e-ISSN 2775-2976 International Journal of Economic.
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php/injects Volume 6 Number 2 page 561-577 The Spread of Information and Interaction on Social Media in Influencing Information Asymmetry and Investment Decision-Making Harry Hidayat Kamil Email: harryhidayatkamil@gmail.
Politeknik Cendana
ABSTRACT
This study examines the influence of social media in Indonesia on investment decision-making.
Currently, social media platforms are developing rapidly and have become an important source of information for investors.
This can be observed through the emergence of corporate social media accounts, investment company social media platforms, and stock analyst social media accounts across various platforms.
These channels aim to provide diverse information to assist investors in making informed investment decisions.
This research explains how information dissemination and user interactions on social media, which generate a wisdom of crowds effect, can reduce information asymmetry in the investment decision-making process.
The study employs primary data collected by distributing questionnaires to investment-related social media groups and communities.
A total of 150 respondents were selected using purposive sampling.
The findings illustrate how information disseminated through corporate social media, investment company social media, and stock analyst social media influences information asymmetry in investment decision-making.
Furthermore, the study describes how interactions among social media users .
isdom of crowd.
within these platforms contribute to reducing information asymmetry and shaping investment decisions.
Keywords: Social Media.
Information Asymmetry.
Investment
INTRODUCTION
Social media platforms have evolved beyond their original role as entertainment channels and have become major sources of information.
Today, many individuals rely on social media as a reference point before making important decisions.
This study focuses on the role of social media as a wisdom of crowds mechanism that influences individuals particularly investors in making investment decisions.
Social media platforms enable users to build webbased social networks with others by creating public or semi-public profiles (Boyd & Ellison.
These web-based networks are utilized by users to exchange information (Kaplan & Haenlein, 2.
Such information exchange occurs because social media functions as an interactive, web-based platform where users can create, modify, and share content containing information (Kietzmann et al.
, 2.
Social media has developed into various forms over time.
Kaplan and Haenlein .
provide a systematic classification scheme for understanding different types of social media.
deeper understanding of social media functions is offered by Kietzmann et al.
, who propose the seven functional building blocks of social media.
This framework describes the social media environment and its audience in detail, highlighting elements such as AuSharingAy and AuConversationsAy as particularly important because they serve as primary sources of Aubig Ay In other words, social media users actively engage in conversations through various formats, including comments, tweets, videos, stories, and live broadcasts, all of which can be shared within their web-based networks.
These data can then be collected and further analyzed.
e-ISSN 2775-2976 International Journal of Economic.
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php/injects Volume 6 Number 2 page 561-577 However, interactions and comments on social media are also influenced by other functional blocks identified by Kietzmann et al.
, including AuPresence,Ay AuIdentity,Ay AuGroups,Ay AuRelationships,Ay and AuReputation.
Ay Social media platforms facilitate interaction and make online participation easier and faster compared to traditional platforms.
Therefore, social media can be viewed as an accessibility technology that enables varying levels of engagement and social participation.
Jenkins et al.
use the term Auspreadable mediaAy to describe the nature of social media as a platform that encourages active engagement in disseminating information in the form of content to other users within established web-based social networks.
Social media has become increasingly embedded in everyday life due to the advancement of Web 2.
0 technologies and improved digital infrastructure.
These online technological tools enable individuals to use the internet not only for communication with friends but also for sharing information and resources within their networks.
Emerging evidence suggests that the impact of social media on both personal and managerial decision-making can be substantial.
Anecdotal evidence indicates that social media shapes opinions and influences choices by affecting consumer decisions as well as managerial business decisions.
This growing stream of research seeks to understand the rapid expansion of social media and its influence on decision-making processes, while also developing theoretical explanations for how communication within social and professional networks alters individual behavior.
In recent years, academic literature has increasingly examined the role of social media in capital markets.
One strand of research investigates how companies utilize these new information channels to communicate with a broader audience and attract investors.
Blankespoor et al.
demonstrate that firms use social media to reduce information asymmetry by disseminating corporate news through platforms such as links to press releases and other traditional news channels.
Jung et al.
find that approximately half of the companies listed in the S&P index around 1,500 firms have established official corporate social media accounts.
Furthermore, a survey conducted by Harvard Business Review Analytic Services reports that more than three-quarters .
%) of the 21,000 organizations surveyed stated that they are either currently using social media channels .
