Vol. 6, No. 1, January 2025
E-ISSN: 2723 - 6692
P-ISSN: 2723 - 6595
http://jiss.publikasiindonesia.id/
Jurnal Indonesia Sosial Sains, Vol. 6, No. 1, January 2025 1
KEYWORDS
ABSTRACT
Opinion Leaders; Consumer
Behavior; SME; Social media
The decline in sales is one of the impacts of the Covid 19
pandemic on SME, and another impact is a decrease in production
and a decrease in the total income of SME. Opinion leadership can
solve consumer behavior in Indonesian society, especially after
the Covid 19 pandemic. This research aim to determine the SME-
based opinion leadership model in Indonesia during the Covid 19
pandemic and to analyze the relationship between opinion
leadership and consumer behavior in SMEs during the Covid 19
pandemic. This research is quantitative through an online survey,
the data analysis and hypothesis testing method use the Structural
Equation Model - Partial Least Square (SEM-PLS). It was found
that opinion leadership significantly affects consumer behavior in
SMEs in Indonesia with four characteristics, professional,
innovative, involved, and socialized. This research can be used for
SME to start digitalizing by having a social media account to share
information alongside the efforts of opinion leaders. Opinion
leaders have a specialty depending on their capability, so they can
promote SME products that match their personality. In addition,
having many followers can make opinion leaders lead a
community.
Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
Introduction
The G20 Summit (Summit) has set 3 priority issues: sustainable energy transition, digital
transformation, and health architecture. The Indonesian government said digital acceleration from
cities to villages is key to economic recovery after the COVID-19 pandemic (Seknet, 2022). SMEs
play a significant role in Indonesia's economic recovery, recorded based on data from the
Indonesian Ministry of Communication and Information, 64.2 million SMEs contribute to 61% of
Indonesia's GDP. However, 17.5 million SMEs owner still use and enter the digital ecosystem. The
digitalization of SMEs includes utilizing e-commerce, digital payment facilities, and digital
promotions (Kominfo, 2023).
The Ministry of Cooperatives and Small and Medium Enterprises asked the public to help
SMEs continue to produce as a sector that relies on the lowest level of the real sector in Indonesia
Development of Sme Based Opinion Leadership Model in Indonesia
Chairunnisya
Universitas Andalas, Padang, Indonesia
Email: chairunnisya@eb.unand.ac.id
Correspondence: chairunnisya@eb.unand.ac.id
*
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Jurnal Indonesia Sosial Sains, Vol. 6, No. 1, January 2025 2
after the COVID-19 pandemic. However, this needs to be addressed because people need to be
encouraged to purchase from SMEs. Many people need to learn about SMEs and the products being
marketed because of the limited marketing carried out by related SMEs. One of the things that can
be done is to maximize the role of opinion leaders. SMEs need to find opinion leaders who have
good credibility to promote their products to increase the customer intention to buy the products
(Hartini & Hanafi, 2021).
Solomon (2020) defines opinion leadership as someone who can often influence the attitudes
and behavior of others. Opinion leaders can play a role in inviting the public to help SMEs by
buying products from SMEs. The decline in sales is one of the impacts of the Covid 19 pandemic
on SMEs, and another impact is a decrease in production and a decrease in the total income of
SMEs (Hernikawati, 2022). Kwon and Song (2014) statethat market mavens significantly influence
consumer behavior, namely people who are experts in a particular field. Market mavens are part of
the opinion leaders. Rahmayanti et al. (2019) also found that opinion leaders and influencers
influence consumer behavior in Indonesia. In other words, the opinion leader's recommendations
have more weight than other people's recommendations. In buying products, consumers are not
only influenced by product quality but are also influenced by other factors, namely opinion leaders.
His ability to inform products and the professionalism of opinion leaders influence consumers in
making purchasing decisions (Wang et al., 2023).
Opinion leaders can influence consumers to buy products through several media, one of them
is Instagram. In this digital era, opinion leaders use technology to influence costumers (Žák &
Hasprová, 2021). Digitalization and the use of social media are essential for the sales process.
