos are likable by the target audience.0.4830.1940.493−0.0220.4220.034
Having a favorable opinion about the influencer.0.2510.3340.4880.2790.374−0.041
Influencer Investment FitThe compatibility between the influencer’s YouTube channel and equity investments is high.0.1580.2440.2280.7350.0760.223
The influencer’s YouTube channel has a good match with the equity investment.0.2870.1440.2460.6660.2650.340
High Congruency between the influencer’s YouTube channel and equity investment.0.2480.4360.4160.4840.098−0.040
Influencer’s YouTube Channel PromotionThe influencer’s YouTube channel contains advertising.0.1820.009−0.070.1660.8430.000
The influencer’s YouTube channel is advertising.−0.038−0.0130.060−0.0720.8410.123
The influencer’s YouTube channel is commercial.0.009−0.0580.3540.0880.4680.009
Influencer-Driven Equity InsightsI do not hesitate to consider the equity investments published by this influencer.0.0460.1510.0780.0940.1060.841
Source: compiled from the questionnaire.
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MDPI and ACS Style

Pandey, L.K.; Singh, R.; Baker, H.K.; Laskar, H.R. Beyond the Screen: How YouTube Influencers Shape Equity Investment Decisions. J. Theor. Appl. Electron. Commer. Res. 2025, 20, 15. https://doi.org/10.3390/jtaer20010015

AMA Style

Pandey LK, Singh R, Baker HK, Laskar HR. Beyond the Screen: How YouTube Influencers Shape Equity Investment Decisions. Journal of Theoretical and Applied Electronic Commerce Research. 2025; 20(1):15. https://doi.org/10.3390/jtaer20010015

Chicago/Turabian Style

Pandey, Lata Kumari, Ranjit Singh, H. Kent Baker, and Habibur Rahman Laskar. 2025. "Beyond the Screen: How YouTube Influencers Shape Equity Investment Decisions" Journal of Theoretical and Applied Electronic Commerce Research 20, no. 1: 15. https://doi.org/10.3390/jtaer20010015

APA Style

Pandey, L. K., Singh, R., Baker, H. K., & Laskar, H. R. (2025). Beyond the Screen: How YouTube Influencers Shape Equity Investment Decisions. Journal of Theoretical and Applied Electronic Commerce Research, 20(1), 15. https://doi.org/10.3390/jtaer20010015

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