%) or preparing to launch social media initiatives .
%).
The development of social media has progressed dramatically.
Investors increasingly consider information available on social media as a relevant source, whether it originates from corporate social media accounts, investment firmsAo social media platforms, or stock analystsAo social media channels.
This growing reliance on digital information sources has the potential to reduce information asymmetry.
Information asymmetry arises when one party in a transaction possesses more or better information than the other party.
It is commonly referred to as asymmetric information.
For example, a seller may have more information than a buyer, or vice versa.
This concept was first formally articulated by Kenneth J.
Arrow in 1963.
With the emergence of corporate, investment firm, and stock analyst social media accounts, investors gain access to more diverse information, which may help mitigate information asymmetry in investment decision-making.
A series of analytical studies demonstrates that public disclosure reduces information asymmetry by providing investors with equal access to information (Diamond, 1985.
Bushman.
Lundholm, 1.
In financial and capital markets, information asymmetry arises when e-ISSN 2775-2976 International Journal of Economic.
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php/injects Volume 6 Number 2 page 561-577 certain investors possess more or superior information compared to others.
According to Gow et al.
, this condition occurs because investors differ in their ability to process These differences stem from variations in investorsAo capacity and willingness to incur costs in acquiring and analyzing information.
According to Philip Kotler and Kevin Lane Keller .
9, p.
, a purchase decision is an integration process used to combine knowledge in order to evaluate two or more alternative behaviors and select one among them.
Consumer decision-making represents a problem-solving approach in human activity when purchasing goods or services to satisfy needs and wants.
The decision-making process consists of five stages: problem recognition, information search, evaluation of alternatives, purchase decision, and post-purchase behavior.
Social media can significantly influence decision-making processes by facilitating access to information and enabling rapid dissemination of content.
The ease of commenting and engaging in discussions fosters a wisdom of crowds dynamic, where collective opinions and shared insights shape individual judgments.
Moreover, the diversity of information available on social media including content from corporate social media accounts, investment firmsAo platforms such as Mandiri Sekuritas.
Indo Premier Sekuritas.
Trimegah Sekuritas.
Phillip Sekuritas, and Stockbit, as well as stock analystsAo accounts such as Ellen May.
Michael Yeoh.
Aline Wiratmaja, and Yudi Chen provides investors with multiple This broad range of information sources contributes to more informed investment decision-making.
METHODS
Data were collected through a questionnaire administered both online, using Google Forms, and manually to facilitate broader distribution to respondents.
The questionnaire consisted of two sections.
The first section contained questions related to respondentsAo demographic information, which was treated confidentially.
The second section included a set of indicators designed to measure the research variables using a Likert scale.
The study employed purposive sampling, as not all individuals met the predetermined selection criteria.
The sample criteria required respondents to be investors who actively use social media as a source of investment-related information.
RESULTS AND DISCUSSION
Descriptive Statistics and Normality The Descriptive Statistics and Normality Assessment Results aim to provide a general overview of the data that have been collected.
Table 1.
Descriptive Statistics and Normality Assessment Results Item Code
Min Max
Mean
Standard
Deviation Excess
Kurtosis Skewness MPRS
MPRS1
MPRS2
MPRS3
Global-MPRS
G-MPRS
MBP
MBP1
MBP2
Construct e-ISSN 2775-2976 International Journal of Economic.
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Global-MBP
MAS
Global-MAS
AMPRS
MBP3
G-MBP4
MAS1
MAS2
MAS3
G-MAS
AMPRS1
AMPRS2
AMPRS3
GlobalAMPRS
AMBP
G-AMPRS
AMBP1
Global-AMBP
AMBP2
AMBP3
G-AMBP
AMAS1
AMAS2
AMAS3
G-AMAS
IMP1
IMP2
IMP3
IMP4
IMP5
IMP6
G-IMP
IMB1
IMB2
IMB3
IMB4
IMB5
IMB6
G-IMB
IMA1
IMA2
IMA3
IMA4
IMA5
IMA6
G-IMA
AMAS
Global-AMAS
IMP
Global-IMP
IMB
Global-IMB
IMA
Global-IMA e-ISSN 2775-2976 International Journal of Economic.
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Global-Kotler MPRS
PM1
PM2
PM3
PI1
P12
PI3
EA1
EA2
EA3
KP1
KP2
KP3
PP1
PP2
PP3
G-Kotler
MPRS1
MPRS2
Redundancy Analysis Results for Formative Construct This study employs a questionnaire designed using a formative construct approach.