Social media can reduce promotion costs and give a significant opportunity to grow in national and
international markets. These are the factors for the success of SMEs (Fraccastoro et al., 2021).
Opinion leaders also increase brand awareness, especially if the posts on social media are of better
quality (Patria et al., 2023). In previous research conducted by Wang, (2017), opinion leaders are
divided into two, namely traditional opinion leaders (influence others through mass media or the
public) and online opinion leaders (influence others via the internet). With a significant influence,
opinion leaders are expected to be able to change the consumer behavior of the Indonesian people
to make purchases at SMEs that are spread throughout Indonesia. This research has novelty from
the perspective of Indonesian people's behavior towards purchasing SME products which are
influenced by opinion leadership. This prompted the author to examine empirical models in
analyzing the linkages of the opinion leadership construct as a determinant of consumer behavior
in Indonesian society.
Understanding the dynamics of SME-based opinion leadership is crucial for enhancing the
effectiveness of marketing strategies and promoting SME resilience in the digital era. The findings
are expected to provide actionable insights for SMEs and policymakers to leverage opinion
leadership for economic recovery and growth.
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Research Methods
The approach used in this study is quantitative. The marketing research design used in this
research is conclusive research using a descriptive method. This study aims to analyze the influence
of opinion leaders on consumer behavior in Indonesian society in SME.
Sample
The population in this study is the Indonesian people. The sample in this study was selected
based on nonprobability sampling. The method used in selecting the sample was purposive
sampling with sample criteria, namely whether or not the public had read, heard, and seen
information from opinion leaders, both traditional and online leaders, regarding suggestions for
making purchases to SMEs. Researchers will collect data through a questionnaire using a sample
of 150.
Data Collection
The data collection technique needed in this research is a questionnaire survey. Malhotra
(2010) defines the survey method as obtaining information based on respondents' answers. Data
was collected using a questionnaire distributed electronically or via the Internet using a Google
form or an online survey. Malhotra (2010) classifies data into two types: secondary and primary.
Primary data is data collected explicitly by researchers to answer research problems. Primary data
in this study were obtained from respondents or samples through the proposed online survey. While
secondary data is data collected for various purposes other than research problems.
Measurements
This study used SEM analysis to examine the relationships and parameters of the research
model design. The SmartPLS statistical application is used to perform the test. Instrument testing
is carried out through validity and reliability tests. A validity test is a test of how well an instrument
developed measures the concept being measured (Sekaran, 2019). Discriminant validity describes
how a variable can differentiate itself from other variables in one model. Discriminant Validity is
calculated by looking at the Cross Loading value of each research indicator. Structural testing is
carried out with the r-square value, and hypothesis testing uses the t-value.
Results and Discussion
Result
Characteristics of Respondents
Based on the research results, the following are the characteristics of most respondents based
on several categories, namely:
Table 1. Characteristics of Respondents
Number
Category
Majority of Respondents
Percentage
1
Gender
Female
70.7%
2
Age
18-28 years
88%
3
Last Education
Elementary school/First Middle
School/Senior High School
78.7%
4
Occupation
Student
84.7%
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5
Expenditures per
month for shopping
for SME products
< Rp2.000.000
89,3%
6
SME product
spending intensity
6-10 times
32%
7
SME products
purchased
Culinary
70%
8
The media used to
view Opinion
Leaders
Social Media
92%
Source: processed data, 2024
Based on the table, most respondents spend small amounts of IDR 2,000,000 to buy SME
products. Most respondents buy culinary products 6-10 times a month, and social media is the most
media where respondents see opinion leaders sharing their opinions regarding SME products.
Testing Research Instruments (Validity and Reliability)
1. Validity Test
The instrument's validity was carried out using the SmartPLS application. It was assessed based on
the convergent validity and discriminant validity of the indicators measured from the value of outer
loadings through an algorithmic process.