Therefore, it is necessary to calculate the Redundancy Analysis Results for the Formative Constructs for each variable as well as for the overall path model.
Media Sosial Perusahaan.
Figure 1.
Redundancy Analysis Results for the Formative Construct of Corporate Social Media.
Table 2.
Convergent Validity Assesment Results for formative Construct Media Sosial Perusahaan.
Construct
Item
Outer
Weight
Outer
Loading VIF
t-value p-value MPS
MPRS1
MPRS2
MPRS3
Investment Company Social Media e-ISSN 2775-2976 International Journal of Economic.
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php/injects Volume 6 Number 2 page 561-577 Figure 2.
Redundancy Analysis Results for Formative Construct Investment Company Social Media Table 3.
Convergent Validity Assessment Results for Formative Construct Investment
Company Social Media Construct
Item
Outer
Weight
Outer
Loading VIF
t-value p-value MBP
MBP1
MBP2
MBP3
Stock Analyst Social Media Figure 3.
Redundancy Analysis Results for Formative Construct Stock Analyst Social Media Table 4.
Convergent Validity Assessment Results for formative Construct Stock Analyst
Social Media Construct
Item
Outer
Weight
Outer
Loading VIF
t-value p-value MAS MAS1
MAS2
MAS3
Corporate Social Media Interaction Figure 4.
Redundancy Analysis Results for Formative Construct Corporate Social Media Interaction e-ISSN 2775-2976 International Journal of Economic.
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php/injects Volume 6 Number 2 page 561-577 Table 5.
Convergent Validity Assessment Results for formative Construct Investment
Company Social Media Interaction Construct
IMP
Outer
Weight
Outer Loading VIF
t-value IMP1
IMP2
IMP3
IMP4
IMP5
IMP6
Item Investment Company Social Media Interaction Figure 5.
Redundancy Analysis Results for Formative Construct Investment Company Social Media Interaction Table 6.
Convergent Validity Assessment Results for Formative Construct Investment
Company Social Media Interaction Construct
Item
Outer
Weight
Outer Loading VIF
t-value p-value IMB
IMB1
IMB2
IMB3
IMB4
IMB5
IMB6
Stock Analyst Social Media Interaction e-ISSN 2775-2976 International Journal of Economic.
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php/injects Volume 6 Number 2 page 561-577 Figure 6.
Redundancy Analysis Results for Formative Construct Stock Analyst Social Media Interaction Table 7.
Convergent Validity Assessment Results for Formative Construct Stock Analyst
Social Media Interaction Construct
Item
Outer
Weight
Outer
Loading VIF
t-value p-value IMA
IMA1
IMA2
IMA3
IMA4
IMA5
IMA6
Information Asymmetry in Corporate Social Media Figure 7.
Redundancy Analysis Results for Formative Construct Information Asymmetry in Corporate Social Media Table 8.
Convergent Validity Assessment Results for formative Construct Information Asymmetry in Corporate Social Media Construct
Item
Outer
Weight
Outer
Loading VIF
t-value p-value AMPRS
AMPRS1
AMPRS2
AMPRS3
Information Asymmetry in Investment Company Social Media Figure 8.
Redundancy Analysis Results for Formative Construct Asimetri Information Asymmetry in Investment Company Social Media Table 9.
Convergent Validity Assessment Results for Formative Construct Information Asymmetry in Investment Company Social Media e-ISSN 2775-2976 International Journal of Economic.
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Construct
Item
Outer
Weight
Outer
Loading VIF
t-value p-value AMBP
AMBP1
AMBP2
AMBP3
Information Asymmetry in Stock Analyst Social Media Figure 9.
Redundancy Analysis Results for Formative Construct Information Asymmetry in Stock Analyst Social Media Table 10.
Convergent Validity Assessment Results for formative Construct Information Asymmetry in Stock Analyst Social Media Construct
Item
Outer
Weight
Outer
Loading VIF
t-value p-value AMAS
AMAS1
AMAS2
AMAS3
Investment Decision Based on KotlerAos Theory Figure 10.
Redundancy Analysis Results for Formative Construct Investment Decision e-ISSN 2775-2976 International Journal of Economic.
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php/injects Volume 6 Number 2 page 561-577 Table11.
Convergent Validity Assessment Results for Formative Construct Invesment Decision Construct Item Outer Weight Outer Loading VIF t-value p-value Kept.
Investasi
EA1
EA2
EA3
KP1
KP2
KP3
P12
PI1
PI3
PM1
PM2
PM3
PP1
PP2
PP3
PLS Path Complete Model Figure 11.
PLS Path Model e-ISSN 2775-2976 International Journal of Economic.
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php/injects Volume 6 Number 2 page 561-577 Convergent Validity Assessment Results for Formative Construct As shown in the table above, it can be concluded that the constructs and their indicators meet the validity requirements for the formative construct model, as the outer loadings are greater than 0.
Table 12.
Convergent Validity Assessment Results for Formative Construct
Item
Outer
Weight
Outer
Loading VIF
t-value p-value AMAS1
AMAS2
AMAS3
AMBP
AMBP1
AMBP2
AMBP3
AMPRS
AMPRS1
AMPRS2
AMPRS3
EA1
EA2
EA3
IMA1
IMA2
IMA3
IMA4
IMA5
IMA6
IMB1
IMB2
IMB3
IMB4
IMB5
IMB6
IMP1
IMP2
IMP3
IMP4
IMP5
IMP6
KP1
MAS
KP2
KP3
MAS1
Construct
AMAS
IMA
IMB
IMP
e-ISSN 2775-2976 International Journal of Economic.
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MBP
MPRS
MAS2
MAS3
MBP1
MBP2
MBP3
MPRS1
MPRS2
MPRS3
PI2
PI1
PI3
PM1
PM2
PM3
PP1
PP2
PP3
Hypotheses Testing Table 13.
Summary of Hypoteses Testing Std.
Beta Std.
Error Hypotesis Path MPRS -> Kep.
Inves MBP -> Kep.
Inves Bias Convidence Interval Decision Supported Supported Not Supported Supported Supported Supported MAS -> Kep.
Inves
MPRS ->
AMPRS
MBP ->
AMBP
MAS ->
AMAS
IMP -> Kep.
Inves Not Supported IMB -> Kep.
Inves Supported Zhao Direct Only Non Mediation Direct Only Non Mediation Indirect Only Mediation No effect Non Mediation Direct Only Non Mediation e-ISSN 2775-2976 International Journal of Economic.
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H10
H11
H12
Indirect Effect IMA -> Kep.
Inves
IMP ->
AMPRS
IMB -> AMBP
IMA -> AMAS
Path Not Supported Supported Supported Supported Std.
Beta Std.
Error
Convidence Interval
Decision Bias H13
H14
IMP ->
AMPRS ->
Kep.
Inves
H15
MBP ->
AMBP -> Kep.
Inves
H16
IMB -> AMBP
-> Kep.
Inves
H17
MAS ->
AMAS -> Kep.
Inves
Supported H18
IMA -> AMAS
-> Kep.
Inves
Supported Not Supported Not Supported Not Supported Not Supported Zhao
MPRS ->
AMPRS ->
Kep.
Inves Indirect Only Mediation Direct Only Non Mediation Non Effect Non Mediation Direct Only Non Mediation Direct Only Non Mediation Indirect Only Mediation Indirect Only Mediation The hypothesis testing results were examined at a 95% confidence level by comparing the confidence intervals and standardized beta coefficients.
Out of the eighteen proposed hypotheses, the findings are summarized as follows:
H1 : Information dissemination through corporate social media has a positive effect on investment decisions supported, direct effect only .
o mediatio.
H2 : Information dissemination through investment company social media has a positive effect on investment decisions supported, direct effect only .
o mediatio.
H3 : Information dissemination through stock analyst social media has a positive effect on investment decisions not supported, effect occurs only indirectly through mediation.
H4 : Information dissemination through corporate social media reduces information asymmetry supported.
H5 : Information dissemination through investment company social media reduces information asymmetry supported.
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php/injects Volume 6 Number 2 page 561-577 : Information dissemination through stock analyst social media reduces information asymmetry supported.
H7 : User interaction on corporate social media has a positive effect on investment decisions not supported, no effect .
o mediatio.
H8 : User interaction on investment company social media has a positive effect on investment decisions supported, direct effect only .
o mediatio.
H9 : User interaction on stock analyst social media has a positive effect on investment decisions not supported, indirect effect only .
H10 : User interaction on corporate social media reduces information asymmetry supported.