Convergent Validity
The convergent validity test with PLS is assessed based on the loading factor of the indicators
that measure constructs (Abdillah & Hartono, 2015). The loading factor is the correlation between
item scores and construct scores. An indicator is considered to have a high level of validity if it has
an AVE value and a loading above 0.7. According to Ghozali (2014), measuring a loading value
of 0.5 to 0.6 is considered sufficient. Based on the first data processing results in this study, there
is one indicator with an Outer Loading value of less than 0.5.
Table 2. Results of Outer Loading Before Dropping
Consumer
Behavior
Innovative
ness
Involvem
ent
Opinion
Leadership
Profession
al
Socialized
CB1
0.517
CB2
0.763
CB3
0.472
CB4
0.797
CB5
0.744
OLI1
0.813
OLI1
0.755
OLI2
0.839
OLI2
0.726
OLI3
0.797
OLI3
0.646
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OLI4
0.696
OLI4
0.551
OLP1
0.817
OLP1
0.704
OLP2
0.733
OLP2
0.503
OLP3
0.819
OLP3
0.753
OLP4
0.685
OLP4
0.534
OLS1
0.869
OLS1
0.726
OLS2
0.936
OLS2
0.768
OLS3
0.945
OLS3
0.755
OLS4
0.762
OLS4
0.713
OLV1
0.897
OLV1
0.737
OLV2
0.848
OLV2
0.614
Source: processed data, 2024
This indicator is the CB3 (I bought SME products that SME promotes) indicator on the Consumer
Behavior variable. Because the indicators do not meet the value of 0.5, it is necessary to test the
data again by removing invalid indicators
Table 3. Results of Average Variance Extracted (AVE) Before Dropping
Variable
Average Variance Extracted (AVE)
Consumer Behavior
0.452
Innovativeness
0.621
Involvement
0.762
Opinion Leadership
0.467
Professional
0.586
Socialized
0.777
Source: processed data, 2024
Based on Table 3, there are 2 constructs that have an AVE value below 0.5, namely the
Consumer Behavior (0.452) and Opinion Leadership (0.467) variables. To get an AVE value
greater than 0.5 to be valid, it must re-test the AVE. The results of the second outer loading are
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carried out by removing 1 indicator, it is found that all indicators have fulfilled the required value,
namely > 0.05, then the indicator has been declared valid. Based on the results of the second AVE
that was carried out, there was 1 construct that had an AVE value below 0.5, namely the Opinion
Leadership variable with an AVE value of 0.467. So, it is necessary to remove the indicators that
have low loading on the AVE construct which has the smallest value and retest the AVE. In the
third outer loading test, no loading value < 0.5 was found. The same thing with the results of the
third AVE that was carried out, obtained an AVE value > 0.5 as presented in the Table 4 and Table
5.
Table 4. Final Outer Loading Results After Dropping
Consumer
Behavior
Innovativeness
Involvement
Opinion
Leadership
Professional
Socialized
CB2
0.772
CB4
0.854
CB5
0.738
OLI1
0.816
OLI1
0.765
OLI2
0.842
OLI2
0.741
OLI3
0.795
OLI3
0.639
OLI4
0.690
OLI4
0.532
OLP1
0.822
OLP1
0.676
OLP2
0.723
OLP3
0.829
OLP3
0.738
OLP4
0.671
OLS1
0.871
OLS1
0.754
OLS2
0.937
OLS2
0.794
OLS3
0.946
OLS3
0.784
OLS4
0.760
OLS4
0.722
OLV1
0.896
OLV1
0.730
OLV2
0.849
OLV2
0.615
Source: processed data, 2024
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Table 5. Results of Average Variance Extracted (AVE) After Dropping
Variabel
Average Variance Extracted
(AVE)
Consumer Behavior
0.623
Innovativeness
0.621
Involvement
0.762
Opinion Leadership
0.506
Professional
0.584
Socialized
0.777
Source: processed data, 2024
So, in the Consumer Behavior variable, the outer loading results that meet the requirements
are found in the CB2, CB4, and CB5 indicators. Meanwhile, the Innovativeness variable has an
outer loading value that meets the OLI1, OLI2, OLI3, and OLI4 indicators requirements. In the
Involvement variable, the outer loading results that meet the requirements are found in all
indicators OLV1 and OLV2. In the Opinion Leadership variable, the outer loading results that meet
the requirements include indicators OLI1, OLI2, OLI3, OLI4, OLP1, OLP3, OLS1, OLS2, OLS3,
OLS4, OLV1, and OLV2. In the Prefessional variable, the outer loading results that meet the
requirements have OLP1, OLP2, OLP3, and OLP4 indicators. Finally, the final outer loading
results that meet the requirements for the Socialized variable are found in all indicators, namely
OLS1, OLS2, OLS3, and OLS4.
Discriminant Validity
Table 6 contain the results of the discriminant validity of each latent construct:
Table 6. Fornell-Larcker Criterion Result
OL
CB
Innovativeness
Involvement
Professional
Socialized
Opinion Leadership
0.711
Consumer Behavior
0.651
0.789
Innovativeness
0.860
0.581
0.788
Involvement
0.775
0.571
0.617
0.873
Professional
0.781
0.509
0.637
0.610
0.764
Socialized
0.868
0.517
0.580
0.535
0.560
0.881
Source: processed data, 2024
Based on Table 6 it can be seen from the Fornell-Larcker Criterion that the construct correlation
value has a value of > 0.7. This shows that the construct has good validity. Thus, it can be concluded
that the latent construct shows good discriminant validity, so it can be said that the data is valid.
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2. Reliability Test
Table 7. Cronbach’s Alpha and Composite Reliability at attachment
Variable
Cronbach's Alpha
Composite
Reliability
Consumer Behavior
0.697
0.832
Innovativeness
0.796
0.867
Involvement
0.690
0.865
Opinion Leadership
0.909
0.924
Professional
0.765
0.848
Socialized
0.901
0.933
Source: processed data, 2024
Based on table 7, the measured Cronbach's Alpha reflective construct has a value greater than 0.6,
and the Composite Reliability value is above 0.7, so the research construct is reliable.
Structural Model and Hypothesis Testing
Tabel 8. R-Square
Variabel
R Square
Consumer Behavior
0.424
Opinion Leadership
0.987
Source: processed data, 2024
Based on Table 8 it can be seen the results of the R-square of the research model. The
Consumer Behavior construct has an R-square value of 0.424 which means that the Consumer
Behavior variable can be explained by the Opinion Leadership, Professional, Innovativeness,
Involvement, and Socialized variables of 0.424 or 42.4%, and the remaining 57.6% is explained by
other variables not included in this study. Furthermore, professional, innovativeness, and
involvement can explain the Opinion Leadership construct and Socialized variables of 0.987 or
98.7%. The remaining 1.3% is explained by other variables not included in this study.
Table 9. Path Coefficient
Original
Sample (O)
Sample
Mean (M)
Standard
Deviation
(STDEV)
T Statistics
(|O/STDEV|)
P
Values
Opinion Leadership ->
Consumer Behavior
0.651
0.650
0.062
10,522
0.000
Innovativeness -> Opinion
Leadership
0.361
0.363
0.029
12,499
0.000
Involvement -> Opinion
Leadership
0.204
0.204
0.022
9,096
0.000
Professional -> Opinion
Leadership
0.173
0.173
0.014
12,689
0.000
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Socialized -> Opinion
Leadership
0.452
0.452
0.031
14,668
0.000
Source: processed data, 2024
Table 9 is the result of the structural model test conducted to see the t-statistic values that
will determine whether a hypothesis is accepted or rejected. With a significance level of 5% = t-
table 1.96, if t-statistics > t-table, then the hypothesis is accepted (Ghozali, 2018). Based on the
table, it can be concluded that the Opinion Leadership variable has a significant effect on Consumer
Behavior because it has a t-statistic value of 10.522 (10.522 > 1.96) this shows the hypothesis is
supported.