H11 : User interaction on investment company social media reduces information asymmetry H12 : User interaction on stock analyst social media reduces information asymmetry H13 : Corporate social media reduces information asymmetry, which in turn influences investment decisions not supported, direct effect only .
o mediatio.
H14 : Interaction on corporate social media reduces information asymmetry, which in turn influences investment decisions not supported, no effect .
o mediatio.
H15 : Investment company social media reduces information asymmetry, which in turn influences investment decisions not supported, direct effect only .
o mediatio.
H16 : Interaction on investment company social media reduces information asymmetry, which in turn influences investment decisions not supported, direct effect only .
o mediatio.
H17 : Stock analyst social media reduces information asymmetry, which in turn influences investment decisions supported, indirect effect only .
H18 : Interaction on stock analyst social media reduces information asymmetry, which in turn influences investment decisions supported, indirect effect only .
CONCLUSION
This study analyzes the role of social media in reducing information asymmetry in investment decision-making in Indonesia.
It examines how information dissemination and user interaction .
isdom of crowd.
within social media platforms may mitigate information asymmetry that influences investorsAo decisions.
Given the rapid growth of social media, the research focuses on three categories of platforms in Indonesia: corporate social media, investment company social media, and stock analyst social media accounts.
The empirical findings indicate that information dissemination through corporate social media and investment company social media directly influences investorsAo decisions to invest (H1 and H.
However, such dissemination does not necessarily reduce information asymmetry (H4.
H5.
H13, and H.
This suggests that information shared through corporate and investment company social media may trigger irrational investor behavior, as the disseminated content does not always contain information that is truly beneficial or decision-relevant.
In contrast, information dissemination through stock analyst social media does not directly influence investorsAo investment decisions (H.
This finding reflects more rational investor behavior, as the information shared by stock analysts must contain valuable and relevant content in order to reduce information asymmetry (H.
, which subsequently influences e-ISSN 2775-2976 International Journal of Economic.
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php/injects Volume 6 Number 2 page 561-577 investment decisions through mediation (H.
Unlike information dissemination, interaction within corporate social media does not directly influence investorsAo investment decisions (H7 and H.
, even though such interaction can reduce information asymmetry (H.
This may be explained by irrational investor responses to corporate social media content, where user interaction tends to be confirmatory rather than analytical.
Conversely, interaction within investment company social media directly influences investment decisions (H.
Investment companies tend to engage actively with investors.
however, the interaction does not necessarily provide information that meaningfully reduces information asymmetry (H11 and H.
Regarding stock analyst social media, user interaction does not directly influence investment decisions (H.
The impact depends on the quality of information embedded in those interactions.
When interactions within stock analyst social media contain valuable and relevant information, they reduce information asymmetry (H.
, which in turn influences investment decisions indirectly through mediation (H.
Research Limitations and Future Research Directions This study focuses exclusively on social media users in Indonesia and therefore represents only the behavior of Indonesian investors who utilize social media.
Another limitation is that the research examines social media broadly (Facebook.
Twitter, and Instagra.
without concentrating on a specific platform.
Prior research by Wisnantiasri and Mutira .
identified differences between Facebook and Twitter regarding corporate disclosure through social media in reducing information asymmetry.
Their findings suggest that Facebook is more frequently used by respondents for information search compared to Twitter, and that Facebook reduces information asymmetry.
However, this result differs from Blankespoor.
Miller, and White .
, who empirically demonstrate that Twitter reduces information asymmetry in the United States.
These contrasting findings may reflect differences in investor profiles and usage patterns between the United States and Indonesia.
In the U.
Twitter is actively used to obtain corporate information, whereas in Indonesia it has traditionally been used more for personal updates and informal communication.
Given the rapid evolution of social media, future research should explore additional factors, such as how the management of negative news on social media influences investor decision-making.
Further studies may also examine the role of specific social media features such as posts, stories, live streaming, and other interactive tools in shaping investment The findings of this study indicate that investor responses to information dissemination through corporate social media tend to be irrational, as such dissemination directly influences investment decisions without necessarily reducing information asymmetry.
This highlights the need for further investigation.
Recently, cases of investment fraud associated with AuflexingAy behavior on Indonesian social media platforms have raised concerns regarding the quality and credibility of information circulating in digital environments, underscoring the urgency of deeper scholarly inquiry.
REFERENCES.