Furthermore, the hypothesis test can be concluded that the Innovativeness hypothesis has
proven to significantly affect Opinion Leadership because it has a t-statistic value of 12.499 (12.499
> 1.96). This shows the hypothesis is supported. In the Involvement hypothesis, it is proven to have
a significant effect on Opinion Leadership because it has a t-statistic value of 9.096 (9,096 > 1.96).
This shows the hypothesis is supported. In the Professional hypothesis it is proven to have a
significant effect on Opinion Leadership because it has a t-statistic value of 12.689 (12.689 > 1.96).
This shows that the hypothesis is supported. Finally, it can be seen from the Socialized hypothesis
that it has proven to have a significant effect on Opinion Leadership because it has a t-statistic
value of 14.668 (14.668 > 1.96). This shows that the hypothesis is supported
Discussion
The influence of the Opinion Leadership variable on Consumer Behavior
The test results show that the effect of the Opinion Leadership variable on Consumer
Behavior leads to a coefficient value with a t-statistic of 10.522. This value is greater than the t-
statistic value of 1.96 and with a small significance level of 0.05, namely 0.000 which proves that
the Opinion Leadership variable significantly affects Consumer Behavior. The original sample
value is positive, namely 0.651, which indicates a positive relationship. This means that Opinion
Leadership positively and significantly affects Consumer Behavior. Respondents argued that
opinion leaders saw the potential of SME products, so they thought so believe that the product the
opinion leader offers can be trusted to try. The way the opinion leader informs SME products is
conveyed differently. This is the background for respondents to trust the opinion leader as a source
of information when purchasing. This aligns with research conducted by Saputra & Chaniago
(2024) that key opinion leaders informally influence consumers, especially the younger generation
who use social media and are easily influenced by opinion leaders. (Casaló et al., 2020) found that
opinion leaders also increase consumers' desire to follow opinion leader accounts on social media
because they trust their experience and knowledge regarding products.
The Influence of Innovativeness variable on Opinion Leadership
The test results show that the influence of the Innovativeness variable on Opinion Leadership
shows a coefficient value with a t-statistic of 12,499. This value is greater than the t-statistic value
of 1.96 and with a small significance level of 0.05, namely 0.000, which means that the
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Innovativeness variable significantly affects Opinion Leadership. The original sample value is
positive, equal to 0.361, indicating a positive relationship. This means that the Innovativeness
variable positively and substantially affects Opinion Leadership. Momtaz et al. (2011) stated that
innovation is one characteristic that shapes opinion leadership. Innovation, or how opinion leaders
introduce products, is a trusted source of information for consumers. Consumers of SME products
in Indonesia feel helped by opinion leaders because they promote SME products differently. This
can provide new insights to consumers about the need to use SME products, which results in
purchasing these products. This is in line with what was conveyed Vodopivec et al. (2021) in his
research that the deeper insights conveyed by opinion leaders affect the diffusion of innovation in
society. Customers think that opinion leaders who share original content about products are creative
and sophisticated. This type of content will get customers attention (Fakhreddin & Foroudi, 2022).
The Influence of the Involvement Variable on Opinion Leadership
The test results show that the influence of the Involvement variable on Opinion Leadership
shows a coefficient value with a t-statistic of 9,096. This value is greater than the t-statistic value
of 1.96, with a small significance level of 0.05, namely 0.000, which means that the Involvement
variable significantly affects Opinion Leadership. The original sample value is positive, equal to
0.204, indicating a positive relationship. This means that the Involvement variable positively and
significantly affects Opinion Leadership. Respondents in this study agreed that high-involvement
products are products informed by opinion leaders through the media used, one of which is widely
used is social media. This product is first evaluated before making a purchase decision. This is in
line with research conducted by Wang, (2017) that long-lasting involvement is the hallmark of
opinion leaders. This explains why consumers can trust opinion leaders. In addition, opinion
leaders need to improve the quality of the messages conveyed to increase their credibility further.
Wang et al., (2023) also said that the engagement of opinion leaders also makes consumers feel
closer and builds trust because consumers tend to trust more and become more willing to listen to
opinion leaders' suggestions.
The Influence of The Professional Variable on Opinion Leadership
The test results show that the effect of the Professional variable on Opinion Leadership shows
a coefficient value with a t-statistic of 12.689. This value is greater than the t-statistic value of 1.96,
with a small significance level of 0.05, namely 0.000, which means that the Professional variable
significantly affects Opinion Leadership. The original sample value is positive, equal to 0.173,
indicating a positive relationship. This means that the Professional variable positively and
significantly affects Opinion Leadership. Respondents feel that opinion leaders have different ways
of promoting SME products. According to Wang et al., (2023), the professionalism of opinion
leaders can increase consumer trust and acceptance of products. Consumers may need help
understanding products, but the information provided by opinion leaders is beneficial for
consumers. Thus, respondents in this study felt that the ability of opinion leaders to inform products
was an essential characteristic in selecting opinion leaders.
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The Influence of The Socialized Variable on Opinion Leadership
The test results show that the effect of the Socialized variable on Opinion Leadership shows
a coefficient value with a t-statistic of 14.668. This value is greater than the t-statistic value of 1.96
and with a small significance level of 0.05, namely 0.000, which means that the Socialized variable
significantly affects Opinion Leadership. The original sample value is positive, equal to 0.452,
which shows a positive relationship. This means that the Socialized variable positively and
significantly affects Opinion Leadership. This is in line with research conducted Wang et al. (2023)
that the way of interaction and communication between opinion leaders and consumers is a
determining factor for opinion leaders. Opinion leaders who have more followers tend to influence
consumers more. Respondents in this study agree that opinion leaders are very active in using social
media to promote SME products because 92% of respondents see information about SME products
that are promoted through social media opinion leaders. In addition, respondents felt that opinion
leaders shared information with their followers. In this study, most Indonesian people view SME
product information from opinion leaders through social media especially Instagram. Opinion
leaders influence consumer behavior, for example, influencing consumer intention to have an
interaction on opinion leaders' Instagram accounts (Casaló et al., 2020).
Conclusion
Based on the analysis carried out in this study, the four characteristics of opinion leadership,
namely professional, innovative, involved, and sociable, are positive and significant factors in
shaping opinion leadership. Based on the test, it was also found that opinion leadership positively
and significantly influences consumer behavior toward SME products. Consumers think that
opinion leaders give excellent information about SME products differently. The way opinion
leadership used the product first and having a risk by trying the new products increases consumer
trust. It makes consumers want to buy the product from SMEs. Most consumers see the information
about the products promoted through opinion leader's social media accounts. The more follower’s
opinion leaders have the more capability of opinion leaders. Consumers believe that opinion leaders
professionally solve their problems by promoting SME products. Consumers think that opinion
leaders are innovative because they use social media to communicate with their followers and have
good interactions through social media. Opinion leaders choose the right products that match their
personality and capability, so the consumers believe that the products match opinion leaders. The
way opinion leaders are involved with the product increases the intention of consumers to buy and
use the SME products. The last characteristic is socialized, consumers believe that opinion leaders
can interact with their followers to share information. Opinion leaders' social media accounts are
also used by their followers to interact about products because they share similar interests. The
quality of opinion leaders’s content also needs to be original because followers will think that the
opinion leaders are creative.
This research has limitations. We hope that for further research, it will increase the number
of sample consumers who have purchased SME products after seeing the promotion of opinion
leaders. Further research is also expected to be able to see different phenomena for several different
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Jurnal Indonesia Sosial Sains, Vol. 6, No. 1, January 2025 12
SME product categories. Further research is needed to examine opinion leaders' strategies to
promote products through social media. This research has limitations. We hope that for further
research, it will increase the number of sample consumers who have purchased SME products after
seeing the promotion of opinion leaders. Further research is also expected to be able to see different
phenomena for several different SME product categories. Further research is needed to examine
opinion leaders' strategies to promote products through social media
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